Waiting experience

at train stations

Mark van Hagen

ISBN 978-90-5972-506-5

Eburon Academic Publishers

P.O. Box 2867
2601 CW Delft
The Netherlands
info@eburon.nl / www.eburon.nl

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© Mark van Hagen. All rights reserved. Nothing from this publication may be
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Waiting experience
at train stations

Proefschrift

ter verkrijging van

de graad van doctor aan de Universiteit Twente,
op gezag van de rector magnificus,
prof. dr. H. Brinksma,
volgens besluit van het College voor Promoties
in het openbaar te verdedigen
op vrijdag 1 april 2011 om 12:45 uur

door

Marcus van Hagen

geboren op 8 november 1961
te Schiedam
Dit proefschrift is goedgekeurd door
de promotor prof. dr. A.Th.H. Pruyn en
de assistent promotor dr. M. Galetzka.
Promotiecommissie
Prof. dr. M.D.T. de Jong, Universiteit Twente
Prof. dr. C.P.M. Wilderom, Universiteit Twente
Prof. dr. A.O. Eger, Universiteit Twente
Prof. dr. ir. A. Smidts, Erasmus Universiteit Rotterdam
Prof. dr. C.J.H. Midden, Technische Universiteit Eindhoven
Dr. ir. A.W. Veenman, professioneel bestuurder; oud-CEO van NS
The old ones speak of winter,
The young ones praise the sun.
And time just slips away.

Running into nowhere,

Turning like a wheel,
And a year becomes a day...

Ronnie James Dio, 1942-2010

 Foreword

It was whilst I was studying geography at Utrecht University, that I became

fascinated by the relationship between time and space, interlinked as they are by
the speed of movement and the way they define people’s range of action. During my
specialization in traffic engineering at Delft University, I noticed just how immense
the focus was on increasing speed. Surely that couldn’t be the only solution? In the
quest for the mechanism of transport choices, it slowly dawned on me that choices
are not just determined by objective travel time but also by less hard qualities as
ease, comfort and experience. Closer scrutiny revealed that travellers experience
their journey holistically, with not the train but the stations and the access and
egress transport appearing to be the weakest links. Gert-Joost Peek and the author
of this book have shared their thoughts on this in a number of articles advocating a
more integrated approach to moving and staying. At (railway) stations in particular,
there are opportunities for synergy. Enhancing the appreciation of the waiting time
at the station is one of the three strategies for improvement. What such an improve-
ment exactly entailed was still something of a mystery to us, however. So it was
defining this notion that constituted the intrinsic drive for this dissertation, one
that addresses how waiting experience can be positively influenced by alterations to
the waiting environment. Reading this thesis will disclose that although time can
be precisely measured, we cannot perceive it with our senses. Events in the waiting
environment are perceivable, however, and it is their intensity that influences our
emotions and behaviour.

Reading guide
The first part of this thesis outlines the connection between waiting time and
environ­mental experience, with practice (Chapters 1, 2 and 5) and theory (Chapters
3 and 4) alternating with each other. In the second part, a number of experiments
are discussed that elucidate how the environment can positively influence waiting
experience (Chapters 6, 7 and 8). The thesis rounds off with scientific (Chapter 9)
and practical (Chapter 10) conclusions and recommendations. Readers who are
more practically oriented are advised to read Chapters 1, 2, 5 and 10, whereas
the more theoretically oriented reader may feed on Chapters 3, 4, 6, 7, 8 and 9.
Pleasant reading!
 Contents

Foreword ix

Part I Waiting experience: theory and practice

Chapter 1 The role of the wait when travelling 3

Chapter 2 The waiting experience of Dutch service providers 17

Chapter 3 Theory of the waiting experience 29

Chapter 4 Theory of the environmental experience 43

Chapter 5 Waiting experience at Dutch stations 61

Part II Influencing the environment

Introduction to the experimental studies  75

Chapter 6 Colour and Light 87

Chapter 7 Music 123

Chapter 8 Advertising and Infotainment 155

Chapter 9 Discussion and research recommendations  181

Chapter 10 Conclusions and recommendations for 203

Netherlands Railways (NS)

References 221
Appendices 247
Summary (English and Dutch) 257
Acknowledgements in Dutch 269
 Part I
Waiting experience:
theory and practice

‘We wander for distraction,

but we travel for fulfilment.’
Hilaire Belloc, 1870-1953
 Chapter 1
The role of the wait
when travelling

‘When you sit with a nice girl for

two hours, it seems like two minutes.
When you sit on a hot stove for two
minutes, it seems like two hours.
That’s relativity.’
Albert Einstein, 1879-1955
1.1 Introduction

When undertaking an activity, people have three budgets at their disposal: money,
time and effort (physical/mental). Although travel is not a primary but a secondary
activity, with passengers opting for the easiest route, i.e. they wish to travel quickly,
cheaply and as effortlessly as possible (Peek & Van Hagen, 2004; Van Wee & Dijst,
2002), time is more important than money when travel choices have to be made.
With the level of affluence having risen, money has become less relevant; most
people are materially satisfied and not only seek an emotional, non-materialistic
way to spend time, but they seek quality time as well (Ackerman & Gross, 2007;
Gourville, 2006; Grotenhuis, Wiegmans & Rietveld, 2007; Hermsen, 2010; Klein,
2007; Kotler & Stonich, 1991; Pine & Gilmore,1999; Van den Broek, De Haan, Harms,
Huysmans & Van Ingen, 2006).
If NS (Nederlandse Spoorwegen – Netherlands Railways) wishes to persuade more
motorists to opt for the train, it will have to heed its (potential) customers’ percep-
tion of time. In the past, the most important investments were made in increasing
the objective travel time of the trains. With calculations derived from meticulous
scheduling offering insight into the extra number of passengers to be expected as
a result of a quicker journey, timetable development now also aims to minimize
the objective waiting time. After all, passengers are not just travelling, they are also
waiting at the station for their connection (Huisman, Kroon, Lentink & Vromans,
2005; Kroon, Huisman & Maroti, 2008).

1.2 Making the station environment more pleasant

Although sufficient attention is paid in the rail sector to passengers’ objective

waiting time, hardly any is paid to the waiting experience. How do passengers
experience their time at the station and how do they perceive their wait? Research
has shown that it is the subjective (waiting) experience that is a good predictor of
consumer satisfaction and how influential the waiting environment is on the time
perception (Pruyn & Smidts, 1998; Smidts & Pruyn, 1994; Taylor, 1994). Although it
became apparent from research conducted among several service providers that
people think that the wait passes more quickly in a pleasant environment than in
an unpleasant one (Pruyn & Smidts, 1998), no study has yet been carried out on the
waiting experience at train stations. Stations are special environments, because
time plays a central role in the service process, and as speed is of the essence,
a wait is considered lost time. Moreover, a train departs at a predetermined time,
which means that passengers have to keep an eye on the clock. NS is thus becoming
increasingly aware of the importance of not only a fast but also a comfortable
journey, both in the train and at the station, where waiting can be unpleasant.
Consequently NS sets itself the following objective: To transport our passengers
safely, on time and in comfort via appealing stations.

chapter 1 The role of the wait when travelling 5

The rationale behind this dissertation is the awareness that waiting is a waste of
time. By making the waiting environment more pleasant, NS can kill two birds with
one stone: passengers will find waiting more enjoyable and the duration of the wait
will seem shorter. The focus in this dissertation is thus not on the objective but on
the subjective experience of time, with the practical question being: Which measures
are effective in making the waiting time at stations more pleasant and/or in shortening
the perception of waiting time?
In order to answer this question, this introductory chapter will first explore what
role the service environment plays in the service process and what role time plays
when undertaking a train journey.

1.3 Services

A service is produced and consumed simultaneously. The consumer thus finds him-/
herself ‘on the shop floor’, as it were, and experiences the service within the physical
facilities of the organization (Grönroos, 1998). The service experience is influenced
by three factors: the service processes, the people present (staff and customers)
and the environment (Bitner, 1990; Zeithaml & Bitner, 2003). The processes have a
strong time-bound character and efficiency is key; the more efficient and smooth
the service process runs, the more satisfied the customers will be (Underhill, 1999).
At a station the passengers’ main focus is on time and punctuality is essential if they
are to catch their train. Also the presence of sufficient and competent staff positively
influences customer satisfaction, and a train journey is no exception. Not only the
staff but also the presence of other people in the service environment influence
how the service is experienced and too many or too few customers can result in
negative feelings (Eroglu, Machleit & Chebat, 2005; Hui & Bateson, 1991; Turley &
Milliman, 2000). Similarly, a deserted or a very busy station can also evoke negative
emotions and avoidance behaviour. Finally, the service environment can strongly
influence the perception of service satisfaction (Bitner, 1990; Pruyn & Smidts,
1998). As a service is intangible, customers often unconsciously seek things in the
service environment that say something about the expected quality (Brady & Cronin,
2001; Verhoeven, Van Rompay & Pruyn, 2009). If the environment is clean, safe and
appropriate for the service offered, then the consumer will have greater confidence
in the quality of the service provider.

1.4 Exceptional circumstances

As customers are present when the service is carried out, they immediately notice
it when something goes wrong. Whereas a smoothly running service is vital to
keep customers happy, the occurrence of service failures is virtually inherent in

6 waiting experience at train stations

the provision of services (Zeithaml, Bitner & Gremler, 2006). A technical malfunc-
tion or a sudden rush of people can lead to inconvenience and extra waiting time
(Tom & Lucey, 1997). In such a situation it is essential that the service provider reacts
appropriately as this can yield much goodwill among its customers, sometimes
even more than if the service had been rendered properly from the start (Chung,
Beverland & Gabbott, 2004; Clow, Kurtz, Ozment & Ong, 1997; Hart, Heskett & Sasser,
1990; Maxham, 2001; Zeithaml & Bitner, 2003).
For NS this means that passengers confronted with a delay will experience their wait
and the service differently. By correctly addressing a disruption, e.g. by taking the
concerns of the customer seriously, by supplying immediate and real-time informa-
tion and by paying careful attention to the waiting environment, any waiting time
will be experienced as less annoying (Pruyn & Smidts, 1998).

1.5 Utilitarian and hedonic motives

Not every customer has the same needs during the consumption of a service. In the
retail sector a differentiation is made between utilitarian and hedonic consumers.
Utilitarian consumers are task- and goal-oriented shoppers who are happy when
they accomplish their goal, e.g. find what they are looking for. Hedonic consumers
value shopping as an activity in itself; shopping is a pleasant and meaningful
experience, regardless of any purchase (Babin, Chebat & Michon, 2003; Batra &
Ahtola, 1991; Kaltcheva & Weitz, 2006; Wakefield & Blodgett, 1994). Babin et al. (2003)
demonstrated that the environment must suit the purpose for which consumers use
the service. Utilitarian consumers experience an environment differently to hedonic
consumers. Babin et al. (2003) showed that when perceptual appropriateness
for a group is diminished, consumers report lower positive affect, lower product
quality ratings, lower perceptions of personal shopping value and fewer approach
behaviours. They regard congruence of environment and goal as an important
explanation for differences in appreciation of the environment between utilitarian
and hedonic consumers. NS customers can have either motive. Particularly ‘must
motives’ demand a fast and reliable service. By ‘must’ we mean passengers who
regularly and systematically travel by train, such as commuters. For them goal-
orientedness and time play an important role in transport. ‘Lust’ journeys, on the
other hand, are only incidental (i.e. social and recreational transport whereby time
plays a less prominent role). Lust passengers attach greater value to the convenience
and comfort of the journey (SENTA, 2005; Steg, 2004; Steg & Vlek, 1999; Van Hagen,
Peek & Kieft, 2000). The commuters who regularly travel by train are utilitarian-
minded, whereas passengers who use the train for recreational purposes are more
hedonic.

chapter 1 The role of the wait when travelling 7

1.6 Experience economy

In the last three decades, the provision of services has been the focus of numerous
studies. In 2001, Chase and Dasu observed that remarkably little time had been
spent on studying services from the customer’s perspective and, in 1999, Pine and
Gilmore ascertained that the services economy was transforming into an experience
economy, i.e. the experience of the service was becoming more important than the
functional qualities thereof. Pine and Gilmore’s insights have been elaborated on
by various authors (e.g. Beck & Davenport, 2001; Boswijk, Thijssen & Peelen, 2005;
Florida, 2002; Fog, Budtz & Yakaboylu, 2005; Jensen, 1999; Nijs & Peters, 2002; Piët,
2004; Postma & Bruel, 2006; Roberts, 2004; Schmitt 2003, 2004; Thys, 2005; Wolf,
1999).
For more and more services the general tenor is that not only should a good service
be rendered on a utilitarian level but that it should also include the component of
hedonic experiential value. Experiential value will always be created somewhere,
sometime. Pine and Gilmore (1999) compared a service with a theatre, in which
the service environment is the stage, the staff are the actors and the customers the
audience. With the railways the station can be seen as a stage set, with the staff as
the actors. The set must serve the performance and the actors must know their role.
Employees need to know what their personal contribution is to the whole. Not only
must the set be well-maintained, clean and fresh but also the used materials and
colours, the layout and ambiance must logically suit the function and experience of
the service. Hence, whether at a station or on a platform, passengers do not expect
to be confronted with graffiti, broken lights or windows, litter or the stench of urine;
instead they expect a safe environment with a pleasant atmosphere in which they
can spend time in an enjoyable fashion (Falk & Dierking, 1992; Keizer, Lindenberg &
Steg, 2008; Pine & Gilmore, 1999; Wilson & Kelling, 1982).

1.7 The role of time in the choice of mode of

transportation

People who wish to cover a long distance can choose whether they travel by car or
train, opting for that mode of transportation which they feel offers the best quality
in relation to the investment of the three budgets, money, time and effort. It has
become apparent from several studies (e.g. Bovy, 1994; Van Hagen, Peek & Kieft,
2000; Van der Heuvel, 1997), that when making a choice between these two alterna-
tives, people particularly weigh up the differences in reliability, travel time, ease,
comfort, experience and costs. The choice of mode of transportation is determined
for 60% by the speed of both alternatives, with the fastest being favourite (Van den
Heuvel, 1997; Van den Heuvel & Van Goeverden, 1993; Van Wee & Dijst, 2002). To
elucidate the relevance of time when making a choice, Van den Heuvel (1993; 1997)

8 waiting experience at train stations

introduced the concept travel time factor (or TTF). The TTF reflects the respective
difference in door-to-door travel time between public transport and the car. The
smaller the TTF-value, the greater the relative quality of the public transport and
the greater the market share. In Figure 1.1 various TTF-values have been combined
with the market share of the public transport. It shows that when the travel time is
the same, public transport has a 60% share but that this decreases to 20% when the
car – in comparison to the same journey by public transport – is quicker (Van den
Heuvel, 1997). The difference in travel time is the most relevant for the choice
between a TTF-value of 1.2 and 2.0 (area of choice).

TTF-VALUES AND MARKET SHARE PUBLIC TRANSPORT

TRAIN-PROFILE CHOICE-PROFILE CAR-PROFILE

100
Public Transport Share (%)

CAR CAPTIVES

±60

AREA OF
CHOICE
CAR & PUBLIC TRANSPORT TRAVELLERS

±20
30 30 30 30 30 30 30
16 17 18
PUBLIC 19 20
TRANSPORT 21 22
CAPTIVES

0
Travel Time Factor
1.2 2.0
COMMUNICATION SERVICE ACCELERATE PUBLIC TRANSPORT
ENHANCEMENT

Figure 1.1 TTF-values and market share public transport

(Van den Heuvel, 1997; adapted by Van Hagen, 1997)

Research into differences between objective and subjective time estimations with
car and public transport to museums showed that people have a distorted idea
of the actual travel time of either mode of transportation and that the subjective
TTF-values appeared close to 1 (Van Hagen & Meurs, 1992; Van Hagen & Van Wissen,
1993). That travellers usually base their choice on the subjective TTF-value might
lead one to assume that the public transport share would be bigger, but that appears
not to be the case. This means that – besides travel time – a journey by public
transport still differs from a car journey in a number of other ways. Motorists,
for example, can travel directly from home to their destination, whereas train
passengers have to change at the station where they can experience uncertainty
and discomfort as well as be confronted with a waiting time.

chapter 1 The role of the wait when travelling 9

1.8 The pyramid of customer needs

One obstacle in opting for rail travel is having to change trains as it has bearing
on the aspects of safety, speed (travel time), convenience, comfort and experience.
To remove this obstacle, attention must be paid to these aspects when designing a
station as together they form the integral package of customer wishes. Analogous to
Maslow’s hierarchy, the various needs can be ranked according to importance in the
shape of a pyramid (Maslow, 1954; Van Hagen, Peek & Kieft, 2000).
The pyramid of customer needs reflects the perception of the quality offered by NS.
The base of the pyramid is formed by the basic needs reliability and safety. For
passengers, safety particularly means social safety and this is a prerequisite for the
functioning of a station as a public space. If potential customers perceive a station
to be unsafe, they will avoid it. Reliability indicates the degree to which passengers
experience receiving what they expect. If the service is not available when and where
customers expect it, it will result in their being dissatisfied. As already ascertained,
speed is the principal customer need, i.e. the majority of customers choose as short
a travel time between origin and destination as possible. If the condition of a fast
journey and transfer has been complied with, then the traveller wants the change
to be easy, i.e. convenient and with little hassle. Travel information and signposting
are a help and must be seen as logical and unambiguous. Also the traveller expects a
certain degree of physical comfort at the station: sheltered waiting and seating areas
and food and refreshment facilities. Finally, the need of a pleasant experience must
be fulfilled and this is influenced by such visual aspects as architecture, design,
cleanliness, used materials and colours. Besides these, however, also less tangible
environmental variables, such as (day)light, smell and music influence the quality
of experience. Offering facilities such as shops and cafés and the obvious presence
of staff enhance a pleasant stay. Figure 1.2 shows the hierarchy in interests of the
various quality dimensions (Van Hagen, Peek & Kieft, 2000; Peek & Van Hagen, 2002).

TRANSFER: MOVING AND STAYING

STAYING STAYING
experience

comfort SATISFIERS
DISSATISFIERS
ease

MOVING speed MOVING

SAFETY AND RELIABILITY

Figure 1.2 Quality dimensions in order of importance

10 waiting experience at train stations

When travellers move through the station, speed and ease are key, but when they
have to stay at a station, like during a wait, then comfort and experience are vital
(Wakefield & Blodgett, 1994; 1999). In this respect, speed and ease are dissatisfiers
in that these quality aspects are rated negatively if they do not meet expectation
(Herzberg, Mausner & Snyderman, 1959). All passengers set great store by a safe,
reliable, easy and speedy journey. Such dimensions are the bedrock of transporta-
tion; they are generic and apply to each station. Comfort and experience are
satisfiers (Herzberg et al., 1959; Johnston, 1985). They are noticed when the station
is evaluated positively, albeit that the interpretation can vary per passenger. Just
as one passenger wishes to travel first class, eat sushi at a station and admire the
architecture, so is another passenger content to travel second class, eat a rissole
from a vending machine and only see the station as an efficient transfer space.

Various transport scientists employ such a pyramid of customer needs. The interest
layers of this pyramid are supported by several qualitative and quantitative studies.
With the Stated Preference approach (N = 800), for example, the order of importance
of quality aspects for a train journey was shown to be the same as in the hierarchy
of the pyramid of customer needs (Peek & Van Hagen, 2003). Also factor analyses on
different customer evaluations of train passengers (N = 480.000; De Bruyn & De Vries,
2009) and public transport passengers (N = 85.000; Van Beek & Konijnendijk, 2008;
Van Beek, 2009) resulted in different quality dimensions, whereby the quality
aspects at the base of the pyramid are more important than those higher up.
On the basis of group interviews with customers, Preston, Blainey, Wall, Wardman,
Chintakayala and Sheldon (2008) ascertained that a ‘hierarchical pyramid of
needs’ also exists for stations. They concluded: ‘A hierarchical pyramid of needs
was suggested, reinforcing the findings from the literature review. At the base of the
pyramid were basic factors, such as reliability and frequency of service, and at the apex
were enhancing factors such as retail and catering facilities…’ Boes (2007b) demon-
strated that train passengers (N = 1781) at a station rank the following in order of
importance: safety, uncertainty reduction, cleanliness, personal control, overview,
comfort facilities, aesthetics, social contact, relaxation, privacy, spending time
usefully and distraction.

1.9 Door-to-door appreciation of time

As travel is predominantly an instrumental activity, the travel time in the transport

economy is considered a disutility (or travel impedance). From transport studies
it appears that the time perception within a movement is not constant. In a train
chain, the sequence of links are assessed differently. In transport economy terms
the ‘in train time’ is valued the highest, the ‘access and egress time’ are valued
twice as low, and the waiting time up to three times as low (Loehlin, 1959; Mackie,

chapter 1 The role of the wait when travelling 11

Fowkes, Wardman, Whelan & Bates, 2001; Wardman 2004). Waiting is thus the least
useful way to spend time. By decreasing the wait, the passenger experiences less
wasted time (Van Hagen, 1998; 2003). However, by making the waiting environment
more pleasant, so too can the wait be perceived as more useful and pleasant, which
in turn enhances the appreciation of the wait (Peek, 2006; Peek & Van Hagen, 2002).

DOOR-TO-DOOR APPRECIATION OF TIME

high
ORIGIN DESTINATION

GAP OF LOST TIME

Enhance Train journey
the appreciation
Time value

of the wait

Access Egress
mode mode

Transfer Transfer

low
Time spent

Shorten the waiting time

Figure 1.3 Two ways to influence waiting time: shorten the waiting time and enhance
the appreciation of the wait

Figure 1.3 visualizes the appreciation of time with regard to stay and movement
from origin to destination, with ‘time spent’ represented on the horizontal axis
and ‘time value’, or how travellers appreciate the wait in the various links, on the
vertical axis. The product of how the time is spent and how it is experienced is
the value given to the activity. This appreciation can be expressed in usefulness
and pleasure or, to be more specific, in a useful wait and in a pleasant wait (Peek,
2006; Peek & Van Hagen 2002; Peek & Van Hagen, 2006; Van Hagen & Peek, 2006).
With service failures, the experiential value (Zeithaml, Bitner & Gremler, 2006)
can be negatively influenced by the dissatisfiers (safety, reliability, speed and ease)
in the same way as it can be positively influenced by the satisfiers (comfort and
experience). The service can be improved by ‘filling’ the gap of lost time in Figure
1.3 with the aid of the following three strategies: Acceleration, Concentration and
Enhancement (ACE). Acceleration refers to the reduction of the travel time, e.g. by
deploying trains with a higher frequency. Concentration concerns the concentration
of multiple activities (e.g. working, studying, living, shopping) close to a station thus
avoiding time-consuming access and egress (the X-axis in Figure 1.3). Acceleration

12 waiting experience at train stations

and concentration particularly influence the perception of (objective) waiting time.
Enhancement of the appreciation of the wait explicitly influences the affective
experience of the wait, for example by offering distraction during the stay at the
station (the Y-axis in Figure 1.3; Peek & Van Hagen, 2002; 2003; Vaessens, 2005).
The basis of this dissertation is the phenomenon that in people’s perception time
seems to go faster or slower and that waiting is often considered tedious. We have
seen that travellers particularly let their choice of transportation depend on the
travel time, whereby their perception of travel time is their reality. If the perception
of the negatively assessed waiting time can be shortened or made more pleasant
by changing the waiting environment, it could have a positive effect on the evalua-
tion of the journey and persuade travellers to opt for the train sooner. Making the
waiting environment more pleasant can positively influence the affective waiting
time and transform a wait into a stay (Klaase & Peek, 2000; Wolf, 1999).

1.10 How can we make the wait more pleasant?

In collaboration with Bureau SENTA, ProRail and NS explored which aspects of a

station are important for a good evaluation of the quality of stay (Pijls-Hoekstra &
Munck Mortier, 2005). In the first study must and lust passengers visited several
stations and had to indicate what they found pleasant or unpleasant. In a subse-
quent study (SENTA, 2005), the results of the qualitative exploration were tested at
40 stations among both must (N = 3099) and lust passengers (N = 4321).
From the findings it appeared that the respondents at all the stations were satis-
fied the most with the staff and the service but the least satisfied with the station
building. They found the stations unattractive, gloomy, boring, dull, busy and noisy;
they stank, were not a pleasant environment in which to have to wait and emanated
no warmth (SENTA, 2005).
The study also showed that – in comparison with must passengers – lust passengers
were significantly more positive about a number of experiential aspects. Lust
passengers prefer to travel by train, have more confidence in it and sooner recom-
mend train travel and visiting a station. Ultimately, lust passengers feel that they
have spent their time at the station more usefully.
In a follow-up study which took the theory of Customer Relevancy (Crawford &
Matthews, 2001) as its starting point, it appeared after 40 interviews and 8 group
discussions that passengers define experience as: ‘The degree of a pleasant wait/stay
due to a pleasant environment and a certain feeling about the journey on the platform,
at the station and on the train’ (Flow Resulting, 2007). From factor analyses of the
quantitative phase of the Customer Relevancy study (N = 4157), it appeared that
experience is divisible into two: a basic experience, with the focus on safety and
cleanliness, and experience with the focus on facilities and a pleasant environment
(De Bruyn & De Vries, 2009).

chapter 1 The role of the wait when travelling 13

1.11 Central question

We have seen that passengers regard waiting at a station as extremely tedious.

Furthermore, it appears that in order to improve the quality of stations, besides
the traditional strategies of acceleration and concentration, also enhancement
is an important condition for success. With particularly the experience of the
environment being so poorly assessed by passengers at every station, it would seem
that much can be gained here and yet it appears that there is little fundamental
know-how on how to improve a station environment. Specifically, there seems to
be insufficient knowledge of the effects that changing colours, light intensities,
music and/or infotainment have on the emotions and behaviour of customers in a
station environment. At the same time it appears that passengers see waiting time
as lost time and that travel time is the decisive factor in the choice of transportation.
In practice, despite paying attention to the reduction of the objective travel time,
management pays hardly any to positively influencing the subjective perception of
the wait.
Also the theory itself offers sufficient leads to heed the effects of waiting on
customer satisfaction. Waiting is often accompanied by dissatisfaction with the
service, i.e. the longer the wait, the more unpleasant it is (Larson, 1987; 1988;
Katz, Larson, & Larson, 1991; Taylor, 1994; 1995; Van Houten, 1986). Waiting has a
negative influence on emotions, which means that people can feel uncomfortable,
uncertain, frustrated, irritated, demoralised, stressed and even frightened (Dubé-
Rioux, Schmitt & Leclerc, 1988; Gardner, 1985; Katz, Larson & Larson, 1991; Maister,
1985; Osuna, 1985). Irrespective of the length of the wait, satisfaction is influenced
by the waiting context. If people are actively doing something during the wait, are
distracted or if they find themselves in a pleasant environment, then the wait is
experienced as more agreeable (Katz, Larson, & Larson, 1991; Pruyn & Smidts, 1998).
With the focus of this dissertation on making the wait in a station environment
more pleasant, two effects of improvement are expected to occur:
1. Measures that change the waiting environment will have a positive effect on
the experience of the wait, i.e. the length of the wait will be perceived as shorter
(X-axis in Figure 1.3).
2. Measures that change the waiting environment will have a positive effect on the
platform evaluation i.e. will generate positive emotions (Y-axis in Figure 1.3).

The central question is thus:

What is the influence of the station environment on passengers’ station

evaluation, time perception and waiting experience?

14 waiting experience at train stations

1.12 Research design

Figure 1.4 illustrates the set-up of this dissertation. After this introductory chapter,
and with the aid of a qualitative (Delphi) study in various service environments
(e.g. amusement park, museum, airport and hospital), Chapter 2 explores the
consequences of waiting time, its related emotions and possibilities to influence
the waiting experience. Chapters 3 and 4 address the theory of waiting experience
and environmental experience respectively. Chapter 5 is an observation study of the
time passengers spent at four train stations in the Netherlands. Besides objectively
recording the (waiting) time at the station, passengers were also asked about their
perception of time during their stay, how they experienced this emotionally and how
they valued the station building.

RESEARCH DESIGN

Introduction and
Studies Conclusions
relevance waiting time

• CHAPTER 1 • CHAPTER 6 • CHAPTER 9

Waiting experience Colour & light Discussion
• CHAPTER 2 • CHAPTER 7 • CHAPTER 10
Delphi service providers Music Recommendations
• CHAPTER 3 • CHAPTER 8
Experience of time Infotainment
• CHAPTER 4
Environmental experience
• CHAPTER 5
Wait perception stations

Figure 1.4 Set-up dissertation

Chapters 6, 7 and 8 describe manipulation studies in which, after altering/adapting

the environment with the aid of coloured light, music and infotainment, the
subsequent experiences of the respondents were recorded. For these experiments,
empirical studies with manipulated music, coloured light and infotainment were
conducted at regular stations. Furthermore, a virtual station was created in which
the respondents, all train passengers, could move freely as avatars. For practicality’s
sake, the simulations were oriented towards the most frequent situations. This
means that the manipulations were carried out on a platform, because that is
where passengers wait the longest and because the quality of the platforms is the
most negatively assessed. Here, too, the experiments departed from the idea of a

chapter 1 The role of the wait when travelling 15

normal service, without disruptions, as is the most frequent situation. As modera-
tors, ‘a hurry/rush’ was simulated in the form of must and lust passengers, as was
‘density’ in the form of a quiet and busy station. Chapter 9 examines the overall
conclusions and reflects on the research findings and the methods employed before
making recommendations for follow-up research. Chapter 10 finalizes this disser­
tation with recommendations for Netherlands Railways.

16 waiting experience at train stations

 Chapter 2
The waiting
experience of Dutch
service providers

‘Waiting is a form of imprisonment.

One is doing time, but why? One is being
punished not for an offense of one’s own,
but for the inefficiencies of those who
impose the wait. Hence the particular
rage that waits engenders the sense of
injustice. Aside from the boredom and
psychological discomfort, the subtle
misery of waiting is the knowledge
that one’s most precious resource, time,
a fraction of one’s life is being stolen
away, irrecoverably lost.’
Morrow, 1984
2.1 Introduction

In Chapter 1 we saw that waiting time is an important part of the journey for
train passengers but that little is still known about the experience of the wait and
how it can be influenced. Before submerging ourselves in the waiting experience
literature, we will explore the problems Dutch service providers experience who are
also confronted with waiting times. Are they also struggling with the phenomenon
of waiting, are they heeding the waiting environment, and what solutions do they
have?

2.2 Maister’s propositions

Maister (1985) was the first to examine the psychological mechanisms of waiting. He
presupposed that the satisfaction with the service was dependent on the perception
of the wait and not just on the objective waiting time. Maister predicted that waiting
is particularly annoying before the service commences (i.e. the pre-process wait) and
furthermore when one is unoccupied, anxious or uncertain, when the wait seems
to be unfair, when the value of what one is waiting for is low or when one has to wait
alone, and when one does not understand why one has to wait at all (Figure 2.1).
Tested by various scientists, it appeared that the first seven of Maister’s propositions
were confirmed: waiting is tedious and seems to take longer in certain situations,
such as when there is uncertainty or a lack of information (Clemmer & Schneider,
1989; Davis & Heineke, 1993; 1994; 1998; Davis & Maggard, 1990; Dubé-Rioux,
Schmitt & Leclerc, 1988; Grotenhuis, Wiegmans & Rietveld, 2007; Groth & Gilliland,
2006; Hui, Thakor & Gill, 1998; Hui & Tse, 1996; Hui, Tse & Zhou, 2006; Katz, Larson
& Larson, 1991; Larson, 1987; Mann, 1970; Mann & Taylor, 1969; Meyer, 1992; Pruyn
& Smidts, 1992; 1993; Seawright & Sampson, 2007; Taylor, 1994). With proposition 8
it appears that waiting with others strongly depends on the context. Although group
waiting can be positive, so too can negative feelings be stronger in the presence of
others (Pruyn & Smidts, 1998). Davis and Heineke (1993; 1994; 1998) described how
companies themselves can exert influence on the majority of the propositions by
heeding the processes. Effective design of the waiting environment and well-trained
staff positively influence the attitude and emotions of the customer and the waiting
experience (Davis & Heineke, 1993; 1998).
Maister did not prioritize his propositions (Durande-Moreau, 1999) nor did he differ-
entiate between various groups of customers, such as users of functional or hedonic
services (Apter, 2007; Babin, Chebat & Michon, 2003; Batra & Ahtola, 1991; Kaltcheva
& Weitz, 2006; Wakefield & Blodgett, 1994; 1999). We took Maister’s propositions as
the starting point when asking Dutch service providers about waiting experience.

Chapter 2 The waiting experience of Dutch service providers 19

 Maister’s Propositions
1. Unoccupied time feels longer than occupied time. When people having nothing to do, time seems
to pass more slowly. Distraction is a good remedy.
2. Pre-process waits feel longer than in-process waits. Waiting before the service seems to take longer
than when (one has the idea that) the service has commenced. By giving people the impression
as soon as possible that the service has started, they will sooner accept the waiting time (for
example, by distributing the menu at a restaurant).
3. Anxiety makes waits seem longer. Empathizing with the (un)realistic concern of the customer and
dispelling that anxiety helps, such as the fear when it’s very busy that the customer will not be
able to check in on time and miss his plane.
4. Uncertain waits are longer than known finite waits. Waiting in uncertainty takes longer than when
one is informed. When an appointment is late in starting, the “appointment syndrome” kicks in
whereby people calmly wait until the scheduled time of the service, however long it takes. The
moment this point in time has passed, people start to worry and get annoyed.
5. Unexplained waits are longer than explained waits. If one is aware why one has to wait, then the
wait will seem shorter than if one is in the dark. Explaining why one has to wait can help, just as
making sure that staff who are apparently not occupied in solving the waiting problem are out of
the customers’ sight.
6. Unfair waits are longer than equitable waits. Nothing more infuriating to those in line than a
queue jumper. A fair system of “first in, first out” (FIFO) can prevent this.
7. The more valuable the service, the longer the customer will wait. People will tolerate a two-hour
wait for a two-minute ride at an amusement park but are really annoyed if they have to wait after
the service has been consumed, such as when checking out at a hotel, waiting for luggage after a
flight or at the supermarket check out.
8. Solo waits feel longer than group waits. If one can talk to others during the wait, time will pass
quicker than when one has to wait on his/her own. Encourage group processes and prevent
people from having to wait on their own.

Figure 2.1 Summary of Maister’s propositons (1985)

2.3 Objective and central question

The objective of this chapter is to discover whether NS is alone in its struggle

to make the experience of time more agreeable or whether other Dutch service
providers are confronted with the same problem. How do others with waiting times
approach this issue? What are they doing about it? Do they differentiate between
various groups of customers and which measures do they consider the most
relevant?

20 waiting experience at train stations

We expect that customers will value waiting in a more functional environment, such
as an airport or a supermarket, differently to waiting in a more hedonic context,
such as a museum or an amusement park. Moreover, we expect time-bound aspects
to be more important with services purchased from a utilitarian perspective, just
as we expect that pressure (of time) is less relevant with services consumed from a
hedonic perspective (Apter, 2007; Babin, Chebat & Michon, 2003; Kaltcheva & Weitz,
2006; Wakefield & Blodgett, 1994; 1999). This leads to the following central question:

How seriously do Dutch service providers view the waiting problem?

Are there differences between functional and hedonic waiting situations and
what possible improvements do service providers expect from shortening
the waiting time and/or improving the waiting experience?

2.4 Research method

For this study we used the Delphi method (Dalkey & Helmer, 1963; Okoli &
Pawlowski, 2004; Rowe & Wright, 1999), whereby experts are consulted in various
steps on a specific subject with the aim of seeking consensus. The subject in this
case was waiting experience. With the first step information is collected from
individual experts. With the second step all the expert information is collated
before it is resubmitted anonymously to the experts for reflection. The third step
entails the exchange of insights between the consulted experts, after which further
rounds may follow.

2.5 Procedure

With waiting time being a relevant part of the service process for any organization
(Pruyn & Smidts, 1993), NS took the initiative in 2007 to approach nine Dutch
service providers for this study. Between 2007 and 2008 the following organizations
participated: Efteling (amusement park), Schiphol (airport), Elizabeth Ziekenhuis
(hospital), Jumbo Supermarkt (supermarket chain), Postkantoren BV (post offices),
KLM (airline), Spoorwegmuseum (railway museum), ProRail and NS itself. In
total, seventeen people were interviewed. The interviews lasted 1-2 hours and the
interviewees were board members and experts with not only a broad view of the
provision of services but who were also experts in the field of research, logistics,
experience and marketing. A semi-structured questionnaire was used with the
central question being how relevant was waiting in the provision of services and
how did the organization anticipate this. Also investigated was the kind of waiting
time (pre-, post- or in-process), the duration of the wait, the acceptance, employed

Chapter 2 The waiting experience of Dutch service providers 21

solutions and attention by management in the shape of time, money and effort,
such as research into waiting times.
Step 1: A report made of each interview was presented to the interviewees in order
to verify that their opinion had been correctly worded. Any additions and/or amend-
ments were incorporated in a second concept that was resubmitted for approval.
The report was then finalized.
Step 2: Contradictory approaches were deduced from the reports and phrased as
propositions, such as whether or not music was played in the waiting environment
(Efteling: yes versus Schiphol: no), or whether priority was given to certain groups
(Efteling: yes versus Spoorwegmuseum: no). The interviewed experts gave individual
feedback on the propositions.
Step 3: During a seminar the experts jointly exchanged views on the propositions.
New information and insights resulting from this seminar complemented the
previous findings.

2.6 Results

2.6.1 Time and waiting time

It became apparent from the interviews that the time consumers invest in a service
provider can be divided into four groups: travel, wait, process and stay.
The travel time is the time consumers need for the journey to and from the
service provider. On average consumers spend 40% of their time doing this, which
corresponds with the travel time ratio for service providers as found by Dijst (Dijst,
1995; Dijst & Vidakovic, 2000).
The wait consists of the pre- or post-wait, i.e. before or after the service is consumed.
Pre-wait: in a queue: at a checkout, counter, side-show, check-in desk, security
control, ticket-dispensing machine (post office, train station, airport, amusement
park) or not in a queue: for an appointment, number system (hospital, post office) or
scheduled departure time (train or airplane). Post-wait: likewise in a queue (super-
market checkout) or not in a queue (airport baggage claim). The wait comprises 20%
of the time invested by consumers with these service providers.
The process is the time in which the service is consumed and the customer’s full
attention is required for the service. At the Efteling and the Spoorwegmuseum it
is the actual visit, at the hospital it is the appointment, at the post office it is the
dealings at the counter, at a supermarket the checking out and with a train or plane
the getting ready to board and disembark. The process comprises 10% of the total
time.
The stay, finally, is the time customers spend at the service provider’s without
participating in the service process or waiting in a queue. It is the time during which
customers can move freely and undertake activities as they please. Besides the time
spent at the airport or station, the stay also includes the travel time on the plane or

22 waiting experience at train stations

train. The stay comprises 30% of the total time. As the consumer spends half the
time (waiting and staying) with the service provider without being involved in the
service process, the quality of the stay environment is important for the customer’s
perception of quality.

2.6.2 Limiting the wait

With each interviewed organization, customers are confronted with certain
moments in the service process when they have to wait. The experts declared that
waiting too long is a dissatisfier. Waiting is not only unfavourable for the customer,
but ultimately also for the service provider, on the one hand because customers
who are waiting are not free to go shopping, for example, on the other hand because
customers who are waiting have more negative emotions. Both result in less
turnover. An expert from the Efteling: “Let me be the first to say that a long wait is
not only disagreeable but also commercially uninteresting, because someone stuck in
a queue does not spend anything.” An expert from the Spoorwegmuseum remarked
that waiting to pay is even more annoying than waiting to go on a ride: “Waiting at
the cash desk is even more tiresome because no one likes having to wait in order to pay.
In fact what you’re then doing is paying twice: in time and in money.”
It was also observed that customers themselves will do anything to make their wait
as short as possible, even if it means other customers having to wait longer. To begin
with, each organization attempts to reduce the waiting time to an acceptable level
– not too long, but sometimes (deliberately) not too short either. A certain amount of
waiting can even add value to the service, such as the building up of excitement for
a feature at the Efteling. An Efteling expert: “A visitor has to see the Python pass by at
least twice before getting on. That enhances the excitement.”
The experts indicated that the total of invested time and the wait situation deter-
mine the tolerance to the wait. When the service provider shows understanding for
the wait situation and does everything possible to shorten the wait and/or to make it
more agreeable, the wait seems to be much more acceptable. The degree of informa-
tion and the freedom of movement also contribute to the waiting experience. The
better a customer is informed and the more activities (s)he can undertake whilst
waiting, the better the waiting experience is evaluated. Deploying extra staff or
self-service technology (SST), such as a check-in kiosk, a postage stamp or ticket
machine, increases the speed of the service process and shortens the objective
waiting time. Particularly the more experienced customers appreciate this.

2.6.3 Information and attention

Providing information on the whys and wherefores of waiting, dispels much uncer-
tainty and has a positive effect on the emotions and evaluations of customers and
on the perception of the duration (Groth & Gillilian, 1999; Hui & Tse, 1996; Hui, Tse &
Zhou 2006; Taylor, 1994). The interviews revealed that the most important measure
to positively influence the perception of waiting time was to offer real-time, clear

Chapter 2 The waiting experience of Dutch service providers 23

and reliable information. In a functional environment and with purposeful activi-
ties, the sense of control seems to be of overriding importance to the evaluation of
the waiting experience. An expert from Schiphol airport remarked: “We currently
have the walking distances to the gates up on the flight departure screens. Passengers
always orient themselves first, where they are and how far it is to the gate, before being
receptive to exploring the airport. First the stress has to be removed; only then can the
passenger start to relax.” In a hedonic waiting environment accurate information is
less important. An expert from the Efteling: “We are quite reticent about handing out
maps. People have to buy them and they are not exactly ordnance survey maps either. It
has to be an exciting experience to wander round the park.”
If something goes wrong in the service process and customers have to wait longer
than with a functional service, the reason or the blame is soon attributed to the
service provider where one finds oneself at that moment. Only with clearly external
causes, such as really bad weather or a power cut, does the customer understand
that the service provider could not help it. The customer is nearly always under-
standing of a disruption, as long as communications are clear and genuine and take
the customer and his/her emotions seriously. An expert from Jumbo Supermarkets:
“It’s rather a sign of the times that a long wait is soon blamed on the company where the
customer is at that moment. However, if you deal with the situation adequately, you’ll
receive only compliments. For example, if it’s really busy at Christmas and all the cash
desks are open, you just walk round with a box of chocolates and liven things up. Just by
indicating that you know how annoying waiting is works wonders.”

2.6.4 Enhancement
Making the waiting environment more pleasant is one way of helping customers
wait more agreeably. All the organizations pay attention to architecture, interior,
comfort and design. An NS expert: “The lighting at Breda station, for example, was
very expensive but the added value is that the customer him-/herself can press a button
and change the lighting to cool, fab or hip after which 300 metres of concrete columns
will change colour. The additional costs are less than 10% of the budget, but it is what
90% of people are talking about.” Also smell is sometimes used to positively influence
the experience (Schiphol, Efteling, Spoorwegmuseum and Elizabeth Ziekenhuis).
An expert at the Spoorwegmuseum remarked: “Nothing attracts more attention than
a locomotive letting off steam. The sounds and the smell of coal has associations with
the olden days.” Elizabeth Ziekenhuis consciously uses smell to make time spent in
the waiting rooms more agreeable and has opted for citrus aromas because both
children and adults prefer these most. An expert at the hospital: “It’s important to
get the dosage right. That when you come in you think: Hey, that’s nice!” Also offering
distraction with music (Efteling), infotainment (post office, Schiphol), art and
entertainment (Schiphol, Jumbo, NS) will put people in a better mood. An expert at
Postkantoor: “We conducted a pilot at 10 locations with info TV and it appeared from
the accompanying study that waiting was assessed more positively.”

24 waiting experience at train stations

2.6.5 Must consumers and enhancement of the appreciation of
the wait
The goal-orientedness of customers determines how much people dislike to wait.
Must customers are goal-oriented consumers with a focus on function, efficiency
and – particularly – time (Van Hagen, 1999; Van Hagen & Peek, 2006). Research by
Gharbi and Nantel (2005) into shopping on the internet showed that consumers
overestimate the time when under pressure. With organizations such as KLM, NS,
Jumbo supermarkets and Postkantoren, who serve many customers with must
motives, most of their attention is spent on physically shortening the wait (i.e.
reducing the objective waiting time). Attention is focused on production manage-
ment, reducing waiting time through strict management and introduction of
self-service technologies (SSTs). Studies conducted in supermarkets revealed that
the bulk of management attention is focused on stepping up the process (East,
Lomax & Wilson, 1991; Rudolph, Pruyn & Wagner, 2002). A salient detail in our study
was that the interviewees emphasized that the use of SSTs not only decreased the
wait but also gave more experienced customers a greater feeling of control.
An important characteristic of the organizations who serve must motives is that
time for these customers is of the essence. After all, a plane or train departs at a
prescheduled moment. A dilemma when increasing the value of the stay experience
is that customers must be able to feel comfortable without forgetting about the
time. Must customers have to be able to keep their eye on the clock, as it were, and
will take any opportunity to inform themselves. Only when they are certain they
have the process under control, will they ease up on the time and be more receptive
to environmental stimuli (Schiphol, KLM, NS). An expert at Schiphol: “It is a real
dilemma. On the one hand you want to let people forget the time, but on the other they
have to remain alert. At the Efteling, people are receptive to all the stimuli but at the
airport people’s focus is somewhat narrower owing not only to the continuous attention
to the time but often also tiredness.”

2.6.6 Lust consumers and enhancement of the appreciation of

the wait
Hedonic customers are out to enjoy, are more relaxed, pay less attention to the
time and are more receptive to environmental stimuli. Organizations who serve
customers with lust motives, such as the Efteling and the Spoorwegmuseum, are
quite consciously engaged in managing their customers’ emotions, even during the
waiting situation. For lust motives the pressure of time is less relevant; it is even nice
when customers can briefly forget the time.
Measures taken to make the environment more pleasant and offer distraction are
particularly valued by lust visitors. Practical experience plays an important role
when taking measures and their success is defined through a process of trial and
error. At airports and stations besides goal-oriented travellers there are also those
with hedonic motives who experience a succession of emotions during their stay.

Chapter 2 The waiting experience of Dutch service providers 25

A KLM expert referred to travellers’ mood fluctuations as follows: “At check-in the
stress is high but once one has received the boarding pass and been relieved of one’s
luggage, then the stress declines only to rise again at customs and security. Then people
relax and go shopping or eat or drink something before the stress returns briefly at the
gate.”

2.6.7 Maister’s propositions revisited

The majority of Maister’s propositions (1985) were recognized and acknowledged by
the interviewed experts. Only with proposition 2 (pre-process wait) was it remarked
that – depending on the context – post-process waits can certainly be just as bad as
pre-process waits. And as for proposition 8 (group waiting), waiting together can
be pleasant but also unpleasant if there is a bad atmosphere. Here, too, context is
important. An expert from the Efteling on this subject: “Waiting with others in a
queue has its advantages and disadvantages. During the wait you can engage in small
talk with people standing in front of or behind you, like ‘Where are you from?’, but you
will never get too personal in a queue because there are always eavesdroppers around.
It can also be quite infuriating if someone behind you keeps pushing up against you or if
other people’s children jump the queue.” The experts also indicated that particularly
a sense of control (propositions 3, 4, 5 and 6) was important in waiting situations.
If people know why and how long they have to wait, they will accept the wait much
more easily. Genuine attention to the consumer’s anxiety seems to have a positive
influence on the waiting experience.

2.7 Conclusions

If we recapitulate the findings of the Delphi study, then it would seem wise to make
the waiting environment more pleasant in every situation.
Utilitarian customers are goal-oriented and they have to keep an eye on the time
and will avail themselves of any information that can help them. Only when these
customers are continuously ensured that they have the process under control, will
they ease up on the time (i.e. relax) and be receptive to environmental stimuli. Clear,
unambiguous and real-time information on the process and a grip on the time
(clocks!) is imperative for this group of customers.
Hedonic customers enjoy the stay with the service provider, are more receptive to all
kinds of environmental stimuli and distractions and are barely occupied with the
process. They are more relaxed and want (and are able) to forget time.

26 waiting experience at train stations

2.8 Recommendations: three steps of improvement

The experts are unanimous in their observation that waiting is annoying. According
to them, the waiting experience can be shortened or made more pleasant in three
steps:
1. Restrict the wait to an acceptable minimum. Self-service technologies (SSTs)
can help and also offer the (experienced) customer a greater sense of control.
2. Offer clear and reliable information and take the customer seriously,
particularly in a disrupted situation. Only when customers have certainty and
the feeling that they have everything under control, will they be receptive to
environmental stimuli.
3. Create a pleasant waiting environment:
a. by adapting the space with the aid of e.g. design, smell, colour and light, and
b. by offering distraction such as music, infotainment and entertainment.

All of the consulted organizations pay attention to the waiting experience, particu-
larly with regard to providing information and sometimes consciously making
the environment more pleasant with the aid of design, music, colour and light,
infotainment and entertainment. All, however, without any systematic approach or
theoretical framework.
Organizations, such as NS, that serve both utilitarian and hedonic customers, could
develop a two-track policy with which both customer groups feel welcome. This
is possible by emphasizing the efficiency of services and by offering little distrac-
tion in areas where functionality is central, such as the transfer areas. Hedonic
consumers pay less attention to the efficiency of the service process yet really value
a lively environment. So, by offering them this, also hedonic customers will enjoy
their stay.
It goes without saying, however, that as the number of service providers interviewed
was limited, these findings cannot be generalized to other providers.

2.9 From practice to theory

In this study we have seen how service providers deal with waiting situations
in practice. It appeared that despite organizations paying a lot of attention to
decreasing objective waiting time, they pay relatively little to the subjective
waiting experience. The most significant measures concern shortening the wait
and offering real-time and reliable information. With a more functional service
(supermarket, hospital, aviation and rail sector), much attention is paid to the basic
processes yet relatively little to improving the waiting environment. Services that are
more tailored to the hedonic consumer (attraction park, museum) are much more
aware of the subjective waiting experience and the role the environment plays in

Chapter 2 The waiting experience of Dutch service providers 27

this. This study elucidates how improving the surroundings occurs mainly through
trial and error without any fundamental theoretical framework.

We will now move on to the theory in which we will seek an answer to the question
how from a theoretical framework we can optimally organize the environment in
order to make the wait more pleasant. First two chapters with theory on waiting
experience and environmental experience. Then in the following chapters we will
discuss several studies in which the experience of both waiting time and environ-
ment are combined and where we opted for experimental field and laboratory
studies in order to distinguish between cause and effect.

28 waiting experience at train stations

 Chapter 3
Theory of the
waiting experience

‘a day full of waiting, of

unsatisfied desire for change,
will seem a small eternity.’
William James, 1842-1910
3.1 Introduction

The focus in this chapter is on the waiting experience and several theories on time
estimation and emotional reactions during the wait will be addressed. First the
meaning of time will be set in the context of daily life in order to understand better
why waiting is so tiresome.

3.2 What is Time?

In a dissertation that is focused on the experience of waiting time, it does not go

amiss to address the concept of time. All of our activities occur in time and space
whereby time moves in one direction, from past to future, in a linear fashion.
Whereas space is then quite tangible, time is the opposite. It is elusive. One of
the most sagacious thinkers on the subject of time, Augustine (354-430), wrote in
his autobiographical Confession(e)s: ‘What then is time? If no one asks me, I know
what it is. If I wish to explain it to him who asks, I do not know…’. (Sizoo, 1940, p 271).
Augustine hit the proverbial nail on the head. We live in an age when time rules our
life; it is something we are constantly aware of, sometimes more than others. Our
language is larded with time-related proverbs and references but when we have to
explain what time actually is, we are at a loss for words. Time fascinates scientists
and the literature on time is extensive. There is even the International Society for the
Study of Time, a society that regularly organizes conferences following which the
essays are published in The Study of Time series. In Volume VIII of aforesaid series,
Macey estimated that the publications on time in the 20th century alone numbered
180,000 (Fraser, 1996). In fact it is difficult to think of one study in which time does
not play a role, because everything is enacted in it.

3.3 Observation of time

Why is it so difficult for us, just like Augustine, to define time? It is because of a
number of anomalies. For people time is an intangible and abstract notion. We
can observe colours, smells, sound, taste and temperature with our senses but
we lack a special sense that is able to observe time. This implies that we can only
indirectly deduce time from events that we perceive with our senses. Although we
have an internal biological clock which can control our physical processes with
the utmost precision, our consciousness has a hard time getting to grips with time
(Block & Zakay, 1997; Dunlap, Loros & DeCoursey, 2004; Klein 2007; Van Bommel,
2003). The difference between biological, objective and subjective time was first
identified in 1962 in an experiment in which the French geologist, Michel Siffre, had
himself locked in a dark cave for 61 days without a clock. When after that period he

Chapter 3 Theory of the waiting experience 31

was released, he resisted, because he thought that only 36 days had passed (Klein,
2007; Siffre, 1963). Although Siffre’s biological clock more or less corresponded
with the objective time, his subjective time deviated from this quite considerably
(Klein, 2007). Subjective time has no fixed dimension and is influenced by thoughts,
feelings, memories and expectations of activities in a specific time span (Zakay &
Hornik, 1991). Consciousness produces its own time, the internal time that does
not depend on the course of mechanical and biological clocks and leads to our often
over- or underestimating the objective time (Klein, 2007). The only way in which
we can perceive time is because things happen around us (Fraisse, 1984; Poynter,
in Levin & Zakay, 1989). Through the familiar rhythm of everyday life and the fixed
duration of certain activities we are able to hazard a guess at the time and how long
we have been doing something. However, if this routine ceases, our time estimate
soon deviates from the actual time, which is exactly what happened to Siffre in
the cave. We are able to make quite a reasonable estimate, for example, when we
explicitly focus our attention on the time by counting to 60. Sometimes, however,
we are barely aware of the time, such as during a lively conversation or when we are
totally immersed in an entertaining or challenging activity. For a brief moment
we seem to forget the time, which then seems to ‘fly’ (Csikszentmhalyi, 1999). At
other moments time seems to drag on, like when we have to do something against
our will or when we are bored, like when time in the dentist’s waiting room seems
neverending (Hornik, 1982; 1984; Van Hagen, 2008). So, if time can be perceived
both objectively and subjectively, that means we can also distinguish between
objective time perception and subjective time perception. This differentiation is
relevant because, as we saw in Chapter 1, it offers the possibility to influence both
perceptions by shortening the waiting time on the one hand and by making the wait
more pleasant on the other.

3.4 Objective time perception

Each individual experiences his/her own subjective time but the objective time
perception is the same for everyone and can also be accurately measured with clocks
and stopwatches. Diaries and calendars are based on objective time; they structure
our lives and help us to keep our appointments. That to us is the most normal thing
in the world and yet the national time, as we now know it all over the Netherlands,
has only existed for a century. It was the railways that played an important role in
this structuring of time. With the creation of interregional movements over the
tracks and with a timetable that could be executed with minute precision, a national
time became vital. Until circa 1909 each town in the Netherlands had its own clock
time, but the introduction of the train with a timetable made it imperative that the
clock times of various towns were synchronized; train connections would otherwise

32 waiting experience at train stations

have been impossible to plan and travellers would not know how long they had to
wait (Knippenberg & De Pater, 1988; Peters, 2003).
Besides the introduction of national time, the beginning of the 20th century also
saw logistics and operations research being conducted on how to more effectively
deploy staff and resources in order to minimize the waiting time in minutes and
seconds (Buffa & Sarin, 1987; Carmon, 1991; Kroon, Huisman & Maroti, 2008; Pruyn
& Smidts, 1993; Van Dijk, 1996). The development of balanced timetables enabled
passengers being able to travel more quickly and reliably, whilst the waiting times
got shorter (Kroon, Huisman & Maroti, 2008; Kroon, Maroti, Helmrich, Vromans
& Dekker, 2008; Van Dijk, 1996). Introducing national time and implementing the
knowledge from operations research were thus the first measures with which train
passengers got a better grip on the length of their wait.

3.5 Subjective time perception

By shortening waiting time we are taking the objective experience of time in hand
which clarifies the expected duration of the wait. However, measures that shorten
waiting time ignore the subjective experience of time. People whose waits are just as
long might experience the length of time totally differently.
Subjective time can be distinguished into two parts: cognitively and affectively
(Pruyn & Smidts, 1998). If someone guesses how long (s)he has waited, if (s)he finds
the wait short or (un)acceptably long, then this is a cognitive assessment of the wait.
If someone experiences the wait as (un)pleasant, frustrating or boring, then this is
an affective assessment. It is also possible to have a certain attitude toward the wait:
hedonic (pleasant time) or utilitarian (useful time).
In the scientific literature, two research streams can be identified with regard
to the subjective experience of time. The first is that of the time perception and
investigates people’s estimation of time and how accurately they are able to guess
(time) intervals. The second research stream studies the experience of time and how
people cognitively and affectively experience it. We will first examine the estimation
of time before discussing the affective and cognitive assessment of time.

3.6 Protracted duration and temporal compression

In daily life we are usually good at estimating time on the basis of experience
(synchronicity), but there are also special circumstances in which time seems to
proceed faster or slower. These are interesting moments from which to discover
how we experience time. The sociologist Flaherty went into this in depth, analysing
705 interviews in which people described situations in which time seemed to
go either quickly or really slowly (Flaherty, 1993; 1999; Flaherty & Meer, 1994).

Chapter 3 Theory of the waiting experience 33

He concluded that time is only experienced as more slow (protracted duration) when
people are strongly emotionally or cognitively involved, with complex stimuli and
when they are trying to understand something difficult. Flaherty ascertained that
waiting is one of the most common situations in which time seems to go slower. In
contrast, the idea that time seems to be going more quickly occurs with a flow expe-
rience. In a moment of flow the purpose of the activity is clear and the concentration
and sense of control optimal. In a flow experience action and awareness seem to
become a confluence and a person becomes so involved in the activity that he loses
any sense of time (Csikszentmhalyi, 1999; Farmer, 1999; Lotz, Eastlick, Mishra, &
Shim, 2010). The person and the activity become a single Gestalt that apparently
takes place in time but without the person being aware of it. Csikszentmhalyi
alleges that people can only have a sense of time if they observe a certain distance to
themselves. If thoughts or feelings are completely monopolized by something, then
one cannot distance oneself and one’s attention to the passage of time will disap-
pear. Flaherty (1999) calls the accelerated experience of time temporal compression.
Both he and Csikszentmhalyi (1999) identified that the sense of time only returns
later and only then does one realize how long or short one has been doing some-
thing. Protracted time can thus be determined in the present, whereas accelerated
time can only be established afterwards.
In recent decades several theories have been developed to explain the discrepancy
between the objective and subjective experience of time, the most important of
which will be briefly elaborated on below.

3.7 Too much time

Assimilation-contrast theory argues that when there is a discrepancy between

expected and experienced duration people are inclined to (over)exaggerate the
length of time. For example: “I have been waiting here for an hour!” whilst one is
only too aware that it has not been longer than a few minutes. Assimilation-contrast
theory also argues that when expectation and experience are close together it does
not make much difference to people how long they have precisely waited. Only when
the acceptable duration of the wait has been exceeded, do people get the feeling that
they have had to wait much longer than the clock indicates (Luo, Liberatore, Nydick,
Chung & Sloane, 2004; Nie, 2000).
Suppressing emotions as is customary/the norm in most public spaces can also
result in overestimating the time. Vohs and Schmeichel (2003) have demonstrated
that consciously suppressing emotions is arduous and results in overestimating
the time. Vohs and Schmeichel explain this with the ironic monitor theory (Wegner,
1994), in which people, owing to the attention paid to their emotions, remain
‘stuck in the present’, the so-called extended now. In the extended-now state, people
become self-conscious and aware of the time, and unconsciously and continuously

34 waiting experience at train stations

monitor whether they have their emotions under control and undesired emotions
do not surface (Vohs & Schmeichel, 2003). Monitoring is implicitly keeping an eye
on changes and thus also on the time, which then seems to go more slowly (Block &
Zakay, 1997; Vohs & Schmeichel, 2003; Wegner, 1994). With the assimilation and the
ironic monitor theories time goes too slowly for people; basically they have too much
time at a moment that is inopportune for them.

3.8 Too little time

Stress management theory presupposes that people under physical or emotional

stress will experience any waiting time as longer (Luo et al., 2004). This means that
if people are tired or in a hurry and have to wait, or have to wait in an unpleasant
environment, they will experience greater physical or emotional stress and thus
overestimate the wait (Nie, 2000; Taylor, 1994). Stress arises predominantly with
loss of control (Averill, 1973; Klein, 2007). If information is given on the expected
duration of the wait, then the consumer knows what to expect, his stress levels will
decrease and he can focus his attention on other activities which in turn means his
time will be efficiently spent after all (Taylor, 1994). Without information on the
duration, the stress will continue, the consumer will be fixated on the wait and time
will seem to drag on (Nie, 2000). In a hurried and stressed situation time goes too
fast for people; basically they have too little time at a moment that is inopportune
for them (Klein, 2007).

3.9 Processing information and experience of time

Many studies point to people’s internal timer and the fact that they use the visible
occurrences around them to estimate the time. Most theories assume that the way
in which information is processed and the attention to that information has an
influence on our sense of time. A few studies have been published over the years
on how the process of estimating time actually works but they (seem to) contradict
one another. The most important of these studies were the storage size model, the
contextual change model and the attentional model.

3.9.1 Storage size model

Ornstein (1969) presupposed that the sense of time is a positive linear function of
the complexity of the number of stimuli. He employed the metaphor of neurological
storage capacity and alleged that time takes longer the more units of information
(discrete events) are stored per event, the more events take place, the more events
differ from one another and the more complex events are. This is also referred to
as Filled Duration Illusion (Poynter, 1989; Poynter & Homa, 1983; Thomas & Brown,

Chapter 3 Theory of the waiting experience 35

1974). Hence a period in which nothing seems to happen seems (in retrospect) to
have passed more quickly than one in which many different and complex activities
took place. The more attention we pay to external stimuli, the more impressions
we gather that we can remember and even more subjective time can be ascribed to
all those memories whereby the period seems to have lasted longer (Hogan, 1978;
Ornstein 1969).
Ornstein’s hypothesis that empty time seems to pass more quickly than filled
time has been corroborated not only in his own research but also in that of others
(Buffardi, 1971; Burnside, 1971; Goldfarb & Goldstone, 1963; Gray, 1982; Mo, 1971;
Underwood, 1975). The assumption that more complex information leads to an
overestimation of the time has been confirmed in several studies (Underwood, 1975;
Underwood & Swain, 1973), but rejected in others (Curton & Lordahl, 1974; Hicks
& Brandige, 1974; Zakay, 1989; Zakay & Fallach, 1984; Zakay, Nitzan & Gliksohn,
1983), with the conclusion being that time was actually underestimated when the
complexity of information increased.

3.9.2 Contextual change model

With four experiments, Vroon (1970) demonstrated that it was not the number of
stimuli, as Ornstein (1969) alleged, but the change in stimuli and the attention paid
to this that determine how many changes we can remember. The more changes, the
longer time seems to have lasted (Vroon, 1970). Also Block (1978) suggested that the
estimated duration is related to the number of cognitive changes, and this was later
corroborated by Block and Reed (1978). Contextual changes form an indication of
the elapsed time (Block, 2006). In essence, the contextual change model claims that
in a retrospective situation the estimation of the duration is based on the number
of changes during a specific time interval (Fraisse, 1984), or in Fraisse’s words:
‘Psychological duration is composed of psychological changes’ (Fraisse, 1963, p. 219).
Block’s contextual change model was later profoundly adapted by Poynter (1983),
who then named it the segmentation model (Block, 1990; Poynter, 1983). According
to Poynter (1983), the difference between the contextual change model and the
segmentation model is that it is not the number of changes but the relevance of the
changes to someone that determines how much information is consciously remem-
bered. The quantity of information is segmented according to what is relevant
information to someone and the number of segments determine the estimation of
the duration. Few relevant changes have little influence on the estimation of time
and many relevant changes have a good deal of influence on the estimation of time.
Also applicable here is that the clearer the information has been structured, the
clearer the marker of time is, the better the time segment is remembered, and the
longer the estimation of time is (Poynter, 1983; 1989). Poynter and Homa (1983) and
Zakay and Feldman (1991) demonstrated that when the complexity of a task and the
degree of information processing were constant, it was the number of meaningful
segments that determined how long the duration was estimated to be. More

36 waiting experience at train stations

segments and complex information result in the longest estimation of the duration
and simple information and few segments the shortest (Poynter, 1989; Poynter &
Homa, 1983; Zakay & Feldman, 1991). This means that the degree of mental load and
the segmentation are two different factors that individually influence the cognitive
processes responsible for estimating time.

3.9.3 Attentional model

Frankenhaueser (1959) and Priestly (1968) argue that there is not a positive but a
negative linear connection between information processing and the estimation of
time. To this end, Frankenhaueser (1959) introduced the theory of the attentional
model, a theory that incorporated both temporal and non-temporal information
processing. This model was later adapted by Priestly (1968), Thomas and Weaver
(1975) and Zakay (1989). Their premise was the commonplace assumption that it is
empty time that is experienced as being unbearably long and that time in which one
is totally absorbed in an activity ( flow) seems to fly. The hypothesis that empty time
seems to last longer than filled time has been substantiated by extensive research
(for further literature references, see Hogan, 1978). Thomas and Weaver (1975) and
Zakay (1989) hypothesized that time estimation is a cognitive process whereby each
stimulus is perceived by two processors:
1. a timer that processes time information, and
2. a processor that processes timeless (i.e. not time-bound) information.
Zakay (1989) introduced the concept of resource allocation for the distribution of
attention between temporal and non-temporal processing. Apparently, during an
interval, attention can be processed in both ways. Temporal processing implies
that people are consciously aware of the passing of time (for example, by guessing
how long one has already been waiting). Non-temporal processing is the pondering
on issues that are not time-related. The more temporal information is processed,
the longer the interval seems. Pleasant surroundings, information, activities and
other forms of distraction result in less information being temporally processed,
which in turn reduces the perceived waiting time (Baily & Areni, 2006; Thomas &
Weaver, 1975). Macar, Grondin and Casini (1994) demonstrated that when a simple
task has to be executed, much attention is paid to the passing of time, whereas with
a complex task the attention is bestowed on the task itself. Zakay and Block (1997)
later refined the attentional model to the attentional-gate model, in which they
explicitly added the fact that the cognitive timer is only set in motion the moment
someone becomes aware of the time. Zakay and Block (1997) specify this as the gate,
i.e. as if a gate is opened in people’s attention that affords a view of the time (Block &
Zakay, 1997; Wearden, O’Rourke, Matchwick, Min & Mears, 2010; Zakay, 2000).

Chapter 3 Theory of the waiting experience 37

3.10 Retrospective and prospective approach

We have seen that the findings from different studies of time experience can yield
contradictory results. In one study, for example, time was found to go faster with a
difficult, complex task, whereas another study demonstrated that time then seemed
to go slower (Zakay & Block, 1997).
Zakay (1989; 1993) discovered that the difference in prospective and retrospective
time estimation provides a good explanation for the contradictory results. With a
prospective time estimation time is central, but with a retrospective time estima-
tion the respondent does not know that (s)he had to keep an eye on the time. In a
prospective situation the respondent is thus aware of the time and his/her attention
is divided between the (waiting) time and other activities. Zakay and Block (1997)
postulated that if people wait for something, their attention is particularly focused
on the cognitive timer and time seems to pass more slowly. If much attention is
bestowed on timeless information, then time seems to go faster. This also happens
when people know beforehand that they will be asked to estimate the waiting time.
That is why it seems to take forever (i.e. ‘a watched pot never boils’), but why we
forget the time when we are engaged in lively conversation (i.e. ‘time flies when you
are having fun’).
In a retrospective situation the brain draws on the memory in order to estimate
the time, which after all we were not paying attention to. If much has happened
in that time, then the time will seem to have taken longer (Block & Zakay, 1997;
Zakay & Block, 1997; Zakay, 1993). We recognize this when we remember a holiday
in which many activities were undertaken. In retrospect, it seems to have lasted for
ages whereas at the time itself time seemed to fly. During the holiday there was no
awareness of the time, and little attention was paid to it, but when we look back at
it later, it is difficult to imagine that so much happened in so short a space of time
(Flaherty, 1999; James, 1890; Klein, 2007). According to Block and Zakay (1997), with
the storage size and segmentation model employing the retrospective method and
the attentional model the prospective method, the different results can be logically
explained (Block & Zakay, 1997; Zakay & Block, 1997).

3.11 Duration and personality

Also personality plays a role when estimating the time. Not everyone processes
information in the same manner. Hogan (1978) incorporated the personality of
the respondents in his time estimation studies. Based on Eysenck’s theory of
personality (1970), Hogan suggested that extroverted as opposed to introverted
people have a higher level of arousal and a greater need and tolerance for the
processing of external stimuli. For extroverted people in an environment with few
stimuli, he alleged, an interval seems to go slower than that same length of time

38 waiting experience at train stations

does for introverted people who have a lesser need and a lower tolerance for external
stimuli (Eysenck, 1970; 1985). Hogan thus assumes that extroverted people need far
more stimuli and get bored sooner than introverted people.
Zakay tested Hogan’s theory and substantiated his finding that extroverts estimate
the duration as being longer than introverts (Zakay & Fallach, 1984; Zakay,
Lombranz, & Kaziniz, 1984). This endorses the attentional model, where more
attention to complex tasks is at the expense of the attention paid to the time and the
duration is thus estimated as being shorter. Hogan also predicted a U-curve on the
basis of the adaption level principle, whereby the preference of stimuli increases to
a certain optimum, after which overstimulation and aversion to the stimuli occurs
which result in decreasing attention to the stimuli and hence the person’s paying
more attention to the time and estimating it as being longer. People start to get
bored with too few stimuli but also with too many. They disengage themselves. Easy-
listening music during a wait can decrease the perceived duration, just as complex
jazz can increase it (Antonides, Verhoef & Van Aalst, 2002). Zakay and Fallach (1984)
concluded that extroverts are more likely to scan the environment for stimuli and
are thus also more sensitive to time stimuli in the environment, which means
that also the cognitive timer receives attention. Introverts have more attention for
internal information processing, cut themselves off from the environment and their
attention to the cognitive timer is smaller (Zakay & Fallach, 1984). The difference
in people who can tolerate many or few external stimuli could be interesting for a
station environment in view of the difference between must passengers, who are
expected to disengage themselves from the environment and lust passengers, whom
we expect to be more receptive to environmental stimuli.

3.12 Waiting in a station environment

Waiting for public transport differs in a number of ways from waiting for other
services. At stations passengers often wait on the platform. Platforms have a
two-fold function: a transfer function and a wait/stay function. There is no queue
formation on a platform nor are there any formal service rules. The waiting situa-
tion, moreover, usually takes place outdoors, with the wait itself randomly spread
(Durrande-Moreau, 1999). The pre-process wait is regarded as the most tedious
(Durrande-Moreau, 1997; 1999; Maister, 1985; Taylor 1994) and on a platform passen-
gers are confronted with two kinds of these: the pre-schedule wait and the delay.
With a pre-schedule wait the passengers are too early and with a delay the train is
late. At a station passengers are per definition preoccupied with the time. As soon as
one arrives, one looks at the clock to see how much time there is before the train’s
departure, whether it is delayed and whether there is still time to do something.
Waiting in comfort on a platform is really important to passengers (Peek &
Van Hagen, 2002; SENTA, 2005). At small stations the platform is the only place

Chapter 3 Theory of the waiting experience 39

passengers can wait, whereas at large stations they can also spend time in the
main hall, the shops, cafés or restaurants. Nevertheless, whatever the location,
passengers tend to spend most of their time on the platform (Chapter 5). Having the
train in direct sight reduces stress and is for many passengers the reason to opt for
the platform as wait location.

3.13 Stations and attentional model

Apparent from the previous reflection is how decisive the context is in which the
time estimation occurs for the over- or underestimation of the time. The degree of
arousal, emotional involvement and information processing (complex or simple)
and personality (introvert or extrovert) determine how much attention we are able
to pay to the time and thus also how fast it seems to pass (Bar-Heim, Kerem, Lamy
& Zakay, 2009). Zakay and Hornik (1991), Zakay (1989) and Pruyn and Smidts (1998)
suggest that the attentional model is better when estimating time prospectively
just as the contextual change model is better to estimate time retrospectively. In a
wait situation people are mindful of the planned event and time awareness is key.
In a wait situation on a platform, where passengers are waiting for the train, it can
be expected that time seems to go slow. After all, all attention is on the time. This
effect will be stronge r the less a passenger has to occupy him-/herself with. We thus
expect that the focus on time can be approached from a prospective perspective.
This research assumes that the attentional model can be applied to the waiting train
passengers, whereby the challenge is to distract people from the time without their
forgetting about it altogether. Through distraction we expect time in the perception
of passengers to pass more quickly and their (wait) emotions to be more positive.

3.14 Sense of time control

In Chapter 2 we saw how important the sense of control is to customers. At a station

this means that passengers can easily and quickly find their way and that they know
where and what time their train departs. A cluttered or inconveniently arranged
station and a disruption of the schedule cause loss of control of time and space and
create stress. According to the principle of think-feel-act, attribution theory argues
that people cannot deal with uncertainties and unexplainable events and automati-
cally seek a reason (Averill, 1973; Diaz & Ruiz, 2002; Schmitt, 2003). Loss of control is
often accompanied by (intense) emotional reactions, such as annoyance, irritation,
frustration and anger (Lawson, 1965). In order to regain their sense of control
with a delay, customers look for a cause. If people know and understand what the
problem is, then waiting seems to be more acceptable and take less long (Kelly, 1997;
Luo et al., 2004). When no cause is given, the customer attributes the cause to the
service provider (Harvey & Weary, 1984; Weiner, 1980; 1985; 2000).

40 waiting experience at train stations

3.15 Acceptance duration of the wait

To increase the customers’ acceptance of the extra wait, a rail company needs
to disseminate reliable information as soon as possible on the cause and the
(estimated) duration of the wait (Hui & Zhou 1996; Larson, 1987; Parthasarathy &
Kumar, 2002). Zakay (1989) argues that people who have or are given information
on the length of the wait will use this – in accordance with the resource allocation
principle – as an anchor to realistically estimate the duration of the wait, and that
they are usually correct. Besides offering information, the wait can also be made
more acceptable by distracting one’s attention from the time with other activities
(Gilliland, Hofheld & Eckstrand, 1946), or as Taylor puts it: ‘Though attribution for
the delay can make the delayed customer more angry and uncertain, the filling of time
should make the customer less angry and uncertain.’ (Taylor, 1994, p. 60). Chebat and
Gelinas-Chebat (1995) recommend influencing the customers’ mood with e.g. music,
television and design which make the wait more acceptable (Chebat & Gelinas-
Chebat, 1995; Chebat, Filiatrault, Gelinas-Chebat, & Vaninsky, 1995). The mood of
passengers can be positively influenced by adding colour, music or infotainment to
the station environment, and this in turn will result in a more positive assessment
of the service (Hornik, 1993; Turley & Milliman, 2000).

3.16 From time experience to environmental experience

This chapter has broached what time means to us, how our brains process events
in time and how we estimate a duration. The time experience determines whether
we think we have waited for a long or a short time, whether we found the wait to be
acceptable and how we assessed the service. In the station environment the atten-
tional model seems to be the best suited for explaining the subjective time estima-
tion. The context in which the wait occurs is relevant to the way it is experienced
and care must be taken that passengers do not lose control of space (orientation,
crowding) and time (clocks, information). When passengers feel safe and in control
they are expected to be more receptive to other activities or stimuli in the environ-
ment (Taylor, 1994). The wait can then be filled in a useful and agreeable manner
(Peek & Van Hagen, 2002).
Waiting can be positively influenced by making the wait environment more
pleasant. The next chapter will address the influence of the environment on how
the wait is experienced. At the end of Chapter 4 the waiting experience and the
environmental experience will converge in a conceptual model that will serve as a
starting point for a number of field and laboratory experiments to predict how the
environment influences the experience of the wait.

Chapter 3 Theory of the waiting experience 41

 Chapter 4
Theory of
the environmental
experience

‘Saying that time is passing slowly

is essentially saying that it is
unpleasant, and expressing impatience
with continuing experience of the
(bad) situation. On the other hand,
people in a positive mood, enjoying
themselves and their current state
may pay less attention to time, and
when asked to estimate recent
events, will respond that time seems
to be passing more quickly.’
Hornik, 1992
4.1 Introduction

In Chapter 1 we saw that passengers attach importance to a safe, reliable, fast,

easy, comfortable and pleasant journey. In Chapters 2 and 3 we saw that the
sense of control is important for a positive evaluation of the service. As we expect
aforementioned aspects to also play an important role in a station environment,
we will examine these further in this chapter. On discussing the phenomenon of
waiting experience in Chapter 3, we saw that it was not only the duration itself but
also the context in which the wait took place that are important factors in how
the wait is experienced. The context is largely determined by the environment in
which people wait. They perceive stimuli in the environment both consciously and
unconsciously, which results in cognitive and emotional reactions that in turn can
influence the evaluation of the service and people’s behaviour. This chapter brings
time experience and environmental experience together and shows how the wait
and the waiting environment influence the waiting experience of passengers.

4.2 Environmental psychology

When customers are asked about the relative importance of the environment with
regard to more objective variables such as travel time, opening hours, parking
facilities etc., then the importance of the environment usually ends up at the
bottom of the list. In in-depth interviews and with associative techniques, however,
the role of the environment to consumers appears to be far more important
(Dickson & Albaum, 1997; Donovan & Rossiter, 1982). Apparently, environmental
psychology reveals, respondents are not very proficient when it comes to cognitively
articulating how important the environment is to them. In 1985, environmental
psychology was defined by Darley and Gilbert as: ‘The reciprocal and interactive
influences that take place between the thinking and behavior of an organism and the
environment surrounding that organism’ (Darley & Gilbert, 1985, p. 949). Since 1960,
much has been published by environmental psychologists on the relationship
between people and their built environment (Cox, 1964; Craik, 1973; Curnhan,
1972; Frank & Massey, 1970; Kotzan & Evanson, 1969; Mehrabian, 1976; Smith &
Curnow, 1966; Stokols, 1978), and it was Kotler who in 1973 was the first to use the
term atmospherics, defining it as follows: ‘The effort to design buying environments to
produce specific emotional effects in the buyer that enhance his purchase probability’
(Kotler, 1973, p. 50). Kotler ascertained that, besides several service providers such
as airline companies, restaurants and department stores, little was still known
about the influence of the environment in which the service was offered. Many
studies of environmental psychology relate to living, working, shopping, recrea-
tional or institutional environments, such as hospitals, schools and prisons, or to
micro-environments, such as the shelf layout in shops (Donovan & Rossiter, 1982;

Chapter 4 Theory of the environmental experience 45

Vroon, 1970). In 1992 and much to her surprise, Bitner observed how little empirical
research had been conducted on environmental factors and consumer behaviour
and how few theories on the subject had been formulated. Almost two decades later
in 2008, Vischer drew the same conclusion: ‘User considerations are rare and unfa-
miliar in conventional building procurement processes, perhaps because they appear
complex and elusive in comparison to the relative simple and technology-oriented tools
of the builder’s trade’ (Vischer, 2008, p. 239).

4.3 The service environment

In 1992, Bitner undertook a first attempt at categorizing service organizations. To

this end she used two dimensions: the type of service organization, based on who
performs the actions within the servicescape (self-service, interpersonal service and
remote service) and the physical complexity of the servicescape (elaborate and lean).
In the case of NS one can speak of an interpersonal service, because both consumers
and employees perform actions within the servicescape and, owing to the large
number of facilities at a station, one can speak of an elaborate physical complexity
of the servicescape. The servicescape consists of a complex mix of environmental
elements that influence internal responses and behaviour. Bitner (1992) classifies
the servicescape into three elements:
–– Ambient conditions: temperature, sound, music, smell, colour etc.
–– Space function: layout, furniture, equipment etc.
–– Signs, symbols & artefacts: signposting, style, decor etc.

Building on the work of Kotler (1973) on atmospherics, Bitner (1992) on services-

capes and Clemmer and Schneider (1989) and Taylor (1990; 1994) on the influence of
waiting experience on the service evaluation, Baker and Cameron (1996) developed
a conceptual model on the basis of an extensive literature study in which they
indicated how delay in a service environment both directly and indirectly influences
affect. Baker and Cameron (1996) defined the waiting environment according to
Baker (1986) in three components:
–– Ambient elements: intangible: light, temperature, sound and music
–– Design elements: tangible/visible: colour, interior design and furniture
–– Social elements: people: customers and staff

Studies in health environments confirm that patients appreciate light, pleasant

colours, plants, art and distraction in a wait environment (Arneill & Devlin, 2002;
Corey, Wallace, Harris & Casey, 1986; Devlin, 1992; Dijkstra, 2009; Ozdemir, 2010;
Verderber, 1986; Verderber & Reuman, 1987). Besides magazines or TV, distraction
can also consist of special elements, such as an open fireplace, an aquarium, fresh
flowers or a table and chairs. Positive distraction puts people at ease and reduces

46 waiting experience at train stations

stress (Arneill & Devlin, 2002; Klein, 2007; Ulrich, 1991). The ambient elements are
taken for granted and the influence is neutral or negative. By changing the ambient
environment, people’s feelings can be subtly influenced (Donovan & Rossiter, 1982;
Gardner, 1985). The design elements draw more attention than ambient ones and
can be grouped according to aesthetical elements (architecture, style) that stimulate
the senses and functional elements (layout, comfort, signposting) that facilitate
behaviour. The social elements, the number of people in an environment and the
interaction between customers and staff, determine together with the tangible and
intangible environmental elements how comfortable customers feel in the environ-
ment (Baker, 1986; Baker & Cameron, 1996).

4.4 Processing environmental stimuli

The servicescape consists of a wealth of stimuli which are experienced holistically

by the consumer as one single Gestalt (Bell, Fischer & Loomis, 1978; Bitner, 1992;
Holahan, 1982; 1986; Ittelson, Proshansky, Rivlin & Winkel, 1974; Lin, 2004;
Ritterfeld & Cupchik, 1996). The environment emits non-verbal signals that
customers cognitively pick up (Aubert-Gamet, 1997; Baker, Grewal & Parasuraman,
1994; Bitner, 1990; Brady & Cronin, 2001; Gardner & Siomkos, 1986; Golledge,
1987; Kaplan & Kaplan, 1982; Ornstein, 1986; 1992; Rapoport, 1982; Sommer, 1969;
Verhoeven, Van Rompay & Pruyn, 2009a: 2009b; Zeithaml, 1988). Whereas customers
continuously notice every stimulus in the environment, the perception thereof is
susceptible to selective attention, which means that not everything is consciously
perceived (Lin, 2004). Particularly the ambient environmental elements such as
temperature, music and coloured light are mostly perceived unconsciously, i.e. they
only attract attention when they are absent or unpleasant, such as a temperature or
sound level that is too high or too low.
Particularly with a first visit, customers seek indications that suggest or hint at
the quality of the service (Zeithaml, 1988). By doing so, customers can form an
opinion of the quality of the service provider, e.g. whether or not the service is
cheap (Bell,1998), and whether the service provider is trustworthy or successful
(Babin, Chebat & Michon, 2003; Bitner, 1990; Gardner & Siomkos, 1986; Greenland &
McGoldrick, 1994; Lin, 2004; Verhoeven, Van Rompay & Pruyn, 2009b).
It is unclear how this process works and how cognition and affect influence one
another. Lazarus (1982), for example, states that affect is a result of cognitive
processes but others, such as Zajonc (1980), allege that it precedes cognition. The
key seems to lie in the unconscious processing of environmental stimuli. Lin (2004)
gives insight into this process on the basis of Gestalt psychology. In a conceptual
model, she describes how cognition and emotion alternate one another step by step:

Chapter 4 Theory of the environmental experience 47

Step 1: our senses perceive environmental stimuli albeit that the majority of them
are unconsciously processed by our brain. This is a cognitive processing as it is done
by our brain only we are not aware of it. The brain filters out those elements that are
irrelevant to the individual at that moment.
Step 2: the (unconsciously) processed stimuli initiate a (primary) emotional reaction,
and
Step 3: a (possible) cognitive evaluation of this reaction follows whereupon approach
or avoidance behaviour arises.

Recent (brain) research corroborates that many decisions of automated behaviour

are made unconsciously (e.g. Dijksterhuis, Smith, Van Baaren & Wigboldus, 2005;
Dijksterhuis, 2007; Lindstrom, 2008; Mieras, 2007; Wiers, 2007; Zaltman, 2008;
Zaltman & Coulter, 1995).

4.5 Stimulus-Organism-Response Model

Mehrabian and Russell (1974) formulated the stimulus-organism-response (SOR)

model in which environmental stimuli influence approach and avoidance behaviour
via emotions (Figure 4.1).

STIMULUS ORGANISM & RESPONSE MODEL

Emotional states:
Environmental Approach or
Pleasure, Arousal,
Stimuli Avoidance responses
Dominance

Figure 4.1 Stimulus Organism & Response model(Mehrabian & Russell, 1974)

The environment evokes emotional reactions that influence people’s behaviour

(Mehrabian & Russell, 1974). Avoidance behaviour is all the negative behaviour
evoked by the environment, such as wanting to leave, not wanting to explore the
area, feeling no connection with the place and not wanting to return to it. People
prefer to avoid an area they do not feel comfortable in, like an unpleasant, noisy and
disorderly place (Donovan & Rossiter, 1982; Mehrabian & Russell, 1974).
Approach behaviour concerns all the positive behaviour evoked by the environment,
such as wanting to stay there, exploring the area, feeling connected to the spot and
wanting to return there. Approach behaviour can be stimulated by consciously
chosen design and by specific addition of the correct (intangible) environmental
stimuli.

48 waiting experience at train stations

Several scales have been developed to measure emotions, whereby a number of
similar ones (emotions) are clustered in a coordinated dimension. An advantage
of clustering the gamut of different emotions in more abstract dimensions is
that with a small set of questions one is still able to gain a clear understanding
of the emotions roused. In environmental psychology (e.g. Richins, 1997; Turley
& Milliman, 2000), the emotional classification in the three PAD dimensions of
Mehrabian and Russell is often used, whereby PAD stands for:
Pleasure: the degree to which a person feels comfortable or content in an
environment;
Arousal: the degree to which a person is stimulated by the environment;
Dominance: the degree to which a person has a sense of control over the situation.

Each emotional experience can be seen as a combination of pleasure, arousal and

dominance. In a service environment particularly the dimensions pleasure and
arousal play a role, which can be visualized (Figure 4.2) in a circumplex model
(Russell, 1980; Russell & Pratt, 1980). All the emotions have a place in this framework
(for examples see Morris, 1995). Generally speaking, environments that are pleasant
and usually stimulating are evaluated the most positively (Mehrabian & Russell, 1974).

EMOTIONAL DIMENSIONS

pleasant

relaxing exciting

sleepy arousing

gloomy distressing

unpleasant

Figure 4.2 Two emotional dimensions and eight emotional states

(Russell & Pratt, 1980)

Research in retail settings has shown that environmental stimuli influence

customer’s emotions (Yoo, Park & MacInnis, 1998), and that pleasant music, smells

Chapter 4 Theory of the environmental experience 49

and colours result in approach behaviour such as a return visit, friendly behaviour
towards others, spending more money, staying longer and exploring the shop
(Donovan & Rossiter, 1982; Gilboa & Rafaeli, 2003; Mehrabian & Russell, 1974;
Sherman, Mathur & Smith, 1997). Research has also shown that when the environ-
ment is experienced as something of a surprise or concurs with expectation in
terms of arousal, this leads to an increase in spending (Baker, Levy & Grewal, 1992;
Donovan & Rossiter, 1982; Tai & Fung, 1997) and greater satisfaction (Babin & Babin,
2001; Babin, Chebat & Michon, 2003; Matilla & Wirtz; 2001). A strongly stimulating
environment that is very busy leads to too much arousal and less pleasure (Baker,
Levy & Grewal, 1992). So, the appropriateness of the environment is important and
for utilitarian and hedonic consumers can result in different behaviour (Babin,
Chebat & Michon, 2003; Foxall & Greenley, 1999). Whereas utilitarian consumers pay
less attention to the environment and more to the quality of the service, hedonic
consumers’ approach behaviour is stimulated via affect by attractive surroundings
(Ang & Leong, 1997; Babin et al., 2003; Baker, Levy & Grewal, 1992; Turley & Fugate,
1992; Wakefield & Blodgett, 1994, 1999).
With relatively small interventions, such as art, music or pleasant advertising,
an attractive environment and thus also a useful or pleasant wait can be created
(Hornik, 1992; 1993; Turley & Milliman, 2000). Such measures are reasonably easy to
achieve in a station environment.

4.6 Crowding

As we have seen, design, ambient and social factors determine how passengers expe-
rience and assess the environment. In stations the social factor is highly important
because it might be either extremely busy or extremely quiet. We expect that the
degree of crowding influences how people feel at a station and how they evaluate the
station. The perception of crowding is a psychological frame of mind in which the
demand for space is greater than the available space (Stokols, 1972). Research into
perceived crowding differentiates between human density (crowding) and spatial
density (Eroglu, Machleit & Chebat, 2005). Although both kinds of density interact
with one another, researchers designate human density as the most important
aspect of perceived crowding (Evans & Wener, 2007; Harrell, Hutt & Anderson, 1980).
Crowding correlates negatively on the degree of pleasure and affects the satisfac-
tion with the service and the behaviour (Babin et al., 2003; Eroglu & Harrell, 1986;
Eroglu & Machleit, 1990; Hui & Bateson, 1991; 1992; Langer & Saegert, 1977; Machleit
& Eroglu, 2000; Stokols, 1972). Crowding goes hand in hand with an increase in
arousal and psychological stress, because people feel that they are restricted in the
available space (Lawrence & Andrews, 2004; Stokhols, 1972; Wijk & Luten, 2001).
Too much crowding soon leads to attentional overload (Bell, Fischer & Loomis, 1978;
Eroglu, Machleit & Barr, 2005; Gilboa & Rafaeli, 2003).

50 waiting experience at train stations

In 2000, Turley and Milliman suggested that too little crowding could also evoke
negative emotions, e.g. in a deserted bar or disco. In a hedonic environment, such as
a disco, on the other hand, crowding is evaluated positively (Pons, Laroche & Mourali,
2006). So it is the context that determines whether crowding is appreciated or not.

4.7 Sense of environmental control

On account of its density, its complexity and the time pressure, a station can evoke
feelings of uncertainty and insecurity, which slows down the time perception
(Bar-Haim, Kerem, Lamy & Zakay, 2010). Research into how Dutch train stations
are experienced has revealed that the reference points of passengers, such as clear/
convenient organization, the flow, the visual orientation and the accessibility, do
not score high (SENTA, 2005). At a station passengers have to get the train on time
and we expect them to evaluate the station more positively if they experience greater
control. With personal control an individual is convinced that in an environment he
or she can effect a change for the better (Greenberger, Strasser & Cummings, 1989;
Oldham, Cummings, Mischel, Schmidthe & Zhan, 1995). Greater control leads to
greater pleasure, greater involvement, a better mood, more arousal, a better attitude
and greater approach behaviour (Hui & Bateson, 1991; Ward & Barnes, 2001). More
arousal in an environment experienced as negative results in an increase in the level
of stress (Averill, 1973; Mehrabian & Russell, 1974). Research by Taylor (1994) into the
influence of delay on feelings of uncertainty and irritation at an airport, showed a
negative connection between these aspects. The longer the delay lasts, the stronger
the feelings of uncertainty appear to be. Supplying information, if up-to-date and
reliable, reinforces the sense of control (Hui & Bateson, 1991; Katz, Larson & Larson,
1991). Also the deployment of technology-based self-services, as long as they are an
extra choice, can reduce the uncertainty and help to acquire more control over the
service (Reinders, Dabholkar & Frambach, 2008; Reinders, Van Hagen & Frambach,
2007). On the platform passengers look for signs/pointers to determine where and
when their train will leave. A good station layout and efficient information services
allow passengers to orientate themselves quickly and prevents unnecessary confu-
sion (Nie, 2000).
Despite the fact that stations are safe, objectively speaking, a station environment is
experienced to be less so particularly in the evening (Boes 2007b; SENTA, 2005). So,
passengers can also feel unsafe at a station. Graffiti, overdue maintenance, neglect
and uncleanliness often evoke feelings of insecurity (Keizer, Lindberg & Steg, 2008;
Walsh, Craik & Price, 2000; Wilson & Kelling, 1982). Indecent, excessive and illegal
behaviour of others likewise result in one’s feeling unsafe, particularly when one
is in an unfamiliar place and both formal and informal supervision is lacking
(Blöhbaum & Hunecke, 2005; Florida, 2002; Putnam, 2000; Skogan, 1990).

Chapter 4 Theory of the environmental experience 51

4.8 Comfort experience

The environment influences people’s physical well-being. On the basis of studied

literature, Baker and Cameron (1996) ascertained that for many environmental
stimuli, such as light, temperature and the volume and tempo of music, there is
a basic level at which most people feel comfortable. This phenomenon has been
termed as collative dimensions, whereby arousal arises through complexity, novelty
and uncertainty. Too much of this affords much arousal, which is visualized in the
inverted U-curve of Wundt (Berlyne, 1971; Wundt, 1910; Figure 4.3), and which is
known as optimal arousal theory (Hebb, 1955; Apter, 1982; 2007). Here, optimal is to
say an optimal presentation of stimuli for the task at hand that leads to an optimally
pleasant experience, the so-called hedonic tone (Apter, 2007). Too few or too many
stimuli result in discomfort, in feelings of negativity and in a negative perception
of the wait (Baker & Cameron, 1996; Berlyne, 1971; Donovan & Rossiter, 1982; Gilboa
& Rafaeli, 2003). Extreme temperatures and/or light intensity, too garish colours,
uncomfortable furniture or too much density draws people out of their comfort
zone (Baker, Levy & Grewal, 1992). If people feel physically uncomfortable, they will
not only assess the aspects of comfort more negatively but also those aspects that
have nothing to do with comfort at all (halo effect), such as affectively responding
to strangers (Griffitt, 1970). In 1982, Donovan and Rossiter ascertained that arousal
in an attractive (retail) setting is the ultimate mediator for the duration of the stay
and they anticipated that arousal in very unpleasant surroundings would initiate
avoidance behaviour.

SERVICESCAPE & COMFORT ZONE

pleasant
OPTIMAL AROUSAL
Hedonic Tone

COMFORT ZONE:
In control, certain, safe
Different colours & light
Different music
Different infotainment

Bored Stressed
unpleasant
low AROUSAL high

Too deserted Too crowded

Too dark Too much light
Too quiet Too much noise

Figure 4.3 Inverted U-curve (Berlyne, 1971; Wundt, 1910)

52 waiting experience at train stations

4.9 Optimal arousal and waiting experience

The various theories on waiting experience in Chapter 3 can be logically linked to

the theory of optimal arousal (Figure 4.4). Too few or too many stimuli result in
time being experienced as taking longer (protracted duration), or in other words,
when too much or too little happens in a period of time then it leads to unpleasant
feelings and an overestimation of the duration. Too few stimuli follow assimilation
theory and the ironic monitor (Luo et al., 2004; Nie, 2000), too many follow stress
management theory (Luo et al., 2004). In the middle, people are in the comfort zone
and the context (goal-orientedness, crowding) defines whether attention is on the
time or on non-time-bound activities. Depending on the perspective, prospective
(attentional) or retrospective (storage size, segmentation), people over- or underesti-
mate the time.

OPTIMAL AROUSAL & TIME PERCEPTION THEORIES

pleasant
OPTIMAL AROUSAL
(Synchronicity)
Temporal compression
Protracted duration
Hedonic Tone

Storage size theory

Segmentation model
Attention model

unpleasant
low AROUSAL high
Too much time Protracted duration Too little time
Assimilation-contrast theory Stress management theory
Ironic monitor

Figure 4.4 Optimal arousal theory (Berlyne, 1971) and time theories

4.10 Waiting experience and environmental experience

Waiting has a negative influence on emotion. Usually waiting goes hand in hand
with discontent with the service, whereby the longer people have to wait the more
tedious it is (Hornik, 1984; 1992; Hui, Dube & Chebat, 1997; Katz, Larson, & Larson,
1991; Taylor, 1994; Van Houten, 1986). However, if people are actively engaged in
something during the wait, if they are distracted or can wait in pleasant surround-
ings, then the wait is experienced as more pleasant (Katz, Larson, & Larson, 1991;

Chapter 4 Theory of the environmental experience 53

Pruyn & Smidts, 1998). From Pruyn and Smidts’ research (1998), it appeared that
the greatest irritation occurs when people have to wait relatively long, when they
are in a hurry and have nothing to occupy themselves with during the wait. There
is less irritation if the wait is shorter than expected and if people wait in pleasant
surroundings (Pruyn & Smidts, 1993).
A negative mood has a negative influence on the waiting experience. People in a
bad mood pay more attention to their bad mood than they do to external stimuli.
Conversely, people in a good mood are not so preoccupied with the cause of their
disposition and are more receptive to environmental stimuli. The consequence of
this is that particularly people in a good mood are inclined to underestimate the
waiting time (Hornik, 1993). Hornik (1984; 1992; 1993) found that people in a good
mood are more future-oriented, whereas people in a neutral or negative mood were
more present-oriented (extended now).
Baker and Cameron (1996) illustrate how the physical environment of an organiza-
tion determines the perceived waiting time and in which way environmental
elements can be employed to influence the perceived waiting time. With light there
seems to be a basic level that is suitable for a certain task. The higher it is above
this basic level, the more negative affect there is and hence the longer the perceived
wait (Van Bommel, 2003). Music produces positive affect and shortens the perceived
waiting time (Tom & Lucey, 1997), but the higher the volume above a desirable level,
the longer the perceived wait. As for colour, the warmer it is (in terms of tint, bright-
ness and saturation), the more negative the affect and the longer the waiting time
perception (Baker & Cameron, 1996). Also for temperature applies that the further
it is from an acceptable level, the more negative affect it evokes and the longer the
perceived wait. In a nutshell, too much or too little (of the wrong) stimuli negatively
influence the sense of well-being, causing the wait to seem to last longer.

4.11 Reversal Theory

With his reversal theory (2007), Apter builds on optimal arousal theory, but argues
that depending on the situation, there is not one but two preferred levels of stimula-
tion: one high and one low. The state in which one finds oneself determines which
level of stimulation is required. The telic state is the mood in which people need
little arousal. In such a mood, people are more serious and more goal-oriented.
In the paratelic state, on the other hand, people need more stimuli; they are more
light-hearted/playful and spontaneous. In the paratelic state it is not the goal-
orientedness but the participation in an activity that gives satisfaction. The telic
and paratelic states are those people desire at certain moments. If there is tension
between the desired state and the state one finds oneself in, then avoidance behav-
iour arises, just as approach behaviour arises when the desired situation is in sync
with the experienced situation (Apter, 2007).

54 waiting experience at train stations

Figure 4.5 shows two curves that represent the systems of the telic and paratelic
state, whereby the telic state is the arousal avoiding system and the paratelic state is
the arousal seeking system. People can ‘suddenly’ switch from one state to the other
due to a (sudden) event (contingency), frustration or satiation (Apter, 2007; Smith &
Apter, 1977).

REVERSAL THEORY
pleasant
relaxation excitement paratelic
telic
Hedonic Tone

OPTIMAL AROUSAL THEORY

boredom anxiety
unpleasant
low AROUSAL high

Figure 4.5 Inverted U-curve and psychological reversal (source: Apter, 2007)

Walters, Apter and Svebak (1982) have demonstrated that people wish to see
soothing colours when they are anxious or relaxed and stimulating colours when
they are bored or excited.

4.12 Utilitarian and hedonic consumers

People often enter an environment with a certain purpose, which might be

utili­tarian (task-oriented) or hedonic (recreational) (Batra & Ahtola, 1991; Foxall &
Greenley, 1999; Katcheva & Weitz, 2006; Umesh, Pettit & Bozman, 1989; Westbrook &
Black, 1985). Task-oriented consumers process environmental stimuli particularly
cognitively (Wakefield & Blodgett, 1994; 1999), and they have an extrinsic orientation
whereby satisfaction arises when they accomplish their goal. Those who shop for
pleasure in a complex and highly stimulating environment (high arousal) appreciate
the surroundings more than those who are goal-oriented shoppers (Kaltcheva &
Weitz, 2006; Westbrook & Black, 1985). Recreational consumers process environ­
mental stimuli particularly affectively (Wakefield & Blodgett, 1994; 1999), and
they have an intrinsic orientation whereby participating in the activity itself gives
satisfaction (Deci, 1975; Deci & Ryan, 1985). Besides the motivational orientation,

Chapter 4 Theory of the environmental experience 55

also the familiarity with the surroundings and the available time will influence how
the environment is assessed.
People with little time or who are unfamiliar with the station will have a greater
task-related orientation than those who know the place well or who are not in a
hurry. Task-oriented consumers appear to get irritated more quickly and are sooner
dissatisfied when the environment is different than expected, whereas customers
with a recreational motive appreciate different surroundings per definition
(Machleit & Eroglu, 2000). Not only do utilitarian consumers want to spend as
little energy on an activity as possible, but also as little time as possible. Hedonic
consumers are less time-sensitive (Davis, 1991; Davis & Heineke, 1998; Davis &
Vollmann, 1990; Luo et al., 2004; Osuna, 1985). In 1976, Harell and Hutt suggested
that people who are impatient or time-sensitive react more affectively to crowding in
a shop than those who are not. In this way, a traveller in a hurry might perceive the
environment differently to someone with all the time in the world. Waiting under
pressure, moreover, seems to have the greatest influence on the satisfaction with
the service (Davis & Heineke, 1998; Davis & Vollmann, 1990; Harell & Hutt, 1976;
Machleit, Eroglu & Mantel, 2000, Nie 2000; Unzicker, 1999), and results in time being
overestimated (Gharbi & Nantel, 2005). The task-related and recreational orienta-
tion can also be found amongst people at train stations, namely as lust and must
passengers (Chapters 1 and 2). Boes (2007a) demonstrated that with Dutch train
passengers (N = 1781) it was must passengers who appeared to find the aspects of
privacy, spending time usefully, peace, waiting alone, a fast flow and knowing how
to get to the platform more important than lust passengers did. Lust passengers, on
the other hand, find facilities, service, a warm atmosphere, sufficient and comfort-
able seating and a sense of control more important. Lust passengers have more
requirements that are connected to recreation, whereas must passengers have more
requirements that are connected to speed and functionality (Boes 2007b; Davis &
Heineke, 1998; Davis & Vollmann, 1990; Kaltcheva & Weitz, 2006; Van Hagen, De Gier
& Visser, 2005). Ang and Leong (1997) expect must passengers to be less receptive to
extra environmental stimuli and lust passengers to be quite the opposite.

4.13 Difference between people with regard to

sensitivity to environmental stimuli

With the optimal arousal curve in Paragraph 4.9 we could see that the environment
influences people’s cognitive, emotional and physical state. All the same, not every
individual reacts identically in the same environment. It all depends on moderating
variables such as personality and situation. One person might be more arousal-
oriented and able to tolerate more stimuli than another, and yet even that can
change from situation to situation. Extroverted people appear to be more receptive
and perform different tasks better with background music than introverted people

56 waiting experience at train stations

(Furnham & Allass, 1999). In Chapter 3 we could see how differently extroverts and
introverts experience the time (Hogan, 1978). Mehrabian and Russell (1974) distin-
guish between screeners and non-screeners, with the screeners filtering out many
environmental stimuli and non-screeners being more receptive to environmental
stimuli (Dijkstra, Pieterse & Pruyn, 2008; Donovan & Rossiter, 1982; Mehrabian
& Russell, 1974). It is the situation that dictates whether people are screeners or
non-screeners. With a raised level of arousal, goal-oriented consumers are unable
to perceive more cues around them (Easterbrook, 1959), filter out more informa-
tion and are sooner bothered by crowding than those who are not goal-oriented
(Donovan & Rossiter, 1982; Eroglu & Machleit, 1990; Kaltcheva & Weitz, 2006; Lewin,
1943). With the aforementioned reversal theory we saw that task-related consumers
in the serious and goal-oriented telic mode can bear fewer stimuli than recreational
consumers who find themselves in the less serious and more light-hearted paratelic
mode (Apter, 2007; Kaltcheva & Weitz, 2006).

4.14 Reversal Theory and motivational attitude

If we combine reversal theory with the perspective of utilitarian and hedonic

consumers, then we should be able to place the must and lust passengers in two
situations. The must passengers are in the telic state and are mainly preoccupied
with information processing and watching the time. They are possibly less receptive
to environmental stimuli and hanker for a lower level of arousal. Lust passengers
are in the paratelic state, are expected to be more receptive to the environment and
value a higher level of stimulation more. It is expected that lust passengers will show
more approach behaviour in entertaining company with music and warm colours.
However, that same kind of company, music and stimulating colours can form a
barrier to goal-oriented must passengers, who in such a situation are expected to
show more avoidance behaviour. Moreover, because they are more sensitive to time
and more in a hurry, must passengers will get irritated or anxious sooner by a delay.
They want to leave as soon as possible.
Figure 4.6 shows that must passengers can find themselves in the situation of
anxiety and aspire after the optimum of relaxation. Lust passengers, on the other
hand, can find themselves in the boredom mood and hanker after the optimum of
excitement. However, in accordance with optimal arousal theory, both groups can
also experience too many or too few stimuli, as is visualized on the right and left
side of the parabola in Figures 4.3 and 4.6.

Chapter 4 Theory of the environmental experience 57

 TWO OPTIMAL AROUSAL LEVELS
pleasant
relaxation excitement
must
lust TWO OPTIMAL AROUSAL LEVELS
Hedonic Tone

boredom anxiety
unpleasant
low AROUSAL high

Figure 4.6 Optimal arousal theory, psychological reversal and must and lust
passengers (after Apter, 2007)

4.15 Conclusion

In Chapter 3 we saw that people’s attention is divided between activities that are/
are not timebound (Zakay, 1989). Much proof was moreover found in the literature
for a negative relationship with waiting time perception, affect and the evaluation
of the service (Clemmer & Schneider, 1989; Hornik, 1984; Katz et al., 1991; Pruyn &
Smidts, 1998; Taylor, 1994). In this chapter we have seen that the environment is to a
large extent perceived unconsciously (Dijksterhuis, Smith, Van Baaren & Wigboldus,
2005), and that the environment influences cognitive, affective and behavioural
reactions. In this dissertation we follow the line of reasoning of Baker and Cameron
(1996), who make a connection between the service environment, affect and waiting
time perception with a delay on the basis of the SOR model of Mehrabian and
Russell (1974). In their model, Baker and Cameron integrate the cognitive timer
model (Zakay, 1989) and conclude that affect has an impact on the service environ-
ment which influences the waiting time perception, whereby too many or too few
stimuli evoke negative feelings causing the wait to seem to last longer.
The SOR model (Mehrabian & Russell, 1974) is the starting point for the studies of
this dissertation with the stimuli from the station environment inducing emotional
and cognitive reactions via the senses and initiating approach or avoidance
behaviour. In the organism the stimuli are processed cognitively and affectively.
Two streams can be distinguished, whereby the attention is divided in accord-
ance with the attentional model (Zakay & Block, 1997) between time-bound and

58 waiting experience at train stations

non-time-bound stimuli. It is expected that the waiting experience is more negative
when attention is consciously focused on the time. Various stimuli have been used
as input in the studies that can be placed in front of the model as a kind of filter.
On the one hand these are ambient variables, such as music, coloured light, which
have an influence during the wait via pleasure, arousal and dominance on the waiting
time perception and the waiting experience. On the other hand, design elements
are capable of distracting one from the time and making the wait more pleasant.
Advertising and infotainment can be deployed as explicit distractors.
Our studies will take the following moderating variables into account: the duration
of the wait and the social environment variables: must and lust passengers and
‘degree of density’.
Passengers who are waiting for a train are aware of the waiting time and – in
accor­­dance with the attentional model – it is expected that they will overestimate the
duration of the wait. Furthermore, we expect passengers, who think their wait has
been short, to be more positive and thus find the wait more acceptable, to expe-
rience their wait as useful and pleasant, to evaluate the duration of the wait and the
platform more positively and show more approach behaviour. Finally, we expect to
see a moderating effect for the degree of density on the platform. (Must) passengers
will be less receptive to environmental stimuli in a dense crowd in comparison with
(lust) passengers in a quiet situation. In such a case we expect reversal theory to be
applicable (Apter, 2007; Walters, Svebak & Apter, 1982).

Before discussing the studies examining the influence of the environment on the
station and waiting experience, Chapter 5 will first address a study in which we
ascertained what length of time passengers actually spent at a station, how long
they waited and how they assessed their waiting time. The study concludes the first
part of this dissertation in which we addressed the theory and practice of waiting
time. The second part discusses the experimental studies and starts with an
introduction. In the chapters that follow the various studies will be discussed per
subject (colour and light, music, and advertising and infotainment). This disserta-
tion will end with conclusions, a discussion and recommendations for both further
research and Netherlands Railways.

Chapter 4 Theory of the environmental experience 59

 Chapter 5
Waiting experience
at Dutch stations1

‘Neither a wise nor a brave man

lies down on the tracks of history
to wait for the train of the future
to run over him.’
Dwight D. Eisenhower, 1890-1969

1 This study has been submitted for publication in Transport Policy.

5.1 Introduction

Travelling costs time, money and effort. People are thereby inclined to opt for the
line of least resistance, i.e. with as little exertion as possible, as cheaply as possible
and with as little delay as possible. Time, money and effort are the three budgets on
which passengers must draw in order to realize movement between one place and
another (Dijst, 1995). In today’s affluent society, money and physical exertion are less
and less of a restriction for consumers. We are, however, under increasing mental
pressure and for many of us time is scarce. As a result of this, not money but time is
becoming increasingly important when choices have to be made (Ackerman & Gross,
2003; Gourville, 2006; Grotenhuis, Wiegmans & Rietveld, 2007; Jensen, 1999; Kotler
& Stonich, 1991; Pine & Gilmore, 1999).
Research and investments in the railway sector have long been aimed at shortening
the train journey, particularly with the optimization of the objective waiting and
travelling time (Mackie, Fowkes, Wardman, Whelan & Bateson, 2001; Peek &
Van Hagen, 2002; Wardman, 2004). The timetable is fixed to the exact minute and
the resulting calculations give insight into the extra number of passengers that
can be expected as a result of shortening the journey (Huisman, Kroon, Lentink &
Vromans, 2005). These efforts are geared to minimize the wait at the station and
thus to accommodate the time shortage of passengers. Less attention is paid to
the passengers waiting at the station and how they experience this wait, i.e. the
subjective waiting and travelling time. How long passengers are actually at a station,
as compared with how long they think they have been there, how they feel there and
the value they attach to the wait is still unclear. Yet it is this subjective (waiting)
time perception that often appears to be a good predictor of consumer satisfaction,
as is also the strong influence of the waiting environment (Pruyn & Smidts, 1998;
Taylor, 1994).
By specifically tailoring the waiting environment, Netherlands Railways (NS) can
possibly make the journey more pleasant. A more pleasant journey will create
more satisfied and loyal customers and can generate more trips. This chapter aims
to contribute more insight into the perception and evaluation of waiting time at
NS stations. We carried out an explorative study at four Dutch train stations to
investigate how long travellers stayed at the station and how long they thought that
they stayed there. We also asked them how they evaluated the service and environ-
ment of the station. Before explaining the methodology and procedure of this study,
we will first have a look at some presumptions based on the literature on waiting.

Chapter 5 Waiting experience at Dutch stations 63

5.2 Hypotheses

5.2.1 Overestimation of the wait

In a station environment, it is of primary importance for passengers to get the
train on time. In this specific service environment, travellers will be time-oriented
because they are primarily focused on getting on the right train at the right time.
Usually, a short wait for the train is unavoidable, and passengers’ perception of time
is prospective. Under these conditions, they are predominantly time-oriented and
this leads to our formulating the following hypothesis:

H1: Passengers who are waiting at the railway station and on the platform will
overestimate their wait.

5.2.2 Active or idle time

However, passengers are also likely to engage in entertainment and distractions
while waiting. Eating or drinking, reading a newspaper, talking to other people
or making a telephone call are all specific activities in which attention may be
drawn away from the time passing (Maister, 1985; Pruyn & Smidts, 1998). Travellers
engaging in such activities may become so fully absorbed in them that they even
forget the time, also known as the ‘time flies when you are having fun’ phenomenon
(Csikszentmhalyi, 1999; Zakay & Hornik, 1991). Therefore we propose:

H2: When passengers have something to do during the wait, their attention is distracted
from the time and they will be less inclined to overestimate the waiting time than those
who do not engage in any activity.

5.2.3 Short and long waits

In the transport sector only a few studies are known to have been carried out on
the perception of the wait in public transport (bus, tram) and at airports (Baaijens,
Bruinsma, Nijkamp, Peeters, Peters & Rietveld, 1997; Hess, Brown, & Shuop, 2004;
Moreau, 1992; Need & Nieuwenhuis, 2003; Pruyn, Smidts & Van Dijke, 1999; Taylor,
1994). Moreau (1992) found that people who are waiting for a bus or tram tend to
overestimate their waiting time. It turned out, however, that the shorter people
had to wait, the greater the overestimation. With longer waiting times, sometimes
up to 15 minutes, passengers even appeared to slightly underestimate the waiting
time. These results were also found in research focused on time estimations, an
effect known as Vierordt’s law, which states that short waits are overestimated and
long waits are underestimated (Boring, 1942; Brown, 1995; Lejeune & Wearden,
2009; Woodrow, 1951). This effect may be understood in terms of a tendency
for perceptual judgments to regress from extreme values to the midpoint of the
stimulus range (Bobko, Schiffman, Castino, & Chiappetta, 1977; Helson, 1964). In
the case of waiting for public transport it may be argued that passengers, who have

64 waiting experience at train stations

just arrived at the station are idly waiting for the bus or train to arrive and are more
focused on the time passing, hence overestimate their waiting time. Passengers who
have been waiting for a long time might lose their focus on time for at least a short
period. They might have started to look for some distraction or engage in activities,
like reading or talking, whereby they did not keep track of the passing time and thus
underestimate their waiting time. We therefore expect that:

H3: The shorter the objective wait, the more the duration is overestimated.

5.2.4 Delays and negative emotions

Railways are service providers and passengers’ appraisals are largely determined
by the actual, moment-to-moment experiences. A service that runs smoothly is
indispensable for keeping customers happy. Almost intrinsic to this is nevertheless
the occurrence of ‘service failures’ (Zeithaml, Bitner & Gremler, 2006). Within the
context of railway stations, delays occur when such failures arise and travellers are
often concerned that their train will not be running on time. Delayed travellers
are prone to negative emotions and will ultimately be dissatisfied with the service
provider (Baker & Cameron, 1996; Hui & Tse, 1996; Groth & Gilliliand, 2006; Hui, Tse
& Zhou, 2006; Taylor, 1994). Baker and Cameron (1996) proposed that people who
experience more arousal during the wait will also overestimate the waiting time
more strongly. Taylor (1994) studied travellers who experienced a delay at airports
and found that they evaluated the service more negatively, especially when they were
in a hurry (Taylor, 1994). Negative emotions have been found to negatively affect
time perceptions (Hornik, 1992; Tipples, 2008). Passengers who experience a delay,
experience more negative emotions. We therefore propose:

H4: Delayed passengers will experience more negative emotions than non-delayed
passengers. Moreover, delayed passengers will overestimate the (duration of the) wait
more than non-delayed passengers.

5.3 Method

In order to find out how much time passengers spend at the station and how
they experience their time and stay there, a combined research was carried out
whereby observations were linked to a structured questionnaire. Fifty research
assistants (students) from the University of Twente paired up and inconspicuously
followed every tenth passenger from the moment he/she entered the station to the
moment he/she got on the train. Subsequently, questionnaires on the perception
of both station and time were handed out in the train to those passengers who
were followed and observed, as well as to a number of other passengers who were
not but who boarded the same train. The choice for this rather roundabout and

Chapter 5 Waiting experience at Dutch stations 65

time-consuming method was made because it is almost impossible for passengers
to give a correct assessment of the duration and emotions at the station and on the
platform retrospectively (Pruyn & Smidts, 1999). Moreover, if the respondents had
been asked to fill in the questionnaire on the platform, this would have directly
influenced the results (and the assessment of the service), i.e. time on the platform
would thus have been filled, whereas on the train passengers had more time to fill
in a questionnaire anyway. The students followed and interviewed passengers at
and from four medium-sized train stations in the Netherlands (Enschede, Deventer,
Zwolle and Amersfoort). These stations were specifically chosen because both the
numbers of people getting on and off the train and their location were similar.

5.4 Procedure

The research assistants divided themselves into pairs among the four stations
according to a pre-arranged plan. One of the two assistants recorded the observed
behaviour of the respondent using an MP3 player which recorded the time in
seconds. The moment the observed respondents got on the train, they were asked by
the second assistant whether they would be willing to participate in a study on the
perception of railway stations. The second assistant then supervised the respondent
whilst he/she filled out the questionnaire. As the train left the station, the first
assistant stopped the MP3 player and randomly distributed the same questionnaire
among passengers who had not been followed but who boarded the train at the
same station. The questionnaires were collected as soon as the respondents had
filled them in. On the return journey both assistants filled in a registration form
with the aid of the recordings on the MP3 player. This form is a precise log of the
respondents’ activities at the station/on the platform and the time they took.

5.5 Research instrument: questionnaire and

registration form

Both the actual length of time spent at the station and the delays were recorded in
a registration form. Actual length of stay was measured by clocking the exact length
of the time passengers spent at the station and on the platform (from arrival at the
station to the departure of the train). Perceived length of stay was measured by asking
the passengers to indicate in the questionnaire how long they thought they had been
at the station and on the platform. The questionnaire also measured the evaluation
of waiting time, activities performed at the station, the emotions experienced and
evaluation of the station.
Evaluation of waiting time was measured with three items. Passengers were first
asked how they had experienced their time at the station (1 = went very quickly,

66 waiting experience at train stations

5 = went very slowly). Subsequently they were asked to what degree they had spent
their time in a useful and pleasant manner (1 = not at all, 5 = perfectly well).
Passengers were asked also to indicate which activities they had performed at the
platform (reading, talking, eating/drinking, looking round).
Station evaluation was measured by asking passengers to give an overall score (from
1 to 10; the higher the score, the more positive the overall evaluation) for the station.
They also had to indicate how irritated (1 = not at all, 5 = quite severely) they had felt
at this station.
Passengers were also asked how they felt on the platform. With previous research
conducted by Netherlands Railways among 1509 railway travellers (Van Hagen,
2007) having deduced the most relevant emotions or feelings for railway travellers,
five emotions were selected: disconcerted, distressed, irritated, alert and observant.
In the present study, passengers could indicate to what extent they felt these
emotions during their stay on the platform (1 = not at all, 5 = extremely). Finally, they
were asked whether their train was delayed or not.

5.6 Results

A total of 181 subjects were randomly selected for observation. Of these, 130 agreed
to participate in the study by filling in the questionnaire (28% non-response).
Another 758 (non-observed) passengers also cooperated by filling in the question-
naire. The non-response among non-observed passengers was in line with previous
studies of Netherlands Railways (59%). Of the total of 888 respondents, 47% were
male and 53% female. Their average age was 32 years (SD = 16.49), with ages varying
from 13 to 84 years.

5.6.1 Duration of the wait at the station and on the platform

It appeared that passengers spent on average 7 minutes and 7 seconds at a station
(N = 129, SD = 07:24). On the actual platform passengers spent on average 4 minutes
and 56 seconds (N = 120, SD = 06:11). This means that at these stations passengers
took on average just over 2 minutes between entering the station and arriving on the
platform and hence spent 62% of the total duration of time at the station actually on
the platform. No differences were observed between the four stations in this study.

5.6.2 Perception of waiting time

A comparison of the actual lengths of waiting observed (objective waiting time
– OWT) and those perceived by the passengers (subjective waiting time – SWT)
indicated that passengers overestimated the wait on average by 01:36 (SD = 06:08).
Proportionally this is an average of 23%, whereby more passengers overestimate
(60%) than underestimate the wait (40%).
The results convincingly support our proposition (H1): Waiting times at the station
and on the platform are overestimated.

Chapter 5 Waiting experience at Dutch stations 67

5.6.3 Time perception and performed activities
When we look at the differences between people who were actively doing something
(reading, talking, eating/drinking, looking around) and those who were not, then
it appears that the passive people significantly overestimated the time spent at
the station (3 minutes and 3 seconds as opposed to 31 seconds for active people),
(F(1, 102) = 4.82, p = .03: Table 5.1). Our proposition (H2) that when passengers are
busy on the platform, they will be less inclined to overestimate the waiting time than
passengers who do not engage in any activity, was supported by these findings.

Table 5.1 Mean difference in actual time and perceived time

Performed activities No performed activities

(N = 53) (N = 51)
M (SD) M (SD)
Perceived time – Clock time 0:00:31 0:03:03*
(0:06:20) (0:05:20)
Note: * p < .05

5.6.4 Delay
Passengers who were delayed found that the time passed more slowly in comparison
with those who experienced none (F(1,782) = 64.32, p < .001). This supports our
proposition (H4): Delayed passengers will overestimate the (duration of the) wait more
than non-delayed passengers.
A multivariate analysis of variance (MANOVA) revealed that the 5 emotions (discon-
certed, distressed, irritated, alert and observant) were affected by the occurrence
of a delay (F(5, 660) = 12.61, p < .001). People with a delay scored significantly higher
on all of these emotions (Table 5.2). Moreover, those who had been delayed also
awarded a significantly lower score for their evaluation of the station (F(1,772) = 7.63,
p < .01) (Table 5.2). This means that when a service failure such as a delay occurs, this
will reflect on the evaluation of the station. The findings supported the first part of
our proposition (H4): Delayed passengers will experience more negative emotions.

Table 5.2 Average score (10-point scale) and (SD) for the station and the accompanying
emotions (5-point scales) of people who did/did not experience a delay with the train

No delay Delay
M (SD) M (SD)
Disconcerted 1.2 (.57) 1.4 (.82)**
Distressed 1.3 (.72) 1.4 (.85)*
Irritated 1.3 (.67) 1.9 (1.15)***
Alert 2.2 (1.09) 2.5 (1.14)**
Observant 2.4 (1.12) 2.6 (1.13)*
Score station (1-10) 7.1 (.84) 6.9 (.81)**
Note: * p < .05, ** p < .01, *** p < .001

68 waiting experience at train stations

5.6.5 Short and long waits
When focusing on differences between OWT and SWT on the platform (Paragraph
5.6.2), a few passengers who waited a relatively long time appeared to influence the
average waiting time more strongly than the majority of passengers who waited
only briefly. In order to check whether this causes a bias in the interpretation, we
also determined a Time Sense Factor (TSF) per individual. This TSF2 shows the
difference in a ratio SWT/OWT and appears to be 1.90 at the station and 1.95 on
the platform, which means that on average passengers overestimate their time
spent at the station and the platform by almost 100%. We also tested to what
extent the length of stay (at the station and on the platform) affected the over- or
underestimation of the time. The waiting period was thus divided into four time
blocks (Table 5.3). Based on studies by Hui and Tse (1996) and Moreau (1992), we
decided to distinguish between 4 time blocks: shorter than 5 minutes, 5-10 minutes,
10-15 minutes and longer than 15 minutes.
Table 5.3 shows that passengers with a short wait – less than 5 minutes – over­
estimate the duration at the station more (factor 2.6). The longer one has to wait,
the closer the estimation is of the actual waiting time. Passengers who waited
between 5 and 10 minutes still slightly overestimated the waiting time (1.35),
passengers who waited between 10 and 15 minutes appear to be the best appraisers
of time (with a TSF of 1.05). Finally, passengers who waited longer than 15 minutes
underestimated their wait at the station by one quarter (factor 0.75). The results are
in line with Vierordt’s law (Boring, 1942; Brown, 1995; Lejeune & Wearden, 2009;
Woodrow, 1951), which states that shorter time intervals are overrestimated and
longer time intervals are underestimated (Paragraph 5.2.3). The platform is the spot
where passengers spend most of their waiting time. If we determine the TSF on
the platform, then it appears that time there is also overestimated despite the fact
that passengers seem to have a clearer notion of time. People who spent less than
5 minutes on the platform overestimated the wait with a factor 2.4. Under longer
waiting conditions the factor eventually decreases to 1. Interestingly, there appears
to be no underestimation of time spent on the platform, not even under the longest
waiting conditions (>15 minutes).
These results support our proposition (H3): The shorter the objective wait, the more
the duration is overestimated.

2 TSF: Time Sense Factor = the subjective waiting time divided by the objective waiting time
per experimental subject.

Chapter 5 Waiting experience at Dutch stations 69

Table 5.3 Means Time Sense Factor of wait on platform and at station

Station < 5 min 5-10 min 10-15 min > 15 min Total
N 55 29 9 13 106
Minimum 0.00 0.12 0.44 0.32
Maximum 10.00 3.43 2.08 1.15
M 2.60 1.35 1.05 0.75 1.9
SD 2.22 0.92 0.63 0.26 1.85
Platform < 5 min 5-10 min 10-15 min > 15 min Total
N 63 22 7 7 99
Minimum 0.0 0.0 0.44 0.33
Maximum 17.14 2.88 1.79 1.81
M 2.40 1.22 1.08 1.00 1.95
SD 3.66 0.71 0.44 0.50 3.0
Note: Time Sense Factor = the subjective waiting time divided by the objective waiting
time per experimental subject.

5.6.6 Time and station experience

On scrutinizing the link between the duration of the wait and the evaluation of the
station, it appears that the longer the subjective waiting time, the more irritated the
respondents were. This significant relationship applies to both the estimated time
on the platform and the estimated time at the station (F(3,699) = 11.24, p <.001 and
F(3,696) = 10.04, p <.001 respectively). On the other hand, the shorter passengers
thought they had to wait, the more useful they thought their time was spent
(F(3,782) = 7.05, p <.001). These results are irrespective of the fact that one might
or might not have experienced a delay. In itself this has a logical bearing. People
who have had to wait longer are more annoyed than those whose wait was short
(Table 5.4).

Table 5.4 Menas irritation, entertainment on platform and at station versus

length of time

< 5 minutes 5–10 minutes 10–15 minutes > 15 minutes Total

Irritation platform 1.30a 1.52b 1.55b 1.88c 1.44
Irritation station 1.30 a 1.34a 1.57b 1.76b 1.46
Time pleasantly spent 4.70 4.69 4.65 4.55 4.66
Time usefully spent 3.69a 3.41b 3.04c 3.16bc 3.38
Note: Means with various superscripts (a, b and c) differ significantly in the row.
Scale: 1 = not at all, 5 = extremely.

70 waiting experience at train stations

5.7 Conclusion and recommendations

In the present study we observed that passengers appear to overestimate the waiting
time at stations. The shorter the wait, the greater the overestimation of the waiting
time. Passengers who spend 15 minutes or longer on a platform have a clearer
notion of the actual time spent there. When they spend 15 minutes or longer at the
station, they underestimate the time.
Passengers particularly overestimate the waiting time when they have nothing
to do and when they are delayed. The perception of both subjective time and the
station are significantly linked to the feeling that one has spent the time usefully
or pleasantly. This confirms the findings by Hornik (1992; 1993) who states that
customers who experience more pleasure will experience a shorter wait compared
with customers who experience an unpleasant stay. The experienced time pressure
plays an important role in the arousal and emotions felt, particularly with delays.
The results confirm the findings of Baker and Cameron (1996), namely that people
who experience more arousal will overestimate waiting time more and the findings
of Zakay (1989), that people who pay more attention to the passage of time will
overestimate the wait more.
Passengers’ subjective perception of time differs from the actual length of the stay.
As a rule, the length of the wait is overestimated. Despite the fact that passengers
at stations are so focused on time – aware as they are of the exact departure time of
their train – there is a considerable discrepancy between clock time and experienced
time. When passengers have a long wait at a station, they tend to underestimate
the time. One explanation might be that people who have to wait longer at a station
will undertake activities and forget the time, hence the underestimation. This is
supported by the fact that when travellers wait less than 5 minutes or more than
ten minutes they award the overall station a higher score, than when their wait was
between 5 and 10 minutes. A long wait is experienced as acceptable as a short wait;
travellers have time to undertake other activities, like shopping. On the platform
there is no question of underestimating the time. The explanation for this might
be that people on a platform do not undertake many activities but stand or sit idly
waiting for the train to arrive. Meanwhile they keep a close eye on the time and the
longer they have to wait, the more precisely they know just how long they have been
waiting. Moreover, the platform offers fewer distractions and fewer possibilities to
fill the time than elsewhere at the station.
Our findings concur with those of previous research which shows that shorter
waiting times are overestimated more than longer ones (Hirsch, 1956; Lejeune &
Wearden, 2009; Moreau, 1992). Passengers who are delayed experience significantly
more arousal and negative emotions (irritation, disconcertion and distress). It is
also clear that people who undertake activities overestimate the time less, are less
aroused and have more positive emotions than those who do not. They also feel that
they have spent their time at the station more usefully. Apparently, people are able

Chapter 5 Waiting experience at Dutch stations 71

to fill their ‘spare’ time with activities which help them to temporarily forget the
time and feel better because of it.
All in all, this study has confirmed that time is of the essence to train passengers.
The question is whether passengers actually experience this time as ‘waiting time’
or that waiting at a station/on a platform is a luxury that only few passengers can
afford. Time at a station, in fact, is primarily and purposefully devoted to catching
the train on time and train operators should do all they can to facilitate this.
Irritation and stress are luring and will influence the perception of time (Van Hagen,
Galetzka & Pruyn, 2007).
Passengers attach considerable importance to time. For those in a hurry to catch
their train on time, time will pass too quickly. For others with more time, if not
spent in a pleasant or useful way, this will be regarded as lost time.
Given the fact that people will always have to wait, it is advisable to particularly
invest in making the platforms more pleasant; the spot where passengers spend
on average more than 60% of their time and where the chance of overestimating
the time is highest. Moreover, the evaluation of the platforms is significantly lower
than for the rest of the station. Passengers attach importance to a pleasant waiting
environment. It is thus not only advisable to keep waiting times to a minimum
but also to enhance the attractiveness of the waiting environment, such as with
the purposeful deployment of atmospheric elements. A pleasant environment is
conducive to passengers’ forgetting the time and passing a more positive judgement
on their time spent there (Baker & Cameron, 1996; Pruyn & Smidts, 1998; 1999;
Turley & Milliman, 2000). Making the waiting environment more pleasant can
be achieved by stimulating the senses in such a way that passengers experience a
maximum level of comfort. Possibilities are to offer sufficient shelters and seating,
pleasant background music, to use congenial and calming colours or to offer suffi-
cient distraction, such as a beautiful view, something to read or television screens
offering infotainment. Further research will have to establish the degree to which
atmospheric elements can contribute to a more pleasant waiting environment in a
railway station. The effects of such measures on platforms will be addressed in the
following chapters.

72 waiting experience at train stations

 Part II
Influencing
the environment

‘How waiting time is experienced

depends predominantly on
unconscious processes that
can be primed by relatively
cheap interventions.’
Ad Pruyn, 2010
 Introduction to
the experimental
studies

‘It appears that the relationship

between time spent in the retail
environment and atmospheric
variables is both complex and not
universal. It appears that some
environmental stimuli affect time
perceptions while others do not.’
Turley and Milliman, 2000
Introduction
In the previous chapters we discussed the theory of waiting experience and saw
what it means in practice to Dutch service providers and to stations in particular.
In the following chapters we will find out by means of empirical studies whether
the insights found in the literature can also be found in a station environment. A
station environment differs from the often studied retail environment in a number
of ways. In a station environment, for example, time is of the essence, because the
departure of the train is scheduled and passengers do not want to miss it. Hence
they are tense, because if they arrive (too) early or their train is delayed, they have to
wait. A wait is experienced as lost time and tedious. Waiting for a train differs in a
number of ways from waiting in a retail environment. When you are waiting for the
train there are no formal (waiting) rules, there is no queue formation and passen-
gers invariably wait in the open air. On the other hand, like in a retail environment,
one can distinguish between utilitarian- and hedonic-oriented customers, with
also on a platform very busy periods alternating with very quiet ones. Due to the
special characteristics of the station environment, emotions and waiting might be
experienced differently to what has been reported in the literature.
This PhD thesis will address which stimuli have an effect on emotions and
behaviour in the station environment. Subsequently, we will discuss a conceptual
model that presupposes that environmental stimuli initiate emotions that together
with the waiting experience determine the evaluation of the station. Finally, we will
address the research methods used and discuss two moderators, passenger type
and density, which we suspect influences the station and waiting experience.

Atmospherics
The studies investigate the influence on the waiting experience of three environ-
mental variables: coloured light, music and advertising & infotainment. We chose
these three environmental variables because they are in keeping with the model of
the servicescape, as used by Baker (1986, Paragraph 4.3), and because they can be
relatively easily manipulated in a real station. This is in line with research stressing
that servicescapes are perceived holistically (Mattila & Wirtz, 2001), implicating
that environmental factors do not act in isolation but interact with customer’s
needs to create the overall experience of the service setting. The three dimensions
distinguished by Baker (1986) are: ambient, design and social.
Ambient factors are invisible, like temperature, smell, noise, music and light. These
factors are often unconsciously or subliminally perceived and are only noticed when
they have exceeded an acceptable limit, such as light that is too bright or music that
is too loud. The assumption is that influencing ambient elements can have positive
effects on the emotions of the passengers, the waiting experience and the evaluation
of the station environment with regard to density and passenger type. We manipu-
lated the ambient environment with music and light. Our choice for music was

Chapter 5 Waiting experience at Dutch stations 77

made not only because some research has already been conducted on its effects in a
waiting environment (Oakes, 2000; Oakes & North, 2008; Tai & Fung, 1997; Turley &
Milliman, 2000), but also because music in a station environment is relatively easy
to realize thanks to the presence of loudspeakers (Baker, Grewal & Parasuraman,
1994; Baker, Levy & Grewal, 1992). Also the light intensity on a platform is easy to
manipulate and appears to influence passengers’ experience (Biner, Butler, Fischer
& Westergren, 1989; Butler & Biner, 1987; Van Bommel, 2003). Hence we studied the
influence of light intensity on the waiting experience of passengers.
Design factors concern visible, functional and aesthetical elements, such as
architecture, colour, style and interior design. In studies on environmental design,
colour, advertising and infotainment were manipulated. Colour can influence
the perception of the environment (Berman & Evens, 1989; Brengman & Geuens,
2004; Golden & Zimmerman, 1986). An internally conducted study by NS revealed
that passengers regard the platform environment as being grey, bland and boring
(SENTA, 2005, Chapter 1), and with modern techniques, such as ambilight, colour
can be easily and flexibly introduced to the environment and ameliorate the wait.
Advertising and infotainment can be employed as explicit distractors. The presence
of advertising and the speed with which the images change are assumed to distract
passengers from their eye on the clock and which in turn will also result in their
experiencing the waiting time as being shorter and the waiting experience as being
more pleasant (Brown, 1995; Dennis, Newman, Michon, Brakus & Wright, 2010).
Social factors concern the people in the environment, both personnel and
customers, whereby their numbers, type and behaviour infuence the environmental
perception (Baker, 1986; Baker & Cameron, 1996; Baker, Grewal & Parasuraman,
1994; Baker, Levy & Grewal, 1992). At rush hour there are many passengers at a
station, but in off-peak hours there are often very few (SENTA, 2005). In the studies
of this dissertation, density, as a social component of the environment, was manipu-
lated by comparing a busy station environment (many passengers) with a quiet one
(few passengers).
Besides environmental factors also other factors play a role in how the station and
the waiting time is experienced, such as personality and motivational orientation.
At a station one can distinguish between goal-directed passengers and those in a
hurry who wish to catch their train (must passengers), and passengers who have
more time on their hands and are in less of a hurry (lust passengers). As we expect
this motivational orientation to determine how the environment is experienced,
our studies will also compare the experiences between must and lust passengers.
The studies in this doctoral thesis hence tests the theories of time experience and
environmental influence by manipulating a number of environmental characteris-
tics. In this way we can ascertain how the process of environmental influence in a
station environment actually works with our findings possibly also being applicable
to similar environments.

78 waiting experience at train stations

Overall design
According to the SOR model, environmental stimuli influence cognitive and
affective processes which in turn determine approach or avoidance behaviour
(Massara, Liu & Melara, 2010; Sweeney & Wyber, 2002). As we saw in Chapter 4, the
environment influences through its degree of arousal the hedonic tone, the sense of
control and the waiting experience. Together these three factors determine approach
or avoidance behaviour. In the studies the hedonic tone is measured with pleasure,
and the sense of control is measured with dominance. The waiting experience is
measured with the time perception, the experience of the duration and the accept-
ance of the wait. Together this ultimately results in a station evaluation measured
with a platform or station score and a waiting time evaluation measured with a
pleasant (hedonic) and useful (utilitarian) waiting experience.
In Chapter 4 we saw that, depending on the context, two levels of optimal stimula-
tion can be distinguished that influence the hedonic tone (Apter, 2007; Paragraph
4.14). The combination of the number of environmental stimuli (few or many)
with density (quiet or busy) or motivational orientation (must or lust) determines
how passengers experience the platform and the wait. This is why our studies
distinguish between two different environments: a stimulating versus a calming
one. A calm environment is created with few enviromental stimuli, such as cool
colours, dimmed lighting, soft music, little distraction and few people on the
platform. A stimulating environment, on the other hand, is created with warm
colours, a high light intensity, stimulating (up-tempo) music, distraction and many
people on the platform. A separate study showed that goal-directed passengers are
more concentrated on what they are doing and are less receptive to environmental
stimuli (Appendix 4). That is why we expect a stimulating environment to result
in a lower hedonic tone for must passengers than for lust passengers. Various
authors have ascertained that the degree of congruence of the number of stimuli
in relation to the goal-directedness of the consumer or the experienced crowding
determines the experienced pleasure (Eroglu, Machleit & Chebat, 2005; Kaltcheva
& Weitz, 2006; Massara, Liu & Melara, 2010; Oakes & North, 2008). In psychology,
congruence implies that someone’s needs, desires and preferences concur with
the situation in which one finds oneself. Incongruence between need and situation
means that people feel more uncomfortable in that situation (Matilla & Wirtz, 2001;
Pruyn & Wilke, 2001; Spokane, Meir & Catalano, 2000). Research has shown that
(in)congruence between various aspects of a product design results in a better (or
worse) processing fluency and thus also in a more positive (or more negative) product
evaluation (Van Rompay, Pruyn & Tieke, 2009). According to Masara, Liu and
Melara (2010), a high level of pleasure is attained with an optimal level of activation.
Goal-directed consumers experience more pleasure with little arousal and much
dominance (hypo-activation) and non-goal-directed consumers experience more
pleasure with much arousal and little dominance (hyper-activation; Massara, Liu
& Melara, 2010). Many environmental stimuli, such as a busy platform, demand a

Chapter 5 Waiting experience at Dutch stations 79

great deal of mental attention and can be experienced as too stimulating, whereas
a lack of stimuli, such as on a quiet platform, can be felt to be tedious. Figure 1
visualizes the relationship between arousal with dominance on pleasure (Massara,
Liu & Melara, 2010).

RELATIONSHIP PLEASURE, AROUSAL, DOMINANCE IN SOR-MODEL

AROUSAL
Must: low arousal
Lust: high arousal

Environmental
PLEASURE APPROACH
stimuli

DOMINANCE
Must: high dominance
Lust: low dominance

Source: after Massara, Liu & Melara, 2010

Figure 1 Relationship PAD emotions in SOR model

By combining the arrangement of Massara, Liu and Melara (2010) with the states of
Apter’s reversal theory (2007), the following four groups can be distinguished:

–– Many stimuli + crowded + must: non-congruent à Anxiety

–– Many stimuli + crowded + lust: congruent à Excitement
–– Few stimuli + quiet + must: congruent à Relaxation
–– Few stimuli + quiet + lust: non-congruent à Boredom

Figure 2 shows the different states of Massara, Liu and Melara (2010) placed in
reversal theory (Apter, 2007).

80 waiting experience at train stations

 ACTIVATION, CONGRUENCY AND REVERSAL THEORY
pleasant (score platform, pleasure, approach, pleasant & useful wait)

Hypo-activation: Hyper-activation:
congruent congruent

relaxation excitement
must
lust
Hedonic Tone

Too quiet Too crowded

understimulation boredom anxiety overstimulation
unpleasant
low AROUSAL high
high DOMINANCE low
Hypo-activation: Hyper-activation:
non-congruent non-congruent

Figure 2 Elements of research design

Conceptual model for the studies

A station is a complex and goal-directed environment in which passengers have to
catch their train on time. For must passengers dominance is important, because
they want to be able to orientate themselves quickly, yet also lust passengers want
to know where and at what time their train leaves. A preliminary study shows that,
in accordance with the conceptual model of Massara, Liu and Melara (2010), must
passengers experience greater dominance at a station than lust passengers, and
that lust passengers are more receptive to arousal than must passengers (Appendix
4). Although Massara, Liu and Melara (2010) did not include waiting time in their
model, it does play an important role in this doctoral thesis, which means that it
will have to be added to the conceptual model. Time experience is divisible into
a cognitive and an affective experience (Pruyn & Smidts, 1998). The cognitive
experience concerns the estimation of the time and the duration experience (short/
long), and the affective time experience represents how people have emotionally
experienced an interval. The affective time experience can negatively influence
pleasure (in which also arousal plays a role) (Baker & Cameron, 1996). In Chapter 3
we saw that cognitive time perception is determined by processing much or little
(complex) information and dividing attention between time- or non-time-bound
activities. If much attention is paid to the wait and there are few environmental

Chapter 5 Waiting experience at Dutch stations 81

stimuli, then passengers experience not only less arousal and less pleasure but also
find the wait boring (Baker & Cameron, 1996). When people are in a hurry, are alert
and have to wait, they experience much arousal and little pleasure, with stress as
a result. In Chapter 4 we saw that the affective waiting experience is influenced by
arousal and pleasure (Baker & Cameron, 1996; Droit-Volet & Meck, 2007; Zakay &
Block, 1997), and that it influences the evaluation of the wait and the service (Davis
& Heineke, 1998; Davis & Vollmann, 1990; Harell & Hutt, 1976; Hornik, 1984; 1992;
1993; Machleit & Eroglu, 2000; Nie, 2000; Unzicker, 1999). Waiting experience can
thus be influenced by arousal and pleasure, but so too can waiting experience
influence arousal and pleasure (dotted arrows in Figure 3). Ultimately, the waiting
experience influences the evaluation of the wait, such as the utilitarian or hedonic
waiting time attitude (Kaltcheva & Weitz, 2006). If we enlarge Figure 1 to include the
waiting experience, and assuming that dominance is important to all passengers,
then the conceptual model of Figure 3 arises. In the following chapters, this
conceptual model will be our starting point for the various studies.

CONCEPTUAL MODEL

Waiting experience
AROUSAL
Must: low arousal
Lust: high arousal

waiting
Environmental evaluation
stimuli PLEASURE APPROACH
Few-Many station
evaluation

DOMINANCE
Must: high dominance
Lust: low dominance

Figure 3 Conceptual model for the various studies

Studies
As this doctoral thesis aims to put its scientific findings into practice, each chapter
will commence with a field study in order to ascertain whether environmental
manipulation has the desired effect when put into practice. If it appears that they
actually do work in practice, then in a conditioned virtual environment follow-up
studies will be conducted on how various environmental characteristics are
experienced in different situations. The field and virtual studies combined should
answer the question how the ambient, design and social dimensions (Baker, 1986)
must be employed to create a positive station and waiting experience.

82 waiting experience at train stations

Virtual world
The environmental manipulations, such as music, infotainment, colour and
light can be studied best by changing the environment in an existing station. The
disadvantage of a field study is that all kinds of interference, whether that be e.g. bad
weather or a delayed train, can influence the results. Adapting manipulations in an
existing station, moreover, costs a lot of time and money (Hui & Bateson, 1992). An
alternative method is thus to use a controlled environment which precludes disrup-
tive influences (Kardes, 1996). There are various possibilities: paper scenarios, a
mock-up of a station, audio or visual simulations, such as photos or videos of a
station (Bitner, 1990; Eroglu & Machleit, 1990; Hui & Bateson, 1991; 1992; Surprenant
& Solomon, 1987). The choice was made for a virtual station because it affords easy
manipulation of the environment, like density or adding different kinds of music,
infotainment, colours and intensity of light. Manipulating the environment is easy
and is relatively cheap and testing in a virtual station allows manipulation of the
objective waiting time per respondent and to record this more easily and accurately.
Moreover, the respondent can find his/her way through the station at his/her own
pace. This is imperative for a complex environment such as a station (Bitner, 1992),
because the sense of control can thus be copied as realistically as possible (Averill,
1973). Finally, before entering the virtual world, experimental subjects can be asked
to imagine themselves in a specific scenario. The ecological validity of the use of
virtual environments has already been shown (Blascovich, Loomis, Beall, Swinth,
Hoyt & Bailenson, 2002; Kardes, 1996; Massara, Liu & Melara, 2010; Riva, Mantovani,
Capideville, Preziosa, Morganti, Villani, Gaggioli, Botella, Alcañiz, 2006). The
advantage of a virtual environment is that it also meets the recommendation of
Hui and Bateson (1992) to imitate ambient sounds that strengthen the ecological
validity. In sum, the findings in a replicated environment are comparable with an
actual environment.
As previously sketched, the studies aim to discover the effects of a calming and a
stimulating environment on the station and waiting experience. In the colour study,
for example, we compare cool colours with warm ones (Kaltcheva & Weitz, 2006),
in the music study we compare calming with stimulating music (Bruner, 1990;
Sweeney & Wyber, 2002), and in the infotainment study we compare slow- and fast-
changing images (Brown, 1995; Dennis, Newman, Michon, Brakus & Wright, 2010).

Procedure virtual world studies

Leiden Central Station was used for both the field and the virtual studies. For the
virtual studies a replica was made of Leiden Central, where from behind a computer
experimental subjects could move with the mouse in the form of an avatar through
the station. Apart from the manipulation (e.g. colour, light or infotainment), the
procedure was identical in each study. Members of the NS panel (Appendix 1) were
invited by email to participate in the virtual research with as an incentive the chance

Chapter 5 Waiting experience at Dutch stations 83

of winning a book token. In the email was a link with which experimental subjects
could download the virtual world. Before entering it, they received an explanation
on how to navigate and were given one of two assignments (must/lust scenario, see
below). Experimental subjects started the virtual world on the forecourt of Leiden
Central Station and were asked to take the train to Amsterdam. The virtual station
had a 10-minute cycle (running from 17:52-18:02 hrs), after which the train departed.
Experimental subjects entered this cycle at an arbitrary moment (depending on their
self-chosen inlog moment) and thus had a different objective waiting time. They
were free to navigate with their mouse through the entire station and with the aid
of departure boards, clocks and/or announcement messages could find the correct
train in time. Once the experimental subjects had ascertained where their train
would depart from, they navigated to the correct platform and waited for the train.
When it arrived, they clicked on the train and were subsequently led to a question-
naire. After answering it, the experimental subjects were thanked for their coopera-
tion and the window closed. Whilst the experimental subjects navigated through
the station, their objective waiting time at both the station (from the entrance to
clicking on the train) and on the platform (from their first step on it to the time they
clicked on the train) was recorded to within a second.

Density
As suggested, customers at a railway station entertain well-defined goals. Most
importantly, customers have to get on the right train at the right time. To this end,
they need freedom of movement and visual control over the environment (i.e. seeing
where to go). In addition, they have to stay alert and attuned to messages informing
customers on departures, platform changes or other unexpected events. Under such
circumstances, high density may be considered a hindrance to goal achievement
(insofar as it restricts both free movement and visual control over the environment,
as well as interfering with any efficient and audible communication of service
messages via the loudspeakers); perceived control is hence negatively affected. On
the other hand, when density is low, e.g. at off-peak hours, and arriving on time or
finding one’s way through the crowd is no longer an issue, customers are likely to
value entertainment or distraction. Under such circumstances, perceived control
sooner relates to the fulfilment of customers’ need for entertainment and distrac-
tion (i.e. experiential goals) in an attractive environment. Lacking direct means to
control density, service managers face the question of how to mitigate such negative
effects of an overcrowded (or undercrowded) environment. As argued, we propose
that service managers may alleviate negative effects of a particular, uncontrollable
factor through informed use (or absence of use) of other, more controllable, environ-
mental influences.
In the virtual world, density was manipulated by placing either few or many other
‘passengers’ on the platform, just as peak and off-peak hours were distinguished in

84 waiting experience at train stations

the real world. To give the impression of a realistic situation, a number of avatars
were waiting on the platform and although they were standing still, they did move,
e.g. with their arms or head. On a quiet platform there were several other passengers
present, whereas on a busy platform there were dozens (Figure 4).

Figure 4 Manipulation density in the virtual world

A manipulation check on density was conducted in each study in order to ensure

that the quiet platform was indeed perceived as quiet and the busy platform was
perceived as busy. To this end we used the Perceived Crowding Scale of Harrell, Hutt
and Anderson (1980), which, as its name suggests, measures the degree to which
people perceive an environment as busy.

Goal-orientedness
Also the motivational orientation is important in a station environment (e.g.
Paragraphs 1.5 and 4.12). A differentiation can be made between the utilitarian and
hedonic orientation of consumers and these particularly differ from one another
in their degree of goal-orientedness (Batra & Ahtolla, 1991; Kaltcheiva & Weitz,
2006). Commuters are utilitarian or must consumers who regularly travel by train
and whose movements are goal-directed. Recreational or lust passengers, on the
other hand, see their train journey as part of the leisure activity; they are more
hedonic and less goal-directed (SENTA, 2005). The assumption is that goal-directed
passengers are more involved in the travel process, and thus also occupied with
the time, than those who are not goal-directed. Before our experimental subjects
entered the virtual world, they were given an assignment that also incorporated
the difference between goal- and non-goal-directed passengers. The experimental
subjects were informed that they were already in possession of a valid railway ticket.
For the goal-directed passengers the text read: “It is Wednesday evening and you have
just arrived on the station forecourt. Tonight you have an appointment in Amsterdam
that is really important for you, so it is imperative that you arrive on time. You must
get the first train to Amsterdam if you want to be there on time. You are in quite a hurry

Chapter 5 Waiting experience at Dutch stations 85

and it would be really inconvenient if the train is delayed.” The text for the non-goal-
directed passenger was: “It is Wednesday evening and you have just arrived on the
station forecourt. With nothing planned tonight, you have decided to go to a museum in
Amsterdam. As you will be going to the museum on your own, it does not matter when
you get there, so you can take your time.”
In order to ensure that the scenario belonging to either the must or lust condition
was actually perceived as such by the respondents, a pre-test was carried out. Twenty
respondents were given one of two scenarios, following which they had to fill in
a short questionnaire comprising four items from the Motivational Orientation
Scale of Kaltcheva and Weitz (2006, Alpha Coefficient 0.79). A t-test was conducted
to compare the scores for motivational orientation. Must passengers (M = 4.8,
SD = 1.32) scored significantly higher for motivational orientation than lust passen-
gers (M = 2.87, SD = 1.19), t(18) = 3.42, p <.01. We could thus deduce that the scenarios
were suitable and would lead to the desired effects.

86 waiting experience at train stations

 Chapter 6
Colour and Light

‘Mere colour, unspoiled by meaning,

and unallied with definite
form, can speak to the soul in
a thousand different ways.’
Oscar Wilde, 1854-1900
6.1 Introduction

In Chapter 1 we saw that passengers label stations as grey, bland and boring
(SENTA, 2005). Hence this chapter broaches our examining whether adding colour
to the platform can result in a more pleasant waiting experience and better station
evaluation. As we saw in Chapter 4 that the combination of colour and light is
relevant to environmental experience (Valdez & Mehrabian, 1994), we will not only
manipulate colour but also the light intensity. The situational circumstances, such
as density and passengers’ goal-orientedness, will be included as moderators. First
we will conduct a field study in order to ascertain whether colour in combination
with light intensity has any influence at all on passengers’ affective appreciation.
Then in two virtual studies we will investigate what influence the warmth of the
colour has on the station evaluation and the waiting experience. The first virtual
study will be conducted in a laboratory and will examine whether a colour’s warmth
influences the affective appreciation and experience of the wait. The second virtual
study will be conducted online whereby we will examine whether colour in combina-
tion with light intensity, passengers’ goal-orientedness and density influences the
station evaluation and the waiting experience. First, however, we will discuss the
relevant literature on colour and light.

6.1.1 Literature overview of colour and light

Many studies on influencing the environment focus on the effects of temperature,
smell, sound and decor. Changing these factors can influence both perceptual and
emotional reactions as well as actual behaviour (Kotler, 1973). Colours also strongly
determine how we feel. In public spaces, such as stations, we are surrounded by
them. By giving stations certain colours, NS can exert influence on the emotions
that customers experience. Colours with a short wavelength are specified as cool
colours (blue and green), whereas those with a long wavelength are warm (red
and yellow). Light comprises the light intensity and the diffusion or spreading of
the colour tone. Bright or dimmed light is determined by the light intensity. Little
research has been conducted on the combination of colour and light (Brengman &
Geuens, 2004; Valdez & Mehrabian, 1994). The majority of (published) studies on the
effects of colour in the retail environment was conducted in a laboratory setting. To
our knowledge, no research has yet been published on the usage of light and colour
in a railway station.

6.1.2 Colour
In public environments there is often a need for the right colour that incorporates
the element ‘pleasantness’. All colours that are perceived as such will generally
result in positive emotions. Although the optimal design may strongly differ across
service contexts and situations (and even across individual customers), it appears
that specific colours, generally perceived as pleasant, may result in very specific

Chapter 6 Colour and Light 89

emotions. Cool colours, such as blue and green, have a relaxing effect, whereas
colours with a long wavelength, such as orange and red, are stimulating (Adams &
Osgood, 1973; Jacobs & Suess, 1975; Valdez & Mehrabian, 1994, Walters, Apter &
Svebak, 1982; Wexner, 1954). Warm colours are perceived as being protective
(Wilson, 1966). Clear and saturated colours are experienced as more pleasant
(Guilford & Smith, 1959), but are also more strongly associated with fear than cool
colours (Jacobs & Suess, 1975). Dark colours are perceived to be more dominant
and more strongly provoke hostility and aggression. So, with the environment and
state of mind determining the effects of colour, red in the cinema foyer will exude
a warm, festive aura whereas the same colour in a hospital can have a negative
influence on the state of mind of the already anxious visitor.

Research on the use of colour in retail environments has shown that it influences
buying behaviour (Belizzi & Hite, 1992), purchasing speed (Belizzi & Hite, 1992), time
spent in the shop (Belizzi & Hite, 1992), pleasure (Belizzi & Hite, 1992; Crowley, 1993),
arousal (Crowley, 1993), image of shop and merchandise (Belizzi, Crowley and Hasty,
1983; Crowley 1993), and the potential to draw customers into the shop (Belizzi,
Crowley and Hasty, 1983). Blue and green are perceived to be the most pleasant in
a retail environment (Eysenck, 1941; Jacobs & Suess, 1975) and are also evaluated
more positively than shops with a warm (orange) interior (Babin, Hardesty & Suter,
2003; Crowley, 1993). The results for pleasure strongly resemble the results for
arousal. From research by Kwallek et al. (1988; in Stone & English, 1998), it appeared
that people who performed a business task in red surroundings later scored higher
for stress and anxiety. Colours with a short wavelength cause a person to be more
externally oriented and to show forceful and extrovert behaviour.
From the study by Belizzi, Crowley and Hasty (1983), it appeared that respondents,
irrespective of their colour preference, felt more physically drawn to warm colours
yet perceived surroundings in warm colours as less pleasant. Warm colours are
apparently successful when it comes to drawing people in (entrance, shop window),
but less so when it comes to making them feel at ease. In situations where people
experience mental pressure, it is better to keep the colours cool; with their calming
effect, people are prepared to remain longer in such surroundings. Brengman
(Brengman, 2002; Brengman & Geuens, 2004) showed respondents photos of a
shop in which the colours were manipulated. She concluded that people will spend
more time and money in a shop if they find the colours agreeable (Brengman, 2002;
Brengman & Geuens, 2004). Blue and yellowish red are perceived as pleasant, as
are light colours. Such atmospheres invoke approach behaviour and the desire to
explore. According to Brengmann (2002), red and yellowish green, just like bright
and dark colours, are perceived as less pleasant; these colours lead to tension
and stress and evoke a feeling of distaste. Such negative stress leads to avoidance
behaviour (Brengman, 2002). Brengman and Geuens (2004) recommended that in
future research the results should be tested in a conditioned environment, which is
after all different than evaluating photos.

90 waiting experience at train stations

6.1.3 Light
Psychologists state that light has a tremendous influence on human behaviour.
Baker and Cameron (1996), Hopkinson, Petherbridge and Longmore (1966) and
Küller, Ballal, Laike, Mikellides and Tonello (2006) demonstrated that there is a
basic level of how people experience light as the most pleasant. A preference for light
intensity depends on the situation, the task and one’s surroundings (Biner, Butler,
Fischer & Westergren, 1989; Butler & Biner, 1987; Van Bommel, 2003).
Light has a strong effect on the degree of arousal (Baron, Rea & Daniels, 1992;
Daurat, Aguirre, Foret, Gonnet, Keromes & Benoit, 1993; Gifford, 1988; Kallman &
Isaac, 1977; Miwa & Hanyu, 2006). Mehrabian suggested that ‘brightly lit rooms are
more arousing than dimly lit ones’ (Mehrabian, 1976, p. 89). Light also influences
a shop’s image and the stimulus to look at and scrutinize the merchandise (Areni
& Kim, 1994; Baker, Grewal & Levy, 1992; Baker, Grewal & Parasuraman, 1994;
Brengman & Geuens, 2004).

6.1.4 Colour and light

Valdez and Mehrabian (1994) have shown that it is not only colour hue that
determines the evoked emotions but also its saturation and brightness (i.e.
intensity). It appears, for example, that although there is hardly any difference in
the way men and women react to colour, women are more sensitive to the colour’s
brightness. In a study of non-chromatic colours (black-white-grey), it appeared that
the brightness strongly determines their degree of stimulation and dominance
(Valdez & Mehrabian, 1994). From a scenario study (Babin, Hardesty & Suter, 2003),
in which a blue and an orange shop were compared, it appeared that the blue shop
was preferred the most and that it generated a greater willingness to shop or buy
there. A brightly-lit orange shop was perceived as having the greatest adverse effect.
However, when soft lighting was introduced to this orange shop, it became almost
as positively rated as the blue one. With a blue shop the effects are even more
positive in a brightly-lit variation. The combination of light and colour seem to
qualify the perceived effects quite convincingly. A restriction, however, is that this
was a scenario study and its results should preferably also be tested in a realistic
setting (Babin, Hardesty & Suter, 2003). Generally speaking, the studies on the
effects of colour have predominantly focused on the wavelength of the colour and
hardly at all on the brightness and the saturation of the colour (Valdez & Mehrabian,
1994; Brengman, 2002). Light and colour combined have seldom been investigated.

6.1.5 Colour, light and time perception

Smets (1969) demonstrated how people estimate the length of an interval as being
shorter after having seen a red as opposed to a blue colour. Under red light time
would appear to pass more slowly and objects seem bigger and heavier, whereas
under blue light time seems to pass more quickly and objects look smaller and
lighter. Casinos use this information and opt for red as basic colour which excites

Chapter 6 Colour and Light 91

the customers without their realizing that they are wasting a lot of time there (Singh,
2006). Research into the waiting time whilst downloading internet pages revealed
that blue screens have a more calming effect than red or yellow ones and that time
seemed to pass more quickly with the blue screen (Gorn, Chattopadhyay, Sengupta &
Tripathi, 2004).
In the context of traditional – offline – shopping, Markin, Lillis and Narayana
(1976) suggested that dimmed light calms customers, causing them to move more
slowly through the shop, which means they can then take the time to scrutinize the
merchandise. In order to stimulate impulse buying, Birren (1969) recommended
using glaring lights. This suggests that the shopkeeper can use the intensity of light
to keep customers in the shop for a longer or shorter period of time. As pleasant
and stimulating colours combined with bright lighting appears to lengthen the
perceived waiting time (Baker & Cameron, 1996), it would be better to opt for softer
lighting and cooler colours so that people do not overestimate the actual wait.

6.1.6 Influence of colour and light on behaviour

Besides the influence of colour on the emotions in the PAD model, colour and light
also influence people’s behaviour in a service environment. The assumption is that
the three emotions affect the perception of the station on the following aspects:
density, time perception and behaviour. Density, or rather perceived density, is
influenced by one’s sense of control (Hui & Bateson, 1991), whereby the space is expe-
rienced as less busy when the colours have a short wavelength (Russell & Mehrabian,
1974). The perceived waiting time is influenced by arousal and pleasure (Baker &
Cameron, 1996; Bellizzi, Crowley & Hasty, 1983; Gorn et al., 2004; Singh, 2006;), and
behaviour by pleasure, arousal and dominance (Mehrabian & Russell, 1974).

6.2 Study 1 Field study: Colour and light at

Leiden Station3

6.2.1 Introduction
This field study examines whether colour in combination with light intensity on
a platform can effect positive affective reactions from passengers and whether
the degree of density on the platform has an influence on their experience. In this
field study the roofing of one of the platforms at Leiden Central Station was lit with
LEDs (Light Emiting Diodes) showing all the colours of the rainbow in a wavelike
movement (Figure 6.1). Per measurement the light intensity was adjusted to high or
low. The measurements were carried out in the evening, when it was dark, because
the LED lighting was then more clearly visible and the light intensity could be more

3 This study was presented at the Colloquium Vervoersplanologisch Speurwerk (Van Hagen,
Galetzka & Sauren, 2010).

92 waiting experience at train stations

easily manipulated owing to the absence of daylight. Besides LED lighting the
platform was also lit by the regular fluorescent lighting, half of which was turned off
when the light intensity was low. By projecting LED lights onto the white platform
roofing, various colours and light intensities could be easily manipulated.

6.2.2 Research questions and hypotheses

The aim of this study was to investigate how waiting passengers react to colour
on a platform. The study focuses, moreover, on the question whether colour can
influence the station evaluation and the waiting experience.

As mentioned before, reversal theory (Apter, 2007) poses that the need of environ-
mental stimuli is dependent on the context, such as the degree of density on the
platform. An environment that corresponds with the desired number of stimuli
seems to effect an increase in customer satisfaction (Wirtz, Matilla & Tan, 2000).
Reversal theory alleges that there are two suitable levels of stimulation: high and
low (Apter, 2007, Chapter 4). If an individual finds him-/herself in a busy environ-
ment (rush hour), then the level of environmental stimulation is already so high
that adding to it – in the form of colour – can cause too many stimuli and result in
irritation and discomfort (Bellizzi, Crowley & Hasty, 1983). The same can apply to
light intensity: a high level of lighting can lead to overstimulation. A combination of
much light and colour evokes even more stimuli and the chance of overstimulation.
This overstimulation can result in a lower hedonic tone. In a quiet environment,
such as during off-peak hours or on a platform with a low light intensity, passengers
are exposed to few stimuli whereby they can perceive the platform as bland and
become bored. By purposely adding stimuli in the form of colour and light, the
arousal level can be increased and passengers can experience greater pleasure. On
the basis of reversal theory we expect an interaction between the degree of density
and coloured light and between the degree of density and light intensity, hence our
formulation of the following hypotheses:

H1: In a quiet environment colour affords more stimuli for passengers and initiates
a more positive station and waiting experience.

H2: In a busy environment colour affords too many stimuli for passengers and leads to
a more negative station and waiting experience.

H3: In an environment with little light, colour affords more stimuli for passengers and
leads to a more positive station and waiting experience.

H4: In an environment with a lot of light, colour affords too many stimuli for passengers
and leads to a more negative station and waiting experience.

Chapter 6 Colour and Light 93

6.2.3 Method
Experimental subjects and design
Of the 278 passengers who participated in this study, 41.3% were male and 58.7%
female. The average age was 31.9 years (SD = 14.53, minimum 13, maximum
82 years).
The stimulus material consisted of seven colours that were alternately projected
in rainbow-like fashion onto the white platform roofing (Figure 6.1). Also the light
intensity on the platform varied between high (74 lux) and low (37 lux).

Figure 6.1 Manipulated colour of platform roofing

94 waiting experience at train stations

Procedure
The effect of the colour and light manipulation was measured by requesting
train passengers to participate in an NS survey on station experience. For four
consecutive days measurements were conducted on platform 1 of Leiden Central
Station. The first two days measured a no-colour condition as control condition; the
platform was then lit with white light, as in the normal situation, albeit the first day
with a low and the second day with a high light intensity. On the third and fourth
day the platform roofing was lit with various colours; on the third with a low and
on the fourth with a high light intensity. This study was conducted at the end of
November 2009 during evening hours in order for the light and colour manipulation
to be clearly visible. Questionnaires were distributed in four trains, all of them
leaving from the platform where the light had been manipulated. The reason why
the questionnaires were not handed out before was so that respondents could not
check to which colour and light intensity they had just been exposed. This also
meant that the waiting experience was not influenced by filling in the questionnaire
(i.e. a distracting task). The measurements were carried out in two trains during
rush hour and two trains after the evening rush hour.

Measurements
The variables (with the exclusion of experience of time and the score) were
measured with a 7-point Likert scale whereby 1 stood for ‘completely disagree’
and 7 ‘completely agree’. The station experience was measured with the following
variables (Table 6.1 for scale values):
–– Pleasure, arousal, dominance: The PAD emotions were measured on the basis
of an adapted scale with bipolar items (7-point scale) (Russell & Mehrabian,
1974). For example: “Please indicate how you felt on the platform: pleasant-
unpleasant.” Pleasure was measured with 6 items (unhappy-happy, annoyed-
pleased, unsatisfied-satisfied, melancholic-contended, despairing-hopeful,
unpleasant-pleasant). Arousal was measured with three items (aroused-
unaroused, relaxed-stimulated, calm-excited). Dominance was measured with
three items (guided-autonomous, controlled-controlling, submissive-dominant).
–– General appreciation of platform: This was measured with ten items – a combina-
tion of a station evaluation scale (used in studies of SENTA, 2005) and the
Environmental Rating Scale of Bitner (1990). For example: “I feel welcome on the
platform” and “The platform looks well cared for.”
–– Platform score: Experimental subjects were requested to award a score for their
assessment of the quality of the platform (1 = very poor, 10 = excellent).

The waiting experience was measured with the following variables:

–– The time experience of the passengers: The time experience at the station, on the
platform and on the train were measured by the open question “How long (in
minutes) do you think you were on the platform?” The cognitive waiting time

Chapter 6 Colour and Light 95

 assessment was determined by the question “How did you experience the time
you spent waiting on the platform?” This was measured with a 7-point scale
(1 = very short, 7 = very long).
–– Acceptance of the waiting time: This was measured with the question “I found the
waiting time on the platform: acceptable – unacceptable.”
–– Utilitarian and hedonic waiting time: The utilitarian waiting time (did one spend
the time usefully, measured with five items) and the hedonic waiting time (did
one spend the time pleasantly, measured with three items) were measured
for the waiting time on the platform by using items of the Shopping Values
of Batra and Ahtola (1991). Example utilitarian waiting time: “Was the time
you spent waiting on the platform: useful–useless, valuable–worthless, etc.”
Example hedonic waiting time: “Was the time you spent waiting on the platform:
pleasing - annoying, happy–sad, etc.”

Finally, the following points were recorded:

–– Questions relating to the light and colour manipulation: Respondents were asked
which colour they had predominantly seen on the platform, whether the light on
the platform was quite dark or quite bright (7-point scale), whether the colours
on the platform were cool or warm (7-point scale), and whether the colours on
the platform were quite grey or quite colourful (7-point scale).
–– Personal details: Also several questions were asked relating to demographics,
particulars on travel frequence and motive (must versus lust passenger), and
whether one usually travels in peak or off-peak hours.
–– Extra information: Finally the respondents were requested to indicate what
time the train in which they were sitting had departed and whether it had been
delayed. The questionnaire ended with a position on the weather: “I think the
weather is fine today – I think the weather is dreadful today.”

Table 6.1 Cronbach Alpha, Min., Max., M and SD of the dependent variables
α Min. Max. M SD
Station experience
Pleasure .90 1 7 4.50 1.06
Arousal .73 1 7 3.38 1.07
Dominance .83 1 7 4.22 .99
General appreciation environment .89 1 7 4.01 1.04
Platform score – 1 10 6.14 1.41
Waiting experience
Time perception platform – 0 20 3.83 5.47
Acceptance waiting time – 1 7 4.57 1.42
Utilitarian waiting experience .87 1 7 3.17 1.21
Hedonic waiting experience .84 1 7 3.84 .98

96 waiting experience at train stations

6.2.4 Results study 1
Manipulation check
To determine whether the quiet or the busy platform was indeed perceived as such,
we conducted a manipulation check. The perceived crowding scale (Harrell, Hutt &
Anderson, 1980) was incorporated in the questionnaire with five items in order to
ascertain the perceived density (e.g. “There are a lot of passengers on the platform”;
α = .75). An analysis of variance revealed that experimental subjects in the busy
condition indeed judged the situation on the platform as being busier (M = 4.51,
SD = 1.10) than experimental subjects in the quiet condition (M = 4.08, SD = 1.10),
F(1, 277) = 40.11, p =.000).

Presence of colour
Of the experimental subjects 150 were in a condition with colour and 128 in a
condition without. Experimental subjects found the colours on the platform more
colourful in the colour condition (M = 3.69, SD = 1.53) than the platform without
colour (M = 2.65, SD = 1.24), F(1, 269) = 28.3, p = .000). Also the colours on the platform
with colour were perceived as being warmer (M = 3.56, SD = 1.51) than the platform
without colour (M = 2.67, SD = 1.20), F(1, 270) = 37,3, p = .000). Experimental subjects
evaluated a platform with colour as being more stimulating than a platform without.

Effects of colour, light intensity and density

A 2 (colour: none vs rainbow) x 2 (light intensity: high vs low) x 2 (density: busy
vs quiet) multivariate analysis of variance (MANOVA; Wilks’ Lambda) was
conducted with dependent variables related to station experience: pleasure,
arousal, dominance, evaluation platform and platform score. With the same
independent variables we conducted a MANOVA on the dependent variables for
waiting experience: subjective time platform, time experience platform, utilitarian
waiting time, hedonic waiting time and acceptance of the waiting time. Corrections
were made in both MANOVAs for the influence of the weather by including the
assessment thereof as covariate. With the station experience significant differences
were found between colour and light intensity (F(5, 233) = 2,79, p = .018). With the
waiting experience a main effect was found for colour (F(5, 211) = 3.41, p = .005) and
density (F(5, 211) = 2.54, p = .03). Also an interaction was found between colour x
light intensity (F(5, 211) = 2.56, p = .02). In order to ascertain which effects occurred
exactly, a number of univariate analyses of variance (ANOVAs) were conducted.

6.2.5 Waiting experience

It appeared that passengers with colour undergo a higher utilitarian waiting
experience (M = 3.32, SD = 1.24) than without colour (M = 3.02, SD = 1.22, F(1,
211) = 3.75, p = .05), and during the rush hour passengers estimated their waiting
time as being shorter (M = 03:42, SD = 05:12) than during off-peak hours (M = 04:28,
SD = 05:45, F(1, 211) = 6.24, p = .013). For the waiting time experience an interaction

Chapter 6 Colour and Light 97

was found with an ANOVA between colour and light intensity on the hedonic evalua-
tion of the wait (F(1, 235) = 4.40, p = .037) and on the utilitarian evaluation of the wait
(F(1, 235) = 5.73, p = .001). Table 6.2 shows the averages and standard deviations.

Table 6.2 Means (SDs) utilitarian and hedonic wait evaluation

Light intensity Colour No colour

M (SD) M (SD) M (SD)
Hedonic waiting time Low 4.07 (.94) 3.60 (.84)*
High 3.68 (.91) 3.78 (1.02)

Utilitarian waiting time Low 3.59 (1.23) 2.96 (1.15)*

High 3.11 (1.17) 3.07 (1.32)
Note: Means with * differ significantly in the row, * p < 0.05.

We see that passengers found waiting in a low light intensity more pleasant with
colour than without (F(1, 238) = 6.98, p = .009). Passengers also found waiting in a low
light intensity more useful with colour than without (F(1, 241) = 7.52, p = .007). These
differences are non-significant for a high light intensity (Figure 6.2).

HEDONIC WAIT (A) UTILITARIAN WAIT (B)

means

means

4.1 4.1

4 4

3.9 3.9

3.8 3.8

3.7 3.7

3.6 3.6

3.5 3.5

3.4 3.4

3.3 3.3

3.2 3.2

3.1 3.1

3 3

low high low high

Intensity of Light Intensity of Light

no colour
colour

Figure 6.2 Interaction effects between colour and light intensity on hedonic (A) and
utilitarian (B) evaluation of the waiting time

98 waiting experience at train stations

6.2.6 Station experience
Colour and light also influence the station experience. ANOVAs revealed that colour
in combination with a high or low light intensity has an effect on the experience of
pleasure, arousal and dominance and in combination with density on the platform
score (Table 6.3).

Table 6.3 Means and standard deviations colour and light intensity on
station experience
Light intensity Density Colour No colour
M (SD) M (SD)
Pleasure Low 4.67 (1.19 3.98 (.77)**
High 4.40 (.91) 4.41 (1.11)

Arousal Low 3.25 (1.01) 3.61 (.85)**

High 3.53 (.95) 3.24 (1.16)*

Dominance Low 4.48 (1.08) 4.12 (1.04)**

High 4.16 (1.02) 4.30 (.94)

Platform score Low Low density 6.00 (1.55) 5.62 (1.13)

High density 6.42 (1.42) 5.50(1.43)**
High Low density 6.16 (1.26) 5.85 (1.43)
High density 6.09 (1.51) 6.62 (1.63)
Note: Means with ** and * differ significantly in the row, ** p < 0.05, * p < 0.1.

Pleasure: An ANOVA showed that in a situation with a low light intensity passengers
experienced greater pleasure with colour than without (F(1, 260) = 14.83, p = .000).
For a high light intensity this difference is non-significant. Arousal: An ANOVA
between colour and brightness (F(1, 234) = 5.84, p = .016) showed that passengers
with a low light intensity were stimulated more without colour than with
(F(1, 258) = 4.13, p = .043). With a high light intensity passengers were stimulated
only marginally more with colour (M = 3.53, SD = .95) than without (F(1, 258) = 2.91,
p = .089). Dominance: An ANOVA revealed that passengers with a low light intensity
also experienced greater control with colour than without (F(1, 252) = 3.80, p = .05).
On a well-lit platform this difference was non-significant. The interactions are
visualized in Figure 6.3.

Chapter 6 Colour and Light 99

 PLEASURE (A) AROUSAL (B) DOMINANCE (C)
means

means

means
4.6 4.6 4.6

4.4 4.4 4.4

4.2 4.2 4.2

4 4 4

3.8 3.8 3.8

3.6 3.6 3.6

3.4 3.4 3.4

3.2 3.2 3.2

low high low high low high

Intensity of Light Intensity of Light Intensity of Light

no colour
colour

Figure 6.3 Interaction between colour and light on pleasure (A), arousal (B) and
dominance (C)

Finally, an ANOVA showed a three-way interaction between colour and light on

the passengers’ score for the platform (F(1, 259) = 4.08, p = .044). It appeared that
passengers with a low level of lighting and with many people on the platform with
colour awarded a higher score than without colour (F(1, 259) = 8.02, p = .005). This
difference was insignificant with a high light intensity or when the platform was
quiet (Figure 6.4).

PLATFORM SCORE (LOW DENSITY) PLATFORM SCORE (HIGH DENSITY)

means

means

6.8 6.8

6.6 6.6

6.4 6.4

6.2 6.2

6 6

5.8 5.8

5.6 5.6

low high low high

Intensity of Light Intensity of Light

no colour
colour

Figure 6.4 Three-way interaction between colour, light intensity and density on
the platform score

100 waiting experience at train stations

6.2.7 Returning to the hypotheses
Hypothesis 1 cannot be confirmed: In a quiet environment colour affords more
stimuli for passengers and initiates a more positive station and waiting experience. In
a situation in which it was quiet on the platform and the light intensity was low, no
significant differences were found for station and waiting time experience. Possibly
the differences between a busy and a quiet platform are not so great that passengers
experience clear differences in station experience and waiting time experience in
combination with colour.
Hypothesis 2 cannot be confirmed: In a busy environment colour affords too many
stimuli for passengers and leads to a more negative station and waiting experience.
It appeared that when it was crowded passengers awarded a higher score with
colour than without in combination with a low light intensity. With a high light
intensity and on a quiet platform, no differences were found for station or waiting
time experience. Apparently, even in a busy situation with a low light intensity, the
addition of colour is appreciated more by passengers (than without colour). One
explanation might be that adding stimuli in the form of colour on a busy platform
with little light has a positive effect, because passengers inherently expect to be
understimulated on the platform. Adding extra stimuli makes the hedonic tone
(score platform) rise. The greater appreciation may stem from an inexperience with
colour on the platform.
Hypothesis 3 can be confirmed: In an environment with little light, colour affords
more stimuli for passengers and leads to a more positive station and waiting experience.
When the light intensity was high and colour was added, passengers experienced
significantly greater arousal. They also experienced more arousal with a low
light intensity and little light. The combination of colour and light is thus able to
influence the number of experienced stimuli. Also a low light intensity in combina-
tion with colour appeared to result in more pleasure, more dominance and a higher
score. This concurs with earlier findings in the literature (Brengman & Geuens,
2004; Valdez & Mehrabian, 1994). In line with these results, passengers experienced
their waiting time as more pleasant and more useful. This confirms the proposition
of Baker and Cameron (1996), in which they allege that a higher hedonic tone affords
a more positive waiting time experience.
Hypothesis 4 cannot be confirmed: In an environment with a lot of light, colour affords
too many stimuli for passengers and leads to a more negative station and waiting
experience. With a high light intensity in combination with colour, no significant
differences were found for the station and waiting experience. When there was little
light present, a colourful platform was indeed positively assessed by passengers. We
see no differences, however, when there was a lot of light. We can conclude from this
that passengers waiting on a platform do not get overstimulated quickly by light in
combination with colour. Maybe platforms are perceived as boring and that adding
stimuli in the form of colour helps to positively influence the station and waiting
experience. The differences found relate mainly to the interaction between colour

Chapter 6 Colour and Light 101

and light and, to a lesser degree, between density, colour and light. The positive
effects, moreover, apply predominantly to a situation with a low light intensity.

6.2.8 Discussion
The aim of this field study was to examine the effect of colour and light intensity
on passengers’ station and waiting experience. Context plays an important role
in reversal theory: in a busy, stimulating environment passengers have no need of
extra stimuli, but in a quiet and barely stimulating environment, they are in contrast
quite receptive to them. When passengers experience an optimal level of stimuli,
the hedonic tone increases. A more positive hedonic tone has an effect on the
waiting experience. If one is entertained, in any way, shape or form, then he/she will
experience the wait more positively. The findings are in accordance with reversal
theory. Not only does colour in combination with light result in a more positive
station and waiting experience, whereby the colours on the platform are perceived
as more stimulating, more colourful and warmer, but so, too, does the combination
of colour and a low light intensity. Despite few differences being found between
peak and off-peak hours, it would seem that even during rush hour passengers do
appreciate colours. Apparently, there are so few stimuli on a platform that extra
colour is positively embraced. Coloured light affords a more pleasant wait but has no
influence on the waiting time perception. Neither the time estimation nor the time
experience (short/long) was influenced by the coloured light. The explanation might
lie in the fact that the alternating colours on the platform, although appreciated by
passengers, might be too subtle to distract them from the time.

6.2.9 Remarks and restrictions

A few methodological comments can accompany this field study. Different from
most of the studies described in the literature, the manipulations in this study
were not conducted by shining a specific light intensity onto coloured areas but by
projecting coloured light onto the white roofing of the platform. Coloured light may
well be perceived differently by experimental subjects than a coloured area on which
light is shed. This may lead to different results.
Besides this, not the entire platform but only part of it was lit. However, the lit part
was on the side where the passengers arrived on the platform, so every passenger
was exposed to the coloured light. The fact that not the entire platform was lit
but only part of it may be a reason why we did not find all the expected results.
Maybe the exposure was too brief to realize substantial effects. A second comment
concerns the fact that the train was often already waiting at the platform concerned
before its time of departure. This meant that many passengers were able to get on
straight away and were thus not only less exposed to the lighting but also that their
waiting experience differed from if they had had to wait on the platform. This might
also explain why hardly any differences were found between colour, light intensity
and density. The reason why this platform was chosen for the study, despite the train

102 waiting experience at train stations

already having arrived, was a practical one: on conducting this experiment, several
saftey regulations had to be followed, i.e. the assembly and removal of the light
installation was dangerous on other platforms where through trains passed (even at
night).

6.2.10 Practical implications for NS

The findings of this study offer insight into the application of coloured lighting on
a platform and how the station evaluation and waiting experience of passengers
can be influenced. With a lower light intensity, coloured light affords more
pleasure, greater control and a more pleasant wait. Waiting passengers feel more
relaxed and better in a colourful environment with a low level of lighting. With the
colours receiving positive reactions in different situations, it can be argued that
on platforms and in a waiting situation one can sooner speak of under- rather than
overstimulation. We propose to deploy coloured lighting during both rush and
off-peak hours, whereby the colours have the most positive effects when combined
with a low light intensity.

6.3 Study 2 Colour and time experience

in a virtual lab4

6.3.1 Introduction
In the previously discussed field study we ascertained that colour in combination
with light results in passengers more positively evaluating both the station and
the waiting experience. In order to gain more insight into the effects of colour on
a platform, our next two studies will take a closer look at more specific aspects of
colour and light. Both studies were conducted in a virtual world, where we could
influence the conditions more easily, i.e. restrict the influence of disturbing/inter-
fering circumstances such as bad weather or delayed trains.

6.3.2 Hypotheses
In Chapter 4 we saw that people do not necessarily have to be aware of the environ-
mental manipulation and in the field study we saw that adding colour in almost
every situation results in a positive evaluation of the station. Colour appeared to
have no effect on the waiting time perception, probably because the effects were
too subtle to be noticed. It is also possible that people did not realize that the
environment had a certain colour, regardless of its actual influence on the waiting
experience. In the virtual world it is not only possible to compare the differences
between colours, but also to ascertain whether the colour present is consciously

4 This study was presented at the European Transport Conference (Van Hagen, Pruyn,
Galetzka & Peters, 2008).

Chapter 6 Colour and Light 103

perceived and whether the colour preference influences the experience. After all,
our experimental subjects will be requested to fulfil a certain task and be unaware
that various conditions at the station are being manipulated (Introduction to the
experimental studies). Hence the following hypothesis:

H1: The majority of the respondents are unaware of the colour of the environment and
the colour preference has no influence on the evaluation of the colour.

In the introduction of this chapter we saw that the warmth of the colour can result
in different effects, such as a short or longer perception of the waiting time (Gorn,
Chattopadhyay, Sengupta, & Tripathi, 2004; Singh, 2006; Smets, 1969). To ascertain
whether a colour’s warmth can also influence the waiting experience in a station
environment, we decided to examine how the wait is experienced on a platform
lit by a cool colour (blue) and a red colour (warm). This resulted in the following
hypothesis:

H2: Time on the platform seems to pass more quickly with the cool colour blue than with
the warm colour red.

6.3.3 Design, procedure and participants

With the virtual world being used for this study (Introduction to the experimental
studies), the experiment was carried out in the Virtual Reality Laboratory (VR lab) at
the University of Twente (NL). The hypotheses were tested with a 2 (colour hue: red
versus blue) between-subjects design, in which the platform roofing was either red
or blue (Figure 6.6). The experiment ran for four consecutive days, during which the
different conditions were arbitrarily distributed among the respondents. Those who
had indicated they wished to take part in the experiment were first subjected to a test
for colour blindness, after which they were invited – into a separate room – to practise
with the navigation system used in the experiment. Subsequently, the respondents
entered the VR lab where the final instructions were given. The experimental subjects
sat at a table in a room in which the virtual world was projected onto a large screen
(Figure 6.5). With the aid of a mouse they could move in the form of an avatar freely
through the virtual station whilst being assigned to catch the train to Amsterdam.
All the experimental subjects had the same amount of time for the exercise and their
waiting time on the platform was determined by the speed with which they navigated
through the station. The quicker they found their train, the longer their waiting
time on the platform. After the simulation the respondent was requested to fill in a
questionnaire. On completing it, (s)he was thanked for his/her time.
In total, 108 respondents (50 male and 58 female; average age 22; range 18-29 years),
all Master/PhD students at the University of Twente, took part in the experiment. All
108 questionnaires were included in the final analyses. Twelve respondents previ-

104 waiting experience at train stations

ously dropped out due to colour blindness or because they had experienced mild
nausea in the virtual environment.

Stimulus material
The virtual simulation was projected onto a 10-metre screen. Two stills (below)
depict the simulation at the Virtual Reality Laboratory at the University of Twente
(Figure 6.5) and the manipulation of the colours (Figure 6.6). After reading an
instruction on the start page, participants could navigate through an animation of
Leiden Station with a mouse and scroll arrows on a keyboard. They were instructed
to: “… get the first train to Amsterdam. Find out from which platform and at what time
your train leaves. Wait on the platform until your train arrives. You have already got
your ticket. Please try to envisage the situation and behave as you would in real life.”
The avatar could then enter the station and freely navigate through the station from
a first-person perspective, i.e. they were able to ‘walk’ through the station, climb the
stairs and go onto the platform. Real-life background noises were played during the
session to enhance imaginative power.

Figure 6.5 Experimental subject in virtual laboratory, study 1

Chapter 6 Colour and Light 105

The colours on the platform were manipulated: blue (colour code 000.128.255)
and red (colour code 255.075.075). Level of saturation and light intensity was held
constant for both conditions.

Figure 6.6 Colour conditions virtual laboratory

6.3.4 Measurement instrument

The questionnaire was used to measure the overall evaluation of the station and the
waiting time.
–– Station evaluation was assessed by asking participants to evaluate the platform
by awarding a score on a 10-point scale (1 = very poor, 10 = excellent).
–– Time perception: Measures included subjective estimations of time spent at the
station and on the platform. “If you had to guess, how long do you think you
were at the station/on the platform (in minutes)?” The cognitive evaluation of

106 waiting experience at train stations

 the waiting time (long/short) was measured with the question: “How did you
experience the time spent at the station?” (1 = very short, 7 = very long).
–– Colour preference was measured by asking the participant which colour they
thought was the most appropriate for a station (grey, green, yellow, red or blue).
–– Perceived colour was measured by asking participants what the main colour was
that they had seen on the platform.

Also included were a number of demographic variables such as age, gender and
gaming experience.

6.3.5 Results cognitive versus affective perception of colour

From the literature it was assumed that passengers have an idea of what they find
suitable and appropriate on a platform and that cognition influences the way a
person assesses an environment. Additional analyses were performed to gain
insight into participants’ preference. When asked which colour they thought was
the most appropriate for a station (grey, green, yellow, red or blue), participants
indicated a cognitive preference for the colour blue (37.1%) followed by the colour
grey (19.2%). The colour red was with 18.5% the least appropriate colour for a
station. Various one-way ANOVAs revealed that this preference had no influence
on the overall evaluation of the station. That is to say that when one prefers blue,
for example, on a platform, one does not necessarily appear to appreciate that
platform more than someone who has a cognitive preference for another colour. It
also appeared that only a small number of the participants could actually indicate
which colour was dominant on the platform (28.7% grey, 25% blue and 17.6% red),
suggesting that the effects of colour occur unconsciously. This result is in line with
studies on automatic consumer behaviour which suggests that consumers are often
unaware of environmental factors influencing their behaviour (e.g. Dijksterhuis,
Smith, Van Baaren & Wigboldus, 2005) and it confirms hypothesis 1.

6.3.6 Results Time Perception

Time perception was included as a specific focus of interest in this study. Generally
speaking, respondents estimated their time spent on the platform as significantly
longer (M = 5:05, SD = 2:01) than the actual time (M = 3:19, SD = 0:29; t(107) = 10.41,
p < .00). The Time Sense Factor (TSF) is the relationship between the objective
waiting time and the perceived waiting time and is calculated by dividing – per
experimental subject – the latter by the former (i.e. perceived waiting time ÷ objec-
tive waiting time). The result shows that the waiting time on the platform was
overestimated (TSF = 1.59 (SD =.84)).
An ANOVA showed a main effect for colour on the short-long time experience
(F(1, 106) = 4.73, p = .03). With time experience we see a difference between the blue
platform (M = 3.34, SD = 1.46) on the one hand, and the red (M = 4.02, SD = 1.79) on

Chapter 6 Colour and Light 107

the other. These results show that on a blue platform time passes relatively faster
than on a red one. This confirms hypothesis 2.

6.3.7 Conclusions VR lab

Although passengers have a definite cognitive preference for the colour blue, it
appeared that not even 20% of the respondents could indicate which colour was
dominant on the platform. In all situations the colour one thought to have seen
most often was grey. Apparently, passengers cling to the image they have of a
platform and it seems that colours are perceived unconsciously. For colour and
station evaluation, affective effects are thus more important than cognitive ones.
According to results found in the literature (Gorn, Chattopadhyay, Sengupta, &
Tripathi, 2004; Singh, 2006; Smets, 1969), time in a blue environment appears to
pass faster than in a red one. Now we have seen that colour can influence the waiting
experience, and unconsciously also the station evaluation, it will be interesting to
examine whether interaction effects can also be found in the virtual world. As this
entails a more complex research design and requires more experimental subjects,
we thus decided to hold the virtual world study online from respondents’ homes.

6.4 Study 3 Virtual station online study5

6.4.1 Introduction
In order to test an elaborate research design, a virtual laboratory is not the optimal
research instrument. Only one respondent at a time can sit in a VR lab, which
is laborious and time- consuming. Moreover, it is not easy to recruit sufficient
respondents who are willing to travel to the lab. The advantage of an online study
is that many experimental subjects can participate and that the time it demands of
them remains limited because it does not involve travel time to the lab. There is also
greater flexibility and the duration of the study is shorter, because the experimental
subjects can log in to the virtual world from home at any given moment and their
answers are automatically stored in an SPSS file. These advantages allow for simula-
tion of more conditions.
It appeared from the field study that colour in combination with light can result
in a more positive station and waiting experience and the VR lab study illustrated
how colours can influence the time experience without them being consciously
perceived. In the field study hardly any effects were found between density and
colour or density and light intensity, despite our high expectations to find differ-
ences. Maybe the difference in density was too marginal on the platform where
the field study was conducted. So to allow for sufficient discrimination, we also

5 This study was presented at the European Transport Conference (Van Hagen, Pruyn,
Galetzka & Peters, 2008).

108 waiting experience at train stations

manipulated density in the second virtual study, besides manipulating the goal-
orientedness by means of a scenario (Introduction to the experimental studies).
The online study used the same virtual environment as in the VR lab and NS panel
members could log in to the virtual station from their own personal computer. NS
panel members are people who have agreed to participate several times a year in NS
research (Appendix 1). The virtual station and the task given to the experimental
subjects were identical to the first virtual study, albeit that the (warm) colour yellow
was now added to the research design as this is one of NS’s corporate colours. In the
online study, besides the three colours, not only the brightness of the light but also
density was simulated by placing many or few people on the platform (Figure 6.7).
Experimental subjects were also asked to envisage themselves in a goal-oriented
or less goal-oriented scenario before entering the virtual world (Introduction to the
experimental studies).

Figure 6.7 Yellow platform x light intensity (above low, below high) x density (left low
density, right high density)

6.4.2 Hypotheses
On the basis of Apter’s reversal theory (2007; Chapter 4), we expect goal-oriented
must passengers to want to avoid too many stimuli. They are, after all, in the telic
state and are concentrated on catching their train, whereby too many stimuli will
induce more stress and a lower hedonic tone. Lust passengers, on the other hand,
will be more receptive to environmental stimuli; they are in the paratelic state, are

Chapter 6 Colour and Light 109

less goal-oriented and are receptive to any distraction from boredom. Hence the
following hypotheses:

H1: A warm colour affords more stimuli and initiates a more positive station and
waiting experience for lust passengers.

H2: A cool colour affords fewer stimuli and initiates a more positive station and waiting
experience for must passengers.

Also density and light intensity can influence the station evaluation and time
experience. In a busy environment, the sense of control can decrease and lead to
stress (Chapter 4), so having a clear (over)view is of paramount importance, which
in turn necessitates a higher level of lighting (Van Bommel, 2003; 2004). In a quiet
and less task-directed environment, the brightness of the lighting is less relevant
and too much may even overstimulate. We thus expect that a low level of lighting in
a quiet environment and a high level in a busy environment will positively effect the
hedonic tone and the waiting experience. Hence:

H3: In a quiet environment with little light, colour affords fewer stimuli to passengers
and this leads to a more positive station and waiting experience.

H4: In a busy environment with a lot of light, colour affords too many stimuli to
passengers and this leads to a more negative station and waiting experience.

6.4.3 Design, participants and procedure

A 3 (colour: blue vs red vs yellow) x 2 (light: high vs low light intensity) x 2 (time:
off-peak vs peak) x 2 (kind of passenger: must vs lust passenger) between-subjects
design was marked out to answer the specified hypotheses. The virtual environment
and the questionnaire from study 1 were converted to an online version that was
put to the NS panel. Panel members received an e-mail in which they were asked to
participate in the survey. Respondents could log in at any time and via a link they
arrived at an introduction page where they were asked to download the software
VirtuoCity 2.4, which was essential to run the virtual model. Each respondent was
randomly assigned to one of the 24 conditions. When the assignment had been
completed, the respondent was redirected to the questionnaire and on completion
thanked for his/her time. In total 1,326 respondents (56.6% male, 43.4% female) were
asked to navigate through the online simulation.

Measures
–– Emotions were measured on the basis of the Pleasure Arousal Dominance
(PAD) scale (Mehrabian & Russell, 1974). Pleasure was measured with 6 items
(unhappy-happy, annoyed-pleased, unsatisfied-satisfied, melancholic-contented,

110 waiting experience at train stations

 despairing-hopeful, unpleasant-pleasant; Coefficient Alpha = .92). Arousal was
measured with 6 items (stimulated-relaxed, excited-calm, frenzied-sluggish,
jittery-dull, wide awake-sleepy, aroused-unaroused; Coefficient Alpha = .72).
Dominance was measured with 6 items (controlled-controlling, influenced-
influential, cared for-in control, awed-important, submissive-dominant,
autonomous-guided; Coefficient Alpha = .76).
–– Station evaluation. Station evaluation was assessed by asking participants to
evaluate the platform by awarding a score on a 10-point scale (1 =very poor,
10 = excellent).
–– Utilitarian and hedonic waiting time was measured on the basis of the shopping
values (Batra & Ahtola, 1991), which measure both the hedonic (3 items, 7-point
Likert scale Coefficient Alpha = .92) and utilitarian time appreciation (3 items,
7-point Likert scale, Coefficient Alpha = .87). An example of utilitarian waiting
time: “Was the time you spent waiting on the platform: useful–useless, valuable–
worthless, etc.?” An example of the hedonic waiting time: “Was the time you
spent waiting on the platform: pleasing–annoying, happy–sad, etc.?”
–– Acceptable wait was measured with one item: “The time I spent on the platform
was: (1) unacceptable to (7) acceptable.”

A manipulation check was included in the questionnaire on the perceived density on

the platform, the perceived colour, the light intensity and realism of the simulation.
Also included were a number of demographic variables.

6.4.4 Results study 3

Manipulation Check
Perceived density was measured with the aid of the perceived crowding scale
(Harrell, Hutt & Anderson, 1980), which consists of 7 items. Examples: “There
are many passengers on the platform” and “On the platform I am limited in my
freedom of movement” (1 = totally disagree, 7 = totally agree; Coefficient Alpha = .79).
The manipulation check confirmed that during peak hours, the station was rated
as much more crowded (M = 3.8, SD = .92) compared to off-peak hours (M = 3.01,
SD = .93, F (1, 1314) = 235.4, p = .000).

MANOVA station experience and waiting experience

A 3 (colour: blue vs yellow vs red) x 2 (light intensity: low vs high) x 2 (passenger type:
must vs lust) x 2 (density: busy vs quiet) multivariate analysis of variance (MANOVA)
was conducted with the dependent variables related to both station experience
(pleasure, arousal, dominance, score platform) and to waiting experience (accept-
able waiting time, utilitarian assessment waiting time, hedonic assessment waiting
time, time perception and time experience). The results can be found below
(Table 6.4).

Chapter 6 Colour and Light 111

Table 6.4 MANOVA (Wilks’ Lambda) for variables station and waiting experience

Variables station experience Variables waiting experience

F df p F df p
Colour 1.52 8, 2554 ns <1 10, 2512
Light intensity 2.78 4, 1277 .03 1.93 5, 1256 .09
Passenger type 2.99 4, 1277 .02 1.24 5, 1256 ns
Density <1 4, 1277 <1 5, 1256

Colour * light intensity 1.42 8, 2554 ns 1.34 10, 2512 ns

Colour * passenger type 2.05 8, 2554 .03 1.66 5, 1256 .08
Light intensity *passenger type <1 4, 1277 2.51 10, 2512 .03
Light intensity * density 1.94 4, 1277 .10 2.76 5, 1256 .03
Colour * density <1 8, 2554 <1 10, 2512
Passenger type * density 1.37 4, 1277 ns 2.25 5, 1256 .06

Colour * light intensity * passenger type <1 8, 2554 1.02 10, 2512 ns
Colour * light intensity * density 1.16 8, 2554 ns 1.04 10, 2512 ns
Colour * passenger type * density 2.25 8, 2254 .02 <1 10, 2512
Light intensity * passenger type * density <1 4, 1277 <1 5, 1256

Colour * light intensity * passenger type <1 8, 2554 1.16 10, 2512 ns
* density
Note: ns = non-significant

6.4.5 Station experience

The MANOVA for station experience revealed significant main effects for light
intensity and passenger type. A two-way interaction was also found between colour
and passenger type and a three-way interaction between colour, passenger type
and density (Table 6.4). As follow-up analysis we thus conducted various univariate
analyses of variance (ANOVAs) to ascertain which effects precisely occurred.

Main effects light intensity and passenger type for station experience
An ANOVA showed that passengers experienced more pleasure with a low light
intensity (M = 4.58, SD = 1.05) than with a high light intensity (M = 4.40, SD = 1.04,
F(1, 1321) = 9.63, p = .002). The same applied to dominance: passengers experienced
more dominance with a low light intensity (M = 4.34, SD = .73) than with a high light
intensity (M = 4.22, SD = .74, F(1, 1313) = 7.99, p = .005). Another ANOVA revealed that
lust passengers experienced more dominance (M = 4.33, SD = .73) than must passen-
gers (M = 4.23, SD = .75, F(1, 1313) = 5.58, p = .018).

112 waiting experience at train stations

 Interactions between colour and passenger type
An ANOVA revealed an interaction between colour and passenger type on pleasure
(F (2, 1317) = 7.02, p = .005) and on arousal (F(2, 1309) = 5.79, p = .003). Table 6.5 shows
the means and standard deviations and Figure 6.8 the interactions on pleasure
(Figure 6.8 A) and arousal (Figure 6.8B). For arousal an ANOVA showed that must
passengers were less stimulated by the colour yellow than by the colours red and
blue (F(2, 1309) = 7.55, p = .001). No significant differences were found for lust passen-
gers. Lust-passengers found the colours yellow and red more pleasant than must
passengers (F(2, 1317) = 4.17, p = .016), who found the colour blue the most pleasant
(F(2, 1317) = 3.13, p = .044).

Table 6.5 Means (and standard deviations) of colour and passenger type for pleasure,
arousal and platform score (Low and High density)

Must Lust
Blue Yellow Red Blue Yellow Red
M (SD) M (SD) M (SD) M (SD) M (SD) M (SD)
Pleasure 4.56 (1.07)a 4.28 (1.04)ae 4.46 (.99)e 4.38 (1.15)bc 4.68 (1.04)b 4.58 (1.02)c
Arousal 4.59 (.89)a 4.23 (.95)ab 4.51 (.84)b 4.48 (.96) 4.55 (.89) 4.49 (.82)

Pleasure Low density 4.63 (1.04)ab 4.24 (1.14)a 4.33 (.88)b 4.29 (1.15)cd 4.75 (1.07)c 4.71 (.99)d
High density 4.45 (1.09) 4.31 (.96)e 4.59 (1.07)e 4.53 (1.15) 4.63 (1.02) 4.51 (1.06)

Platform Low density 6.82 (1.36)e 6.49 (1.52)e 6.69 (1.25) 6.58 (1.34)ab 7.04 (.88)a 6.89 (1.13)b
score
High density 6.87 (1.32) 6.85 (1.22) 6.87 (1.24) 6.85 (.98) 6.77 (1.34) 6.71 (1.44)
Note: Means with identical superscripts (a,b,c,d and e) differ significantly in the row:
a,b,c,d p < 0.05, e p < 0.1

PLEASURE (A) AROUSAL (B)

means

means

4.7 4.7

4.6 4.6

4.5 4.5

4.4 4.4

4.3 4.3

4.2 4.2

must lust must lust

Passenger Type Passenger Type

Colour blue
yellow
red

Figure 6.8 Interaction between colour and passenger type on pleasure (A) and arousal (B)

Chapter 6 Colour and Light 113

Interactions between colour, passenger type and density
An ANOVA revealed a three-way interaction between colour, passenger type and
density (F(2, 1311) = 6.51, p = .002) on pleasure. Table 6.5 shows the average values
and standard deviations. It appeared that at quiet moments lust passengers expe-
rienced greater pleasure with the colours yellow and red than with the colour blue
(F(2, 1311) = 7.29, p = .001), whereas at quiet moments must passengers experienced
greater pleasure on a blue than on a yellow or red platform (F(2, 1311) = 1.88, p = .015).
At busy moments no differences were observed.
Finally, an ANOVA revealed a three-way interaction between colour, passenger type
and density on the platform score (F(2, 1303) = 2.83, p = .059). Table 6.5 shows the
average values and standard deviations and Figure 6.9 visualizes the interaction. It
appeared that at quiet moments lust passengers appreciated yellow on the platform
more than blue (F(2, 1303) = 3.68, p = .026). Although the results point in the right
direction, we did not find any significant differences between the colours yellow
and blue for must passengers (F(2, 1303) = 1.50, p = ns, Figure 6.9). The findings are
in accordance with reversal theory, which alleges that lust passengers are more
receptive to environmental stimuli than must passengers.

PLATFORM SCORE (LOW DENSITY) PLATFORM SCORE (HIGH DENSITY)

means
means

7 7

6.9 6.9

6.8 6.8

6.7 6.7

6.6 6.6

6.5 6.5

6.4 6.4

must lust must lust

Passenger Type Passenger Type

Colour blue
yellow
red

Figure 6.9 Three-way interaction between passenger type, density and colour on
platform score

6.4.6 Waiting experience

A MANOVA (Table 6.4) on waiting experience found interactions between passenger
type and light intensity and between light intensity and density. Moreover, a
marginal interaction effect was found between colour and passenger type and
density and passenger type (Table 6.4). A number of ANOVAs were conducted to
discover which effects occur for colour and light.

114 waiting experience at train stations

Interactions between colour and passenger type
An ANOVA revealed that the combination of colour and passenger type does indeed
influence both the hedonic assessment of waiting time (F(2, 1310) = 6.77, p = .001) and
the utilitarian assessment of waiting time (F(2, 1311) = 3.28, p =.04). The Means (and
SDs) can be seen in Table 6.6. The results are also visualized in the interaction plots
of Figure 6.10, in which yellow and blue are again the more dominant.

Table 6.6 Means (SDs) of colour on pleasant and useful waiting time assessment
(for must and lust passengers)

Blue Yellow Red

Means (SD) Means (SD) Means (SD)

Hedonic waiting time Must 4.09 (0.94)b 3.85 (1.02)bc 4.06 (1.03)c
assessment Lust 3.89 (1.07)ad 4.18 (0.96) a 4.05 (0.93)d

Utilitarian waiting time Must 3.52 (1.12) 3.39 (1.12) 3.47 (1.12)
assessment Lust 3.36 (1.14)bc 3.64 (1.11)b 3.57 (1.09)c
Note: Means with identical superscripts (a,b,c and d) differ significantly in the row:
a p < 0.001, b,c p < 0,05, d p < 0.1

HEDONIC WAIT (A) UTILITARIAN WAIT (B)

means

means

4.2 4.2

4.1 4.1

4 4

3.9 3.9

3.8 3.8

3.7 3.7

3.6 3.6

3.5 3.5

3.4 3.4

3.3 3.3

must lust must lust

Passenger Type Passenger Type

Colour blue
yellow
red

Figure 6.10 Interaction effect of colour and passenger type on hedonic (A) and
utilitarian (B) wait

Chapter 6 Colour and Light 115

Lust passengers experienced the waiting time on the yellow platform as more
pleasant (F(2, 1310) = 4.26, p = .014) and more useful (F(2, 1311) = 3.43, p = .033) than
on the blue platform. In contrast, must passengers experienced a more pleasant
waiting time (F(2, 1310) = 3.06, p = .047) on the blue platform than on the yellow one.

The results for colour on station and time experience support reversal theory. Must
passengers are serious and plan their journey ahead. Consequently, this group
demands fewer external stimuli. Lust passengers, on the other hand, are more
relaxed, more spontaneous and whimsical, which becomes apparent from their
greater need for stimuli. According to reversal theory (Apter, 2007; Walters, Apter &
Svebak, 1982), a desire for stimuli goes hand in hand with a preference for colour.
Must passengers prefer colours with a short wavelength (i.e. blue), whereas lust
passengers tend to opt for more stimulating colours, i.e. with a long wavelength (i.e.
yellow).

Light intensity and waiting experience

The MANOVA on waiting experience showed a marginally significant main effect on
light intensity. Hence, as a follow-up analysis, we conducted several ANOVAs.

Main effects light intensity on waiting experience

The ANOVAs revealed significant effects for the utilitarian waiting time assessment
(F(1, 1315) = 5.35, p = .02), the acceptance of the waiting time (F(1, 1322) = 7.61, p = .01),
and the short/long waiting experience (F(1, 1317) = 6.13, p = .01). The averages and
standard deviations can be seen in Table 6.7. It appeared that with a low light
intensity the waiting time was not only experienced as being more useful and more
acceptable but that it also appeared to last less long than with a high light intensity.

Interactions light intensity and density

ANOVAs showed that the combination of light intensity and density also influences
the acceptance of the waiting time (F(1, 1320) = 8.90, p = .003) and the waiting expe-
rience (F(1, 1315) = 5.58, p = .018). The averages and standard deviations can be found
in Table 6.7.

Figure 6.11 shows that on a busy platform the light intensity has hardly any
influence on the acceptance of the waiting time or how the duration thereof is expe-
rienced. However, on the quiet platform, the waiting time is experienced as more
acceptable with a low rather than a high light intensity (F(1, 1320) = 16.1, p = .000).
Also the time on a quiet platform seems to take less long with a low versus a high
light intensity (F(1, 1315) = 11.83, p = .001). In quiet periods, a low light intensity
would thus seem to result in positive effects for the waiting experience.

116 waiting experience at train stations

Table 6.7 Mean scores (SDs) for light intensity on utilitarian wait, acceptable wait and
short/long experience of the wait on platform with low and high density

Low light intensity High light intensity

Mean (SD) Mean (SD)
Utilitarian wait 3.56 (1.12) 3.43 (1.12)*
Acceptable wait 5.79 (1.13) 5.59 (1.43)**
Experience of the wait 3.37 (1.76) 3.62 (1.85)**
(1 = short, 7 = long)

Acceptable wait Low density 5.90 (1.27) 5.49 (1.41)**

High density 5.70 (1.32) 5.74 (1.43)
Experience of the wait Low density 3.24 (1.80) 3.71 (1.80)**
(1 = short, 7 = long)
High density 3.49 (1.71) 3.48 (1.91)
Note: Means with ** and * differ significantly in the row: ** p < 0.001, * p < 0.05.

Figure 6.11 Interactions between light intensity and density on acceptable wait
(A, 1 = unacceptable, 7 = acceptable) and waiting time and experience of
the wait (B, 1 = short, 7 = long)

Chapter 6 Colour and Light 117

What is remarkable is that despite the positive affective evaluation of the lower light
intensity, 92.6% of the experimental subjects claimed to have a (cognitive) preference
for a station with a high light intensity.

6.4.7 Returning to the hypotheses

Hypothesis 1 is confirmed: A warm colour affords more stimuli and initiates a more
positive station and waiting experience for lust passengers. Regardless of the light
intensity with the yellow colour, lust passengers appeared to experience more
arousal and greater pleasure with the warm colours red and yellow. On a yellow
platform lust passengers not only experienced the waiting time as being both more
pleasant and useful but they also awarded a higher score to the (quiet) platform with
the red and yellow colour. Must passengers, on the other hand, experienced more
pleasure with the blue colour, as well as finding the wait more pleasant.
Hypothesis 2 is confirmed: A cool colour affords fewer stimuli and initiates a more
positive station and waiting experience for must passengers. With the blue colour,
must passengers experienced more stimuli than lust passengers and more pleasure
on a blue platform than on a yellow one. Must passengers also awarded the (quiet)
blue platform a higher score and claimed to find waiting on the blue platform more
pleasant than on the yellow one. These findings support reversal theory: must
passengers prefer to wait in cool colours, just as lust passengers prefer to wait in
warm colours.
Hypothesis 3 is confirmed: In a quiet environment with little light, colour affords fewer
stimuli to passengers and this leads to a more positive station and waiting experience.
Regardless of the colour, a quiet platform with a low light intensity affords a more
positive waiting experience than a quiet platform with a high light intensity. Waiting
on a quiet platform with a low light intensity is not only deemed as being more
acceptable but also the wait seems to be shorter.
Hypothesis 4 cannot be confirmed: In a busy environment with a lot of light, colour
affords too many stimuli to passengers and this leads to a more negative station and
waiting experience. With a high light intensity combined with colour, no differences
were found for the waiting experience when the platform was quiet or busy. Light
intensity and colours have thus no effect on the waiting experience combined with
density.

6.4.8 Conclusions virtual study

After analysing the results per scenario, the preference for colour appears on
whether one is a must or lust passenger (and thus in a hurry or not). The findings
from this study support Apter’s reversal theory (Apter, 2007; Walters, Apter &
Svebak, 1982), which alleges that people under pressure prefer cool colours and in
a relaxed situation incline towards warm ones. Needing a colour thus appears to be
dependent on the demand for stimuli, whereby lust passengers prefer warm colours
and must passengers cool ones.

118 waiting experience at train stations

Also, the results particularly show positive effects in dimmed situations. Dimly lit
surroundings appear to evoke more positive affective reactions to the waiting time
and the acceptance of the waiting time than when the lights are brighter. Moreover,
time seems to pass more quickly in dimly lit situations than when the lights are
brighter. This confirms the findings of Baker and Cameron (1996). Apparently, a
lot of light in a waiting situation is too aggravating, despite passengers having a
cognitive preference for a high light intensity. It may be that they feel that a high
light intensity offers greater safety. However, research by Van Bommel (2001; 2003;
2004) shows that it is not the intensity of the light that is important but the way it is
shed, i.e. being able to see the faces of others.
The results show that manipulations in a virtual retail environment successfully
allow effects with colour, light, density and time pressure to be demonstrated and
that the findings are comparable with those from the field study.

6.5 Conclusion of the three studies

The findings of the three studies offer an initial insight into the way colour and
light work in a railway station. Generally speaking, the conclusion is that platforms
are experienced as boring, grey and unappealing and that adding colour generates
positive effects, both on the station evaluation and on the waiting experience (Van
Hagen, Galetzka & Sauren, 2010; Van Hagen, Pruyn, Galetzka & Peters, 2008). As also
became apparent from earlier research, colour and light intensities afford interac-
tions (Babin, Hardesty & Suter, 2003; Brengman & Geuens, 2004; Mehrabian, 1976;
Valdez & Mehrabian, 1994). The findings of the studies reveal that the hedonic tone
and the waiting experience can be influenced by the combination of colour and light
but that this depends on the context. From the field study it became apparent that
colour, particularly with a low light intensity (as compared with a high light inten-
sity), results in a positive station experience. Also in the virtual online study, low
light intensity yielded positive results for station and waiting experience, particu-
larly when the platform was quiet. The same study also revealed that time seemed to
take less long and was more acceptable in dimmed lighting when the platform was
quiet. The required level of lighting depends on the task to be performed; the more
complex the task, the more lighting it requires (Biner, Butler, Fischer & Westergren,
1989; Butler & Biner, 1987; Van Bommel, 2001; 2003; 2004). Earlier research also
showed that people feel the most comfortable with a certain level of lighting (Baker
& Cameron, 1996; Hopkinson, Petherbridge & Longmore, 1966; Küller, Ballal, Laike,
Mikellides & Tonello, 2006). Light intensity, moreover, has an effect on the level of
arousal (Baron, Rea & Daniels, 1992; Daurat, Aguirre, Foret, Gonnet, Keromes &
Benoit, 1993; Gifford, 1988; Kallman & Isaac, 1977; Mehrabian, 1976; Miwa & Hanyu,
2006). Apparently, when passengers have to wait on a platform they experience too
many light stimuli as negative and prefer dimmed lighting.

Chapter 6 Colour and Light 119

The virtual studies also revealed that time in a cool colour seems to go faster than in
a warm colour and that must passengers prefer the cool colour blue on a platform.
In contrast, lust passengers experience greater pleasure with the warm colours red
and yellow. The shorter time perception with the colour blue concurs with findings
from earlier studies (Gorn, Chattopadhyay, Sengupta, & Tripathi, 2004; Singh,
2006; Smets, 1969). Cool colours such as blue and green are seen to be calming and
warm colours such as yellow and red are seen to be stimulating (Adams & Osgood,
1973; Jacobs & Suess, 1975; Valdez & Mehrabian, 1994; Walters, Apter & Svebak,
1982; Wexner, 1954). With task-related activities, cool colours are preferred to warm
colours that evoke negative emotions (Kwallek et al., 1988; in Stone & English, 1998;
Walters, Apter & Svebak, 1982). However, people are attracted to warm colours
(Belizzi, Crowley & Hasty,1983). Hence the explanation that passengers who are
waiting and not performing a task are more receptive to the more stimulating warm
colours and less goal-directed passengers prefer the colour blue because it is less
distractive.
In all three studies optimal arousal theory applies: too few or too many stimuli lead
to a more negative hedonic tone, just as an optimal level of stimuli leads to a positive
hedonic tone. The context appears to be of importance here. In reversal theory, two
levels of optimal stimuli can be distinguished, depending on the state of the experi-
mental subject. In accordance with reversal theory, goal-oriented (must) passengers
appear to react more positively to cool colours, whereas less goal-oriented (lust)
passengers prefer warmer colours. From the interaction effects between colour and
light, the number of stimuli appear to be complementary: particularly in a quiet
environment, a low level of lighting and colours result in a more positive hedonic
tone and a more positive waiting experience. It would seem that an optimal level of
stimuli, with a correct mix of light intensity, stimulation of the colours and density,
provides a congruent processing fluency, whereby people feel more comfortable
(Van Rompay & Pruyn, in press). If the number of stimuli is mildly incongruent, the
optimal level of stimulation in various situations is achieved (Eroglu, Machleit &
Chebat, 2005; Heckler & Childers, 1992). When adding colour and light to a platform
environment, it is vital that the density on the platform and the goal-orientedness
of the passengers is taken into consideration. Only by carefully tailoring the correct
colour with the right light intensity can a more positive station and waiting experi-
ence be achieved.

6.6 Recommendations for NS

In practice this means that in peak hours, when it is busy and there are relatively
more must passengers at the station, cool colours should be used with a high light
intensity. The cool colours afford visual calm and the high light intensity keeps
people more on the alert and encourages the task-related getting on and off the

120 waiting experience at train stations

train. In contrast, stimulating colours and a lower light intensity could be used in
off-peak hours, when it is quieter and there are more lust passengers, in order to
assuage any feeling of boredom. NS could consider varying the light intensity and
coupling it to the arrival of a train. Passengers prefer less light whilst waiting for the
train but when it comes in, they are alert. A temporary higher light intensity would
ease the boarding process.

Chapter 6 Colour and Light 121

 Chapter 7
Music

‘To stop the flow of music would

be like the stopping of time itself,
incredible and inconceivable.’
Aaron Copland, 1900-1990
7.1 Introduction

Besides atmospheric influences such as colour and lighting, music has been
acknowledged as one of the most important and effective elements in the service-
scape. This is partly due to the fact that it is relatively inexpensive to deploy and
easy to control and partly because music has been shown to positively impact a
wide range of consumer responses in retail and service settings (e.g. Garlin & Owen,
2006), and more specifically in restaurants (Caldwell & Hibbert, 2002; Milliman,
1986; North, Shilcock & Hargreaves, 2003), banks (Dubé, Chebat & Morin, 1995;
North, Hargreaves & McKendrick, 1999) and travel agencies (Bitner, 1990). As far as
we know, no studies have been conducted to date on the effect of music at railway
stations. Although a considerable number of studies have examined isolated effects
of music, few have incorporated effects of other atmospheric cues or contextual
variables such as situational and personal variables (but see for exceptions Eroglu,
Machleit & Chebat, 2005; Massara, Liu & Melara, 2010; Mattila & Wirtz, 2001 and
Michon, Chebat & Turley, 2005). Moreover, understanding the processes through
which atmospherics interact to affect customer experiences is limited.

7.1.1 Impact of music

Music is an intangible (ambient) environmental variable which is capable of evoking
complex emotional, cognitive and physiological reactions (Grewe, Nagel, Kopiez
& Altenmüller, 2007; Magnini & Parker, 2009; Tansik, & Routhieaux, 1996; Wirtz &
Bateson, 1999). Bruner (1990) alleges that each piece of music has a physical dimen-
sion (volume, pitch, rhythm and tempo), an emotional tone (minor or major) and a
preferential dimension (the degree to which the music is appreciated and known).
Although music is composed of different components, it is perceived holistically, i.e.
as a whole (e.g. Botschen & Growther, 2001; Holahan, 1982). It is not a prerequisite
that music be consciously perceived (Dijksterhuis, Smith, Van Baaren & Wigboldus,
2005), and research shows that music can influence behaviour without consumers
being aware of it (Milliman, 1982; Gulas & Schewe, 1994; North, Hargreaves &
McKendrick, 1999).
Studies have revealed that music can produce a myriad of effects, depending on
the manipulation and the context. Music influences the degree of arousal (Kent &
Kellaris, 2001; Smith & Curnow, 1966; Sweeney & Wyber, 2002; Yalch & Spangenberg,
2000), the perception of crowding (Eroglu, Machleit & Chebat, 2005), the store
image (Gulas & Schewe, 1994), the interaction between client and salesperson
(Dubé, Chebat & Morin, 1995), the purchasing speed (Smith & Curnow, 1966), the
purchasing and consumption behaviour (Areni & Kim, 1993; Lammers, 2003; Yalch
& Spangenberg, 1990), the tendency towards impulse buying (Kellaris & Kent, 1991),
the state of mind (Bruner, 1990) and the experience of time (Kellaris & Altsech,
1992; Kellaris & Kent, 1992). The impact of music can be mediated by music tempo
(Milliman, 1982; 1986), music volume (Kellaris & Kent, 1992; Smith & Curnow,

Chapter 7 Music 125

1966), musical preference (Herrington & Capella, 1996), the use of background or
foreground music (Yalch & Spangenberg, 1990; 1993; Areni & Kim, 1993) and by age
(Gulas & Schewe, 1994; Yalch & Spangenberg, 1990).
The volume, tempo and genre of music can have a stimulating effect (arousal). Loud
music stimulates more powerfully than soft, just as fast music does more than slow
and techno more than classical. Various studies have shown that tempo induces the
greatest physiological reactions in breathing, blood pressure and heartbeat (Kellaris
& Kent, 1992). Music with a tempo below 50 BPM (beats per minute) even has a
calming effect, because our body attunes itself, as it were, to the speed of the music.
Besides this therapeutic effect of slow music on our body, research findings reveal
that slow-tempo music induces greater positive reactions for satisfaction, relaxation
and pleasure than more up-tempo music (Oakes, 2003).

7.1.2 Music and emotions

Whether a person wants (or does not want) to hear (a specific kind of) music,
depends on one’s goal, state of mind and personality (Stratton & Zalanowski, 2003).
Extroverts, for example, seek more complex stimuli and are more receptive to
intricate music. On listening to music, extroverts experience greater pleasure and
achieve better than introverts (Furnham & Allas, 1999). According to Kellaris and
Kent (1994), classical music initiates more pleasure and pop music more arousal.
Positively valued music evokes a more positive emotional response and stronger
approach behaviour towards the service organization (Hui, Dubé & Chebat, 1997;
Lindstrom, 2005; Sweeney & Wyber, 2002). Music is not just stimulating but it can
also evoke associations and appeal to certain target groups (Herrington & Capella,
1996). The positively associative effect of music appears from a research in which
consumers in a supermarket bought German wines when they heard German
music and French wines when they heard French music, without their being aware
of German or French music being played (North, Hargreaves & McKendrick, 1999).
Similarly, with classicial music in the background, consumers in a wine shop also
tended to buy the more expensive wines (Areni & Kim, 1993), and in a cafetaria were
even prepared to pay more (North & Hargreaves, 1998).
Music can also evoke negative emotions. If at a given time an individual has no
desire for music, e.g. when one has to perform a (complex) task, the presence of
music will be experienced as annoying and will induce stress (Kaltcheva & Weitz,
2006; Massara, Liu & Melara, 2010). Also in combination with density can music
lead to more stress. The (negative) effects of too much density can be compensated
by ‘low arousal’ stimuli (Baker & Cameron, 1996; Eroglu, Machleit & Chebat, 2005).
Creating a quiet zone during busy moments may well decrease the stress caused by
crowding. When someone has the choice whether or not to listen to music, the sense
of personal control increases and feelings of stress can be avoided or weakened.

126 waiting experience at train stations

7.1.3 Music tempo, musical genre and waiting time
Positive or negative affective reactions of consumers to music can influence the
subjective waiting time and length of stay (Caldwell & Hibbert, 2002). On the
basis of a literature study, Baker and Cameron (1996) posited that music which
creates a positive affect among consumers results in the waiting time in a service
environment as appearing to be less long (Chapter 4). Various studies have shown
that music tempo has contradictory effects on the estimation of the waiting time
(Oakes, 2000; 2003). With slow music, for example, people spend a longer period in a
restaurant (Caldwell & Hibbert, 1999; Milliman, 1982; 1986), but fast music results in
an overestimation of the waiting time (Kellaris & Mantel, 1996; Oakes, 2003). Smith
and Curnow found that a high volume effected a shorter length of stay in a super-
market (Smith & Curnow, 1966), just as Kellaris and Altsech found that a higher
volume led to a longer time estimation (Kellaris & Altsech, 1992; Kellaris, Mantel &
Altsech, 1996). Cameron, Baker, Peterson and Braunsberger (2001) determined that
music influences the perception of the waiting time and mood.
Sometimes no relationship is found at all between music and waiting time. Areni
and Kim (1993), for example, found no differences for length of stay with classical
music compared with the Top 40, just as Herrington and Capella (1996) found no
relationship between music tempo and volume and the objective length of stay in a
supermarket. They did, however, determine that consumers stayed in a supermarket
longer when music was played that they liked. Pleasant music (major key) can lead
to a longer waiting time perception (Kellaris & Kent, 1992), but familiar music in a
waiting situation can shorten the time perception (Baily & Areni, 2006). According to
Hui, Dubé and Chebat (1997), the style of music does not influence the time percep-
tion but it does initiate a more positive mood and more positive emotions.
The studies give the impression that the attention is focused on familiar music
and music in a major key or with a higher volume (Baker & Cameron, 1996; Kellaris
& Kent, 1992; Yalch & Spangenberg, 1990; 2000). One explanation might be that
music that draws attention is remembered better and that in retrospect more would
seem to have happened with as a result that the perceived time seems longer. That
would mean that the storage size (Ornstein, 1969) or segmentation model (Homa &
Poynter, 1983) is applicable. However, a station environment differs from a retail
environment in a number of ways. At a station, passengers keep a close eye on the
time because they have a train to catch. Music might then distract passengers from
the time which, according to Zakay and Block’s attentional model (1997, Chapter 3),
could lead to their assessing the wait as shorter.

Music in relation to the waiting situation

Reversal theory (Apter, 2007) alleges that the context is important for the number of
stimuli that people appreciate (Chapter 4). In a busy environment and with a goal-
oriented task, people are less receptive to extra stimuli than in a quiet environment
and when they have no task at hand. We expect music to distract passengers from

Chapter 7 Music 127

the waiting time and that they will experience the (kind of) music differently at busy
or quiet moments.
To test these predictions, we conducted two field studies and one experimental
study in a virtual station in which the effects of music were tested during peak and
off-peak hours. Study 1 addresses the effect of music on perceived control under
variable conditions of density. Study 2 explores how to make informed choices
on the type or kind of music employed and investigates the relationship between
density, music tempo and station evaluation. By means of an online experiment, the
third study examines what influence stimulating and calming musical genres have
on the waiting experience. Besides density, the motivational orientation (must/lust)
were included as moderating variables.

7.2 Study 1 The role of perceived control in the

relation between human density and background
music in a railway station: A field experiment

7.2.1 Introduction
Although the potential positive effects of background music have been firmly
established, recent findings indicate that effects of music should not be studied
in isolation but rather in its interplay with other atmospheric variables (Eroglu,
Machleit & Chebat 2005; Matilla & Wirtz, 2001; Oakes & North, 2008).
However, research addressing combined effects of atmospheric variables is scarce
and insights into the underlying processes through which atmospherics affect
consumer behaviour are limited. Of particular interest for the present purpose is
the finding that music may aggravate or alleviate effects of an important variable
that is particularly hard to control: aversive density conditions resulting from too
few or too many customers in the service environment (Eroglu, Machleit & Chebat,
2005). Since perceptions of crowding are an important determinant of service evalu-
ation (e.g. Hui & Bateson, 1991), service managers are advised to mitigate negative
effects of density conditions as much as possible.
Departing from the given that railway stations by definition are settings with large
fluctuations in density, the degree to which music can attenuate negative conse-
quences of density will be explored. In considering the consequences of density on
consumer response, perceived control, i.e. the extent to which people can realize
their goals in a specific situation, has been shown to be a key variable of interest
(Dion, 2004; Hui & Bateson, 1991; Van Rompay, Galetzka, Pruyn & Moreno-Garcia,
2008).
In railway stations, two types of goals may be distinguished. It is of paramount
importance to travellers to arrive at the station on time and to find their way to the
platform within a span of a few minutes. Such goals may be considered functional
insofar as they relate to practical activities aimed at securing the service offer (i.e.

128 waiting experience at train stations

catching the right train at the right time). However, practical goal achievement may
not always claim top priority. For instance, during extended waits or delays, goals
related to wayfinding and time management may have already been met. Likewise,
during off-peak hours (i.e. when density is low), stations allow for easy wayfinding
since access to information displays, information messages and platforms is
unobstructed. In other words, under these circumstances, practical goals may
recede to the background either because they have already been met or because goal
attainment poses no difficulties. In consequence, customers may be more attuned
to distractions and entertainment that allow for a pleasant platform experience.
Taking note of these considerations, the two-sided function of music becomes
apparent. More specifically, it is argued that music may decrease feelings of
control by interfering with customers’ needs to stay alert and tuned to information
messages and the sounds of approaching trains (i.e. by thwarting practical goal
achievement). Alternatively, however, it is argued that music may increase feelings
of control and the hedonic tone (Apter, 2007) during off-peak hours when functional
goal achievement is less demanding and experience-related goals come into play. It
is then that music may facilitate (experiential) goal achievement by being a welcome
source of distraction or entertainment.

7.2.2 Density and Perceived Control

Of all environmental factors, human density, i.e. reflecting the number of customers
in the service setting, is, for obvious reasons, the most difficult to control. Density is
generally conceptualized as a stressful experience (Cozby, 1973; Eroglu, Machleit &
Barr, 2005; Hui & Bateson, 1991; Machleit, Eroglu & Mantel, 2000), and is considered
the primary determinant of crowding perceptions (Stokols, 1972). In addition, highly
crowded environments have been found to evoke higher levels of negative emotions
while shopping (Machleit et al., 2000), and decreased shopping satisfaction
(Machleit, Kellaris & Eroglu, 1994). Naturally, effects of density may vary with person-
ality (Van Rompay, Galetzka, Pruyn & Moreno-Garcia, 2008), culture (Pons & Laroche,
2007; Pons, Laroche & Mourali, 2006), shopping intentions (Eroglu, Machleit & Barr,
2005), and the architectural space (Evans, Lepore & Schroeder, 1996).
Explanations of density effects usually stress the role of perceived control (Dion,
2004; Hui & Bateson, 1991; Langer & Saegart, 1977; Van Rompay et al., 2008), in
general terms defined as the need to be master over one’s environment (White,
1959). In more practical terms, perceived control has been conceptualized in terms
of goal achievement (cf. Ward & Barnes, 2001); environmental factors obstructing
goal achievement reduce feelings of control whereas factors facilitating goal
achievement increase feelings of control. High density may decrease perceptions
of control by, for example, reducing privacy or hindering free movement through
the environment. Hui and Bateson (1991), for instance, demonstrated that density
negatively affects perceptions of control in a bank setting, thereby reducing
experienced pleasure and, in turn, approach behaviours.

Chapter 7 Music 129

7.2.3 Formulation of hypotheses
In considering the relation between music and perceived control for a railway
station, it could be argued that under conditions of high density, the presence
of music negatively influences customer experience insofar as it aggravates the
negative effects of high density on perceived control. After all, when perceived
control is already low due to high density, the presence of music may further
aggravate these effects by being an additional hindrance to, for instance, clear
reception of information messages. At the same time, however, customers may
positively value music when density is low, since finding one’s way and staying tuned
to information messages is less of a problem. In other words, under these circum-
stances, the primary goal of being at the right place on time has been met and
secondary goals come into play. Although high levels of density and music may be
considered ‘too much’, situations involving low levels of density and no music may
be characterized as boring. In such low density situations, perceptions of control are
positively affected by music because it provides a welcome distraction or source of
entertainment.

Based on the foregoing, we predict that:

H1: In a high-density service environment, the presence of background music, as

opposed to the absence thereof, thwarts practical goal fulfilment (i.e. decreases control),
in turn negatively affecting station evaluation.

H2: In a low-density service environment, the presence of background music, as opposed

to the absence thereof, facilitates experiential goal fulfilment (i.e. increases control), in
turn positively affecting station evaluation.

By implication, evaluations are expected to be the most positive in situations where

density is low and music is playing, and, conversely, in situations where density is
high and music is absent.

7.2.4 Method
A 2 (no music vs music) x 2 (density: off-peak hours vs peak hours) between-subjects
design in a field setting was employed to test the hypotheses. The study was
conducted at a large railway station in the Netherlands. Background music was
played at a moderate volume level over the course of the study.

Participants
A total of 88 passengers (52% male, 48% female; mean age 35; range 18-80 years)
participated in this field experiment. On the platform, passengers were randomly
approached by a researcher who asked them to fill in a questionnaire on the
ambience of the railway station. The respondents were given the opportunity to

130 waiting experience at train stations

finish and (anonymously) hand in the questionnaire during their train journey.
Ultimately, the music condition included 24 participants during peak hours and
18 participants during off-peak hours. The no music condition included 26 partici-
pants during peak hours and 20 participants during off-peak hours.

Experimental Procedures
The study was conducted on four consecutive weekdays (Tuesday-Friday).
Background music was played on the platform during peak and off-peak hours.
On Tuesday and Wednesday no music was played. Music (a mix of Eurocharts’
international hits) was played on Thursday and Friday (from 06:30-23:59hrs).
Taking into account that stations are much more crowded during peak than
off-peak hours, density conditions (low versus high) were set depending on the time
of day (peak hours vs off-peak hours).

Measures
–– Manipulation Check. We used peak and off-peak hours to manipulate density.
Since people may vary in the extent to which they perceive a dense condition as
crowded (Stokols, 1972), a measure of perceived crowding was used (cf. Hui &
Bateson, 1991). Perceived density was measured with the item “This station is
crowded” (1 = totally disagree, 7 = totally agree).
–– Dominance. Perceived control was measured with three items (Russell &
Mehrabian, 1977): “I felt in control at the station”, “At the station I could find
what I was looking for” and “I felt unrestricted at the station” (1 = not at all,
7 = totally; Coefficient Alpha = .75).
–– Station Evaluation. Station evaluation was measured with three items: “At this
station I enjoy travelling by train”, “I enjoy being at/travelling to and from this
station” and “I would recommend others to travel from and to this station”
(1 = not at all, 7 = totally; Coefficient Alpha = .75).
–– Relaxed wait. Two questions also measured whether the wait at the station was
found to be relaxing: “I found the wait at the station comfortable” and “I was
calm and relaxed at the station” (1 = not at all, 7 = totally; r = 0,50).
Finally, demographics and travel frequency were recorded.

7.2.5 Results study 1

Manipulation check
We conducted an analysis of variance to test the density manipulation. The
respondents in the peak hour condition rated the station as more crowded (M = 4.9,
SD = 1.37) than the respondents in the off-peak condition (M = 3.9, SD = 1.85,
F(1, 82) = 7.75, p < .01), indicating that the density manipulation was successful.

Chapter 7 Music 131

Test of hypotheses
The interactive effects of background music and density on customer responses
(perceived control and station evaluation) were explored by means of a multivariate
analysis of variance (MANOVA). Results showed a significant interaction between
the conditions (F(3, 75) = 7.23, p < .001). The main effects for density (F(3, 75) = 1.12,
ns) and music (F(3,75) = 1.02, ns) did not reach significance.
Univariate analyses of variance (ANOVAs) were conducted to test the hypothesized
interaction effects between music and density on perceived control, station evalu-
ation and relaxed wait. Results showed significant interaction effects on perceived
control (F(1, 79) = 14.72, p < .001), station evaluation (F(1, 77) = 5.29, p < .03), and
relaxed wait (F(1, 77) = 11.98, p < .001)6.

PERCEIVED CONTROL (A) STATION EVALUATION (B) RELAXED WAIT (C)

means

means

means
5.6 5.6 5.6

5.4 5.4 5.4

5.2 5.2 5.2

5 5 5

4.8 4.8 4.8

4.6 4.6 4.6

4.4 4.4 4.4

4.2 4.2 4.2

4 4 4

3.8 3.8 3.8

3.6 3.6 3.6

3.4 3.4 3.4

3.2 3.2 3.2

3 3 3

low high low high low high

Density Density Density

no music
music

Figure 7.1 Perceived control (A), station evaluation (B) and relaxed wait (C) as a
function of density and background music

6 Because it is possible that commuters travel from the station 5 days a week, their opinion
might be influenced by previous station experiences. Therefore, we conducted a 2 x 2
ANCOVA on station evaluation with station experience as covariate. The reported results
remained significant when controlled for station experience.

132 waiting experience at train stations

As can be seen in Figure 7.1, when density is low, background music positively
affects perceived control (F(1, 79) = 12,81, p < .001), station evaluation (F(1, 77) = 3.21,
p < .08) and relaxed wait (F(1, 77) = 10,26, p = .002). Under conditions of high density,
the effects of background music (although pointing in the predicted direction) did
not reach significance (F(1, 79) = 2.95, ns for perceived control, (F(1, 77) = 2.08, ns for
station evaluation and (F(1, 77) = 2.49, ns for relaxed wait).
In sum, these results partly confirm our predictions by indicating that under condi-
tions of low density, the presence of music resulted in higher perceived control,
more positive station evaluation and relaxed wait.
Hypotheses 1a and 1b state that the interaction effect of music and density on
station evaluation is mediated by perceived control. For this type of mediation to
apply, the relation between perceived control and station evaluation should be
significant, as was confirmed by a correlation analysis (r = .33, p < .01). In addition,
the observed interaction between density and music on station evaluation should
become non-significant when perceived control is included in the analysis with
density and music as independent variables and station evaluation as dependent
variable. Finally, the effect of the mediator (perceived control) on the dependent
variable (station evaluation) should remain significant. To complete the require-
ments for mediation perceived control was included as a covariate in the 2×2
ANCOVA for station evaluation. In line with the requirements for mediation, the
interaction between density and music became non-significant (F(1, 76) = 1.84, ns),
whereas the effect of the mediator (perceived control) on the dependent variable
(station evaluation) remained significant (F(1, 76) = 4.70, p = .03). The results indicate
that, as expected, the interactive effect of background music and density on station
evaluation is mediated by perceived control.

7.2.6 Discussion study 1

The findings from study 1 demonstrate that music can be used to counteract
negative effects of low density. In line with predictions, it was shown that music
may best be used in low-density conditions, i.e. during off-peak hours. These
findings reveal a prime mechanism through which music and density conjointly
affect the experience of the service setting under discussion. In line with previous
research (e.g. Dion, 2004; Hui & Bateson, 1991; Van Rompay et al., 2008), music
and density were shown to impact feelings of perceived control (i.e. extent of goal
fulfilment), and, hence, to conjointly shape the station experience. However,
whereas in previous research atmospherics were mostly studied in isolation (Eroglu,
Machleit & Chebat, 2005), the findings presented contribute to existing literature by
incorporating the interactive effects of two important atmospheric variables and by
focusing on the mediating process. With respect to the mediating process outlined,
future research should establish whether music and density affect customers’ sense
of control via different routes. For instance, it could be argued that music primarily
affects auditory control, whereas density affects visual control. Nonetheless such

Chapter 7 Music 133

fluctuations in different types of control may ultimately transpire in a general
feeling of being in or out of control. We will come back to this in Chapter 9.

7.3 Study 2 Influence of music tempo in a busy and

quiet platform environment

7.3.1 Introduction
The results from study 1 indicate that music can be used to counteract negative effects
of low or high density. In line with predictions, it was shown that music may best be
used in low-density conditions, i.e. during off-peak hours. However, these results
are not very informative when it comes to the choice of music. As discussed, musical
selections may vary on many dimensions, genre and tempo being the most obvious.

7.3.2 Formulation of hypotheses

Interestingly, music tempo has received considerable research attention (e.g.
Eroglu, Machleit & Chebat, 2005b; McElrea & Standing, 1992; Milliman, 1982; 1986;
Oakes, 2003). On the basis of a literature review, Oakes and North (2008) concluded
that congruency of music together with other environmental stimuli determines
the finding of either positive or negative effects. Of particular importance for the
present context is a study by Eroglu, Machleit & Chebat (2005) that showed that
slow-tempo music in a retail setting positively affected hedonic and utilitarian
evaluations under conditions of high density, whereas up-tempo music had positive
effects under conditions of low density (Eroglu, Machleit & Chebat, 2005). An
explanation for these results holds that under moderate incongruity (arising from
low density and up-tempo music or vice versa), consumers’ evaluations are the most
positive. Also optimal arousal theory offers an explanation: in a quiet environment
with quiet music, too few stimuli are perceived, whereby the pleasure to remain
in that environment diminishes (Apter, 2007; Hebb, 1955). In service marketing
literature, no studies have been reported that address the interaction of these two
factors. Based on these findings, it is expected that:

H1: In a high-density service environment, slow- as opposed to up-tempo music

positively affects station evaluation.

H2: In a low-density service environment, up- as opposed to slow-tempo music positively

affects station evaluation.

7.3.3 Method
A 2 (music: slow- vs up-tempo music) x 2 (density: off-peak hours vs peak hours)
between-subjects design in a field setting was employed to test the hypotheses
presented. Background music was played at a Dutch railway station at a moderate
volume level over the course of four consecutive days.

134 waiting experience at train stations

Participants
A total of 104 passengers (59 male and 44 female; mean age 33; range 17-70 years)
participated in this field experiment. Again, passengers were randomly asked to fill
in a questionnaire on station ambience in the train after it left the station.

Experimental Procedures
Music was played all day (from 06:30-23:59hrs) on four weekdays at the railway
station. On Friday and Monday slow music was played (‘easy listening’ pop songs at
minus 72 BPM), and on Tuesday and Wednesday up-tempo music was played (hits,
over 94 BPM).
As in study 1, the density manipulation was effected by variations in the time of day
that the questionnaires were distributed, filled in and collected. Again, the meas-
urement periods were categorized as either peak hours (16:00–18:00hrs) or off-peak
hours (21:00-23:59hrs).

Dependent Measures
For methodological reasons, the first two field experiments were carried out with a
minimal number of questions so that the time between the confrontation with the
stimulus and the moment of measurement (in the train) would remain as short as
possible. For this reason, choices had to be made on the number of questions.
–– Manipulation check. Perceived density was measured with the item “This station
is crowded” (1 = totally disagree, 7 = totally agree).
–– Relaxed wait. This variable specified how the experimental subjects perceived
the environmental stimuli and whether they felt comfortable at the station:
“I was calm and relaxed at the station” (1 = totally disagree, 7 = totally agree).
–– Station evaluation. This was determined by asking participants to evaluate the
station by awarding a score on a 10-point scale (1 = very poor, 10 = excellent).
–– Service evaluation. As an organization, NS is interested to find out whether
music influences the perception of the service evaluation. This two-item variable
thus specified how the experimental subjects experienced the service of NS:
“I find the level of service at this station good” and “The service staff seem quite
friendly” (1 = totally disagree, 7 = totally agree; r = .58).

7.3.4 Results study 2

The manipulation check confirmed that during peak hours, the station was rated
as much more crowded (M = 3.8, SD = .91) compared with off-peak hours (M = 2.7,
SD = 1.12; F (1, 101) = 26.94, p < .001).
It was predicted that in a high-density environment, slow- as opposed to up-tempo
music would positively influence customer evaluations, and vice versa. To test these
hypotheses, first a MANOVA explored the effect of density and music tempo on the
dependent variables and revealed a significant interaction that supported our predic-

Chapter 7 Music 135

tions (F(3, 95) = 8.16, p = .000). Next, univariate 2 (slow-tempo vs up-tempo music) x 2
(low density vs high density) ANOVAs were performed for each dependent variable.
First we saw for relaxed wait an effect for the interaction between music and density
(F(1, 97) = 6.15, p = .015). In a busy environment waiting was more relaxing with slow-
than up-tempo music (F(1, 97) = 3.80, p < .05). For quiet periods this difference was
non-significant (F(1, 97) = 2.51, ns, Figure 7.2A).
For station evaluation, the results also yielded a significant effect for the interaction
between music and density (F(1, 97) = 4.05, p < .05). In a high density environment,
up-tempo music resulted in a less positive station evaluation whereas slow-tempo
music positively impacted station evaluation (F(1, 97) = 4.89, p < .03). In the low
density environment, however, the difference between the music conditions was
non-significant (F< 1, ns, Figure 7.2B).
Finally, we also conducted an ANOVA for service evaluation and saw a similar
interaction effect (F(1, 100) = 20.44, p = .000). In a quiet environment, the service was
positively rated with up-tempo music (F(1, 100) = 11.39, p = .001), just as the service
was positively rated in a busy environment with slow-tempo music (F(1, 100) = 8.51,
p = .004, Figure 7.2C).

RELAXED WAIT (A) STATION SCORE (B) SERVICE EVALUATION (C)

means

means

means

5.4 7.4 5.4

5.2 7.2 5.2

5 7 5

4.8 6.8 4.8

4.6 6.6 4.6

4.4 6.4 4.4

4.2 6.2 4.2

4 6 4

3.8 5.8 3.8

3.6 5.6 3.6

3.4 5.4 3.4

3.2 5.2 3.2

3 5 3

low high low high low high

Density Density Density

Music slow-tempo
up-tempo

Figure 7.2 Relaxed wait (A), Station score (B) and Service evaluation (C) as a function
of density and background music

136 waiting experience at train stations

This pattern of results confirms hypothesis 1 that predicted that in a high-density
environment, slow- as opposed to up-tempo music positively influences customer
evaluations. The results indeed partly support the prediction that in a low-density
environment, up- as opposed to slow-tempo music positively influences customer
evaluations. Also for the service evaluation hypothesis 2 is confirmed but, despite
the interactions pointing in the right direction, these are not significant for station
evaluation and relaxed wait.

7.3.5 Discussion study 2

Findings from study 2 demonstrated the importance of music choice, indicating
that music tempo is a variable of key interest with respect to managing density
conditions. In addition, arousal should be addressed in order to further explore the
effects of music tempo under various conditions of density. Apart from perceived
control, the findings from study 2 suggest that music and density might also
influence arousal levels, as also suggested in or evidenced by previous research
(Caldwell & Hibbert, 2002; Eroglu, Machleit & Chebat, 2005). With respect to music,
the findings demonstrate that music is a multidimensional factor that has different
effects depending on, among other things, context (e.g. density conditions), and
type of manipulation (e.g. absence or presence, tempo). Naturally, variables such as
volume and genre are also likely to codetermine the effects of music on perceived
control, and, in turn, on the ‘waiting’ experience. For instance, regardless of tempo,
preferences with regard to genre are likely to codetermine the effects of music. It is
for that reason, that mainstream, easy listening music was used in these studies.
Interestingly, music tempo has received considerable research attention (e.g. Eroglu,
Machleit & Chebat, 2005; McElrea & Standing, 1992; Milliman, 1982, 1986; Oakes,
2003). Of particular importance for the present context is a study by Eroglu, Machleit
& Chebat (2005), which showed that slow-tempo music in a retail setting positively
affected hedonic and utilitarian evaluations under conditions of high density,
whereas up-tempo music had positive effects under conditions of low density. An
explanation for these results holds that under moderate incongruity (arising from
low density and up-tempo music or vice versa), consumers’ evaluations are the most
positive (Eroglu, Machleit & Chebat, 2005). The results concur with reversal theory,
which suggests that travellers in a busy environment have no desire for stimulation
and thus prefer no or only slow-tempo music, as opposed to their embracing many
stimuli and also up-tempo music in a quiet environment.
Regardless of characteristics, such as tempo and volume, preferences with regard
to genre are likely to codetermine the effects of music. Lacking specific information
concerning customers’ musical preferences, service managers are advised to avoid
such styles as modern jazz or heavy metal, which can be expected to elicit a less
uniform response. Clearly, follow-up research should incorporate variations in
musical characteristics to address both these and related issues. Further studies
could address the importance of perceived control in other types of service settings.

Chapter 7 Music 137

For instance, to what extent do perceptions of goal fulfilment mediate environ-
mental effects in a hedonic or leisure environment? Although explicit or implicit
goals are at the basis of service encounters in general, the extent to which percep-
tions of goal fulfilment are central to overall satisfaction and attitude formation
may vary across services. Arguably, control perceptions are particularly influential
in services which demand task-oriented actions (i.e. locating and walking to the
right platform or locating and collecting products in a retail environment) from
customers in order for service delivery to succeed.

7.4 Study 3 Influence of musical genre on station and

time experience at a virtual station7

7.4.1 Introduction and theoretical background

In the first two studies we demonstrated that music in a quiet environment has an
extra stimulating effect and results in more positive emotions and evaluations. In
the second study, with the tempo of the music as the key variable, it appeared that
a more positive station evaluation resulted from up-tempo music being played in a
quiet environment. In this third study we will examine whether musical genre can
also influence the station and waiting experience.

7.4.2 Research purpose

This study investigates whether music can influence the station and waiting
experience by comparing two different genres with one another: calming and
stimulating music. The pieces of music were selected after conducting two
preliminary studies. The first had to ascertain which musical genre was appreciated
by passengers at a station, and the second was conducted with a music expert
first to select various calming and stimulating pieces of music and subsequently
to ascertain whether passengers did indeed experience these as calming and/or
stimulating (Appendix 2).

Research questions and hypotheses

According to Apter’s reversal theory (2007), the preference for the level of stimuli
is moment-dependent. In off-peak hours the stations are often deserted. When
it is quiet, passengers experience few environmental stimuli and this can lead
to boredom. Playing stimulating music on a quiet platform affords extra stimuli
which passengers might rate positively. At rush hour, on the other hand, stations are
extremely busy. Crowding is an environmental factor that influences evaluations
and behaviour. In a crowded situation, passengers already experience sufficient

7 This study was presented at the European Transport Conference (Van Hagen, Pruyn,
Galetzka & Sauren, 2010).

138 waiting experience at train stations

stimuli and to add to this in the form of stimulating music would result in an
overstimulation whereby the hedonic tone decreases. As we expect passengers in a
crowded situation to rate calming music more positively than stimulating music, we
thus formulated the following hypotheses:

H1: Stimulating music in a quiet environment affords a more positive waiting

experience and station evaluation as opposed to calming music.

H2: Calming music in a crowded environment affords a more positive waiting

experience and station evaluation as opposed to stimulating music.

NS has to cater for passengers with divergent travel motives who differ in goal-
orientedness, the so-called must and lust passengers. Reversal theory also makes a
distinction in goal-orientedness, and refers to the terms telic and paratelic state. In
the telic state consumers are serious and goal-oriented and have little need of extra
stimuli. In the paratelic state consumers are more spontaneous and less bent on
things going according to plan and thus they appreciate extra stimuli. Must passen-
gers are cognitively engaged in the processing of information and keep their eye on
the clock. They are also expected to be less receptive to stimuli and aspire more to
peace and quiet. In comparison, lust passengers are less goal-directed, are not in a
hurry and are expected to be more receptive to enviromental stimuli. This resulted
in the following hypotheses:

H3: Must passengers rate the waiting experience and station more positively with
calming music than with stimulating music.

H4: Lust passengers rate the waiting experience and station more positively with
stimulating music than with calming music.

Not only does music create extra environmental stimuli but it can also offer distrac-
tion from waiting. The attentional model (Zakay & Block, 1997) poses that people pay
less attention to the time when they are occupied in a non-time-bound activity, such
as listening to music, and that the wait therefore seems to be shorter. Passengers
pay less attention to the time when they are distracted and are thus less capable of
estimating how long they have waited (Chapter 3). We did not expect any difference
in time estimations for must passengers, because they are totally focused on the
travel process and do not allow themselves to be distracted (Appendix 4). We did
expect, however, that lust passengers would estimate the wait as being shorter. On
the basis of reversal theory it can be expected that it is indeed stimulating music
that stimulates the waiting lust passenger more and that this will lead to a positive
affective reaction. By giving passengers a more positive feeling, the wait will be
experienced as less boring (Chebat et al., 1995; Gardner, 1985; Mayer, Gaschke,

Chapter 7 Music 139

Braverman, & Evans, 1992; Pruyn & Smidts, 1998) and lead to a shorter time percep-
tion (Baker & Cameron, 1996; Hornik, 1984; 1992). With regard to waiting time
perception, the following is expected:

H5: In a quiet environment, lust passengers experience a shorter perceived waiting time
with stimulating as opposed to calming music.

7.4.3 Method

Experimental subjects and design

For this study we approached members of the NS customer panel, i.e. passengers
who have agreed to participate in studies conducted by NS (Appendix 1). The online
assignment and questionnaire was fully completed by 517 members of the panel
(58.9% male, 41.4% female). The mean age of the panel members was 43 years
(SD = 15,73). In a 3 (musical genre: stimulating vs calming vs no music) x 2 (passenger
type: must vs lust) x 2 (density: busy vs quiet) between-subjects design we studied
what influence the differences in musical genre have on the passenger’s waiting and
station experience.

Procedure
The effects of the musical genre were measured by having the experimental subjects
carry out an assignment in a virtual reality station of Leiden Central. Subjects were
asked to take the first train to Amsterdam, whereby half of them had to imagine
themselves in the goal-directed ‘must scenario’ and the other half in the hedonic
‘lust scenario’ (Introduction to the experimental studies). Half of the subjects were
in a station with few passengers, the other half in a station with many. Before the
subjects entered the virtual world, they were expressly requested to adjust the
sound on their computer (to a comfortable volume), the reason being that they
would be hearing announcements. The music was played at a lower volume than
the announcements. Half of the subjects could listen to calming tracks, whereas
the other half were allocated stimulating pieces of music. The six tracks per genre
were played at random (Appendix 3). As subjects entered the virtual world at an
arbitrary moment, their objective waiting time differed. The objective waiting time
at the station and on the platform was recorded. After completing the assignment,
subjects filled in a questionnaire that addressed the experience of both the wait and
the station as well as their appreciation of the music.

Measurements
The variables (with the exception of the time, the score and the appreciation of the
music) were measured with a 7-point Likert scale whereby 1 was ‘totally disagree’
and 7 was ‘totally agree’. Table 7.1 shows the Cronbach’s Alphas, the minimum and

140 waiting experience at train stations

maximum values, the mean and standard deviations of the constructs. The station
experience was measured with the following variables:
–– Pleasure: For the PAD emotions an adapted scale of Mehrabian and Russell
(1974) was used. Pleasure was measured with six bipolar items (unhappy-happy,
annoyed-pleased, melancholic-contented, unsatisfied-satisfied, despairing-
hopeful, unpleasant-pleasant).
–– Arousal was measured with 6 items (relaxed-stimulated, calm-excited, jittery-
dull, wide awake-sleepy, sluggish-frenzied, unaroused-aroused).
–– Dominance was measured with four items (influenced-influential, cared for-in
control, guided-autonomous, submissive-dominant).
–– Station score: experimental subjects gave a score for their opinion on the quality
of the station (1 = very poor, 10 = excellent).

The waiting experience was measured with the following variables:

–– Time perception: How the time on the platform was experienced was measured
with the open question: “If you had to guess, how long do you think you were at
the platform (in minutes)?” The cognitive evaluation of the waiting time (long/
short) was measured with the question: “How did you experience the time spent
at the station?” (1 = very short, 7 = very long).
–– Acceptation of the waiting time: This was measured with the question: “I found
the waiting time on the platform: acceptable – unacceptable.”
–– Utilitarian and hedonic waiting time: The utilitarian waiting time (did one spend
the time usefully, measured with five items) and the hedonic waiting time (did
one spend the time pleasantly, measured with three items) were measured
for the waiting time on the platform by using items of the Shopping Values
of Batra and Ahtola (1991). Example utilitarian waiting time: “Was the time
you spent waiting on the platform: useful–useless, valuable–worthless, etc.”
Example hedonic waiting time: “Was the time you spent waiting on the platform:
pleasing–annoying, happy–sad, etc.”

The appreciation of the music was determined by the (seven answers to the)
following question: “What did you think of the music?”: unpleasant-pleasant;
unfitting-fitting; annoying-not annoying; cheerless-cheerful; sleep-inducing-
stimulating; stress-enhancing-calming; meaningless-impressive (α = .89). The end
of the questionnaire enquired after demographics and whether the experimental
subjects had heard music at the station.

Chapter 7 Music 141

Table 7.1 Cronbach’s Alpha, Min., Max., M and SD of the dependent variables
α Min. Max. M SD
Station experience
Pleasure .89 1 7 4.38 .90
Arousal .81 1 6 3.53 .88
Dominance .80 1 7 3.93 .77
Score station – 1 10 7.16 1.23
Waiting experience
Time perception – 0 20 3:50 3:00
Acceptance waiting time – 1 7 4.86 1.36
Utilitarian waiting experience .93 1 7 3.05 1.41
Hedonic waiting experience .93 1 7 3.94 1.23

7.4.4 Results

Manipulation checks
Of the 517 experimental subjects, 426 (82.4%) were in a condition with music. The
other 91 subjects (17.6%) were in a condition without music. Of the 426 subjects in a
condition with music, 298 of them (57.6%) reported they had heard music.
To determine whether the quiet versus busy platform was indeed experienced as
either, a manipulation check was conducted. Three items of the perceived crowding
scale (Harrell, Hutt & Anderson, 1980) were incorporated in the questionnaire in
order to ascertain the perceived density (α = .79). For example: “There are many
passengers on the platform.” An analysis of variance showed that experimental
subjects in the crowded condition indeed assessed the platform as more busy
(M = 3.02, SD = 1.38) than subjects in the quiet condition (M = 2.22, SD = 1.18,
F(1, 499) = 48.25, p = .000).
Also a manipulation check was carried out to ascertain whether stimulating music
was indeed assessed as being more stimulating than calming music. An analysis
of variance showed that stimulating music was indeed experienced as being
more stimulating (M = 4.54, SD = 1.19) than calming music (M = 3.93, SD = 1.49,
F(1, 208) = 11.02, p = .001).

MANOVA station experience and waiting experience

A 3 (musical genre: stimulating vs calming vs no music) x 2 (density: busy vs quiet) x 2
(passenger type: must vs lust) MANOVA was conducted with the dependent variables
relating to station experience (pleasure, arousal, dominance and score station)
and to the waiting experience (utilitarian and hedonic assessment of waiting time,
acceptable waiting time, cognitive waiting experience and waiting perception). The
result of both MANOVAs can be found in Table 7.2.

142 waiting experience at train stations

Table 7.2 MANOVA (Wilks’ Lambda) for variables stations and waiting experience

Variables stations Variables waiting experience

F df p F df p
Music 1.77 8, 670 .08 <1 12, 638
Density 1.38 4, 335 ns 1.54 6, 319 ns
Passenger type <1 4, 335 <1 6, 319

Music * density 3.72 8, 670 .00 1.34 12, 638 ns

Music * passenger type <1 8, 670 1,72 12, 638 .06
Density * passenger type <1 4, 335 1.36 6, 319 ns

Music * density * passenger type <1 8, 670 1.79 12, 638 .05

Station experience
For the station assessment, interactions between musical genre and density were
found on pleasure, arousal and the station score. Table 7.3 shows the averages and
standard deviations.
For the waiting experience, interactions between music and passenger type
were found on the waiting time perception and the acceptance of the wait, and a
three-way interaction was found between density, music and passenger type on the
hedonic waiting time. The interactions will now be discussed and visualized with
interaction plots.

Table 7.3 Means(SDs) between musical genres and density on station experience

No music Calming music Stimulating music

M (SD) M (SD) M (SD)
Pleasure Low density 4.49 (.72)a 4.15 (.86)ab 4.58 (.83)b
High density 4.55 (.90)a 4.55 (1.01)b 4.01 (.93)ab

Arousal Low density 3.60 (.84) 3.59 (.89) 3.47 (.75)

High density 3.28 (.85)a 3.30 (.95)b 3.84 (.94)ab

Dominance Low density 3.90 (.71) 3.82 (.63) 3.97 (.80)

High density 4.21 (.88) 4.01 (.80) 3.79 (.84)

Station score Low density 7.20 (1.03) 6.97 (1.47)a 7.52 (.69)a
High density 7.49 (1.10)a 7.19 (1.45)c 6.80 (1.66)ac
Note: Means with identical superscripts (a,b and c) differ significantly in the row:
a,b p < 0.05, c p < 0.1

Chapter 7 Music 143

Arousal
As the degree of stimulation influences the hedonic tone, we will first look at the
results of arousal. On arousal an interaction effect was found between music and
density (F(2, 338) = 6.43, p = .002, Figure 7.3). An ANOVA showed that when it was
busy passengers experienced more arousal with stimulating music than with
calming music and no music (F(2, 344) = 8.41, p = .000). This difference is non-signifi-
cant for quiet moments. Also apparent was that at busy moments stimulating music
aroused more than at quiet moments (F(1, 344) = 6.16, p = .014). The interaction plot
(Figure 7.3) clearly shows how density and stimulating music incite extra stimuli.

AROUSAL
means

3.8

3.6

3.4

3.2

low high
Density

no music
calming music
stimulating music

Figure 7.3 Interaction between music and density on the experienced arousal

Hedonic Tone
Musical genre in combination with density influenced the hedonic tone with regard
to pleasure and the station score. An interaction was found between music and
density on pleasure (F(2, 338) = 9.56, p = .000, Figure 7.4A). An ANOVA revealed that
passengers at quiet moments experienced greater pleasure when stimulating or no
music was played in comparison with calming music (F(2, 343) = 4.42, p = .013). At
busy moments passengers experienced more pleasure when calming or no music
was played in comparison with stimulating music (F(2, 343) = 7.71, p = .001). It also
appeared that stimulating music at quiet moments gave more pleasure than at
busy moments (F(1, 343) = 13.96, p = .000). For calming music the opposite is the
case: calming music gave greater pleasure at busy moments than at quiet moments
(F(1, 343) = 6.99, p = .009). For no music this difference is non-significant. Other
effects on the degree of pleasure were not found.

144 waiting experience at train stations

An interaction was also found between music and density on the station score
(F(2, 338) = 6.51, p = .001, Figure 7.4B). An ANOVA revealed that at quiet moments
passengers assessed the station with a higher score when stimulating music was
played as compared with calming music (F(2, 345) = 3.47, p = .032). No significant
differences were found with the condition without music. At busy moments
passengers awarded the station a higher score when no music was played as opposed
to stimulating music (F(2, 345) = 3.97, p = .020). There were no significant differences
with the calming music condition. Furthermore, stimulating music received a higher
station score at quiet moments when compared with busy moments (F(1, 345) = 10.20,
p = .002). This difference was non-significant for calming and no music. The analyses
showed no significant effects for the appreciation of the music. Figure 7.4 clearly
shows how stimulating music affords a higher hedonic tone on a quiet platform,
whereas calming (or no) music affords a higher hedonic tone on a busy platform.

PLEASURE (A) STATION SCORE (B)

means

means

4.6 7.8

4.5 7.6

4.4 7.4

4.3 7.2

4.2 7

4.1 6.8

4 6.6

low high low high

Density Density

no music
calming music
stimulating music

Figure 7.4 Interaction between music and density on pleasure (A) and station score (B)

Waiting experience
This study recorded the objective time. On average respondents spent 7.05 minutes
(SD = 4.18) at the station, of which an average 4.05 minutes (SD = 3.30) were on the
platform. A t-test revealed a significant difference between the objective and subjec-
tive time on the platform (t(516) = 28.30, p = .000). The time on the platform appeared
to be significantly longer than the actual or objective time. The Time Sense Factor8

8 TSF: Time Sense Factor = the subjective waiting time divided by the objective waiting time
per experimental subject.

Chapter 7 Music 145

for the platform is 1.51 (SD = 4.23). On average, passengers overestimated their
waiting time, which is in keeping with the literature (Hornik, 1984; 1992; 1993).

Interactions waiting experience

For waiting experience, two interactions were found between musical genre and
passenger type on the time estimation and acceptance of the waiting time. Two
three-way interactions were also found on acceptance of the waiting time and
hedonic appreciation of the waiting time (pleasant wait). The averages and standard
deviations can be found in Table 7.4.

Table 7.4 Means (SDs) of musical genre for time estimation, acceptable and pleasant
wait (with low and high density)

Must Lust
No music Calming Stimulating No music Calming Stimulating
music music music music
M (SD) M (SD) M (SD) M (SD) M (SD) M (SD)
Time estimation 3:04 (1:50)a 3:56 (3:13) 4:26 (3:21)a 3:57 (1:48) 4:44 (3:36)b 3:18 (2:42)b
in minutes
Acceptable wait 4.83 (1.38) 4.81 (1.45) 4.68 (1.22) 5.13 (1.32)a 4.59 (1.38)ab 5.06 (1.43)b

Pleasant Low density 3.94 (1.13) 4.06 (1.36) 4.10 (1.16) 3.76 (1.21)a 3.30 (1.21)b 4.47 (1.20)ab
wait
High density 4.03 (1.48) 3.50 (1.28) 3.57 (1.02) 4.39 (1.25)a 3.86 (1.14)c 3.59 (1.30)a
Note: Means with identical superscripts (a,b and c) differ significantly in the row:
a,b p < 0.05, c p < 0.1

An interaction was found between music and type of passenger on the time estima-
tion on the platform (F(2, 319) = 4.79, p = .009, Figure 7.5A). An ANOVA revealed that
with stimulating music lust passengers estimated their waiting time as shorter than
with calming music (F(2, 344) = 3.45, p = .033). There was no significant difference
with the condition without music nor were significant differences found for must
passengers. It also appeared that with stimulating music lust passengers assessed
their waiting time as being shorter than must passengers did (F(1, 344) = 4.64,
p = .032). This difference was neither significant for calming or no music. No other
effects on the estimation of the waiting time on the platform and the waiting
experience were found.

146 waiting experience at train stations

 TIME ESTIMATION (MINUTES) (A) ACCEPTABLE WAIT (B)
5.2

means

means
5 5.1

4.5 5

4 4.9

3.5 4.8

3 4.7

4.6
must lust must lust
Passenger type Passenger type

no music
calming music
stimulating music

Figure 7.5 Interactions music and type of passenger on time estimation (A) and
acceptable wait (B)

An interaction was also found between music and type of passenger on the accept-
ance of the waiting time on the platform (F(2, 319) = 3.31, p = .038, Figure 7.5B).
An ANOVA revealed that lust passengers found the waiting time on the platform
more acceptable when there was stimulating music or no music as compared with
calming music (F(2, 338) = 3.59, p = .029). This difference was non-significant for
must passengers.

Hedonic waiting time

Finally, the musical genre afforded a more pleasant waiting time. A (marginally)
significant three-way interaction was found between music, density and passenger
type on the hedonic waiting time of the platform (F(2, 319) = 2.91, p = .056,
Figure 7.6). An ANOVA revealed that lust passengers spent their waiting time more
pleasantly at quiet times when stimulating music was played as compared with
calming or no music (F(2, 333) = 7.10, p = .001). When it was busy, lust passengers
indicated they spent their waiting time more pleasantly when no music was played
than with stimulating or calming music (F(2, 333) = 3.25, p = .040). These differences
were non-significant for must passengers. Furthermore, calming music at quiet
moments appeared to have the effect that must passengers experienced their
waiting time more pleasantly than lust passengers (F(1, 333) = 5.86, p = .016). This
difference was neither significant for busy moments nor for stimulating and no
music. No other effects on the hedonic waiting time were found. The same applies to
effects on the utilitarian waiting time.

Chapter 7 Music 147

 HEDONIC WAIT (MUST) HEDONIC WAIT (LUST)
means

means
4.4 4.4

4.2 4.2

4 4

3.8 3.8

3.6 3.6

3.4 3.4

3.2 3.2

low high low high

Density Density

no music
calming music
stimulating music

Figure 7.6 Three-way interaction between music, density and passenger type on the
hedonic wait on the platform

7.4.5 Returning to the hypotheses

Hypothesis 1 is confirmed: Stimulating music in a quiet environment affords a more
positive waiting experience and station evaluation as opposed to calming music. In a
busy environment passengers experienced more arousal with stimulating music.
At quiet moments with stimulating music the experimental subjects experienced
a higher hedonic tone (pleasure and station score). Lust passengers, moreover,
seemed to find their wait more pleasant when stimulating music was played on a
quiet platform.
Also hypothesis 2 is confirmed: Calming music in a crowded environment affords a
more positive waiting experience and station evaluation as opposed to stimulating
music. In a busy environment with calming music the experimental subjects
experienced a higher hedonic tone (pleasure and score).
Hypothesis 3 can be partially confirmed: Must passengers rate the waiting experience
and station more positively with calming music than with stimulating music. For must
passengers hardly any significant effects were found on the station evaluation or the
waiting experience. Must passengers did, however, rate their wait more positively
than lust passengers when calming music was played in a quiet environment.
Hypothesis 4 can be confirmed: Lust passengers rate the waiting experience and
station more positively with stimulating music than with calming music. Lust passen-
gers appeared to find the wait more acceptable with stimulating music and they
found that stimulating music in a quiet environment made the wait more pleasant
than calming music.

148 waiting experience at train stations

Hypothesis 5 is confirmed: In a quiet environment, lust passengers experience a
shorter perceived waiting time with stimulating as opposed to calming music. Lust
passengers estimated the waiting time as being shorter when stimulating music
was played as opposed to calming music. In accordance with the attentional model,
music distracted lust passengers from the wait. For must passengers no significant
differences were found between stimulating and calming music.

7.4.6 Discussion
Interpretation of the results
The assumption of this study was that by playing the right music on a platform,
waiting passengers would be offered an optimal level of stimuli which would
result in a more positive station and waiting experience. With an optimal level of
stimuli the hedonic tone (much pleasure, high score) is raised. In order to achieve
the optimal level of stimuli the context is of importance: reversal theory predicts
that stimulating music at quiet moments and calming music at busy moments
has a positive effect. This also applies to the type of passenger: lust passengers are
more receptive to environmental stimuli and it is to be expected that they prefer
stimulating music during the wait, whereas must passengers are less receptive to
extra environmental stimuli and will have a greater preference for calming music
(Appendix 4). A more positive hedonic tone has an effect on the waiting experience;
if the passengers experience pleasure, then they will experience the wait more
positively (the waiting time is more pleasant and more acceptable), and the wait will
seem to be shorter (Baker & Cameron, 1996; Hornik, 1992).

Our findings concur with reversal theory. It is indeed at quiet moments that stimu-
lating music results in a higher hedonic tone (greater pleasure and a higher station
score) than calming music, just as it is at busy moments that passengers experience
greater pleasure when calming music is played, as opposed to stimulating music
(Van Hagen, Pruyn, Galetzka & Sauren, 2010). Figure 7.7 shows how the musical
genres and the degree of density are related to the degree of stimulation (arousal)
and hedonic tone.

Chapter 7 Music 149

 DENSITY & MUSIC GENRE
pleasant
1 = calming music
2 = stimulating music
3 = calming music
2 3 4 = stimulating music
Hedonic Tone

comfort zone

1 4

unpleasant
low AROUSAL high
low density high density

Figure 7.7 Density and music genre related to arousal and hedonic tone

In accordance with reversal theory, calming music appears to result in a more

positive waiting experience for must passengers, just as stimulating music does for
lust passengers. This applies to the acceptance of the waiting time and to a pleasant
wait. Lust passengers find the waiting time more acceptable and pleasant with
stimulating music than with calming music. This result supports the premise of
reversal theory when applied to the type of passenger: lust passengers are receptive
to environmental stimuli. If this need of stimuli is met, then the pleasure increases
and the waiting experience is improved. Also apparent is that lust passengers
estimate the time as being shorter with stimulating as opposed to calming music.
This not only concurs with the attentional model (Zakay & Block, 1997) but also
with reversal theory (Apter, 2007). For lust passengers stimulating music affords
sufficient distraction, causing them to pay less attention to the time and hence
underestimate its duration (attentional model). Lust passengers apparently have a
greater need of environmental stimuli and/or allow themselves to be distracted,
and this concurs with reversal theory. A more pleasant wait and greater acceptance
of the waiting time result in a more positive hedonic tone whereby lust passengers
underestimate the time (Baker & Cameron, 1996; Hornik, 1984; 1992; 1993).
A remarkable conclusion is that the combination between music and density was
actually found on the variables that measured the station experience and that
the combination between music and type of passenger had a greater influence on
the variables that measured the waiting experience (only with lust passengers). A
possible explanation for this might be that the waiting experience depends more on
the person, whereas the station experience is based more on the physical environ-
ment, e.g. whether the platform is busy or not. Must and lust passengers apparently
distinguish themselves more in their preoccupation with time than passengers who
travel at busy versus quiet moments.

150 waiting experience at train stations

Restrictions and areas for special attention with regard to future research
Earlier studies showed that music can be effectively deployed in e.g. restaurants
(Milliman, 1982; 1986) and supermarkets (Eroglu, Machleit & Chebat, 2005; North,
Hargreaves & McKendrick, 1999). Studies into the effects of musical genre in a
functional and time-sensitive station environment is a valuable addition, particu-
larly because this study also investigated interactions between type of passenger
and density. The findings of the two field studies and the virtual study reinforce
one another. By conducting the research in a virtual world, musical genre, density
and passenger type could be easily manipulated whilst all the other conditions
remained exactly the same. Also the threshold to take part in the study was low,
because experimental subjects could participate from behind their own PC at home
at a time that suited them.
However, as with any study, also this current method has a number of shortcom-
ings. Although the virtual station appeared to closely reflect reality, the actual level
or degree of realism was still lower than in the real world. At a real station, and
on a real platform, the senses have to process a richer input than at home behind
the computer. This restriction could be overcome by repeating the study at a real
station. Another weak point of the study is the possible familiarity with the music.
Just how familiar one is with the tracks could influence the perceived waiting time.
Yalch and Spangenberg (2000) demonstrated that experimental subjects estimated
the time that they spent in the shop as being longer when familiar music was played.
Bailey and Areni (2006) found that when tasks had to be performed, unfamiliar
music resulted in an underestimation of the waiting time. Sweeney and Wyber
(2002) ascertained that it was not the unfamiliarity but how pleasant consumers
found the music that determined the waiting experience. Also Hui, Dube and
Chebat (1997) observed that the appreciation of the music affords positive emotions
and greater approach behaviour, even if familiar music meant the time was overesti-
mated. In order to overcome the influence of preference and familiarity, it might be
worth opting in a following study for pleasant yet less well-known music.

Practical implications for NS

This current study offers concrete results for NS. On the basis of the findings, a
programme of music can be compiled with the aim of increasing the hedonic tone
and shortening the waiting time perception. When it is busy, passengers prefer
either no music or calming music. When it is quiet, passengers have a preference for
stimulating music. This gives them greater pleasure and results in their awarding
the station a higher score. When stimulating music is played, lust passengers
moreover estimate their waiting time as being shorter and they find the waiting time
more acceptable and pleasant. With regard to the music programming, it would
be best not to play any music in the morning peak hours. At such a time of day,
people still have to ‘get going’, which means they are less receptive to extra stimuli.
Moreover, the public in the morning rush hour primarily consists of goal-targeted

Chapter 7 Music 151

must passengers. During the daytime it is quiet, which is when the majority of
lust passengers travel who are more receptive to extra stimuli. In off-peak hours
stimulating music could be played on the platforms. In the evening rush hour it is
busy again but by this time people have ‘got going’ and can tolerate more stimuli.
In addition, the evening rush hour is a mix of must and lust passengers. Music
must contribute to a better atmosphere but not overstimulate. At such a moment,
calming music would seem to be the best option. By consistently deploying such
a programming, the waiting time of passengers will be ameliorated. For smaller
stations, where it is quieter on the platforms and passengers are exposed to fewer
stimuli, the music compilation can be richer, e.g. by also including calming tracks
during the morning rush hour. The volume of the music must be low at all times,
however. Audible, yet in the background, so that it is more sub-consciously perceived
than immediately noticed. As soon as an information announcement is made, the
music will temporarily have to fade further in the background so as not to interfere
with the message. Finally, it is important that the passenger can withdraw from the
music, e.g. to a quiet zone on the platform.

7.4.7 General discussion

Since customers’ visits to both stations and to other public transportation services
are to a large extent comprised of waiting, i.e. for the train to arrive, effects of
music on perceptions of waiting time are of particular relevance. Previous research
suggests that music may contract perceived waiting time (Bailey & Areni, 2006). In
addition, research addressing waiting experiences of bus commuters (Durrande-
Moreau & Usunier, 1999) stresses the importance of individual differences in
explaining effects of waiting. For instance, customers with a more economic time
style, i.e. those acutely aware of the usefulness and purpose of their time, were
shown to be especially prone to impatience. These customers in particular are likely
to appreciate distractions while waiting, such as the presence of music. Research
addressing automatic influences on consumer behaviour indicates that consumers
are often unaware of environmental factors influencing attitude formation and
behaviour, either because these are subliminally presented or because they are not
heeded (e.g. Dijksterhuis, Smith, Van Baaren & Wigboldus, 2005).
The findings of the three studies indicate that effects of music were particularly
strong under conditions of low density, perhaps suggesting that music was much
more salient in the quieter, low-density condition compared with the high-density
condition. All three studies demonstrate that stimulating and up-tempo music at
quiet moments has positive effects on both the station evaluation and the waiting
experience. At busy moments the music must be more carefully chosen, because
passengers could easily get overstimulated. At such times it would be better to either
abstain from playing music altogether or opt for slow and calming music.

152 waiting experience at train stations

Future research
The combined findings clearly indicate that, although a public transportation
environment can be considered a function-oriented or informational service
environment rather than a hedonic or leisure one, customers do value distractions
or entertainment when used appropriately. In other words, by meeting customers’
need for stimulation at all too quiet times, the availability of entertainment and
distractions may increase customers’ perceptions of control, and in turn positively
impact the service experience. As such, our findings are in line with the conceptuali-
zation of control as a direct consequence of need fulfilment (Ward & Barnes, 2001),
indicating that perceived control is not only a matter of physical control, e.g. sensory
control or freedom of movement, over the environment.
Although music may certainly contribute to the service experience, service
managers should keep in mind that freedom of choice (i.e. in our study the choice
of whether or not to listen to music) is (also) an important antecedent of perceived
control (Averill, 1973; Hui & Bateson, 1991; Mills & Krantz, 1979). Of course, for
specific segments of travellers, portable music systems provide alternative means to
withdraw from aversive stimuli.

Finally, a few limitations of the present studies deserve attention. In the studies,
data were gathered in a very specific service setting (i.e. a railway station in the
Netherlands), which calls into question the generalizability of our findings. A note
concerns also the measurement of our variables. As discussed, in the field studies
the participants filled in the questionnaires on the platform but were given the
chance to complete the task in the eagerly awaited train. In hindsight, it may well
be the case that the change of environment, i.e. from the platform to the train, had
an impact on the results reported. In our studies we tried to minimize this problem
by restricting the number of questions to an absolute minimum. In the study in the
virtual world, despite a few shortcomings, disruptive environmental factors, such as
delayed trains or bad weather, can be easily controlled. Although the virtual station
was a close rendering of reality, it does remain a quite sterile environment. At a real
station and on a real platform the senses have to process other input than when at
home behind the computer, which implies that there might be a discrepancy in the
results. The present study should therefore be replicated, e.g. by testing the same
conditions in a real-life situation. In the meantime, our findings stress the impor-
tance of insights into the interactive effects of environmental factors in service
environments. A clear understanding of the processes involved allows managers to
counteract potential negative effects of uncontrollable factors, such as density, and
to lay the foundation for a memorable service experience.

Chapter 7 Music 153

 Chapter 8
Advertising and
Infotainment

‘It must take longer

for more things to happen.’
Kellaris & Altsech, 1992
8.1 Introduction

In Chapters 6 and 7 we saw that manipulating the ambient dimension (Baker, 1986)
of the servicescape with colour, light and music had a positive influence on the
evaluation of both platform and waiting experience even though passengers were
barely aware of the manipulations. Several studies have shown that with the aid
of technical measures, such as infotainment, the quality of the service in retail
environments can be increased (Burke, 2002; Newman, Dennis & Zaman, 2006).
It is for that reason that screens with infotainment are being used increasingly
often in shops and public areas (Derval, 2007; 2009). As infotainment can also
offer distraction and easen the wait on a platform, this chapter will address the
effects of the design dimension (Baker, 1986) of the servicescape with alternating
commercials and screens narrowcasting infotainment. We expect the changing
images to function as explicit distractors and to attract greater attention from
the passengers than other ambient environmental elements, such as colour and
light. As in Chapters 6 and 7, this chapter will commence with a field study to first
ascertain whether the manipulation with moving images does actually lead to a
positive station and waiting experience. Following the field study will be two studies
in a virtual world, where the effects of moving images in the shape of advertising
and infotainment will be studied in various situations. Differences in density and
passenger type are included as moderators.

8.1.1 Advertising, infotainment and waiting experience

Very little research has been published on outdoor advertising and its influence
on the emotions, behaviour and waiting experience. It appeared from research
by Derval (2007; 2009) that people in a wait situation have more time to take in
their surroundings and that the advertising content is remembered two to three
times better than television commercials. Dennis, Newman, Michon, Brakus and
Wright (2010) posited in a study of ‘digital signage’ (narrowcasting), that it might be
considered part of the surroundings. They demonstrated how digital signage evokes
approach behaviour and is mediated by an affective reaction.
Research on outdoor advertising has shown that people usually take one to two
seconds to look at it (Van Meurs & Aristoff, 2009), and that moving images attract
more attention than static ones (Bolls, Darrel & Muehling, 2003; Dennis, Newman,
Michon, Brakus & Wright, 2010; Katz, Larson & Larson, 1991; Reeves & Nass, 1996).
Apter (2007) distinguished between focus and fringe, whereby focus is that to which
attention is paid and fringe the rest of the environment of which one is continually
aware albeit not fully consciously. It has been shown that moving images draw
people’s attention both consciously and unconsciously (Bolls, Darrel & Muehling,
2003; Dennis et al., 2010), whereby infotainment not only consists of an informative
component that is consciously perceived and processed but also an ambient compo-
nent (colours, background images) that is unconsciously perceived and processed

Chapter 8 Advertising and Infotainment 157

(Bolls, Darrel & Muehling, 2003; Lang, 2000). Conscious attention (focus) is paid to
the content of the images and unconscious attention (fringe) to the appeal thereof
(Apter, 2007; Bolls, Darrel & Muehling, 2003). In the studies in this chapter, we
expect infotainment to primarily attract passengers’ attention, thereby distracting
them from the time, but that the images themselves might also be so appealing
as to have a positive effect on the platform experience and thus also the waiting
experience. As density and goal-orientedness will co-determine how infotainment is
evaluated, these will be included in the studies as moderators.

8.2 Study 1 Effects of infotainment on the platform,

a field study

The focus of this study was to investigate how waiting passengers react to infotain-
ment on a platform and whether infotainment can influence the waiting experience
and evaluation of the platform. As mentioned before, reversal theory (Apter, 2007)
poses that the need of environmental stimuli is dependent on the context, such as
the degree of platform density. An environment that corresponds with the desired
number of stimuli seems to effect an increase in customer satisfaction (Wirtz,
Matilla & Tan, 2000). A combination of infotainment and a dense platform can
create overstimulation which in turn can result in a lower hedonic tone. In a quiet
environment, such as during off-peak hours, passengers are exposed to few stimuli
whereby they can perceive the platform as bland and become bored. By purposely
adding stimuli in the form of infotainment, the arousal level can be increased and
passengers can experience greater pleasure. NS also has to cater for passengers with
divergent travel motives who differ in goal-orientedness, the so-called must and lust
passengers (Chapter 4). Must passengers are cognitively engaged in the processing
of information. They are also less receptive to stimuli and aspire more to peace and
quiet. In comparison, lust passengers are less goal-directed, are not in a hurry and
are expected to be more receptive to environmental stimuli, such as infotainment.
On the basis of reversal theory, we expect an interaction between the degree of
density and infotainment and passenger type and infotainment, hence our formula-
tion of the following hypotheses:

H1: In a quiet environment infotainment affords more stimuli for passengers and
initiates a more positive station and waiting experience. We expect this effect to be
more pronounced for lust passengers.

H2: In a busy environment infotainment affords too many stimuli for passengers and
leads to a more negative station and waiting experience. We expect this effect to be more
pronounced for must passengers.

158 waiting experience at train stations

8.2.1 Method
In this field study we enquired after the effects of infotainment on the perception
of the waiting and platform experience on a platform of Leiden Central Station.
A 2 (infotainment: infotainment vs no infotainment) x 2 (density platform: low
density x high density) x 2 (passenger type: must vs lust) between-subjects design was
marked out to answer the specified hypotheses. The experiment consisted of two
phases and concerned a trial run of seven flatscreens installed in several places on
the platform. In the first phase (September 2009) infotainment was not narrowcasted
(control situation) and participants saw black screens, but in the second phase (May
2010) infotainment was narrowcasted (Figure 8.1). In order not to overstimulate
the passengers, the images were not accompanied by sound. The 15-minute
programmes disseminated information on domestic and foreign news, the weather,
the arts, events, local history, work on the rail and on NS and ProRail. The program-
ming was updated each morning and afternoon. Passengers who had been waiting
on the platform were invited to fill in a questionnaire after their train had departed.

Figure 8.1 Travellers watching an infotainment screen

Chapter 8 Advertising and Infotainment 159

8.2.2 Measurement instruments
–– Acceptance of waiting time was measured on a 7-point scale: “I found the waiting
time on the platform: unacceptable–acceptable.”
–– Utilitarian and hedonic waiting time was measured on the basis of the shopping
values (Batra & Ahtola, 1991), which measure both the hedonic (3 items, 7-point
Likert scale Coefficient Alpha = .86) and utilitarian time appreciation (3 items,
7-point Likert scale, Coefficient Alpha = .87). An example of utilitarian waiting
time: “Was the time you spent waiting on the platform: useful–useless, valuable–
worthless, etc.?” An example of the hedonic waiting time: “Was the time you
spent waiting on the platform: pleasing–annoying, happy–sad, etc.?”
–– Time perception: Measures included the subjective estimations of time spent
on the platform: “If you had to guess, how long do you think you were on the
platform (in minutes)?”
–– Evaluation of the platform was assessed by asking participants to evaluate the
platform by awarding a score on a 10-point scale (1 = very poor, 10 = excellent).
–– Perceived density was measured on a bipolar scale: “The platform was full of
people” vs “There were hardly any people on the platform.”
–– Passenger type: The difference between must and lust passengers was based
on the purpose of the journey: must = work, school, study, dentist, hospital;
lust = social or recreational purposes.
–– Infotainment: The independent variable ‘infotainment’ relates to whether info-
tainment was either narrowcasted or not (the latter being the control condition).

8.2.3 Subjects
The control condition consisted of 615 respondents who had been waiting on the
platform with screens hanging from the ceiling on which no infotainment was
narrowcasted. In the infotainment condition infotainment was continually narrow-
casted and 211 respondents participated. Of the total sample 55% were woman.
Average age of respondents was 30.6 years (SD = 14.5) in the first sample and 36.1
years (SD = 15.7) in the second.

8.2.4 Results study 1

Noticing the screens
In the control condition 35% of the passengers noticed one or more screens hanging
on the platform ceiling, compared to 65% during the second measurement when
infotainment was narrowcasted. In total 17.5% reported to have looked at the
content. On average passengers reported to have watched the infotainment screens
for two minutes. We can thus conclude that infotainment does attract the attention
of passengers.

160 waiting experience at train stations

Effects of infotainment
First we performed a MANOVA with four dependent variables: acceptable wait,
perceived waiting time, utilitarian waiting time and hedonic waiting time.
Infotainment, perceived density and passenger type were specified as independent
variables in the model. In the multivariate tests, main effects were found for
passenger type and infotainment versus no infotainment (Table 8.1). No main effect
was found for perceived density nor were any interactions found.

Table 8.1 MANOVA (Wilks’ Lambda) for variables waiting experience (acceptable
wait, perceived waiting time, hedonic and utilitarian wait)

Variables waiting experience

F Df p
Infotainment 2.43 4, 724 .05
Density <1 4, 724 ns
Passenger type 3.0 4, 724 .02

Infotainment * density <1 4, 724 ns

Infotainment * passenger type <1 4, 724 ns
Passenger type * density <1 4, 724 ns

Infotainment * density * passenger type <1 4, 724 ns

Waiting experience
As the MANOVA showed significant results, ANOVAs were performed, the averages
and standard deviations of which are reported in Table 8.2. The ANOVAs showed
that passengers found the wait more pleasant with infotainment than without
(F(1, 735) = 4.74, p = .03). Passengers also felt they had spent their time more usefully
with infotainment than without (F(1, 735) = 6.34, p = .01). Also apparent was that
must passengers assessed their wait as shorter (M = 06:36, SD = 5:36) than lust
passengers (M = 08:32, SD = 6:53; F(1, 757) = 9.88, p = .002). However, as the objective
waiting time was not recorded, it is unclear whether lust passengers did indeed
have a longer wait or whether they assessed it as being longer than must passengers.
Furthermore, no main effects or interactions were found for acceptable wait and
perceived waiting time.

Chapter 8 Advertising and Infotainment 161

Table 8.2 Means (SDs) main effect infotainment on hedonic wait, utilitarian wait
and platform score

Infotainment
No infotainment Infotainment
M (SD) M (SD)
Hedonic wait 2.33 (1.42) 2.65 (1.28)*
Utilitarian wait 2.97 (1.32) 3.35 (1.28)**
Platform score 6.6 (1.4) 7.1 (1.2)**
Note: Means with * and ** differ significantly in the row: ** p < 0.01, * p < 0.05

Evaluation of the platform

Also the evaluation of the platform was enquired after, besides the waiting expe-
rience. An ANOVA with platform evaluation as dependent variable and infotainment,
passenger type and density as independent variables showed a main effect and two
interactions. As main effect the evaluation of the platform appeared to be higher
with infotainment than without infotainment (F(1, 756) = 17.3, p = .000; Table 8.2).
Moreover, interactions were found between infotainment and density
(F(1, 756) = 4.2, p = .04) and between infotainment and passenger type (F(1, 756) = 3.8,
p = .05). When it was busy, passengers awarded a higher platform score with info-
tainment than without it (F(1, 756) = 14.58, p = .000). This applies to a lesser degree
to a quiet platform, i.e. passengers still award a higher score with infotainment
than without but these differences are smaller and not significant (F(1, 756) = 3.26,
p = .07). Figure 8.2A shows the interaction and Table 8.3 the averages and standard
deviations.

Table 8.3 Means (SDs) infotainment and density (low/high) on platform score

No Infotainment Infotainment
M (SD) M (SD)
Platform score Low density 6.8 (1.3) 7.0 (12)#
High density 6.5 (1.2) 7.3 (.8)*
Note: Means with * and # differ significantly in the row: * p < 0.001, # p < 0.1

Table 8.4 Means (SDs) infotainment and passenger type (must/lust) on platform score

No Infotainment Infotainment
M (SD) M (SD)
Platform score Must 6.6 (1.4) 6.9 (1.2)*
Lust 6.7 (1.3) 7.5 (.9)**
Note: Means with * and ** differ significantly in the row: ** p < 0.001, * p < 0.05

162 waiting experience at train stations

 PLATFORM SCORE (A) PLATFORM SCORE (B)

means

means
7.4 7.4

7.2 7.2

7 7

6.8 6.8

6.6 6.6

6.4 6.4

low high must lust

Density Passenger Type

no infotainment
infotainment

Figure 8.2 Influence of yes/no infotainment on the platform evaluation for density (A)
and passenger type (B)

Lust passengers also appeared to give a higher score to the platform with infotain-
ment than without (F(1, 756) = 13.85, p = .000), and the same applied to must
passengers although to a lesser extent (F(1, 756) = 3.73, p = .05). Figure 8.2B shows
the interaction and Table 8.4 the means and standard deviations.

8.2.5 Returning to the hypotheses

On coupling the results with the hypotheses, it appears that the latter can be
partially confirmed. As expected, infotainment affords passengers a more pleasant
and useful wait and a higher score, with the highest score for the platform being
awarded by lust passengers. A remarkable result (and different to what we expected)
was that infotainment was more highly appreciated on a busy platform than on a
quiet one. It is possible that passengers in a busy environment together with screens
with moving images experience so many stimuli that an information overload (Lang,
2000) arises. In such a situation, passengers might stop paying attention to the
intrinsic message of the infotainment yet be more receptive to the appeal of the
images (Bolls, Darrel & Muehling, 2003), whereby infotainment in a busy environ-
ment sooner functions as an ambient than as a design element and is thus more
positively valued. However, it is also possible that there is so little to arouse when
it is quiet that even with infotainment passengers experience too few stimuli and
hence have a lower esteem for the platform. In contrast, a busy platform combined
with infotainment affords passengers sufficient stimuli, thus resulting in a better
appreciation.

Chapter 8 Advertising and Infotainment 163

8.2.6 Conclusions
The results of this study demonstrate how passengers find the wait more useful and
pleasant with infotainment than without, as well as their awarding the platform
with infotainment a higher score (7.1 instead of 6.6). Passengers awarded the highest
score when infotainment was shown on a busy platform. Particularly lust passen-
gers gave the platform with infotainment a higher score. It can be concluded that
platform infotainment is a welcome distraction that makes the wait more pleasant
and useful and leads to a positive evaluation of the platform. As this study demon-
strated in practice the notably positive effects of infotainment on the platform
experience, it was interesting to take a closer look at whether it also influences the
waiting experience. To this end we conducted two studies in the virtual world, the
first addressing the effect of advertising and the tempo or pace of screen changes
(study 2) and then addressing different kinds of infotainment: topical affairs, train
information and entertainment (study 3). One advantage of the virtual world is that
the objective waiting time can be easily recorded and the moderators density and
goal-orientedness can be incorporated in the research design.

8.3 Study 2 Effects of the screen change pace of

advertising on busy and quiet platforms9

8.3.1 Infotainment and time perception

Research has shown that the speed, also known as the pace (Bolls, Darrel &
Muehling, 2003) with which images alternate can be regarded as contextual changes.
The pace influences arousal (Bolls, Darrel & Muehling, 2003; Lang, 2006; Reeves
& Nass, 1996) and the waiting experience (Brown, 1995; Poynter, 1989; Poynter &
Homa, 1983). Brown (1995, p. 115) posits that: ‘Given that change is a fundamental
property of the natural environment, it is perhaps not surprising that timing is attuned
to, and affected by, the motion and speed of moving objects.’ Studies have demon-
strated that fast screen changes sooner attract one’s attention than slow ones but
that they also afford an information overload sooner, causing the ad’s message to be
less well remembered than with slower screen changes (Bolls, Darrel & Muehling,
2003; Lang, 2000; Newman, Dennis & Zaoman, 2006). It is unclear whether moving
images result in a shorter estimation of time owing to distraction (attentional
model) or actually to a longer estimation of time owing to more information having
to be processed (storage size and contextual change/segmentation model, Chapter 3).
In the following two studies, to be carried out in a virtual world, we will investigate
what influence advertising and infotainment have on the station and waiting
experience.

9 This study was presented at the European Transport Conference (Van Hagen, Pruyn,
Galetzka & Kramer, 2009).

164 waiting experience at train stations

8.3.2 Hypotheses study 2 and 3
Several studies have shown that a distractor reduces the perceived waiting time
and makes the wait more pleasant. Advocates of the attentional model allege, for
example, that a distractor reduces people’s perception of time because they are
being kept cognitively occupied – hence there is less cognitive power to be occupied
with the time, which makes it seem to pass more quickly (Pruyn & Smidts, 1998;
Thomas & Weaver, 1975; Zakay & Block, 1997). A meta- analysis by Durrande-Moreau
(1994; 1999) comprising 18 studies of waiting experience demonstrated that when
one is cognitively occupied with an activity, time seems to pass more quickly than
when one passively lets it pass by. We found the same results in the field study on
waiting time (Chapter 5). Adding a distractor to the station environment, such as
advertising or infotainment, can therefore cause the passenger’s perceived waiting
time to be reduced. On the basis of relationships and connections found in the
literature, we formulated the following hypotheses

H1a: Passengers experience a shorter perceived wait in a station environment with

advertising and infotainment than without advertising and infotainment.

According to the contextual change model, explicit distractors such as advertising

and infotainment actually result in a more prolonged time interval (the wait),
because more seems to have happened during that period (Bolls, Darrel & Muehling,
2003; Poynter, 1989; Poynter & Homa, 1983). Hypothesis 1b was thus formulated as
an alternative to hypothesis 1a:

H1b: Passengers experience a longer perceived wait in a station environment with

advertising and infotainment than without advertising and infotainment.

Fast screen changes afford greater arousal, thus automatically drawing one’s
attention to the images (Bolls, Darrel & Muehling, 2003) and distracting one from
the time. A great deal of information with fast screen changes can result in a
longer estimation of the time and even to an information overload (Bolls, Darrel
& Muehling, 2003; Lang, 2000). From Brown’s research (1995), it appears that the
duration of fast stimuli was perceived as being longer than slow stimuli. Also the
perceived time was longer with fast moving images than with slow moving images.
On the basis of these findings, we expect a slow image tempo to result in a shorter
time perception than a fast image tempo. Hypothesis 2 thus reads:

H2: A slow pace of platform wall advertising results in a shorter subjective waiting time
than a fast pace of platform wall advertising.

The physical service environment is an important factor when assessing the service
and is likewise important when determining the quality (Hui, Dubé & Chebat, 1997).

Chapter 8 Advertising and Infotainment 165

Adding an environmental element to the service environment can be compared
with the addition of good quality to a product (Bitner, 1992). Advertising and
infotainment can be considered an environmental element which can positively
influence the evaluation and quality assessment of the service provider (Burkes,
2002; Newman, Dennis & Zaman, 2006). Hypothesis 3 is thus:

H3: The evaluation of the service and quality is more positive on a platform with
advertising and infotainment than on a platform without advertising and infotainment.

Passengers who experience the wait as pleasant and who are not bored will return to
the station with greater enthusiasm. This expectation was endorsed in research by
Hui, Dubé and Chebat (1997), who found that a positive affective reaction to waiting
time results in greater approach (and less avoidance) behaviour. Also Dennis et al.
(2010) ascertained that digital signage leads to approach behaviour. Hypothesis 4
thus reads:

H4: Passengers on a platform with advertisement and infotainment will show

more approach behaviour compared with a platform without advertisement and
infotainment.

8.3.3 Method
In an on-line experiment, subjects (members of the NS customer panel, Appendix 1)
were invited to navigate through a virtual station on the basis of a fixed passenger
scenario. Half of the respondents were asked to imagine that they were in a hurry
(must scenario) and the other half was asked to imagine that they were going on
a pleasure trip (lust scenario). The density on the platform was also manipulated.
Half of the respondents were confronted with a quiet station and the other half with
a busy station. On the spot the train was expected to depart from, advertisements
were projected onto the opposite platform wall (Figure 8.3) under varying conditions
of image renewal. One quarter of the respondents saw ad messages that followed
one another relatively quickly (renewal every 20 seconds), one quarter saw ad
messages that were alternated more slowly (every 40 seconds), one quarter saw no
renewal of the message (i.e. they saw one and the same message during the entire
wait), and the final quarter saw no ad message at all (control condition).

166 waiting experience at train stations

Figure 8.3 Platform wall advertising

The experimental design consisted of a 4 (pace screen change: no advertising vs

static vs slow vs fast) x 2 (density: peak vs off-peak) x 2 (passenger type: must vs lust)
between-subjects design.

8.3.4 Procedure
Members of the NS panel (Appendix 1) received an email in which they were asked to
participate in the study. A link led respondents to an introduction page where they
were asked to install a plug-in which was required to allow the virtual model to run
on their computer. After further instructions, respondents were given a scenario
to read in which they were asked to catch a specific train. The scenario explained
whether one was a must passenger (in a hurry for an important meeting) or a lust
passenger (not in a hurry and with the prospect of a pleasant day out). Respondents
were then sent to the virtual station and randomly assigned to one of the eight
conditions (pace screen change and density). The virtual station had a 10-minute
cycle. Respondents entered the cycle at a random moment and thus had a different
objective waiting time. After catching the right train, respondents were redirected to
the questionnaire.

8.3.5 Respondents
Respondents were all members of the NS customer panel and hence a good
represen­t ative of its daily passenger population. Respondents were free to choose
their moment of participation. In total 487 panel members took part in the experi-
ment, of which 303 (62%) were men and 184 (38%) were women. The mean age of the
respondents was 43 years (SD = 15.3, min. 14 years, max. 78 years).

8.3.6 Measurement instrument

After navigating the virtual station and catching the train, respondents had to fill
in a questionnaire in order to measure the perception of both station and waiting
time. The questionnaire commenced with constructs that measured waiting time
perception and were included at the beginning because the wait experience would
then still be fresh in the respondents’ memory.

Chapter 8 Advertising and Infotainment 167

Measures Waiting experience
The variables (with the exclusion of time experience and score) were measured
with a 7-point Likert scale. The station waiting experience was measured with the
following variables (Table 8.4):
–– Time perception: First asked was the perceived (subjective) waiting time in minutes
at the station and on the platform with the question: “If you had to guess, how
long do you think you were at the station/on the platform (in minutes)?” Then
we measured the cognitive evaluation of the waiting time (long/short) with the
question: “How did you experience the time spent at the station?” (1 = very short,
7 = very long).
–– Acceptable wait: Subsequently we measured the acceptance of the waiting time by
asking how acceptable one found it (1 = unacceptable, 7 = acceptable).
–– Utilitarian and hedonic waiting time: The utilitarian waiting time (did one spend
the time usefully, measured with five items) and the hedonic waiting time (did
one spend the time pleasantly, measured with three items) were measured
for the waiting time on the platform by using items of the Shopping Values
of Batra and Ahtola (1991). Example utilitarian waiting time: “Was the time
you spent waiting on the platform: useful–useless, valuable–worthless, etc.”
Example hedonic waiting time: “Was the time you spent waiting on the platform:
pleasing–annoying, happy–sad, etc.”

Measures Station evaluation

The station experience was measured with the following variables (Table 8.5):
–– Emotions: For the PAD emotions an adapted scale of Mehrabian and Russell
(1974) was used. Pleasure was measured with six bipolar items (unhappy–happy,
annoyed–pleased, melancholic–contented, unsatisfied–satisfied, despairing–
hopeful, unpleasant–pleasant). Arousal was measured with six items (stimu-
lated–relaxed, excited–calm, frenzied–sluggish, jittery–dull, wide awake–sleepy,
aroused–unaroused). Dominance was measured with four items (influenced–
influential, cared for–in control, guided–autonomous, submissive–dominant).
–– Approach behaviour was measured on the basis of the ‘approach and avoidance’
scale of Russell and Mehrabian (1974), and consisted of five items. Examples:
“I would recommend this station to others” and “I would have no problem
returning to this platform.”
–– Platform score: Experimental subjects were requested to award a score for their
assessment of the quality of the platform (1 = very poor, 10 = excellent).

The questionnaire also included several manipulation checks. Perceived density was
measured with the aid of the perceived crowding scale (Harrell, Hutt & Anderson,
1980), which consists of three items (Coefficient Alpha = .80). Furthermore there
were three items that aimed to measure the attitude to advertising at the station
(Coefficient Alpha = .95), and finally, several demographic variables (gender, age).

168 waiting experience at train stations

Table 8.5 Cronbach Alpha, Min., Max., M and SD of the dependent variables

Advertisement study
α Min. Max. M SD
Station experience
Pleasure .89 1 7 4.29 .46
Arousal .81 1 7 3.77 .53
Dominance .72 1 7 3.74 .64
General appreciation environment .88 1 7 4.40 1.31
Approach behaviour .90 1 7 4.14 1.22
Platform score – 1 10 6.73 1.35
Waiting experience
Time perception platform – 0 25 4:31 3:25
Acceptance waiting time – 1 7 5.35 1.45
Cognitive time perception – 1 7 4.15 1.85
Utilitarian waiting experience .89 1 7 3.61 .73
Hedonic waiting experience .94 1 7 3.96 .50

8.3.7 Results study 2

Presence of platform wall advertising and station experience
A large portion of the experimental subjects (62.4%) indicated having seen the
platform wall advertising. On average they looked at the screen for 52 seconds. On
enquiry, the presence of the platform wall advertising was valued just below the
scale average. The experimental subjects did not find that the presence of the wall
advertising improved the appearance of the platform (M = 3.71, SD = 1.96), nor that
the station as a whole looked better due to the screens (M = 3.87, SD = 1.92). This
already gives an indication for the testing of hypothesis 3 in which the expectation
was formulated that platform advertising would lead to a more positive evaluation
of the service quality at the station. A correct testing of the hypotheses entailed that
subjects who had seen the advertising were distinguished from those who had not.
A comparison of the two groups revealed a difference in the overall evaluation of
the quality of the platform, albeit the opposite to what we had expected (Table 8.6):
passengers who had seen the wall advertising awarded a lower score to the platform
than passengers who had not seen it (F(1, 473) = 6.87, p <.01). However, the platform
evaluation might be influenced by the waiting time. In their study of the influence
of television in hospital waiting rooms, Pruyn and Smidts (1998) found that people
who watched TV objectively had a longer wait and posited that people only look at
the screen when they start to get bored, i.e. when they have already been waiting for
a while: ‘Presumably, people start to watch TV only after some time. Our results would
rather seem to indicate that it is sooner the length of the wait (and thus boredom) that

Chapter 8 Advertising and Infotainment 169

induces people to start watching’ (Pruyn & Smidts, 1998, p 332). On closer analysis it
appeared that experimental subjects who had seen the advertising had indeed waited
twice as long on the platform (F(1,487) = 45.16, p = .000) and thought their wait was
long (F(1,486) = 82.97, p = .000, Table 8.7). It seems feasible that the lower platform
score was influenced by the longer waiting time and this was confirmed by further
analyses on the platform experience. Platform wall advertising also affects domi-
nance, arousal, pleasure and approach behaviour. The sense of control (dominance)
appeared greater in the condition without platform wall advertising than in the
condition with advertising (F(1, 575) = 33.90, p <.01, Table 8.6). Also arousal appeared
greater in the condition without advertising than in the condition with advertising
(F(1, 472) = 6.72, p = 0.01, Table 8.6). However, the experimental subjects experienced
greater pleasure with the presence of platform wall advertising than without
(F(1, 581) = 29.38, p <.01, Table 8.6), just as its presence also scored higher in approach
behaviour (F(1, 590) = 4.95, p = .03, Table 8.6), even if the passengers’ wait had been
longer than those who did not see the advertisements. So, subjects would return to a
platform with greater enthusiasm if it had wall advertising and they would be more
positive about the station to friends and acquaintances than if the platform had
none. These findings support both hypothesis 3, which predicted that platform wall
advertising would be appreciated by passengers, and hypothesis 4, which predicted
that advertising would lead to more approach behaviour from passengers.

Table 8.6 Means (SDs) of platform experience if advertising was seen yes/no

Platform experience No advertising seen Advertising seen

M (SD) M (SD)
Platform score 7.15 (1.18) 6.82 (1.39)**
Pleasure 4.01 (.58) 4.29 (.46)**
Arousal 3.85 (.56) 3.72 (.56)**
Dominance 4.14 (.68) 3.75 (.64)**
Approach behaviour 3.86 (1.16) 4.15 (1.23)*
Note: Means with * and ** differ significantly in the row: ** p < 0.01, * p < 0.05

Presence of platform wall advertising and waiting experience

Hypothesis 1 proposed that the presence of platform wall advertising alters the way
in which passengers perceive the subjective waiting time as shorter (hypothesis 1a)
or longer (hypothesis 1b). No differences were found in the estimations of waiting
time as a function of platform wall advertising (F < 1). The presence of platform wall
advertising did not appear to have an effect on the time sense factor10 either (F < 1).
However, passengers did find that their wait was spent more usefully (Table 8.7,

10 TSF: Time Sense Factor = the subjective waiting time divided by the objective waiting time
per experimental subject.

170 waiting experience at train stations

utilitarian waiting time) when there was platform wall advertising than when there
was none (F(1, 594) = 13.31, p <.01), and that the time was also more pleasant with
than without (F(1, 596) = 3.50, p = .06, Table 8.7, hedonic waiting time). True, this
last difference is not significant but it does show a very strong leaning toward the
predicted direction. So, advertising does not seem to influence the time perception
but it does positively influence the experience of the waiting time.

Table 8.7 Means (SDs) waiting experience if advertising was seen yes/no

No advertising seen Advertising seen

M (SD) M (SD)
Objective waiting time platform 3:39 (4:05) 6:14 (4:59)**
(in minutes)
Cognitive waiting experience platform 2.93 (1.77) 4.39 (1.67)**
(1 = short, 7 = long)
Utilitarian waiting time 3.28 (1.34) 3.61 (.73)*
Hedonic waiting time 3.83 (1.16) 3.96 (.50)#
Note: Means with *, ** and # differ significantly in the row: ** p < 0.01, * p < 0.01, # p < 0.1

The tempo of ad renewal and waiting experience

In hypothesis 2 we expected that a slow tempo of screen change would result in a
shorter subjective waiting time than a fast one. This hypothesis cannot be confirmed
(F<1). However, other main effects of the renewal tempo of the platform wall
advertising were found that indeed warrant further investigation of the relation­ship
between image pace and waiting experience. The tempo of the platform wall adver-
tising influenced the cognitive evaluation of the wait. In the fast condition the short/
long assessment is significantly lower than in the static condition (F(2,483) = 3.43,
p = .03). This implies that subjects in the fast condition felt that their wait had been
shorter (M = 3.61, SD = 1.54) than subjects in the static condition (M = 4.07, SD = 1.58).
Furthermore, the tempo also influences the acceptance of the wait. In the condition
with the slow tempo, subjects found the waiting time less acceptable (M = 5.33,
SD = 1.51) than in the condition with the fast tempo (F(2, 486) = 3.51, p = .03; M = 5.75,
SD = 1.34). In accordance with Zakay and Block’s attentional model (1997), one expla-
nation might be that passengers sooner appreciate the extra stimuli offered by the
quickly alternating ad images, thus distracting them from the wait. To summarize:
fast screen changes (every 20 seconds) with platform advertising have positive effects
on the evaluation of the waiting time (short/long assessment) and the acceptance
of the wait, without this resulting in an actual lower estimated (subjective) waiting
time.

Conclusion
Platform wall advertising seems to result in a quite varied and interesting pattern
of findings. On the one hand, respondents in this study do not react particularly

Chapter 8 Advertising and Infotainment 171

positively when they are asked to pronounce judgement on this form of station
advertising. They do not think that such forms of advertising contribute to a positive
appearance. On the other hand, the presence of platform advertising does result in
all kinds of positive experiential, attitudinal and behavioural effects and so, too,
does the tempo of screen change seem worthy of deployment in influencing the
waiting experience.
In the third study we will investigate whether these findings can be replicated with
another form of distraction in the service environment, namely infotainment.
Particularly the choice of content is definitive for the user’s assessment of infotain-
ment. For this reason, we manipulated the type of programming in the experimental
study in order to evaluate the effects of passengers’ evaluation and behaviour.

8.4 Study 3 Different types of programming

infotainment on the platform11

8.4.1 Method
In this study we investigated whether and how infotainment as an explicit distractor
in a station environment influenced the station and waiting experience. This was
done with a 4 (type of programming: no programme vs (passenger) information vs
entertainment vs an NS promotion film) x 2 (density: off-peak hours vs peak hours) x
2 (passenger type: must vs lust) between-subjects design. As in the second study, this
experimental design was tested at an online virtual station. On the virtual platform,
screens had been placed on which non-stop infotainment was shown (Figure 8.4).
One quarter of the subjects were able to watch an informative programme with
passenger information, one quarter saw a entertainment programme which also
contained current affairs, one quarter could watch an NS promotion film (Railaway),
and the final (control) group saw nothing but a dark screen.

Figure 8.4 Screens with infotainment

11 This study was presented at the European Transport Conference (Van Hagen, Pruyn,
Galetzka & Kramer, 2009).

172 waiting experience at train stations

8.4.2 Subjects
As in the second study, we used the NS customer panel (Appendix 1). Ultimately,
898 panel members participated in the experiment, of which 532 (58.8%) were
male and 366 (41.2%) were female. The mean age of the respondents was 43 years
(SD = 15.68, min. 13 years, max. 80 years).

8.4.3 Measurement instrument

After navigating the virtual station and boarding the train, respondents had to
fill in a questionnaire. The reliability analyses and findings of the first study did
not warrant any major changes and/or addition of constructs (Table 8.8). Only the
constructs used in the second study to measure the attitude to advertising were
adapted to a scale that measured the attitude to the programming.
Two of the hypotheses from the second (advertisement) study will be tested. Owing to
the outspoken support found in the second study for hypothesis 4, in which platform
advertising was predicted to lead to greater approach behaviour, this variable was not
measured in this study. Also hypothesis 2 could not be tested in this study because
with infotainment the tempo of the screen change was not manipulated.

Table 8.8 Cronbach Alpha, Min., Max., M and SD of the dependent variables

Infotainment study
α Min. Max. M SD
Station experience
Pleasure .87 1 7 4.54 .97
Arousal .75 1 7 4.78 1.12
Dominance .73 1 7 4.21 .74
General appreciation environment .88 1 7 4.52 1.23
Approach behaviour .90 1 7 4.23 1.23
Platform score – 1 10 6.92 1.26
Waiting experience
Time perception platform – 0 40 3:35 3:14
Acceptance waiting time – 1 7 5.67 1.39
Cognitive time perception – 1 7 4.47 1.80
Utilitarian waiting experience .86 1 7 3.52 1.22
Hedonic waiting experience .93 1 7 4.04 1.12

8.4.4 Results study 3

Infotainment and station evaluation
The majority of the experimental subjects (67.5%) indicated having seen the screens.
On average they looked at them for 53 seconds. When there was no programming,
a larger portion of the subjects (52.5%) admitted to not having seen the screens, as

Chapter 8 Advertising and Infotainment 173

opposed to when there was programming (27.5%). This suggests that the moving
images almost certainly attracted attention to the screens. Whether or not the
screens were seen showed no effects for pleasure, arousal and dominance, but in
Table 8.9 we can see that experimental subjects who admitted to having seen the
screens awarded a higher platform score than those who had not seen a screen
or who had only seen a dark screen (F(1, 820) = 10.9, p = .001). This implies that
hypothesis 3 for infotainment can be confirmed.

Infotainment and waiting experience

Differences with infotainment were found with regard to the waiting experience
(Table 8.9). Experimental subjects who noticed the screens and the infotainment felt
that they had waited longer (F(1, 840) = 50.01, p = .000) than those who had not seen the
screens. These results suggest that hypothesis 1b can be confirmed for the infotain-
ment stimuli and would hence support the contextual changes model of time perception
where more processed information results in a longer time experience. However, just
as in the advertisement study, a closer analysis revealed that subjects who had seen
the screens also spent a significantly longer time on the platform than those who had
not seen them (F(1, 845) = 24.82, p = .000). Also apparent is that the time sense factor of
experimental subjects who did see the infotainment was lower than those who did not
see it (F(1, 845) = 4.26, p = .039), Table 8.9. This means that experimental subjects who
saw infotainment, irrespective of the duration of the wait, assessed their wait as being
shorter than those who did not see infotainment. As the experimental subjects not
only awarded a higher score to the platform with infotainment but also assessed the
wait as shorter, the attentional model would seem to apply here, i.e. passengers allow
themselves to be distracted by the moving images, pay less attention to the time and
are thus less inclined to overestimate its duration. This confirms hypothesis 1a.

Table 8.9 Means (SDs) score and waiting experience platform if infotainment was seen
yes/no12

No infotainment seen Infotainment seen

M (SD) M (SD)
Score platform 6.9 (1.3) 7.2 (1.1)**
Objective waiting time platform 3:58 (5:35) 5:50 (5:31)**
(in minutes)
Cognitive waiting experience platform 2.92 (1.80) 3.81 (1.72)**
(1 = short, 7 = long)
Time sense factor platform12 1.53 (1.79) 1.20 (2.28)*
Note: Means with * and ** differ significantly in the row: ** p < 0.001, * p < 0.05

12 TSF: Time Sense Factor = the subjective waiting time divided by the objective waiting time per
experimental subject.

174 waiting experience at train stations

 Appreciation of infotainment
Having asked the subjects (7-point Likert scale) what type of content they found the
most suitable on the platforms, it appeared that NS-related (passenger) information
was regarded as the best kind of content (M = 6.32, SD = 1.15), followed by entertain-
ment (M = 5.35, SD = 1.69). Advertising and promotion were considered the least
suitable (M = 2.45, SD = 1.60). An analysis of variance demonstrated that there was no
connection between the kind of content seen and the assessment of the suitability
of the different types. Other analyses showed that there were no main effects of type
of content, although several interesting interaction effects were found.

Attitude towards the content

Lust passengers valued the informative content higher than must passengers
(F(1, 508) = 3.82, p = .05, Figure 8.5 and Table 8.10).

Table 8.10 Means (SDs) of attitude towards the content

No content Railaway Informative content Entertainment

M (SD) M (SD) M (SD) M (SD)
Attitude towards Must 4.19 (1.46) 3.93 (1.43) 3.71 (1.35) 4.29 (1.50)
the content
Lust 4.25 (1.25) 4.29 (1.28)# 4.11 (1.15)* 3.86 (1.38)#
Note: Means with * and # differ significantly in the column: *p < 0.05, # p < 0.1.

ATTITUDE TOWARDS THE CONTENT

4.4 must
lust
4.3

4.2

4.1

3.9

3.8

3.7

3.6

3.5

3.4
no content railaway informative content entertainment

Figure 8.5 Interaction passenger type and content on attitude towards the content

Notably the entertainment content was valued higher by must than by lust
passengers (F(1, 508) = 3.34, p = .06). Although marginally significant, we can see in

Chapter 8 Advertising and Infotainment 175

Figure 8.5 that lust passengers also value the Railaway content higher than must
passengers (F(1, 508) = 2.77, p = .09, Table 8.10). There appeared to be no differences
between lust and must passengers when no content was narrowcasted.

Perceived waiting time

An interaction effect was found with regard to density and type of content on
the perceived waiting time (F(3,881) = 2.55, p = .05). When there was no content, the
perceived waiting time was shorter on a low density than on a high density platform
(F(1, 881) = 7.96, p <.01, Table 8.11).

Table 8.11 Means (SDs) of perceived waiting time

No content Railaway Informative content Entertainment

M (SD) M (SD) M (SD) M (SD)
Perceived Low density 6:16 (3:54) 7:19 (5:10) 8:18 (5:48) 7:11 (5:46)
waiting time
High density 8:17 (5:38)* 7:46 (4:20) 7:53 (5:49) 6:56 (4:23)
Note: Means with * differ significantly in the column: * p < 0.01.

This difference did not appear to be significant for entertainment, informative and
Railaway programming. This finding places hypothesis 1a in a remarkable perspec-
tive. Figure 8.6 demonstrates that distractors – particularly in the form of news
and passenger info – can lead to a lower time estimation (in comparison with no
programming), but that this occurs on busy (not on quiet) platforms. These findings
suggest that the attentional model offers a suitable underpinning of platforms where
much is going on: activity combined with distraction by infotainment.

PERCEIVED WAIT (IN MINUTES)

8.5 low density

high density
8

7.5

6.5

5.5

5
no content railaway informative content entertainment

Figure 8.6 Interaction density and content on perceived waiting time (in minutes)

176 waiting experience at train stations

 Dominance
No significant differences were found for pleasure and arousal, but an interaction
effect of density and type of content was found on dominance (F(3, 842) = 3.15, p = .03,
Figure 8.7). In the entertainment variant, greater control was experienced when the
platform was busy than when it was quiet (F(1, 842) = 5.87, p = .02, Table 8.12).

Table 8.12 Means (SDs) of dominance

No content Railaway Informative content Entertainment

M (SD) M (SD) M (SD) M (SD)
Dominance Low density 4.26 (.67) 4.26 (.67) 4.11 (.67)# 4.14 (.75)*
High density 4.18 (.64) 4.17 (.62) 4.28 (.73)# (.87)*
Note: Means with * and # differ significantly in the column: * p < 0.05, # p < 0.1.

This difference was marginally significant for informative content (F(1, 842) = 2.99,
p = .08, Table 8.12) and did not appear to be significant in the conditions of no
programming, informative and Railaway programming. The conclusion may thus
be drawn that infotainment on a busy platform increases the sense of control.

DOMINANCE

4.45 low density

high density
4.40

4.35

4.30

4.25

4.20

4.15

4.10

4.05

4.00

3.95
no content railaway informative content entertainment

Figure 8.7 Interaction density and content on dominance

Chapter 8 Advertising and Infotainment 177

8.5 Conclusions

The pattern of results emerging from the three studies is quite subtle and in
some cases even unexpected. Apparent from the field study was that in practice
infotainment results in a positive evaluation of both station and waiting experience.
Passengers awarded a higher score to the platform and found the wait with infotain-
ment more pleasant and useful. Particularly when the platform was busy, infotain-
ment yielded the most positive scores. It would seem that in the second study the
appraisal of the platform wall advertising was negative, whereas positive behavioural
effects did indeed occur as were also convincingly demonstrated by the possibilities
to influence the time perception with the image tempo. True, experimental subjects
made it known that they were not interested in advertising nor did they find platform
advertising suitable, but they did allow themselves to be influenced by it neverthe-
less. The presence of platform wall advertising moreover produced positive affective
reactions. Experimental subjects indicated enjoying themselves more during the
wait and experiencing the waiting time as more useful and pleasant when platform
wall advertising was present. These results suggest that one can consciously express
a negative opinion of such forms of advertising (i.e. when explicitly asked), yet still
affectively and unconsciously react to it in a positive way.
Passengers reacted with greater enthusiasm to infotainment on the platform
screens (first and third study). In their opinion, infotainment offered a more positive
contribution to the appearance of the station and actually led to more positive reac-
tions and higher scores. Infotainment, moreover, seemed to be particularly noticed
when passengers had a longer wait on the platform; in accordance with Zakay and
Block’s attentional model (1997), with infotainment providing them with a distrac-
tion from the waiting time, they were less inclined to overestimate its duration. This
means that particularly with longer waiting times infotainment is a ‘wait softener’.

8.5.1 Discussion
A number of effects were found concerning the presence of the two kinds of
platform distractors that are directly relevant if the decision is made to actually
exploit (either of) them.
First it appeared that with platform wall advertising the screen change pace can be
deployed to influence the perception and experience of waiting time. This finding
makes platform wall advertising an excellent instrument to favourably improve the
total servicescape without the passenger being aware per se of these positive effects
(Van Hagen, Pruyn, Galetzka & Kramer, 2009).
On a quiet platform passengers experienced greater pleasure when the tempo of
the platform wall advertising was slow. When the platform was busy, then it was
the fast tempo that gave the greater pleasure. An explanation for this phenomenon
may be found in the socio-psychological theories of ‘(in)congruence’. Congruence
means that someone’s needs, wishes and preferences correspond to or match the

178 waiting experience at train stations

situation in which one finds oneself and this usually leads to greater satisfaction.
Incongruence between need and situation, on the other hand, leads to people
feeling less comfortable in that situation (Spokane, Meir & Catalano, 2000). It
has also been shown (Van Rompay, Pruyn & Tieke, 2009), that (in)congruence
between varying aspects of the design of products can result in a better (or worse)
processing fluency, and hence to a more positive (or negative) assessment. In the case
of passengers waiting on the platform, we suspect that congruence between the
tempo (fast/slow) of the platform wall advertising and the environment (low/high
density) positively affects the degree of pleasure because it enhances processing
fluency. Incongruency (e.g. fast tempo of screen changes in combination with a
quiet platform, or slow tempo in combination with a busy platform) is not highly
valued by passengers, due to lower processing fluency, and the fact that it can create
an information overload (Bolls, Darrel & Muehling, 2003; Lang, 2000). It is also
possible that passengers in a busy environment with fast screen changes pay less
attention to the content of the message (information overload), but instead are more
receptive to the appeal of the images (Bolls, Darrel & Muehling, 2003; Lang, 2000).
In this case infotainment in a busy environment functions sooner as an ambient
than a design element. That none of the expected effects of infotainment on arousal
were confirmed, makes it plausible that infotainment can be seen as an appealing
distraction from waiting.

Infotainment leans more on the content that is narrowcasted. Lust passengers

value the informative kind of content higher than must passengers. This is probably
because lust passengers are less in a hurry and are thus more receptive to distraction
and information. For must passengers the informative variant probably offers little
extra information, which results in a lower assessment, whereas the entertainment
variant with current affairs does have the content that must passengers value.
Whatever the case, for the practical organization of the programming, these findings
offer interesting leads: a segmented supply of the type of information during peak
and off-peak hours. Lust passengers experience more dominance (perceived control)
when it is quiet on the platform and must passengers when it is busy. Respondents
were primed in the must and lust scenario and this probably also influenced their
experience and expectations. A must passenger travels during peak hours and will
therefore be accustomed to and expect a busy platform. A lust passenger, on the other
hand, travels primarily during off-peak hours and thus expects a quiet platform.
When the situation on the platform does not match expectation and experience,
there is a lesser sense of control. Finally, many similarities were found between the
field study and the virtual studies with regard to the platform score, pleasant wait
and useful wait. Also apparent from both the field and the virtual studies was that
the waiting time was overestimated and that infotainment was particularly positively
valued in a busy situation. This suggests that research in a virtual environment is a
reliable method for studying stations and waiting experience.

Chapter 8 Advertising and Infotainment 179

8.5.2 Recommendations
In conclusion we can state that the presence of platform wall advertising or screens
with infotainment contributes positively to the waiting experience as both of them
soften the wait and distract attention from the waiting time.
Seeing as with public transport the objective waiting time can often not be
shortened and passengers spend the largest part of their wait on the platform, we
recommend making the waiting environment and waiting conditions as pleasant
as possible. Particularly the deployment of screens with infotainment (with well-
considered programming and under optimal screen change conditions) would seem
an interesting instrument to influence the perception of the wait.

180 waiting experience at train stations

 Chapter 9
Discussion
and research
recommendations

‘While emotional evaluation

of the service environment is
primarily a function of various
ambient, design, and social factors,
emotional response to the wait is
a function of many environmental
and non-environmental factors
such as the service stage at which
the wait occurs and whether
consumers know in advance how
long they will have to wait.’
Hui, Dubé & Chebat, 1997
9.1 Introduction

This chapter will take a retrospective look at the findings of our studies and link the
theories on the experience of both the wait and the environment as discussed in
Chapters 3 and 4. With this PhD thesis having investigated how waiting experience
can be positively influenced by making the environment in which it takes place
more pleasant, it has become clear that as people do not possess a sense with which
they can perceive time, time perception is a cognitive process (Block & Zakay, 1997).
Although they can indeed perceive the environment with their senses, it is on the
basis of events occurring in it that they estimate time. As visualized in Figure 9.1,
the events and the environment moreover influence the affective perception of time.
With the X-axis relating to the cognitive perception of time, such as the estimation
of the duration (in minutes) and the experience thereof (short/long), the Y-axis
defines the affective evaluation of the wait as environmentally influenced emotions,
such as pleasure, arousal and dominance, but also emotions evoked by the wait,
such as the affective appreciation of the waiting time, acceptance thereof and
whether the waiting time was perceived as useful and pleasant (Hui, Dube & Chebat,
1997). The underlying principle of this chapter is the conceptual model elucidated
in the Introduction to the empirical studies (Figure 9.3, Paragraph 9.5), and it is on the
basis of this model that the findings of our studies will be discussed. First we will
address the cognitive perception of time (the X-axis in Figure 9.1) and subsequently
the affective evaluation of the wait (the Y-axis in Figure 9.1).

DOOR-TO-DOOR APPRECIATION OF TIME

high
ORIGIN DESTINATION

GAP OF LOST TIME

Enhance Train journey
the appreciation
Time value

of the wait

Access Egress
mode mode

Transfer Transfer

low
Time spent

Shorten the waiting time

Figure 9.1 Two ways to influence waiting time: shorten the waiting time and enhance
the appreciation of the wait

Chapter 9 Discussion and research recommendations 183

9.2 Objective and subjective time

Chapter 3 revealed how people often overestimate the duration of their wait
(Flaherty, 1999; Hornik, 1984; Maister, 1985; Larson, 1987; Zakay & Block, 1997),
and the studies in this thesis have determined that this also holds for the station
environment. For several of these studies Table 9.1 shows the objective waiting
times and the time sense factor (TSF)13 of the station and the platform. The data
originate from the field study of waiting time at stations (Chapter 5) and four virtual
online studies (Chapters 6, 7 & 8). Table 9.1 illustrates that the average objective
stay at the station was just over seven minutes both in the field study and in the
online studies, which indicates that the wait in the virtual world was successfully
simulated. Passengers moreover appeared to wait five minutes on the platform and
overestimated the duration of the wait. This concurs with findings in the literature
(Block, 2006; Hornik, 1984; 1992; 1993; Katz, Larson & Larson, 1991; Block, Zakay
& Hancock, 1998). The overestimation of the waiting time on the platform also
appeared to vary between 30% in the infotainment study (TSF = 1.30) and 95% in the
field study on waiting time (TSF = 1.95). Considering the gross overestimation of
the waiting time in the field study, it is plausible that waiting in a real-life situation
is more vehemently undergone than in a virtual one (where passengers are also
inclined to amply overestimate the wait).

Table 9.1 Means objective waiting time and TSF of station/platform

and waiting time share platform

Studies Field study Online studies

Waiting time Colour Music Advertising Infotainment
(H5) (H6) (H7) (H8) (H8)
M time at station* 7:07 7:09 7:05 7:17 7:22

TSF station 1.90 1.17 1.10 1.26 1.29

M time on platform* 4:56 3:54 4:05 5:06 4:52

TSF platform 1.95 1.85 1.51 1.57 1.30

% time on platform 69% 55% 58% 70% 66%

* = Objective waiting time in minutes and seconds.
TSF: Time Sense Factor = the subjective waiting time divided by the objective
waiting time per experimental subject.

13 TSF: Time Sense Factor = the subjective waiting time divided by the objective waiting time
per experimental subject.

184 waiting experience at train stations

9.3 Attention and time

The attentional model presupposes that people who pay attention to the time will
also be able to estimate it more accurately (Block, 2006; Zakay, 1989; Zakay & Block,
1997). In order to test whether paying attention to time influences the perception
and experience thereof, the four online studies included questions on time aware-
ness (e.g. “When you were on the platform did you look at the clock?”) and the affective
experience of time (Pruyn & Smidts, 1998)14.
Table 9.2 illustrates the average waiting time on the platform of passengers who
kept an eye on the clock (and who were thus consciously aware of the time) and
passengers who did not. It appeared that the first group waited on average longer on
the platform than the latter group (i.e. those who did not heed the time). Apparently,
a longer objective waiting time results in passengers becoming more aware of the
time and thus their paying attention to it. If we look at the TSF (time sense factor), we
can see that passengers who did not heed the time overestimated their time spent
on the platform with a factor of almost 2.5 on average (Table 9.2). These findings
concur with earlier research (Katz, Larson & Larson, 1991; Larson, 1987; Maister,
1985; Pruyn & Smidts, 1998). In accordance with the attentional (gate) model, the
results in Table 9.2. make a reasonable case for dividing one’s attention between
time- and non-time-bound activities (Zakay & Block, 1997). With longer waiting
times passengers start to pay attention to the clock (Pruyn & Smidts, 1998), the gate
opens and time then seems to go more slowly and can be more easily estimated
(Zakay, 1989, Zakay & Block, 1997). What is striking is that passengers who (as good
as) ignore the time, and who are thus less occupied with the wait, actually grossly
overestimate its duration. One explanation may be offered by Vierordt’s Law (Lejeune
& Wearden, 2009), whereby short durations are overestimated and long durations
are underestimated. It is possible that experimental subjects who ignore the time
indeed overestimate a relatively short wait because they find themselves in a waiting
situation in which time usually seems to pass more slowly (Flaherty, 1999; Hornik,
1984; 1993; Larson, 1987; Moreau, 1992). The conclusion may be drawn that people
can only estimate the time accurately when they consciously pay attention to it.
As not all passengers have to wait the same length of time, it was interesting to find
out if the attention to time also influenced the cognitive and affective time percep-
tion irrespective of the objective waiting time. That is why MANOVAs were carried
out for the four online studies, whereby did/did not heed the time were independent
variables and the time experience on the platform and the affective wait evaluation on
the platform were dependent variables, with objective time on the platform included as
co-variate (Appendix 5 for the values).

14 Affective evaluation of the waiting time was measured with 4 items based on a study by Pruyn
and Smidts (1998) on waiting time. Examples of items: ‘I was annoyed because of the time
I had to wait’ and ‘I felt bored during the waiting time’ (1 = totally disagree, 7 = totally agree;
coefficient alpha = .78).

Chapter 9 Discussion and research recommendations 185

Table 9.2 Means (SDs) from four online studies on time experience
Colour online Music online Advertising Infotainment
online online
M (SD) M (SD) M (SD) M (SD)
Objective platform time (minutes & seconds)
Heeded time 4:44 (2:43) 4:55 (3:10) 5:35 (4:14) 5:35 (5:03)
Did not heed time 2:06 (2:25)** 2:09 (2:50)** 2:59 (5:38)** 2:59 (5:44)**
Time Sense Factor (TSF) platform
Heeded time 1.33 (2.12) 1.11 (1.26) 1.09 (1.05) 1.17 (2.16)
Did not heed time 2.93 (4.94)** 2.58 (7.90)** 2.01 (2.53)** 1.68 (1.95)**
Time experience platform (1 = short, 7 = long)1
Heeded time 3.93 (1.72) 3.85 (1.67) 4.15 (1.76) 3.90 (1.75)
Did not heed time 2.60 (1.64)** 2.72 (1.64)** 2.46 (1.60)** 2.54 (1.61)**
Affective wait evaluation platform (1 = low, 7 = high)
Heeded time 4.50 (1.30) 4.01 (1.63) 4.15 (.58) 4.83 (1.16)
Did not heed time 5.17 (1.27)** 5.01 (1.59)** 4.32 (.55)* 5.37 (1.24)**
Differences between heeded time and did not heed time, ** = p < 0.05, * = p < 0.1,
1 = corrected (co-variate) for objective waiting time platform.

The analyses of each study show that passengers who heeded the time found the
wait longer – irrespective of its duration – and that their affective wait evaluation
was more negative in comparison with those who did not heed the time (Table 9.2).
Again the findings can be explained with the attentional model: passengers who
heed the time think that it passes more slowly and is more boring (Zakay & Block,
1997). The results can also be explained with reversal theory (Apter, 2007): passen-
gers who heed the time are more occupied with the travel process, are more serious,
concentrated, stressed (telic) and less receptive to environmental stimuli (Apter,
2007; Easterbrook, 1959; Gilboa & Rafaeli, 2003). In contrast, passengers who do not
heed the time are less hurried, less fixed on the travel process (paratelic), are more
receptive to environmental stimuli and thus react more positively to their stay at
the station.
Pruyn and Smidts (1998) concluded in their study on the waiting experience in
hospitals that enquiring after the cognitive time experience (short/long) and the
affective time experience appeared to be a better predictor of customer satisfaction
than an estimation in minutes. Our findings would seem to corroborate that this
also applies to stations.

186 waiting experience at train stations

9.4 Environmental stimuli and time perception

The studies in this thesis demonstrate that waiting time sometimes seems to pass
more quickly in an environment with few stimuli as well as in an environment with
many. In the colour and light studies, time seemed to pass more quickly with the
barely stimulating colour blue and dimmed lighting (Chapter 6), whereas in the
music and infotainment studies time appeared to pass more quickly with stimu-
lating music and fast screen changes on a busy platform (Chapters 7 and 8). Several
explanations may be given for these (apparently) opposite results. For example,
we know that conscious attention plays a role when estimating time (Block, 2006;
Ornstein, 1969; Poynter, 1983; Thomas & Weaver, 1971; Weick & Guinote, 2010;
Zakay, 1989; Zakay & Block, 1997). Zakay and Block (1997) concluded that the various
(pro- or retrospective) research methods determine what holds people’s attention,
namely the time or other activities (Chapter 3; Block & Zakay, 1997; Zakay & Block,
1997). Conscious attention to the time also played a role in our studies, albeit that
any contrast was determined by the kind of environmental stimuli. Although every
stimulus in the environment is perceived and influences our behaviour, selective
selection allows only few to reach our consciousness (Dijksterhuis, 2007; Gladwell,
2005; Lin, 2004; Mieras, 2007; Wegner, 2002; Wilson, 2002). When environmental
stimuli are barely consciously perceived (such as cool colours and a low level of
lighting, Paragraph 9.6), one’s attention is not consciously distracted from the time.
However, a more stimulating environment (warm colours, high level of lighting)
does afford more information processing (Belizzi & Hite, 1992; Belizzi, Crowley
& Hasty, 1983). Ornstein’s storage size model (1969) might offer an explanation
here, comparable as it is to the retrospective approach in which more information
processing results in a longer estimation of the duration.
When attention is consciously distracted from the time, such as with music,
advertising and infotainment, passengers notice their environment more and can
even experience a moment of ‘flow’ (Csikszentmhalyi, 1999; Lotz, Eastlick, Mishra,
& Shim, 2010). As less processing capacity remains to follow the time, it seems to
pass more quickly. Here, in accordance with the attentional model, and as with the
prospective approach, distraction from the time affords a shorter estimation of the
duration (Block, 2006; Zakay, 1989; Zakay & Block, 1997).
Although Apter’s reversal theory (2007) paid no attention to the experience of time,
it might still explain our findings. Both few and many stimuli can afford a higher
hedonic tone in the shape of relaxation (few stimuli) or pleasure (many stimuli)
and make time seemingly pass more quickly (Baker & Cameron, 1996). Our studies
have shown that the experimental subjects indeed experienced greater pleasure
not only with dimmed lighting but also with stimulating music, advertising and
infotainment.
Combining aforementioned explanations implies that as satisfied passengers do
not pay attention to the time, it seems to pass more quickly (attentional model, Zakay

Chapter 9 Discussion and research recommendations 187

& Block, 1997). Relaxed passengers neither (consciously) heed the time nor their
surroundings and are probably so deep in thought that they also estimate the time
as shorter (storage size model, Ornstein, 1969). Figure 9.2 visualizes the relationship
between hedonic tone, attention and waiting experience. It also clearly demon-
strates that passengers with an extremely low hedonic tone grossly overestimate the
time because they are bored due to a long wait (ironic monitor/assimilation theory) or
because the wait itself induces stress (stress management theory, Paragraph 4.9).

TIME EXPERIENCE THEORIES AND REVERSAL THEORY

pleasant
Attention on thought DENSITY & MUSIC GENRE Attention on environment
Storage size model Attentional model
time faster comfort zone
storage size model
attentional model
relaxation excitement
Hedonic Tone

time slower
Too few stimuli Too many stimuli
Understimulation boredom anxiety Overstimulation
unpleasant
low AROUSAL high
Attention on waiting time Attention on waiting time
Ironic monitor and Stress management theory
assimilation theory

Figure 9.2 Relationship research findings and theories on waiting time

9.5 Station experience and affective experience of time

We have just looked at the cognitive component of waiting time and seen how
objective time is perceived. We have also seen that environmental stimuli influence
cognitive time perception and that a role is played by the affective evaluation of
the environment. Various researchers have ascertained that approach behaviour is
not just influenced by the cognitive but particularly by the affective component of
waiting (Cameron, Baker, Peterson & Braunsberger, 2001; Hui, Dube & Chebat 1997;
Pruyn & Smidts, 1998). That is why this thesis also investigated how environmental
stimuli can influence the affective evaluation of the wait. The conceptual model
addressed in the Introduction to the experimental studies (Figure 9.3) serves as a

188 waiting experience at train stations

guide to the rest of this chapter. Each paragraph focuses on one of the elements
in the conceptual model and includes a discussion of the findings of the various
studies. First the environmental manipulations will be addressed, then the affective
reactions (arousal, dominance, pleasure and affective waiting experience) and the
effect they have on the station and waiting evaluation.

CONCEPTUAL MODEL

Waiting experience
AROUSAL
Must: low arousal
Lust: high arousal

waiting
Environmental evaluation
stimuli PLEASURE APPROACH
Few-Many station
evaluation

DOMINANCE
Must: high dominance
Lust: low dominance

Figure 9.3 Conceptual model for the various studies

9.6 Perception of the environment

The objective of this thesis was to discover the degree to which a pleasant and
distracting environment can contribute to a more positive station and waiting
experience for passengers awaiting their train. To this end, use was made of such
models from environmental psychology as created by Bitner (1992) and Baker (1986).
In various experiments manipulations were operationalized with Baker’s three
environmental dimensions: ambient, design and social.
The ambient dimension was manipulated in this thesis with music and light
intensity. The design dimension was manipulated on the platform by altering the
roofing with various colours and showing advertising and infotainment, and the
social dimension was manipulated with the degree of platform density.
Although passengers continuously perceive stimuli in their environment, their
perception is subject to selective attention which means that they do not perceive
everything consciously (Lin, 2004). Particularly the ambient environmental
elements, such as temperature, music and light, are mostly perceived unconsciously.
Only when absent or unpleasant, such as a temperature that is too high/low or an
environment that is too busy/quiet, are these elements salient (Bitner, 1992; Baker,
1986; Baker & Cameron, 1996).

Chapter 9 Discussion and research recommendations 189

The results of the environmental manipulations show that the surroundings in the
various studies were indeed partly unconsciously perceived. Whereas less tangible
elements such as colour and light intensity were less consciously perceived, the
experimental subjects did notice the more striking stimuli, such as infotainment,
sooner (Bitner, 1992; Baker & Cameron, 1996). With regard to the studies in Chapters
6, 7 and 8, Table 9.3 illustrates how many people consciously perceived the environ-
mental manipulations.

Table 9.3 Percentage experimental subjects who consciously perceived the stimulus
on the platform

Manipulation* Field Study Virtual lab Study Online Study

Music 1 9%
Music 2 10%
Music 3 58%
Colour & Light 1 22%
Colour & Light 2 27%
Colour & Light 3 33%
Infotainment 1 65%
Infotainment 2 62%
Infotainment 3 72%
* = Order of the studies is in accordance with the content of Chapters 6, 7 and 8.

What is remarkable is that music in the field study was hardly consciously perceived
at all, whereas in the online study it was noticed by the majority of the experimental
subjects. In a pilot study on music (Appendix 2), 42% of the experimental subjects
heard the music in the physical station, which would seem to suggest that the
volume in the field study of Chapter 7 was lower, and thus less audible.
On comparing the insights with the classification of the servicescape as formulated
by Baker (1986), one can see that as colour is so evidently visible, she groups it with
the design elements. Despite the findings of our colour and light studies indeed
showing the evident visibility of colour is, that is not to say it is always consciously
perceived. In this respect colour should sooner be allocated to the less conspicuous
ambient dimension than the more conspicuous design dimension.
It has been established in the various studies of this thesis that the stimuli evoke
both cognitive and affective reactions but the apparent general antithesis between
them is striking. For example, experimental subjects indicated a preference for no
music or advertising on the platform, yet the music study demonstrates how the
right music in the right context resulted in a more positive waiting experience just as
the advertising study shows that advertising not only initiated greater pleasure and
approach behaviour but also that the affective wait was more positively evaluated
with advertising than without. Moreover, experimental subjects in the colour and

190 waiting experience at train stations

light studies indicated a preference for the colour blue and a high light intensity on
the platform yet the same studies also show that the affective evaluation was not
influenced by the colour preference or the colour one thought to have seen, nor the
preference for the light intensity. Experimental subjects thus judged the environ-
ment with the low light intensity, both in the field and the online study, as the most
positive and perceived a shorter wait with a low than with a high level of lighting.
Apparently, people’s cognitive assessment of certain matters is at odds with their
affective experience. In accordance with the SOR model, it is however the affective
experience that determines how people feel and how they evaluate the service.
The findings are in keeping with socio-psychological research demonstrating
that conscious perception is not a prerequisite for the evaluation of a service
(Dijksterhuis, Smith, Van Baaren & Wigboldus, 2005).

9.7 Arousal

Apter (2007) poses that it is the desired and not the experienced level of arousal
that determines how people feel: ‘Both bored and excited indicate a preference for
high arousal whether or not it is being experienced, and anxious and relaxed likewise
both imply a preference for low arousal’ (Apter, 2007, p. 48). This might explain why
effects were not found for arousal in all the studies (Paragraph 9.10). In the virtual
music study it appeared that stimulating music evoked more arousal than calming
music, albeit only when the platform was busy. In the field study of colour and light
it appeared that colour combined with a high light intensity afforded more arousal
and in the online colour and light study it appeared that the warm colour yellow
had a particularly stimulating effect on lust passengers. No results for arousal were
found in the infotainment study.
It can be concluded that although the results point in the predicted direction,
passengers did not become overly stimulated in terms of arousal. One explanation
might be that arousal knows two levels of stimulation: an intense one and a more
controlled one. Apter (2007) posed that sleepy/wide-awake is a totally different form
of arousal than boredom/excitement or anxiety/relaxation. In their investigation
into layout and signing in various bank environments, Ang and Leong (1997)
demonstrated that there are indeed two kinds of arousal: a more passive and a
more active form (Ang, Leong & Lim, 1997; Leong, Ang, & Low 1997). As a station is
a functional public space in which people usually show more self-control than in
a private or hedonistic environment, they are more likely to experience a passive
form of arousal. Arousal can thus be better interpreted as information processing,
whereby little results in boredom and complex information processing leads to
stress. Too much information can result in a mental overload (Easterbrook, 1959;
Huffman & Khan, 1998; Klapp, 1986; Lang, 2000; Milgram, 1970; Saegert, 1973;
Smith, 1961), which lowers the hedonic tone. Understimulation, on the other hand,

Chapter 9 Discussion and research recommendations 191

can lead to boredom (mental underload), which also lowers the hedonic tone. Hence
arousal does influence pleasure but more via mentally processing the number of
environmental stimuli than via physically influencing the organism (Furnham &
Allass, 1998; Oakes, 2000; Oakes & North, 2008). The differentiation between passive
and active arousal can also successfully explain why time passes more slowly in an
environment in which passengers have to suppress their emotions (extended now,
Vohs & Schmeichel, 2003; Paragraphs 3.7 and 9.4).

9.8 Dominance

It appeared from the Delphi study (Chapter 2) that – particularly with the more
functional services – a sense of control is important to consumers. A station
environment is such a functional area, with passengers oriented on catching their
train and thus setting great store by their control over time and space. A sense of
control over the space demands a clear overview and correct signing, whereas a
sense of control over the time requires accessibility to the correct time and real-time
travel information.
The findings of the field study with music show that dominance played an impor-
tant role when music was played at a station, i.e. passengers experienced greater
control on a quiet platform with music than without. The sense of control thus plays
a mediating role in the station evaluation. Apparent from the findings of the online
study on colour and light was that greater control (dominance) was experienced
with a low light intensity than with a high one, just as the field study on colour and
light demonstrated that a low light intensity combined with colour initiated greater
dominance than without colour. It can be concluded that in an environment with
few stimuli (quiet platform, little light) a greater sense of control can be experienced
by adding extra stimuli (music, colour). One explanation might be that passengers
experience greater control with an optimal level of stimuli, enabling them to
remain in their comfort zone and feel less lost. This is in keeping with optimal
arousal theory (Apter, 2007; Hebb, 1955), whereby the hedonic tone is higher with an
optimal number of stimuli. Massara, Liu and Melara (2010) consider dominance as
a ‘processing emotion’, which together with arousal determines the level of pleasure
which Messara and collegues regard more as an ‘output emotion’. In this respect,
dominance, like pleasure and platform score, can be seen as a component of the
hedonic tone.
The results of the advertising study show that the experimental subjects expe-
rienced less control with advertising than without, although they did experience
greater pleasure and approach behaviour. Also apparent from the findings of the
infotainment study is that passengers experienced greater control when viewing
news bulletins on a busy platform and that must passengers were more receptive
to news programmes than any other type. One explanation for this might be that

192 waiting experience at train stations

passengers in a busy environment are more concentrated and alert to achieving
their goal and receptive to informative content. The number of stimuli might be
optimal for the experienced pleasure but too great for the sense of control. The
findings give the impression that advertising and infotainment are positively
embraced as distraction, but for a positive sense of control the content must fit the
passengers’ current objective (Bolls, Darral & Muehling, 2003). Congruency and
processing fluency (Van Rompay & Pruyn, in press) could offer some explanation for
these results: must passengers particularly value short, informative programmes,
and the busier the platform, the faster the screen change should be. Density and
fast screen changes afford congruent visual stimuli, enabling an optimal processing
fluency to be reached and costing the least mental energy (Osuna, 1985).

9.9 Pleasure

This paragraph will address our findings for the studies on pleasure on the platform
and Figure 9.3 illustrates how pleasure is influenced by arousal and dominance. The
results of the online music study reveal that pleasure was positively influenced by
the number of stimuli. At quiet moments passengers experienced greater pleasure
when not calming but stimulating music was played, whereas at busy moments it
was the other way round. These findings concur with those of Eroglu, Machleit and
Chebat (2005). From the results of the online colour and light study it appeared
that – regardless of the light intensity – lust passengers experienced greater pleasure
with the (more stimulating) warm colours red and yellow. In contrast, must passen-
gers leant more towards the colour blue. In the field study on colour and light the
colours on the platform not only appeared to be experienced as more stimulating,
colourful and warm but together with a low light intensity also initiated a more
positive station evaluation. Although few differences were found between peak
and off-peak, it appeared that passengers appreciated colour even during peak
hours. Apparently there are so few stimuli on the platform that extra colour will be
positively assessed.
Finally the advertising study revealed that passengers experienced greater pleasure
with advertising than without. Also the slowly changing advertising images on a
quiet platform and the faster change on a busy platform afforded greater pleasure.
These findings concur with those of Massara, Liu and Melara (2010), and can be
successfully explained with reversal theory. It became evident that stimulating
music, warm colours and advertising at quiet moments result in greater pleasure
than calming music, cool colours and no advertising.

Chapter 9 Discussion and research recommendations 193

9.10 Waiting experience

The conceptual model (Figure 9.3) showed that pleasure and arousal influenced
the waiting experience (Paragraph 9.4), but also that the waiting experience itself
can influence pleasure and arousal. When people have to wait for a long time, they
experience less pleasure and become more irritated than those whose wait is short
(Larson, 1987; Maister, 1985). In Paragraph 9.3 we saw that passengers are not very
successful when it comes to estimating time and that – irrespective of the objective
waiting time – it is predominantly the perception whether one’s wait has been
short or long that influences the affective waiting experience (Table 9.2). In order to
ascertain whether a long or short wait influences other variables of the conceptual
model, such as pleasure and arousal (Figure 9.3), we conducted various analyses on
the online studies on colour, music and infotainment (Chapters 6, 7 and 8). A corre-
lation analysis was performed for the variable ‘long-short’ and pleasure, arousal,
dominance, score platform, utilitarian and hedonic wait appreciation (Table 9.4). The
results show that passengers who felt that their wait was short awarded the platform
a higher score in all of the studies, as well as experiencing greater pleasure and
finding the wait more useful and enjoyable than passengers who felt that their wait
had been long (Table 9.4). In the online colour study and the infotainment study
passengers who felt their wait was short experienced greater dominance than those
who felt their wait was long (in the music study this difference in dominance was
not significant). So, the longer the wait is experienced, the more negative the sense
of control is.
For arousal the results vary. From the online colour study it appeared that the
experimental subjects experienced greater arousal when their wait was short, but
in the music and infotainment study they felt greater arousal when their wait was
long. Music and infotainment might afford more distraction than a coloured roof,
and also greater arousal. Also the findings of the field study on waiting experience
at station (Chapter 5) showed that delayed passengers felt stronger emotions and
awarded the station a lower score than those who had left on time. It seems plau-
sible then that passengers who unexpectedly have to wait longer become irritated
and thus experience more arousal and a lower hedonic tone. The conclusion may be
drawn that the waiting experience, as posited in the conceptual model (Figure 9.3),
has an influence on the evaluating variables (score platform, useful and pleasant
wait) and that there is a reciprocal relationship between waiting experience and
arousal and pleasure. The findings also showed reciprocity between waiting
experience and dominance in the online colour and infotainment study, though not
in the music study. Maybe the passengers’ attention was distracted from their travel
process more by the auditive music stimuli than the visual environmental variables
(colour and infotainment).

194 waiting experience at train stations

 Table 9.4 Correlations between short/long wait for pleasure, arousal, dominance,
platform score, utilitarian and hedonic wait
Online studies M, (SD) Pleasure Arousal Dominance Platform Utilitarian Hedonic
N score wait wait
Colour Short/ 3.4, (1.8) -.49** -.38** -.21** -.27** -.36** -.41**
long wait 1319
Music Short/ 3.5, (1.7) -.36** .23** -.06 -.19** -.33** -.35**
long wait 517
Infotainment Short/ 3.5, (1.8) -.48** .22** -.08* -.15** -.38** -.38**
long wait 884

Colour M (SD) 4.5, (1.1) 4.5, (.89) 4.3, (.74) 6.8, (1.3) 3.5, (1.1) 4.0, (1.0)
N 1323 1315 1315 1315 1317 1316
Music M (SD) 4.4, (.9) 3.5, (.9) 3.9, (.8) 6.8, (1.4) 3.0, (1.4) 3.9, (1.2)
N 514 515 510 515 499 498
Infotainment M (SD) 4.5, (1.0) 3.5, (1.0) 4.2, (.7) 7.1, (1.2) 3.5, (1.2) 4.1, (1.1)
N 875 881 850 862 878 871
** = Pearson Correlation is significant at the 0.001 level (2-tailed).
* = Pearson Correlation is significant at the 0.05 level (2-tailed).

9.11 Station evaluation

Various environmental manipulations influence the station evaluation (Figure 9.3)

via pleasure and waiting experience, as expressed in a higher score. It appeared
from both the field and the virtual studies on infotainment, that passengers
awarded a platform a higher score when it showed infotainment than one that
did not. The results of both the field and the virtual study on music revealed a
higher score being given to a quiet platform when up-tempo or stimulating music
was played, but at busy moments it was the platform without music that scored
the highest. The findings of the field study with colour and light revealed that a
higher score was awarded to a busy platform combined with a low light intensity. In
contrast, the online colour and light study showed that lust passengers on a quiet
platform gave a higher score to a platform with the warm colours red and yellow,
whereas must passengers on a quiet platform awarded a higher score with the cool
colour blue. The positive influence of the various measures, as expressed in a score,
amounts to over half a point per measure15. The results show that the most positive
evaluation is created when the number of stimuli is in keeping with the passenger’s
goal-directedness and the situation (such as how busy it is). What is striking about
the results is that for the less conspicuous variables, such as colour, light and music,
incongruent environmental stimuli led to a more positive station experience. This
complies with reversal theory in which mildly incongruent environmental stimuli

15 E.g. platform score field colour study: 6.6 with and 5.5 without colour; field infotainment
study 7.0 with and 6.2 without; online music study station score 7.5 with and 6.8 without.

Chapter 9 Discussion and research recommendations 195

are key (Apter, 2007; Eroglu, Machleit & Chebat, 2005; Massara, Liu & Melara, 2010;
Walters, Apter & Svebak, 1982).
However, the results of the advertising and infotainment study, whereby the most
positive evaluation resulted from fast screen changes in a busy environment, do
not tally with reversal theory. This discrepancy might be due to the fact that there
is a difference between the processing of auditive and visual stimuli. Perceiving
the environment demands mental energy and the more congruent it is perceived
by all the senses (fast images, busy surroundings), the less information capacity is
required. It is possible that with visual stimuli the human mechanism strives for
congruent visual input, with an optimal processing fluency, so that as little energy
as possible needs to be spent on perceiving the environment (Hui, Dube & Chebat,
1997; Osuna, 1985). A visually barely stimulating environment embraces auditive
stimuli, whereas in a visually stimulating one, the extra auditive stimuli (e.g. music,
which all but supports the task) afford too much arousal which can lead to a mental
overload and a more negative station evaluation (Bruins & Barber, 2008; Lang, 2000).

9.12 Wait evaluation

Our findings show that the environmental manipulations also influenced the
utilitarian and hedonic waiting experience, i.e. whether people found their wait
useful or pleasant. We have seen that people who found their wait on the platform
short also found the time more useful and pleasant (Table 9.4). Also apparent
from the online music study was that lust passengers preferred waiting on a quiet
platform with stimulating music but preferred calming music when waiting on
a busy platform. From the online colour and light study it appeared that must
passengers preferred waiting on a blue platform and lust passengers on a yellow
one. These results of the hedonic waiting appreciation thus support reversal theory
(Apter, 2007; Walters, Apter & Svebak, 1982). Furthermore, from the colour and
light field study it appeared that colours on the platform softened the wait and that
waiting on a platform with colour and dimmed lighting enhanced both the useful-
ness and the pleasantness of the wait. Finally, the advertising study revealed that
passengers found waiting on a platform with advertising more useful than without.
In a similar vein, also the infotainment field study showed that passengers found
their wait more useful and pleasant with infotainment than without. Apparently
they experienced the platform as boring and bland, particularly at quiet moments.
The conclusion can be drawn that when a platform is quiet, the wait is more useful
and agreeable to passengers when environmental stimuli are added in the shape
of music, advertising and infotainment, as well as coloured light combined with
dimmed lighting.

196 waiting experience at train stations

9.13 Conclusion

In the studies we have seen that passengers spend most of their time waiting on
the platform (Table 9.1) and that those who keep an eye on the time are reasonably
successful in estimating the duration but find the wait longer and more tedious
(Table 9.2). Passengers with a short wait award a higher score to the platform,
experience greater pleasure and find the wait more useful and pleasant (Table 9.4).
The conclusion may be drawn that the duration of the wait and the degree of
environmental stimulation influence the waiting experience, which is shortened
by both a shorter wait and a higher hedonic tone (relaxed, pleasant). A shorter
waiting experience on the platform can be explained with the attentional model
for environmental stimuli that consciously distract one from the time (music and
infotainment) and with the storage size/segmentation model for environmental
stimuli that are unconsciously perceived (colour and light).
It appeared from the Delphi study of the role of waiting experience among
Dutch service providers that managers and other professionals have woken up
to the importance of their customers’ sense of control and desire for pleasant
surroundings. What is remarkable, however, is that not one of these experts
names the level of environmental stimulation as a focus of their attention, despite
the studies having shown that the degree of stimulation is the key factor in the
waiting experience. The studies in this thesis have demonstrated that the degree
of stimulation particularly depends on the mental processing of the number of
stimuli and that it can enable passengers to instinctively remain in their comfort
zone. The level of stimulation is crucial to the experienced pleasure, dominance
and the waiting experience, just as the correct number of stimuli influences the
processing fluency whereby the surroundings must support the customer’s objec-
tive. Our results furthermore support reversal theory, whereby mildly incongruent
stimuli afford the most positive station evaluation and waiting experience. For
example, our environmental manipulations have clearly shown that not only did
cool colours make all passengers feel that their wait had been shorter but that with
cool colours must passengers also more positively experienced the platform. Lust
passengers, on the other hand, experienced the platform more positively with warm
colours and a low light intensity; they then felt greater pleasure and found the wait
more agreeable and useful. Stimulating music on a quiet platform afforded more
pleasure, dominance, a higher score and a more agreeable wait. The opposite was
the case on a busy platform. Platform infotainment, finally, afforded more pleasure,
a higher score, greater approach behaviour and the wait was experienced as being
more useful. Also fast screen changes on a busy platform gave greater pleasure and
the wait seemed to last shorter. Furthermore we saw that different environmental
stimuli influenced one another. The combination of colour and light, for example,
led to other results than when only the light intensity or the colour’s wavelength was
altered. The same applied to playing different musical genres in combination with

Chapter 9 Discussion and research recommendations 197

the degree of platform density – the last mentioned playing a particularly large role
with any kind of manipulation, whether that be colour, light, music, advertising
or infotainment. From this we can deduce how notably modifying the degree of
density is on the cognitive and affective waiting experience. When influencing the
extent of stimulation of the other environmental dimensions (design and ambient),
the number of passengers on the platform must therefore expressly be taken into
consideration. Too many stimuli on a busy platform has a counterproductive effect
on the station and waiting experience, and the same applies to too few stimuli on a
quiet platform. The exception is advertising and infotainment, both being judged
more positively on a busy platform than on a quiet one.
The conclusion may be drawn that, in accordance with the conceptual model
(Figure 9.3), environmental stimuli influence the processing emotions arousal and
dominance, which in turn influence the output emotion pleasure (Massara, Liu &
Melara, 2010). Pleasure and arousal then influence the waiting experience, which
together with pleasure influences the evaluation of both station and waiting time
(Figure 9.3).
With regard to the servicescape, it can be observed that Bitner (1992) distinguishes
in her model between ambient, functional and social components, whereas Baker
(1986) classes hers into ambient, design and social elements. The findings of our
studies demonstrate that it is not so much the arrangement in social, functional,
design or ambient factors that plays a role in the station and waiting experience, but
the degree to which the environmental characteristics are consciously or uncon-
sciously perceived. Light intensity (ambient) and colour (design) are barely perceived
consciously, whereas music (ambient) and infotainment (design) draw people’s
attention much faster. By differentiating between consciously and less consciously
perceived environmental elements, people’s attention can be steered in a desired
direction. So, colour and light intensity can be deployed to positively influence the
atmosphere of the waiting area and music and infotainment can be deployed to
offer people distraction from their wait.

9.14 Employed research methods

The experiments in this thesis were carried out as field studies and in a virtual
world. Both methods have advantages and disadvantages that may influence the
interpretation of the results. From a practical perspective the choice was made to
always conduct a field study prior to the experiments with colour and light, music
and infotainment in the virtual world. If the desired effects were found in practice,
they formed the basis for the studies in the virtual world where more diverse condi-
tions could be tested. The advantage of a field study is that it is immediately clear if
a certain environmental manipulation actually works in practice. The disadvantage
of a practical experiment, however, is that it is laborious, costs a lot of time and

198 waiting experience at train stations

money and that not all conditions can be kept constant. The results, for example,
might be undesirably influenced by delayed trains, poor information provisions and
ambient noise.
In order to rule out the influence of irregularities, studies were also conducted in a
virtual station in which all the environmental conditions were identical. Besides the
advantage of conditioned surroundings, a virtual station also has the benefit that
various environmental elements can be manipulated quickly and relatively cheaply.
With its visual images, ambient sounds and freedom of movement, the virtual
environment offers a true to life representation of reality (Blascovich, Loomis,
Beall, Swinth, Hoyt & Bailenson, 2002; Kardes, 1996; Massara, Liu & Melara, 2010;
Riva, Mantovani, Capideville, Preziosa, Morganti, Villani, 2006). The respondents
were unaware of any change in the degree of stimulation, such as the addition of
certain music, colour, light intensity, advertising and infotainment. Also relevant,
considering the subject of this dissertation (waiting experience), is that in the
virtual world the objective duration of stay at the station/on the platform can be
recorded both easily and accurately. Another great advantage of an online enquiry
is its extensive reach – a large and widespread group of experimental subjects in a
short period of time (Gosling, Vazire, Srivastava & John, 2004; Kraut, Olson, Banaji,
Bruckman, Cohen & Couper, 2003). Last but not least, many different simulations
can be tested, such as when the experimental subjects were asked to take a certain
train and using two scenarios: must (in a hurry) and lust (not in a hurry). Also the
degree of density (busy/quiet) was varied in all studies.
However, a virtual environment also has its disadvantages. Respondents have
to have certain skills to manoeuvre their way through the station with the aid of
mouse or arrow keys (Huang & Claramunt, 2005; Loomis, Blascovich & Beall, 1999).
Moreover, all experimental subjects perform the research from behind their own
computer, which means the screen and volume settings cannot be influenced, nor
other possibly distracting environmental variables. Nevertheless, despite these
differences in methodology, both research methods deliver comparable results.
Waiting time, for example, was overestimated in both the field study and the virtual
studies and in all studies it appeared that the longer the objective waiting time,
the longer and more boring the wait was perceived. Also apparent from both the
field and the online colour and light studies was that a low light intensity resulted
in the most positive station and wait evaluation. From the results of the music
studies we can conclude that, both in the field studies and the online study, music is
appreciated on a quiet platform but not on a busy one. Finally, the results of the field
and virtual studies on infotainment reveal that a platform with infotainment was
appreciated more than one without and both methods demonstrate that infotain-
ment on a busy platform generated the most positive effects. The conclusion may be
drawn that a virtual world serves the purpose of measuring dissimilarities between
different environmental manipulations and that its ecological validity is high.

Chapter 9 Discussion and research recommendations 199

9.15 Recommendations for future research

The results of the studies in this thesis have shed new light on the relationship
between the environment and the station and waiting experience, including the
differentiation between busy and quiet surroundings and between goal- and less
goal-directed passengers. With these insights, measures can be taken to ameliorate
the station and waiting experience (Chapter 10) as well as being applicable for
enhancing the (busy) areas of other functional and hedonic service providers, such
as airports, hospitals, shopping malls and amusement parks.
However, the results also raise new questions that future research can answer. For
example, it has become clear that arousal plays a central role in the processing of
environmental stimuli but that these stimuli are sooner processed mentally than
physically. Further investigation into the role of arousal in relation to information
processing can offer more insight into the discrepancy between physical and
mental stimulation. In our studies it was the experimental subjects themselves who
indicated how aroused they felt. Arousal can, however, also be measured physically
by ECG, blood pressure, heart rate and skin conduction (Bolls, Darrel & Muehling,
2003; Droit-Volet & Meck, 2007). Moreover, these studies did not enquire after how
complex the environment and the information density was experienced. Including
the measurement of physical arousal in future research and combining this with
questions on the complexity of the environment will enable a keener analysis of how
arousal actually works in the organism.
With regard to the station and waiting experience, the combination of (un)conscious
attention and the perceived hedonic tone seem to determine whether the environ-
ment is more/less positively experienced and the wait as longer or shorter. With
regard to the manipulations, future research could systematically study the level of
the degree of stimulation, from barely to intensely noticeable. The manipulations
in our studies, for example, used a limited number, namely a few colours, types of
music, light intensities and forms of infotainment. Future research could study
the effects of a larger range of intensities per environmental manipulation, such
as a gradation in music volume from barely to extremely audible. The same applies
to the visibility of the light intensity and infotainment, from barely to extremely
visible. This will enable the ascertainment of how station and waiting experience
is influenced by the intensity of stimuli, of where the line is between conscious and
unconscious perception and of where the comfort zone begins and ends. Other
research might incorporate more colours, types of music or forms of infotainment
to determine more accurately which content of the stimuli leads to certain reactions.
Also the effects of environmental manipulations that influence the perception of
other senses, such as smell, touch and maybe even taste could be studied.
Whereas our studies always focused on manipulating just one of the senses, inter­
actions between diverse environmental stimuli might produce different results. Our
findings reveal that identical stimuli are processed differently by various senses.

200 waiting experience at train stations

Incongruent auditive stimuli in a quiet environment, for example, influence the
waiting experience positively, as congruent visual stimuli do in the same context.
Our results suggest that the combination of auditive and many visual stimuli lead
to a mental overload (Bruins & Barber, 2008, Lang, 2000). A further investigation into
the (in)congruent processing of combined stimuli perceived by various senses can
offer an even more detailed insight into the processing of environmental stimuli,
the evaluation of the service, the waiting experience and people’s behaviour.
Finally, our studies considered two moderators: motivational orientation and the
degree of density. As with the environmental stimuli, a further refinement of the
moderators could encompass other motivations or a gradation in density. Also other
moderators could be investigated, such as the time of day or the influence of the
weather. Identical environmental manipulations might well show other effects early
in the morning than late at night, just as fine or bad weather might influence the
evaluation of the service or the waiting experience differently (Eroglu, Machleit &
Chebat, 2005; Kaltcheva & Weitz, 2006; Massara, Liu & Melara, 2010; Oakes & North,
2008; Van Bommel & Van den Beld, 2004).

Chapter 9 Discussion and research recommendations 201

 Chapter 10
Conclusions and
recommendations
for Netherlands
Railways (NS)
‘As soon as we make full use of our
faculties, commit ourselves heart
and soul to anything, live life richly
instead of merely existing, our inner
time spends our ration of clock time
as a drunken sailor his pay. What are
hours outside seem minutes inside.’
John Boynton Priestley, 1894-1984
10.1 Introduction

In this dissertation we have investigated the degree to which the environment

influences the station and waiting experience of passengers. Whereas the previous
chapters studied the relevance of waiting time (Chapters 1 and 2), discussed various
theories on waiting time and environment (Chapters 3 and 4), presented the
results of empirical studies (Chapters 5–8), and linked the findings to the theories
previously examined (Chapter 9), this current chapter will first address the general
role of waiting time for Dutch service providers before scrutinizing a number of
relevant theoretical concepts and translating insights gained from this dissertation
into recommendations for NS.

10.2 Services and waiting

From our exploration of the waiting time problem for service providers (Chapter 2)
it appeared that waiting is usually experienced as tedious unless the service
is considered extremely useful. In such a case, waiting can even contribute to
experiencing the service more intensely, such as waiting for a thrilling attraction at
an amusement park. Particularly with functional services, such as an airport, post
office or train station, clients are goal-directed and conscious of the time and they
find waiting tedious. With more hedonic services, such as a museum or amusement
park, visitors are less goal-directed and aware of the time and they experience
waiting as less bothersome. Furthermore, with both functional and hedonic
services, customers can find themselves in the telic or paratelic state (Paragraph
4.11), i.e. certain people can enjoy a train journey, a flight or a visit to the shops or
a hospital, while others regard this as a functional activity. In this way, occasional
visitors take their time more and are more open to new experiences than those who
use the same service on a regular basis; the latter are already acquainted with the
service and set greater store by an efficient service process. In Figure 10.1 various
services have been arranged in a matrix that shows the degree of functionality on
the Y axis and the importance of service-related time on the X axis. The same figure
also shows the motivational orientation of customers according to the telic and
paratelic state and we can see that the time awareness is greater with functional
than with hedonic services. As the focus of the majority of customers of functional
services is efficiency-oriented, it is important that they experience a sense of control
on the time (clocks, real-time information) and space (overview), and a positive envi-
ronment and waiting experience is created when the surroundings are calming and
not overly stimulating. With a hedonic service on the other hand, efficiency is of less
importance to the majority of the customers; as enjoyment is paramount, a sense
of control on time and space is secondary. In this case, a positive environmental
and waiting experience is created when the surroundings are stimulating and offer

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 205

distraction. With regard to waiting experience it seems plausible that the attentional
model (Paragraph 3.9.3) is applicable to functional services, and the storage size/
segmentation model (Paragraph 3.9.1 and 3.9.2) to hedonic services. After all,
with functional services more attention is paid to the time, whereas with hedonic
services everything revolves around the activity and the creation of a memorable
event (Pine & Gilmore, 1999; Gilmore & Pine 2008).

TIME AWARENESS AND MOTIVATIONAL SERVICE ORIENTATION

Hedonic

F T = Paratelic
A

T T = Telic
F M

Aware of Forgot
the time the time

A
S A = Airport
T = Train station
H
T P S = Supermarket
F = Amusement park
M= Museum
P
H P = Post office
H= Hospital
Utilitarian

Figure 10.1 Time awareness and motivational orientation of various services

(Chapter 2)

The differences between customers in the telic or paratelic state are not as great
with purely functional or purely hedonic services as they are with travel. Travelling
by plane or train might be functional but it can also be a pleasant experience.
However, owing to the prescheduled departure, time itself can never be fully
abandoned and thus remains a focus of the passengers’ attention. With must and
lust passengers being found at either an airport or a train station, we will now
discuss their waiting experience at a station in greater detail.

206 waiting experience at train stations

10.3 Station environment and waiting experience

Various studies in this dissertation have shown how one’s experience of time
is qualified by the attention paid to it. Passengers who heed the time find the
wait more tedious and long (Table 9.2). On average, train passengers spend just
over seven minutes at a station, five of which are spent waiting on the platform
(Table 9.1). In accordance with the conclusion of Pruyn and Smidts (1998), the evalu-
ation of the wait (short/long, pleasant/tedious) seems to determine the satisfaction
with the wait more than the estimation of the time does. The studies also elucidate
the influence of the environment on the waiting experience. As with time also the
attention to the environment plays a role, whereby passengers indeed perceive the
environment, albeit in part unconsciously. For example, passengers experience that
time passes more quickly on a platform with stimulating music, dimmed lighting
and cool colours than on a platform with calming music, much lighting and warm
colours. However, on interrogation, their opinions diverge. Apparently, passengers
have a conscious, primarily cognitively inspired image of a station that is at odds
with the unconscious, affective experience. They say they do not need advertising or
music at the station whereas the findings of the experimental studies show that they
do appreciate them. Passengers also feel that the station should be brightly lit, yet
here, too, the results show that dimmed lighting affords the most positive station
and waiting experience. In order to interpret the environmental influence better,
several theoretical concepts will now be briefly discussed.

10.4 Optimal arousal theory

When passengers wait on a platform for their train, they have sufficient time to
take in their surroundings (Derval, 2007; 2009). Together with the quality of the
staff and the service, the quality of the environment determines how the service is
experienced (Baker 1986; Bitner, 1992). Environmental stimuli are cognitively and
affectively processed via the senses and initiates approach or avoidance behaviour.
With avoidance behaviour people want to leave the area as soon as possible, whereas
with approach behaviour they want to stay longer, to explore and to purchase (more)
(Mehrabian & Russell, 1974).
Passengers feel pleasant when they perceive sufficient environmental stimuli;
they then find themselves in the comfort zone. The opposite is the case when they
perceive too few or too many stimuli. This is demonstrated in Figure 10.2 by the
inverted U-curve (Hebb, 1955; Berlyne, 1971; Wundt, 1910). With an optimal number
of environmental stimuli the stimuli are experienced as congruent, i.e. logical
and in keeping with the expectation and the goal of the consumer or the degree of
density at that moment (Eroglu, Machleit & Chebat, 2005; Kaltcheva & Weitz, 2006;
Massara, Liu & Melara, 2010; Oakes & North, 2008). Congruent visual stimuli afford

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 207

the attainment of an optimal processing fluency, one that demands the least mental
energy (Houston, Bettencourt & Wegner, 1998; Hui, Dube & Chebat, 1997; Osuna,
1985). With the aim of making the waiting environment and waiting experience
more pleasant, the studies in this dissertation added either more or fewer stimuli to
the environment in the shape of music, infotainment, colour and light (Chapters 6,
7 and 8 and Figure 10.2).

SERVICESCAPE & COMFORT ZONE

pleasant
OPTIMAL AROUSAL
Hedonic Tone

COMFORT ZONE:
In control, certain, safe
Different colours & light
Different music
Different infotainment

Bored Stressed
unpleasant
low AROUSAL high

Too deserted Too crowded

Too dark Too much light
Too quiet Too much noise

Figure 10.2 Comfort zone regulation with environmental stimuli

10.5 Reversal theory

Michel Apter (2007) goes one step further and posits that it is the context that
determines how many stimuli result in pleasure at any given time. He differentiates
between two levels (low and high) of optimal arousal, whereby people who are
stressed require few environmental stimuli and people who are bored require many
(Figure 10.3). This is why our studies have distinguished between the passengers’
motivational orientation. Must passengers are utilitarian, are more in a hurry,
focused on the journey and heed environmental distraction less. They prefer orderly
surroundings that are not too stimulating. Lust passengers, on the other hand, are
more hedonistically oriented; they are less in a hurry, less focused on the journey
and their attention is more on their surroundings. They are more receptive to
distraction and environmental stimuli. Figure 10.3 shows the two optimal arousal
curves, one for must and one for lust passengers. It is clear that must passengers are
less tolerant of environmental stimuli than lust passengers.

208 waiting experience at train stations

 TWO OPTIMAL AROUSAL LEVELS
pleasant
relaxation excitement
must
lust TWO OPTIMAL AROUSAL LEVELS

Hedonic Tone

boredom anxiety
unpleasant
low AROUSAL high

Figure 10.3 Optimal arousal curves for must and lust passengers

Also the presence of many other passengers evokes extra environmental stimuli,
whereas a sparsely populated platform hardly stimulates at all. Hence the reason
why our studies also allowed for the degree of platform density, besides motiva-
tional orientation. The findings will be discussed from different perspectives,
following which recommendations for NS will be made. We will start by addressing
the results of environmental stimuli and density and subsequently environmental
stimuli and passenger type.

10.6 Conclusion environmental stimuli and density

It has become clear from these studies that the presence of other people affords
more stimuli. When the platforms are busy, the number of stimuli in the environ-
ment should therefore be minimized, but when it is quiet, stimuli could be added.
In busy and quiet periods, the right balance of stimuli in the shape of coloured light,
music and infotainment can induce positive, affective reactions. As passengers
do not appear to be receptive to extra stimuli on a busy platform, soft music, cool
colours and a low level of lighting afford greater pleasure, a better evaluation of
the platform and more approach behaviour. In contrast, passengers in more quiet
surroundings are receptive to stimuli and they appreciate stimulating music,
warm colours and (also!) a low level of lighting. Congruent visual stimuli provide
an optimal processing fluency, which is to say that passengers on a busy platform
require congruent visual input. With infotainment this means a fast screen change
on a busy platform and a slower one on a quiet platform.

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 209

10.7 Conclusions environmental stimuli and
passenger type

What also appeared from the studies in this dissertation was that must and lust
passengers react differently to environmental stimuli, often in combination with
the degree of density. Lust passengers, for example, feel better on a quiet platform
with stimulating or fast music, dimmed lighting and warm colours and they prefer
the screens to offer distraction, such as (rail-related) informative programmes.
Must passengers, on the other hand, find greater pleasure when they feel they are in
control of their stay, i.e. not only that they can orient themselves, feel assured and
have a grip on the time but also be distracted as little as possible by environmental
stimuli. Must passengers thus lean strongly towards cool colours, a low level of
lighting, no or only relaxed/slow music and wish to see serious content on the
screens, such as news and topical affairs. By adding the correct environmental
stimuli at the right time, the score for the general evaluation of the platform can
increase the score by a half to a full point. It goes without saying that negative
stimuli should first be eliminated or neutralized before adding positive ones. With
regard to visual impressions, negative visual stimuli, such as graffiti, dirt and an
unappealing view, should be prevented as much as possible. With regard to colour,
the negatively experienced colour grey of the platform could be broken up here
and there by adding colour or coloured light. With regard to sound this means that
unwelcome ambient sounds, such as from noisy machines, traffic or other sources,
should be avoided and replaced by music to soften the wait.

10.8 Moving versus staying

With the gained insights it is possible to relate environmental stimuli, density

and motivational orientation to the prime functions of a station: moving and
staying. Whilst moving, passengers are goal-directed and, like must passengers, are
utilitarian in orientation, whereas those who are static (i.e. in the stay mode) are not
and, like lust passengers, are hedonistically oriented. The transfer areas (pedestrian
routes) allow passengers to change quickly and easily from one means of transport
to another, with their focus being on catching the next connection. The stay areas
at the station (waiting rooms, commercial facilities) enable passengers who are in
good time to spend it pleasantly. The moment passengers switch from moving to
staying, their focus shifts from speed and ease to comfort and experience. Having
arrived at the platform, the travel orientation changes from utilitarian to hedonic,
which is why passengers on the platform are then more receptive to environmental
stimuli. Distraction and a stimulating environment are now welcome (Apter, 2007).
The difference between moving and staying is visualized in the pyramid of customer
needs (Figure 10.4, Paragraph 1.8).

210 waiting experience at train stations

 TRANSFER: MOVING AND STAYING

STAYING STAYING
experience

comfort SATISFIERS
DISSATISFIERS
ease

MOVING speed MOVING

SAFETY AND RELIABILITY

Figure 10.4 Different qualities for moving and staying

Our studies reveal that must and lust passengers react differently to stimuli in a
busy or quiet environment. From internal NS research (KTO, 2009) we know that
during peak hours substantially more must passengers travel and that the platform
is more crowded at those moments (Figure 10.5). During off-peak hours the platform
is less crowded and we find a more balanced mix of must and lust passengers.
Measures to improve the waiting experience on the platform can thus be logically
tailored to two periods: the peak hours and the off-peak hours.

DISTRIBUTION MUST AND LUST JOURNEYS ON AN AVERAGE WEEKDAY (2009)

number of journeys on average weekday

80000
must
70000
lust

60000

50000

40000

30000

20000

10000

0
00 730 800 830 900 930 000 030 100 130 200 230 300 330 400 430 500 530 600 630 700 730 800 830 900 930 000 030 100 130 200 230 300
07 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2

Must = work-school-business journeys

Lust motive = leisure and other journeys.
Sources: Relatiematrix 2009 (= file with all journeys between all stations);
KTO 2009 (= Customer Satisfaction Survey, 2009),
N KTO = 60.000 observations;
cross table: planned departure time from departure station * travel motive.

Figure 10.5 Distribution must and lust journeys on an average weekday (2009)

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 211

10.9 Creating a steering matrix

When combining moving and staying with the degree of density, we arrive at a
matrix with four quadrants in which moving and staying are set alongside peak and
off-peak hours (Figure 10.6). As with a kaleidoscope, the different quadrants can
be turned in such a way that each perspective requires its own interpretation with
regard to environmental stimuli. The extreme quadrants are formed by the combi-
nation moving/peak and staying/off-peak. During peak hours, moving passengers
desire control and overview and an environment with few stimuli. During off-peak
hours, staying passengers desire distraction and a stimulating environment. With
regard to environmental stimuli, the combinations of moving/off-peak and staying/
peak can be found somewhere in between, whereby the accent with moving is more
on the utilitarian support of the travel process and the accent with staying is more
on the hedonic support of the stay. We will now address the different quadrants one
by one.

Quadrant 1 is the one in which passengers are the least receptive to environmental
stimuli. When it is busy, goal-directed passengers are already quite stimulated
and too many environmental stimuli could cause them to become overstimulated
and (even more) stressed. By creating a sense of calm with soothing colours and
(possibly) music, the number of stimuli can be instinctively decreased, causing
stressed passengers to wind down. When moving, the sense of control (sense of place
and time) is important and this should follow through to the transfer areas, which
should be orderly, well-signposted and offer travel information whilst keeping the
degree of distraction to a minimum. During peak hours we recommend that the
platforms be brightly lit, with no or only soft background music, not to use too
stimulating colours and to show predominantly serious content on the screens,
such as (travel-related) news and topical affairs. As stated earlier in Paragraph 10.6,
fast screen changes are congruent with density and are positively assessed.

Quadrants 2 and 4 are those in which passengers are receptive to stimuli albeit
that over- and understimulation should be avoided. In quadrant 2 passengers are
goal-directed and, as in quadrant 1, require control but because it is quiet they have
a better overview. Calming music stimulates them enough to feel pleasant but not
enough for them to lose their sense of control. Sufficient lighting and cool colours
allow passengers to move quickly and remain in control. Infotainment with real-
time travel information combined with travel-related content can offer certainty
and results in greater satisfaction.
In quadrant 4 passengers are in the stay mode, which means they are receptive to
environmental stimuli, but as it is also busy, they already have sufficient stimuli
to process. Here, too, the stimuli will have to be chosen carefully so as not to
overstimulate and they must be as congruent as possible with the passengers’ goals.

212 waiting experience at train stations

With passengers now less goal-directed and the human density affording sufficient
visual input, music would cause too much arousal. Warm colours are found to be
pleasant and infotainment distracts them from the wait. Preferably, the content of
the infotainment should be related to the destination, i.e. information on (activities
in) the towns serviced by the train.

ENVIRONMENTAL STIMULI, GOAL-ORIENTEDNESS AND DENSITY

HEDONIC STIMULATION MAXIMUM STIMULATION

• Destination information • Destination information
• Calming music • Stimulating &
• Colour and normal lighting up-tempo music
STAYING • Infotainment: topical & • Warm colours & low-level
entertainment lighting
• Little distraction • Infotainment: entertainment
• Much distraction

4 3
1 2
MINIMUM STIMULATION UTILITARIAN STIMULATION
• Real-time travel information • Real-time travel information
MOVING • No or calming music • Calming music
• Cool colours & high-level • Colours & normal lighting
lighting • Infotainment: topical &
• Infotainment: topical entertainment
• No or minimal distraction • Little distraction

PEAK OFF-PEAK

Figure 10.6 Environmental stimuli, goal-orientedness and density

Quadrant 3 is the one in which passengers are the most receptive to environmental
stimuli. Here, passengers are in the stay mode and it is quiet, which means they
are most in need of environmental stimuli. Currently, the platforms at most of the
stations have the neutral colour grey and passengers are barely offered any distrac-
tion, particularly when it is very quiet. It is at such quiet moments, that passengers
waiting on the platform are thus impoverished when it comes to stimulation and
they become bored. Adding an optimal number of stimuli by way of (dimmed)
ambient lighting, stimulating colours and music draws passengers from their
boredom and into the comfort zone. Distraction during off-peak hours can be
offered with infotainment by alternating news and topical affairs with more relaxed
content, such as travel-related information and entertainment (albeit that the
screen changes should not be too fast). Finally, during off-peak hours passengers
feel the most comfortable with dimmed lighting.

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 213

10.10 Recommendation environmental programme

This PhD thesis has demonstrated how considerable the influence is of station
and platform design on the cognitive and affective experience of passengers.
Specifically, a dynamic programme could be developed for each environmental
stimulus, thereby taking density (e.g. peak/off-peak) and the function of the station
area (e.g. moving and staying) into account.

Colour and light programme: for colour and light a station plan can be drawn up
that appoints where and at what time different colour and light stimuli are added
to the environment in order to create a positive station and waiting experience.
Both during peak and off-peak hours, coloured lighting can accent the platform to
break up the dominant colour grey and make passengers feel more comfortable.
We recommend using cool colours in the transfer areas, because these calm people
down and shorten the perceived time. Passengers are then less stressed whilst
moving and think that they reach their train sooner. We also recommend using
warm colours in stay/waiting areas as they are more stimulating, have greater
appeal and afford greater pleasure. Passengers feel more comfortable in dimmed
lighting and during off-peak hours the wait seems to be less long. We thus recom-
mend using low-level lighting on the platform and turning this up automatically
when the train enters the station. Passengers feel more comfortable with dimmed
lighting whilst they are waiting but will be alerted by the increased brightness when
their train arrives; moreover, they will have better vision when boarding.

Music programme: for music, too, a station plan can be drawn up that specifies
where and at what time different musical genres will be played to create a positive
station and waiting experience. When programming music it is important to avoid
overstimulation. That is why we recommend not playing any music in the transfer
areas so as not to overstimulate the goal-directed passenger. Whilst minimizing
noise pollution there, one could opt for soundscapes (nature sounds) to calm moving
passengers. Also when crowding is dense, such as on a busy platform, music can
over-excite, hence our recommendation to play no music at large stations during the
busy morning peak hours. In the morning people still have to ‘get going’ and are
already confronted with enough stimuli. Music would then result in a mental overload
and a lower hedonic tone. However, when it is quiet, passengers are understimulated
and with their hedonic tone being too low, the addition of stimulating music can fill
the so-called empty space with pleasant stimuli, hence making the passengers feel
better. We recommend playing stimulating music in waiting areas in quiet periods
(off-peak or small stations) to make the wait more pleasant and seem to take less
long. During the afternoon rush hour passengers have already got going and are more
receptive to stimuli than in the morning peak. We now recommend playing calming
music in waiting areas and harmonious music on the platform. In the evening it is

214 waiting experience at train stations

quiet at the station and music can fill the emptiness but at the end of the day people
are less energetic and are less tolerant when it comes to stimuli. Hence our recom-
mendation to play calming music in the evening, such as instrumental, classical
music. The extra calming stimuli afford a more pleasant wait and a sense of security.

Infotainment programme: finally, a station plan can also be drawn up for infotain-
ment that stipulates where and at what time certain content is shown with the
aim of creating a positive station and waiting experience. We recommend only
showing infotainment in waiting areas (platform, catering establishments, shops);
in transfer areas passengers are moving and have neither the time to look at the
screens nor notice them. We also recommend that the programme be mute so as not
to overstimulate either must passengers or when it is busy (see music programme).
When programming infotainment it is imperative that the content is congruent
with other visual stimuli and that it concurs with the passengers’ objectives.
During peak hours we suggest showing short and quickly alternating topical news
items. For goal-directed passengers the content should be serious, informative
and topical; they will then experience a congruent processing fluency and find the
wait pleasant. Longer items can be shown during off-peak hours, with commercial
breaks alternating with topical affairs and entertainment. The tempo of items and
screen changes can be slower than during peak hours as this concurs better with
the visual impressions of the passengers. With screens being suitable for showing
both utilitarian and hedonic images, as well as topical and specific information,
the passengers’ pleasure and sense of control is increased. Their sense of control is
augmented further by incorporating real-time travel information of the platform
concerned in the standard programming (e.g. with a ticker tape stating departure
time of the next train and the current time). The programming will have to be
renewed at least twice daily (morning and evening programme), so that passengers
are not confronted with the same content on their return journey. Infotainment
can also be shown in shops and catering establishments, likewise with a ticker tape
stating upcoming train departures, the current time and possible anomalies. This
way passengers will also remain in control of their travel process in other parts of
the station.

10.11 Environmental stimuli and station domains

It has become clear in this thesis which environmental stimuli can be influenced
the best to steer the waiting experience in a positive direction. The insights from
our studies not only concur with but also give additional underpinning to the four
station domains used in the Dutch rail sector: arrival domain, welcome domain,
travel domain and leisure domain (Bureau Spoorbouwmeester (Bureau Dutch Rail
Architecture), 2006; 2010).

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 215

We have also demonstrated that the situation (busy or quiet, must or lust) has an
effect on the waiting experience. This means that for an optimal travel experience
the design of the station environment must not be static but dynamic. On
discussing the four quadrants (Paragraph 10.9) and the environmental programme,
it became evident that people’s requirements change during the day: (must) passen-
gers have little need of extra stimuli during peak hours, whereas (lust) passengers
certainly appreciate them during off-peak hours. In dual station areas, where
passengers stay and move, such as on a platform, careful thought is warranted
on the programming of environmental stimuli. We recommend developing a
dynamic programme of stimuli that is specially tailored to the density and function
of the areas in which the passengers find themselves. It goes without saying that
few stimuli should be added to the platform during peak hours and extra during
off-peak hours. Also the passenger’s mood should be taken into consideration; not
every passenger wants extra stimuli and he/she should be able to withdraw from
them. The environmental stimuli could be adapted to the situation, e.g. by not
adding extra stimuli in the vicinity of stairs or escalators where it is usually busier.
In contrast, extra stimuli could be added to the central section of the platform to
attract and encourage those who are receptive to them to walk further down, thus
stimulating a more even distribution of passengers over the platform. The end of the
platform can be kept stimulus-free for those passengers who are in search of peace
and quiet and wish to distance themselves from the crowd.
A stimulus dynamic is less relevant in purely stay and transfer areas. Shops and
waiting areas can always be stimulating, e.g. with warm colours and stimulating
music. In the transfer areas, such as the pedestrian routes, the number of stimuli
must always be low, e.g. with cool colours and little distraction. We recommend
NS to have formal discussions with Bureau Spoorbouwmeester and ProRail on the
function of the platform from the perspective of passengers’ needs and the time
they spend there with the aim of alternating the stimuli they experience during the
day and thus meeting their varying needs as optimally as possible.

10.12 Suggestions for further research for NS

This dissertation has offered insights into passengers’ behaviour and their
processing of environmental stimuli. Further research can embroider on these
insights and enable NS to hone customer satisfaction.
–– Although our studies were conducted at a large station (Leiden Central), it is
fair to assume that the insights can also be employed at smaller or even foreign
stations. In order to ascertain whether our findings are indeed applicable to all
stations (Van Hagen & De Bruyn, 2002), one could consider conducting the same
research there.

216 waiting experience at train stations

–– In the virtual studies a train departed every ten minutes, which meant that the
majority of the passengers never had to wait long. With longer waiting times
possibly leading to other findings, further research into this with regard to
station and waiting experience might yield new insights.
–– The studies discussed here focused on the influence of auditive and visual
stimuli on the waiting experience on the platform. This focus could be widened
to other senses such as smell and touch (e.g. tactile value) or sensation/feeling
(e.g. temperature/climate) and the interactions between them (Derval, 2010;
Morrison, Gan, Dubelaar & Oppewal, 2010). It is known that smell can influence
a person’s behaviour, not only with regard to making a wait more pleasant
(Chebat & Michon, 2003; Mitchell, Kahn & Knasko, 1995; Spangenberg, 1990;
Spangenberg, Crowley & Henderson, 1996), but also for example to initiating
behaviour that is conducive to a cleaner or safer environment (Holland,
Hendriks & Aarts, 2005; Van Bommel, 2001; Keizer, Lindenberg & Steg, 2008;
Wilson & Kelling, 1982).
–– By choosing a unique content (of music, infotainment and smell), the environ-
ment can take on a character of its own which might well boost the brand
perception of NS (Lindstrom, 2005; 2008). With the focus on branding currently
being quite visual and static, NS might consider showing content that fits
the company’s mission and objectives as well as varying the light intensity
and colours in the course of the day. With regard to the other senses, a subtle
corporate fragrance could be diffused in station areas and on the train, thereby
awarding them extra cachet (Derval, 2010, Lindstrom, 2005; 2008), and as for
auditory stimuli, NS might consider developing its own unique sound logo
(jingle) and playing a personal repertoire16 to match the mood of the passengers.
Further research can disclose the influence of the environment on brand
perception.
–– The insights gained from this thesis can also be applied to other environments
than just the platform, such as station shops or the train.
–– In station shops passengers who are in a hurry have limited time and they
will thus want to orient themselves quickly, make a hasty purchase and
remain in control of the travel process. Those who have more time on their
hands wish to spend it leisurely and are thus more receptive to surprises
and distraction. One could consider investigating the degree to which a
shop could be divided into a fast and slow area. This would enable the must
passenger to do his/her daily shopping quickly (overview, few stimuli) and
the lust passenger to take his/her time in a more relaxed fashion (stimuli and
distraction).
–– On the train passengers are not so occupied (anymore) with the travel
process but sooner with staying (waiting) on the train until it reaches their

16 Source: Several interviews with Maarten Hartveldt, a renowned composer of film scores.

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 217

 destination. This means that they can undertake other activities during
the journey. Some of the passengers will be utilitarian in their orientation
and will want to undertake serious and goal-directed activities, such as
working or preparing for a meeting. They want a quiet environment with
sufficient lighting so that they can concentrate better on their task. Other
passengers are hedonistically oriented; they are more receptive to distrac-
tion and environmental stimuli and will wish to undertake activities of a
more hedonic nature, such as looking out the window, talking to others or
listening to music. It goes without saying that even on the train the hedonic
tone, the sense of control and passengers’ behaviour can be influenced by
environmental stimuli. In this case one can distinguish between a quiet
and a lively area. The first findings concerning influencing behaviour with
environmental stimuli on the train reveal encouraging results (Debets &
Ruitenburg, 2010).
–– This PhD thesis has drawn on environmental psychology with the aim of
ameliorating the waiting environment. The methods used here can also be
employed in studies that have other objectives, such as:
–– increasing the sense of security, reliability or cleanliness.
–– decreasing undesirable or rough behaviour (vandalism, loutishness, talking
loudly in a quiet compartment) or the sense of density.
–– stimulating desired behaviour, such as improving the flow of the station
(pedestrian route and walking speed) or accelerating the process of getting
on and off the train.
–– The experimental subjects in this thesis were unaware of the environmental
manipulations. Our studies have shown that their cognitive reactions were
usually the antithesis of their affective reactions. Further research could be
conducted in two ways:
–– First, with measures aimed at positively influencing the station experience,
meticulous research methods should be chosen that distinguish between
instrumental and experiential aspects. The first studies of experiential
measures at stations reveal that by taking combined measures the score can
be raised by (up to) one full point and that ambience contributes more to
the general evaluation than instrumental aspects (NS Poort, 2010; NS Visie
op stations, 2006; Van Hagen, Boes & Van den Heuvel, 2009; Van Hagen &
Heiligers, 2010).
–– Second, research could be conducted on environmental changes with the
experimental subjects previously being informed thereof. The chances are
that they will experience the environment differently and that this can lead
to other cognitive and affective reactions.
–– Although this dissertation distinguished between two types of passenger (must
and lust), one could broaden this to include more types, as formulated with, for
example, the needscope types (Van Hagen, 2009). Based on Jung’s archetypes

218 waiting experience at train stations

 (1959), NS differentiates six passenger types: explorer, individualist, functional
planner, certainty seeker, socializer and convenience seeker (Van Hagen, 2009;
Van Hagen, De Gier & Visser, 2005; Van Hagen & Hulster, 2009; Van Hagen & De
Gier, 2010). Combining the insights of this PhD thesis with the needscope types
can afford a more precise differentiation between directive solutions for specific
customer groups or in the development of future services and the design of the
environment. Further research should offer a more accurate insight into how
each passenger type experiences the environment, which in turn will enable NS
to address their various needs even more explicitly.
–– We have demonstrated that the needs of passengers at a station differ. In order
to allow different passengers to experience a pleasant stay at the station, the
lay-out thereof should thus not be static. The passengers’ emotions are not static
either; they change on an individual level according to the place and activity in
the station. The design of the station can be tailored to the different phases of
emotions that a customer undergoes during a visit. Figure 10.7 visualizes how
different emotional phases succeed one another at the station. When passengers
arrive at the station, they check whether they are on time for their train and
from which platform it will depart (stress). They feel euphoric if they catch it
just in time, but irritated if they have just missed it. If they arrive in good time,
they can wait in leisure, but if it takes too long, they will become bored. Further
research can hone the various phases that passengers undergo and provide
insight into the emotions and needs in each phase. This insight will moreover
enable NS to design a station that is even more specifically tailored to passenger
requirements.

EMOTIONAL PHASES OF THE TRAVEL PROCESS

pleasant
DENSITY & MUSIC GENRE
3. Caught the train 2. Caught the train
with time to spare just in time
relaxation excitement

must
lust
Hedonic Tone

4. Waiting for the train 1. Looking for the train

boredom anxiety
unpleasant
low AROUSAL high

Figure 10.7 Travel process and corresponding emotions

Chapter 10 Conclusions and recommendations for Netherlands Railways (NS) 219

10.13 Overall Conclusion

The results of the studies in this thesis have shed new light on the relationship
between the environment and the station and waiting experience, including the
differentiation between busy and quiet surroundings and between goal- and less
goal-directed passengers. With these insights, measures can be taken to ameliorate
the station and waiting experience as well as being applicable for enhancing the
(busy) areas of other functional and hedonic service providers, such as airports,
hospitals, shopping malls and amusement parks.
It can be generally concluded that waiting passengers are receptive to environ-
mental stimuli so as to be distracted from the unpleasant wait. We have demon-
strated that adding the correct environmental stimuli to the platform at the correct
moment can afford a score increase of more than half a point and that passengers
experience greater control and satisfaction, show more approach behaviour and
evaluate the wait as more useful and pleasant. The key to the correct influencing
lies in the intensity and complexity of the environmental stimuli to be processed. In
the stay areas, such as platforms but also waiting areas and commercial facilities,
passengers can be distracted by a large number of stimuli on condition they can
remain in control of the travel process – hence the presence of clocks and real-time
travel information (ticker tape on screens). In the transfer and congested areas the
number of environmental stimuli should be minimized because passengers already
have to contend with enough stimuli. The findings of our studies also demonstrate
that opting for an ‘easy’ solution, such as a grey platform without music or any
other distraction, is not conducive to a more pleasant wait. Nevertheless, with
technical means it is relatively easy to alter the environment re time and space in
such a way that it optimally matches passenger requirements. During the too quiet
off-peak hours it is quite simple to add extra stimuli such as warm accents with
coloured lighting or stimulating music and ditto infotainment. Music, coloured
light and infotainment can be programmed to within a second to create different
atmospheres at the station. This can be programmed ahead but also dynamically
by using, for example, visual pattern recognition (Blunsden, 2005) whereby sensors
and software determine how busy it is and then automatically start up the correct
programme of music, infotainment, light intensity and colour. The advantage of
automatic manipulation is that it can help assuage the stress passengers undergo
when there is a disruption to the rail service, for example, and the platform is even
busier owing to the train arriving late.

220 waiting experience at train stations

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APPENDICES
Appendix 1

NS Panel
The NS panel consists of people who have voluntarily stated that they wish to partici-
pate now and again in NS research. Anno 2010 the panel has 110,000 members
who are approached for various studies 4-5 times per year. They receive no fixed
remuneration for their participation but with each study a number of book tokens
are raffled among respondents. Each panel member fills in a basic questionnaire
so that the most important socio-demographic characteristics are known, albeit
that their anonimity is guaranteed. Not only do the basic questionnaires allow us to
create a representative composition of the passenger population, but respondents
can also be approached for research without having to repeatedly fill in the same
data. The response level is between 35% and 40%. Examples of basic characteristics
are travel data: travel motive and travel frequency (example Figure 1), travel time and
days of travel, use of access and egress transport, type of ticket, first/second class,
etc. Examples of background data: gender, age, education, owner of driver’s license,
availability of car/motorbike, composition of household, age of children, current
occupation, place of residence, etc.

MOST IMPORTANT TRAVEL MOTIVE AND FREQUENCE

panel members

30000

25000

20000

15000

10000

5000

0
4 days per week 1-3 days 1-3 days 6-11 days 3-5 days 1-2 days
or more per week per month per year per year per year

other to and from school or study

varies strongly a business/official trip
visit to doctor, dentist, physiotherapist, hospital, etc. commuting
sport or hobby
holiday or outing
shopping
visiting family, friends, acquintances

Figure 1 Travel motives and travel frequency of panel members

APPENDICES 249
Appendix 2
Two preliminary studies for
musical genre (Chapter 6)
Introduction
Lindstrom (2005) identified that music is a stimulus that can have the most direct
emotional effect on people. As NS strives to offer its passengers a pleasant stay
at both the station and on the platform, we investigated whether music can be
deployed to raise their spirits and thus create a more positive waiting and station
experience. Besides the tempo of the music also the genre influences the effect of
music (Bruner, 1990; Oakes, 2000; 2003; Oakes & North, 2008). The basic premise
of reversal theory (Paragraph 4.11) is that with stressed people calming music
affords a positive hedonic tone, whereas with people who are bored it is stimulating
music that affords a higher hedonic tone. In order to ascertain what music people
appreciate and find suitable at a station, an online study was conducted among the
NS panel to find out their musical preferences and the associations and emotions
they, as passengers, had with stimulating and calming music. We also enquired
after their musical preferences in different situations, e.g. when they were stressed
or relaxed, and to what degree they, as passengers, would value music at a station.
A subsequent study was carried out to test whether the stimulating and calming
musical genres were indeed experienced as such in practice. In the online study in
the virtual world the tested musical genres (calming and stimulating) were tested in
various contexts (passenger type, density, Chapter 7).

Preliminary study 1.
Online study of musical preferences and associations
Of the 4,000 NS panel members (50% commuters and 50% non-commuters) to whom
an online questionnaire was sent, 1,013 responded (26% response). It comprised
questions on musical preference and respondents could hear and evaluate two
musical genres, namely stimulating and calming. The tracks were selected by a
music expert (Maarten Hartveldt, a renowned composer of film scores). The selection
criteria for the tracks concerned the emotional tone (melodical complexity, rhythmic
complexity, vocal meaningfulness and consonant harmony), whereas other criteria
such as volume, tempo and pitch (Bruner, 1990) were kept as similar as possible in
order to prevent confounding effects (Kellaris & Kent, 1994). The findings revealed that
96% of the respondents enjoy listening to music and that pop/easy listening was the
most favourite genre (54%), followed by classical music (41%). The musical preference
barely differed from the average when respondents were either happy or relaxed; only
classical music was then chosen relatively seldom. In a stressful situation a large

250 waiting experience at train stations

group of respondents (28%) preferred to hear no music at all, and the largest group
(34%) opted for classical music. On enquiry, 70% of all people at stations like to hear
music during off-peak hours, with easy listening being the favourite. Commuters
claim to have the least need for music at the station, both during the day and in the
evening. Students and holidaymakers have the greatest need for music, both during
the day and in the evening. In the evening there is also a greater preference for clas-
sical music than during the day. After the respondents had evaluated several musical
fragments online, it appeared that stimulating fragments were assessed as being
more uplifting, busy and exciting than calming fragments. The latter were found to
be more nostalgic and calming than their stimulating counterparts.

Preliminary study 2.
Live investigation effects musical genre
at Leiden Central
To ascertain whether the findings of the online study would also be found in an
actual station environment, various tracks from these two musical genres were
played at Leiden Central Station over a period of four days. The effect of the genres
was measured by asking customers in the hall and on the platform a brief number
of questions. A total of 129 passengers (47% female, 53% male; average age 36.8
(SD = 17.3)) were asked whether the music was sleep-inducing/stimulating and
calming/stress-enhancing (10-point scale). It appeared that 42% of the passengers
had noticed the music. No significant differences were found between passengers
who said that they had/had not heard the music. An analysis of variance showed
a significant main effect for the degree of stimulation: stimulating (F(2, 69) = 3.10,
p = .05) and stress-enhancing (F(2, 69) = 3.72, p = .03). A post hoc analysis revealed
that stimulating music was found to be more stimulating (M = 6.8, SD = 1.7) than
calming music (M = 5.1, SD = 2.0), and that stimulating music was also found to be
more stress-enhancing (M = 5.3, SD = 2.2) than calming music (M = 3.3, SD = 1.8). It
also appeared that stimulating music (M = 6.1, SD = 2.3) afforded a better apprecia-
tion of the environment than calming music (M = 5.5, SD = 1.8, F(2, 125) = 3.0, p = .05).
At the same time passengers appeared to become bored sooner with stimulating
music (M = 6.1, SD = 2.8) than with relaxing music (M = 2.8, SD = 2.9, F(2, 125) = 3.3,
p = .04). The connection might, however, be the other way round. People who are
bored are more receptive to stimuli, hence a greater arousal with stimulating music
and their actually noticing it (Pruyn & Smidts, 1998).
Finally, an ANOVA showed an interaction between passenger type and musical
genre with regard to the degree of stimulation (F(1, 34) = 4.01, p = .05). Must passen-
gers found stimulating music more stress-enhancing (M = 5.55, SD = 2.12) than
relaxing music (M = 2.5, SD = 1.0, F(1,34) = 15.33, p = .000). No significant differences
were found for lust passengers (M = 4.33, SD = 2.51; M = 4.17, SD = 2.13, F < 1). Figure 2
shows the interaction plot.

APPENDICES 251
 RELAXING − STRESSFUL
means

must lust
Passenger Type

calming music
stimulating music

Figure 2 Interaction passenger type and musical genre on degree of stimulation

Discussion
The findings confirm reversal theory, according to which must passengers are
more in a telic (systematic/goal-directed) state; with extra arousal then soon being
too much, must passengers experience more stress with stimulating music. As
lust passengers find themselves in a paratelic (activity-directed/playful) state, they
do not react strongly to extra stimuli and experience an optimum between stress-
enhancing and relaxing with either stimulating or calming music. Must passengers
seem to find the desired peace with calming music. On the basis of these results six
tracks were selected per musical genre (Appendix 3) to serve as stimulus material for
a further study in the virtual world (Chapter 7).

252 waiting experience at train stations

Appendix 3
Musical genres online study
virtual station (study 3)
Table 1. The tracks used in the online virtual music study (Chapter 7)

Muziekgenre Performer & title BPM Subjective BPM

Stimulating Marvin Gaye – Got to give you up 122 61
Stimulating Earth, Wind & Fire – September 124 62
Stimulating Miriam Makeba – Pata Pata 126 63
Stimulating Paul Simon – Late in the evening 120 120
Stimulating Jocelyn Brown – Always there 120 120
Stimulating Oscar d’León – Que Muchacho 120 120

Calming Michael Bublé – Quando, Quando, Quando 116 58

Calming Madeleine Peyrouth – Blue alert 112 56
Calming Michael Franks – Nightmoves 108 54
Calming Van Morrison – Have I told you lately 71 71
Calming Oleta Adams – Get here 55 55
Calming Sheryl Crow – We do what we can 64 64

Control condition Normal station background noises – –

In many studies, the tempo of music plays an important role in how both the
emotion and the time is experienced (Kellaris & Kent, 1992; McElrea & Standing,
1992; Milliman, 1982; 1986; Oakes, 2003). How music is experienced does not solely
depend on the tempo but also on the subjective impression thereof. The subjective
tempo is the emotional interpretation of the exact BPM (beats per minute) to half
of the assigned tempo. This can be regarded as the subjective BPM. The emotional
interpretation is evident with dance, for example: with certain songs people dance
twice as slow as the beat (BPM). People perceive and then interpret a half tempo.
This interpretation occurs simultaneously among large groups of people and is
not restricted to culture or place. In musical scores, the subjective tempo is visible
by a two-two instead of a four-four time. In the same duration, two slow beats can
be counted instead of four. Hence with music, as with time perception, one can
speak of the objective tempo and the ‘more subjective, emotionally interpreted
tempo’17. The perceived BPM determines whether music is found to be relaxing or

17 Source: Several interviews with Maarten Hartveldt, a renowned composer of film scores.

APPENDICES 253
stimulating. That is to say the BPM can designate the music as relaxing but it might
not be perceived as such. The same applies to stimulating music, which might be
designated as such by the number of BPM yet not perceived to be so. In the online
study the explicit choice was made to include, besides tempo, also the subjective
music tempo. The two musical genres were thus selected whereby not the BPM but
the degree of stimulation (subjective tempo) defined the difference between the
genres.

254 waiting experience at train stations

Appendix 4
Preliminary study responsiveness
must and lust passengers to
environmental stimuli

Introduction
A separate study dealt with the question whether lust passengers are more receptive
to environmental stimuli than must passengers. On a weekday (Thursday), 350
questionnaires were randomly distributed to passengers on various trains in the
Netherlands, of which 239 could be used for analysis. Of the respondents 49% were
male and 51% were female and their average age was 35.8 years (SD = 16.46). Of the
239 passengers 61% were identified as lust passengers and 39% as must passengers.

Measures
Lust and must passengers were identified according to their travel motive. Must:
work, business/official trip, school/study; lust: visiting family/friends/acquaint-
ances, shopping, holiday/outing, sport/hobby. Arousal was measured with six items
(relaxed-stimulated, calm-excited, jittery-dull, wide awake-sleepy, sluggish-frenzied,
unaroused-aroused). Dominance was measured with four items (influenced-
influential, cared for-in control, guided-autonomous, submissive-dominant).
Hedonic orientation was measured with three items by using items of the Shopping
Values of Batra and Ahtola (1991). All measures on a 7-point Likert scale whereby 1
stood for ‘completely disagree’ and 7 ‘completely agree’

Results
It appeared from several ANOVAs that, as expected, lust passengers are more recep-
tive to environmental stimuli than must passengers. Lust passengers appear to be
more hedonistically oriented (M = 3.71; SD =1.33) than must passengers (M = 3.20;
SD = 1.27, F(1, 236) = 8.69, p = .004). Lust passengers experience less arousal (M = 2.25;
SD = .65) than must passengers (M = 3.88; SD = 1.29, F(2, 231) = 2.80, p = .008) and
must passengers experience greater dominance (M = 4.36; SD = .66) than lust
passengers (M = 4.92; SD = 1.13, F(2, 231) = 2.32, p = .001). These results concur
with the findings of Massara, Liu and Melara (2010). It can be concluded that lust
passengers have a more hedonic orientation, are more receptive to environmental
stimuli and feel less in control than must passengers.

APPENDICES 255
Appendix 5
Table 2 MANOVAs online studies time perception* (Wilks’ Lambda)

MANOVA
F df Error p
MANOVA Colour online 184.413 2 1302 .000
Time experience platform 32.13 1 1303 .000
Affective wait evaluation platform 12.17 1 1303 .001

MANOVA Music online 7.26 2 503 .001

Time experience platform 9.50 1 504 .002
Affective wait evaluation platform 11.48 1 504 .000

MANOVA Advertising online 51.31 2 477 .000

Time experience platform 45.61 1 478 .000
Affective wait evaluation platform 3.03 1 478 .082

MANOVA Infotainment online 40.36 2 862 .000

Time experience platform 79.90 1 863 .000
Affective wait evaluation platform 19.67 1 863 .000
* Objective time platform = co-variate

256 waiting experience at train stations

 Summary

Research question
In the railway sector there is a great deal of interest in objective time but hardly any
in passengers’ subjective experience of time. The focus of this thesis is thus not
on (shortening) objective time but on how time itself is experienced and how this
can be improved. Aware that a journey must not only be quick but also pleasant,
Netherlands Railways (NS) consequently sets itself the following objective: “To
transport our passengers safely, on time and in comfort via appealing stations.”
Particularly the wait is found to be unpleasant, with passengers regarding stations
and especially platforms as sombre, boring and grey places, devoid of atmosphere
and colour. By improving the waiting environment, we can kill two birds with one
stone: passengers will find waiting more pleasant and the waiting time will appear
to be shorter. The practical question in this thesis thus reads: “Which measures
are effective to make the waiting time at stations more pleasant and/or to shorten the
perception of waiting time?”

Time and environmental experience

People do not possess a sense with which they can perceive time but they can
perceive the waiting environment with the senses they do have. It is the quality of
the environment, that together with the quality of staff and service, determines the
total quality experience of the service. Whilst waiting on a platform, passengers
have sufficient time to take in their surroundings. Environmental stimuli are
cognitively and affectively processed and lead to approach or avoidance behaviour
(SOR model). With avoidance behaviour, people wish to leave as soon as possible
and with approach behaviour they prefer to stay longer and explore the area – as
well as being prepared to purchase more. The waiting experience is also a cognitive
and affective process, with the number and relevance of events in the waiting
environment determining how time is experienced. The affective experience of time
reflects how people emotionally experience a period of time, with pleasure, arousal
and the degree of experienced control playing a key role. Conversely, the cognitive
experience of time concerns the estimation of time and how the duration thereof
(short/long) is experienced; it is moreover influenced by the having to process little
or much information (storage size & segmentation model) and by the having to divide
one’s attention between time- and non-time-bound activities (attentional model).
When much attention is paid to the surroundings, time seems to pass more quickly,
whereas when much attention is paid to the time, it seems to pass more slowly. A
shorter time estimation affords a more positive appraisal of the service and greater
approach behaviour.

Environmental stimuli
Environmental psychologists, such as Baker & Cameron (1996), divide the
waiting environment into three components: ambient elements (intangible: light,
temperature, sound and music), design elements (tangible/visible: colour, design
and furniture) and social elements (people: customers and staff). Optimal arousal
theory poses that with an optimal number of stimuli, people experience greater
pleasure than when there are too few or too many. With an optimal number, the
stimuli are experienced as congruent, i.e. logical and in accordance with the
expectation, fitting the consumer’s goal or the degree of density/crowding at that
specific moment. Congruent stimuli afford an optimal processing fluency, realized
with the least mental energy. With his reversal theory, Apter (2007) distinguishes two
levels of optimal arousal, a low and a high one, with the context determining which
level is preferred. Hence people who are stressed are less receptive to extra stimuli,
although they welcome them when they are bored.

Set-up of the studies

The field and laboratory studies in this thesis answer the question how the
ambient, design and social dimensions must be implemented in order to create a
positive station and waiting experience. With Apter’s reversal theory occupying
centre stage when testing the hypotheses, the waiting environment in each study
was thus manipulated with two levels of stimulation: little versus many stimuli.
Examples: cool/warm colours, little/much light, calming/stimulating music and
static/moving (adverstising) images. The ambient dimension in the studies was
manipulated with music and light intensity, the design dimension with colour,
advertising and infotainment, and the social dimension by varying the degree
of density on the platform. As reversal theory presupposes that in different situ-
ations identical environmental stimuli will lead to divergent reactions, we also
explored the influence of environmental stimuli on two moderators: motivational
orientation and platform density. It was expected that the presence of many other
passengers sufficed as stimulation and that more stimuli would draw people out
of their comfort zone. Conversely, we expected passengers on a deserted platform

258 waiting experience at train stations

to experience so few stimuli that extra ones would actually draw them into their
comfort zone. For motivational orientation we used two types of customer, namely
must and lust passengers. Must passengers are utilitarian re orientation, are more
in a hurry, concentrated on the travel process and less receptive to distraction in
their surroundings. Our assumption was, therefore, that must passengers want a
well-organized/surveyable environment that is not too stimulating and that they
would not appreciate the addition of extra stimuli. Lust passengers, on the other
hand, are more hedonistic; they are in less of a hurry and less occupied with the
travel process. We expected lust passengers to be more receptive to distraction and
to welcome extra environmental stimuli.

Results time experience

In our studies we saw that passengers spend two-thirds of their time at the station
actually waiting on the platform. Passengers not only find waiting tedious but they
also systematically overestimate the duration of the wait. Although those with a
short wait overestimate its length more than those whose wait is long, they still
awarded the platform a higher score as well as experiencing greater pleasure and
finding the wait more useful and enjoyable. Further analysis showed that it is not
the estimation of the time but the appraisal of the wait (short/long, pleasant/boring)
that determines how satisfied passengers are with the service. Attention to the time
and the processing of environmental stimuli moreover determine how passengers
experience the time. Passengers who do not heed the time feel pleasant and relaxed
and time thus seems to pass more quickly. Conversely, passengers who do heed
the time feel bored or stressed and time seems to pass more slowly. Furthermore it
appeared that (un)conscious attention to one’s surroundings also has an influence
on how time is experienced. Subtle environmental stimuli, such as colour and light
intensity, are barely consciously perceived, whereas in a stimulating environment
(with warm colours, much light), passengers do have more stimuli to process which,
in accordance with the storage size/segmentation model, seems to make time go
slower. Consciously perceived stimuli, such as music, advertising and infotainment,
afford distraction from the time which means that there is less processing capacity
to keep an eye on the time, which – in accordance with the attentional model – then
seems to pass more quickly.

Results environmental experience

Particularly when it is quiet, passengers experience the platform as boring and
barely stimulating. By adding environmental stimuli in the shape of music,
advertising, infotainment and coloured light, passengers find the wait more enjoy-
able, useful and pleasant. The degree of stimulation appears to be crucial to the
experienced pleasure, degree of control and the wait, with the stimuli influencing

Summary 259
the processing fluency and needing to be congruent with the customer’s objective.
As expected, the findings demonstrated that the most positive evaluation is created
when the number of stimuli is in sync with the passenger’s goal-orientedness and
the density on the platform. The most positive effects occurred by either adding
many stimuli to a quiet platform or few stimuli to a busy one. Conversely, too many
stimuli on a busy platform has a negative effect on the station and waiting experi-
ence, as do too few on a busy platform. Also apparent was that lust passengers are
more receptive to extra environmental stimuli than must passengers. On a quiet
platform they feel better with stimulating or fast music, dimmed lighting, warm
colours and they seek distraction by screens narrowcasting (rail-related) informative
programmes. In contrast, must passengers sooner covet having a sense of control
on their stay, i.e. being able to orientate themselves better, feeling certain and able
to keep abreast of the time, as well as being as minimally distracted as possible by
environmental stimuli. Must passengers thus lean strongly towards cool colours,
a lower level of lighting, no or only relaxing/slow music and serious content on the
screens, such as news and topical affairs. For light, colour and music it thus applies
that incongruent environmental stimuli afford a more positive station experience.
This is in keeping with reversal theory’s ‘mildly incongurent’ environmental stimuli.
The findings of the advertising and infotainment study, whereby the most positive
appraisal occurs with a fast screen change in a busy environment, on the other
hand, are not in keeping with reversal theory. One explanation for this might be that
– irrespective of the task – the human mechanism aspires after a congruent visual
input (with an optimal processing fluency), so that as little energy as possible need
be invested in visually perceiving the environment. With much visual input, other
senses, such as hearing, can become overstimulated, resulting in stress. In this way,
music is welcomed in a visually understimulating environment and the passenger
is aroused enough to be drawn into his/her comfort zone. However, in a visually
stimulating (busy) environment that same music affords too much arousal, which
can lead to mental overload and a more negative station evaluation.
One remarkable finding of these studies is that the passengers’ opinion is at odds
with their emotional experience. On enquiry, passengers claim not to need adver-
tising or music at a station, yet the results of the experimental studies demonstrate
that those same passengers feel better with both. Passengers also find that the
station should be brightly lit, yet here, too, the findings show that dimmed lighting
affords a more positive station and waiting experience. Apparently, passengers have
a conscious, predominantly cognitive image of a station that is at variance with
their unconscious, affective perception. With the Delphi study of the role of waiting
experience for Dutch service providers (Chapter 2) having revealed that managers
and experts are convinced of the importance to their customers of a sense of control
and a pleasant waiting environment, the findings of the studies in this thesis
demonstrate just how vital the intensity of environmental stimuli is when pursuing
and realizing this.

260 waiting experience at train stations

Recommendations
It goes without saying, that negative stimuli should first be eliminated or neutralized
before adding positive ones. As regards visual impressions, negative visual stimuli,
such as graffiti, dirt or an unattractive view, should be prevented as much as possible.
To improve the appeal of the platform, the negatively perceived colour grey on the
platform could be punctuated by adding colour or coloured light. As regards sound,
undesirable ambient noise should be avoided, such as the din made by machines,
traffic or other sources of sound and, instead, the wait should be ‘softened’ with
fitting music (or calming nature sounds). By differentiating between consciously
and unconsciously perceived environmental elements, people’s attention can be
steered in a desired direction. We have seen that colour and light intensity are often
perceived unconsciously, just as music and infotainment are more noticeable.
This implies that colour and light intensity can be deployed to positively influence
the atmosphere, just as music and infotainment can be implemented to distract
people from their wait. We recommend the development of a dynamic programme
of stimuli, adapted to the density and function of the area in which the passengers
find themselves. This means few stimuli in transfer areas and many in stay areas. By
adding warm colours and stimulating music to waiting areas and shops, passengers
will experience greater pleasure. In transfer areas, such as pedestrian routes, cool
colours and silence afford a more pleasant experience. The conclusion is that by
adding the right environmental stimuli at the right moment, both the station and
the wait are more positively evaluated, resulting in the score for the general appraisal
of the platform increasing by half to one full point.

Summary 261
 Samenvatting

Onderzoeksvraag
In de spoorsector bestaat veel aandacht voor de objectieve tijd, maar nauwelijks voor
de subjectieve tijdbeleving van reizigers. De focus in dit proefschrift ligt daarom
niet op de objectieve tijd en het verkorten daarvan, maar op de beleving van de tijd
en het veraangenamen daarvan. NS beseft dat een reis niet alleen snel, maar ook
aangenaam moet zijn, verwoord in de missie: “Meer reizigers veilig, op tijd en comfor-
tabel vervoeren via aantrekkelijke stations”. Vooral wachten op stations wordt door
reizigers als onaangenaam ervaren. Reizigers vinden stations en vooral perrons
doorgaans somber, saai, grauw, sfeer- en kleurloos en ze vinden het niet prettig
om er te wachten. Door de wachtomgeving te veraangenamen kunnen twee vliegen
in één klap worden geslagen: reizigers vinden het plezieriger om te wachten en de
wachttijd lijkt minder lang te duren. De praktische vraag van dit proefschrift is dan
ook: Welke maatregelen zijn effectief om de wachttijd op stations te veraangenamen en/
of de wachttijdperceptie te verkorten?

Tijd en omgevingsbeleving
Mensen bezitten geen zintuig om de tijd waar te nemen, maar kunnen met de
beschikbare zintuigen wel de wachtomgeving waarnemen. De kwaliteit van de
omgeving bepaalt (samen met de kwaliteit van het personeel en de dienst) de
kwaliteitsbeleving van de dienstverlening. Wanneer reizigers op een perron wachten
hebben ze voldoende tijd om de omgeving in zich op te nemen. Prikkels uit de
omgeving worden cognitief en affectief verwerkt en leiden tot toenaderings- of
vermijdingsgedrag (SOR model). Bij vermijdingsgedrag willen mensen de omgeving
zo snel mogelijk verlaten en bij toenaderingsgedrag willen mensen langer in de
omgeving blijven, de omgeving gaan verkennen en zijn ze bereid om meer aankopen
te doen. De beleving van de wachttijd is eveneens een cognitief en affectief proces,
waarbij het aantal en de relevantie van de gebeurtenissen in de wachtomgeving
bepalen hoe de tijd ervaren wordt. De affectieve tijdbeleving geeft weer hoe mensen
een tijdsinterval emotioneel hebben beleefd waarin pleasure, arousal en de hoeveel-
heid ervaren controle een centrale rol vervullen. De cognitieve tijdbeleving betreft
de schatting van de tijd en de tijdsduurervaring (kort of lang) en wordt beïnvloed
door verwerking van veel of weinig informatie (storage size & segmentation model),
alsmede de verdeling van aandacht tussen tijd en niet-tijdgebonden activiteiten
(attentional model). Wanneer veel aandacht naar de omgeving gaat dan lijkt de tijd
sneller te gaan, wanneer veel aandacht naar de tijd gaat, dan lijkt de tijd langzamer
te gaan. Een kortere tijdschatting leidt tot een positievere evaluatie van de dienstver-
lening en tot meer approachgedrag.

Omgevingsprikkels
Omgevingspsychologen (bijv. Baker & Cameron, 1996) verdelen de wachtomgeving
in drie componenten: Ambient elements (ontastbaar: licht, temperatuur, geluid en
muziek), design elements (tastbaar/zichtbaar: kleur, inrichting en meubilair) en
social elements (mensen: klanten en personeel). De optimal arousal theorie stelt dat
mensen bij een optimaal aantal prikkels meer plezier ervaren dan bij te weinig of
teveel prikkels. Bij een optimaal aantal prikkels worden de prikkels als congruent
ervaren, dat wil zeggen logisch en in overeenstemming met de verwachting,
passende bij het doel van de consument of de mate van drukte op dat moment.
Congruente prikkels zorgen ervoor dat een optimale processing fluency wordt
bereikt, welke de minste mentale energie kost. Apter (2007) onderscheidt met zijn
reversal theorie twee niveaus van optimal arousal, een laag en een hoog niveau,
waarbij de context bepaalt welk niveau geprefereerd wordt. Zo staan mensen die
gestrest zijn minder open voor extra prikkels, maar worden extra prikkels verwel-
komd, wanneer mensen zich vervelen.

Opzet studies
De veld- en laboratoriumstudies in dit proefschrift geven antwoord op de vraag hoe
de ambient, design en social dimensies ingericht moeten worden om een positieve
stations- en wachttijdbeleving te creëren. De reversal theorie van Apter (2007) staat
centraal bij het toetsten van de hypothesen. Daarom is de wachtomgeving in alle
studies steeds met twee niveaus van prikkeling gemanipuleerd: weinig stimuli
versus veel stimuli. Voorbeelden zijn koele/warme kleuren, weinig/veel licht, rustige/
stimulerende muziek of stilstaande/bewegende (reclame)beelden. De ambiente
dimensie is in de studies gemanipuleerd met muziek en lichtsterkte, de design
dimensie met kleur, reclame en infotainment en de social dimensie door de mate
van drukte op het perron te variëren. De reversal theorie veronderstelt dat dezelfde
omgevingsprikkels in verschillende situaties tot andere reacties zullen leiden.
Daarom is tevens onderzocht wat de invloed van omgevingsprikkels is op twee
moderatoren, motivationele oriëntatie en drukte op het perron. Verwacht wordt dat
veel andere reizigers voor voldoende prikkels zorgen en extra omgevingsprikkels

264 waiting experience at train stations

mensen buiten de comfortzone brengt. Aan de andere kant verwachten we dat
reizigers op een verlaten perron zo weinig prikkels ervaren dat juist extra prikkels
hen in de comfortzone brengt. Voor de motivationele oriëntatie is uitgegaan van
twee reizigerstypen, must- en lustreizigers. Mustreizigers zijn utilitair georiënteerd,
hebben meer haast, zijn geconcentreerd bezig met het reisproces en hebben
minder oog voor afleiding uit de omgeving. We veronderstellen dat mustreizigers
een overzichtelijke omgeving wensen die niet te prikkelend is en verwacht wordt
dat toevoeging van extra prikkels door mustreizigers niet zal worden gewaardeerd.
Lustreizigers hebben daarentegen een hedonistische oriëntatie, zijn minder gehaast
en minder bezig met het reisproces. We veronderstellen dat lustreizigers meer open
staan voor afleiding en extra omgevingsprikkels door hen worden verwelkomd.

Resultaten tijdbeleving
In de studies hebben we gezien dat reizigers tweederde van hun stationstijd
wachtend op het perron doorbrengen. Reizigers vinden wachten vervelend en
overschatten de wachttijd stelselmatig. Hoewel reizigers die kort wachten de wacht-
tijd meer overschatten dan reizigers die lang wachten, geven ze het perron toch een
hoger rapportcijfer, ervaren ze meer pleasure en vinden ze het wachten nuttiger
en aangenamer. Nadere analyses leren dat niet de schatting van de tijd, maar de
waardering van de wachttijd (kort/lang, aangenaam/vervelend) bepaalt in hoeverre
reizigers tevreden zijn met de dienst. De aandacht voor de tijd en de verwerking van
omgevingsprikkels bepaalt daarbij hoe reizigers de tijd ervaren. Reizigers die niet
op de tijd letten voelen zich plezierig en ontspannen, waardoor de tijd sneller lijkt
te gaan. Reizigers die wel op de tijd letten voelen zich verveeld of gestrest, waardoor
de wachttijd langzamer lijkt te gaan. Verder blijkt dat de (on)bewuste aandacht voor
de omgeving ook invloed heeft op de tijdbeleving. Subtiele omgevingsprikkels als
kleur en lichtsterkte worden nauwelijks bewust waargenomen, maar in een prik-
kelende omgeving (warme kleuren, veel licht) moeten reizigers wel meer prikkels
verwerken, waardoor de tijd conform het storage size/segmentation model langzamer
lijkt te gaan. Prikkels die bewuster worden waargenomen, zoals muziek, reclame en
infotainment zorgen ervoor, dat de aandacht afgeleid wordt van de tijd, waardoor
minder processing capacity over blijft om de tijd te volgen en deze sneller lijkt te
gaan, conform het attentional model.

Resultaten Omgevingsbeleving
Reizigers ervaren het perron vooral op rustige momenten als saai en weinig prik-
kelend. Door het toevoegen van omgevingsprikkels in de vorm van muziek, reclame,
infotainment en gekleurd licht ervaren reizigers het wachten als plezieriger, nuttiger
en aangenamer. De mate van prikkeling blijkt cruciaal te zijn voor de ervaren
pleasure, de hoeveelheid ervaren controle en de wachttijdbeleving, waarbij de prik-

Samenvatting 265
kels de processing fluency beïnvloeden en congruent moeten zijn met het doel van de
klant. Zoals verwacht laten de resultaten zien dat de meest positieve evaluatie wordt
gecreëerd, wanneer het aantal prikkels aansluit bij de doelgerichtheid van reiziger
en de drukte op het perron. De meest positieve effecten ontstaan door toevoeging
van veel prikkels op een rustig perron en toevoeging van weinig prikkels op een
druk perron. Omgekeerd hebben teveel stimuli op een druk perron een negatief
effect op de stations- en wachttijdbeleving, evenals te weinig stimuli op een rustig
perron. Ook blijken lustreizigers meer open te staan voor extra omgevingsprikkels
dan mustreizigers. Zo voelen lustreizigers zich op een rustig perron prettiger met
stimulerende of snelle muziek, gedimde verlichting, warme kleuren en willen ze op
beeldschermen afleiding zien, zoals (railgerelateerde) informatieve programma’s.
Mustreizigers ervaren juist meer plezier als ze een gevoel van controle hebben over
hun verblijf, dat wil zeggen dat zij zich goed kunnen oriënteren, zich zeker voelen
en grip op de tijd kunnen houden, maar ook dat ze zo min mogelijk worden afgeleid
door omgevingsprikkels. Mustreizigers hebben daarom vooral behoefte aan koele
kleuren, een laag verlichtingsniveau, geen/ontspannen of langzame muziek en
willen serieuze inhoud op beeldschermen zien, zoals nieuws en actualiteiten.
Voor licht, kleur en muziek geldt dus dat incongruente omgevingsprikkels tot een
positievere stationsbeleving leiden. Dit sluit aan bij de reversal theorie welke uitgaat
van mildly-incongruente omgevingsprikkels. De resultaten van de reclame- en
infotainmentstudie, waarbij de meest positieve waardering ontstaat bij snelle wisse-
lingen van beelden in een drukke omgeving stroken niet met de reversal theory.
Een verklaring zou kunnen zijn dat het menselijk mechanisme ongeacht de taak
streeft naar congruente visuele input, met een optimale processing fluency, zodat
zo min mogelijk energie gestoken hoeft te worden in het visueel waarnemen van de
omgeving. Prikkels van andere zintuigen, zoals gehoor, kunnen bij veel visuele input
overprikkelen, waardoor stress ontstaat. Zo wordt muziek in een visueel weinig prik-
kelende omgeving verwelkomd en ontvangt de reiziger voldoende prikkels om in de
comfortzone te komen. Echter, bij een visueel prikkelende (drukke) omgeving zorgt
dezelfde muziek voor teveel arousal wat kan leiden tot een mentale overbelasting en
een negatievere stationsevaluatie.
Opvallend resultaat uit de studies is dat de mening van reizigers afwijkt van hun
emotionele ervaring. Zo geven reizigers desgevraagd aan, dat ze geen behoefte
hebben aan reclame of muziek op een station, maar de resultaten uit de experimen-
tele studies tonen aan dat dezelfde reizigers zich plezieriger voelen met muziek en
met reclame. Ook vinden reizigers dat het station helder verlicht moet zijn, maar
ook hier laten de resultaten zien dat gedimde verlichting leidt tot een positievere
stations- en wachttijdbeleving. Blijkbaar hebben reizigers een bewust, voornamelijk
cognitief geïnspireerd beeld van een station dat afwijkt van de onbewuste, affectieve
beleving. Uit de Delphi studie naar de rol van wachttijdbeleving bij Nederlandse
dienstverleners (hoofdstuk 2) bleek dat managers en deskundigen doordrongen zijn
van het belang van het gevoel van controle en een aangename wachtomgeving voor

266 waiting experience at train stations

haar klanten. De resultaten van de studies in dit proefschrift tonen aan dat de inten-
siteit van de omgevingsstimuli de centrale schakel is om een gevoel van controle en
plezier te realiseren.

Aanbevelingen
Het ligt voor de hand om eerst negatieve prikkels uit de omgeving te elimineren
of te neutraliseren om daarna positieve prikkels toe te voegen. Ten aanzien van
visuele indrukken moeten negatieve visuele stimuli, zoals graffiti, vuil of een
onaantrekkelijk uitzicht zoveel mogelijk voorkomen worden. Om het perron te
veraangenamen kan de als negatief ervaren kleur grijs op het perron op bepaalde
plekken worden doorbroken door toevoeging van kleur of gekleurd licht. Voor geluid
geldt dat ongewenst omgevingsgeluid vermeden moet worden, zoals herrie van
lawaaiige machines, verkeer, of andere geluidbronnen, waarna met het inzetten
van passende muziek (of rustgevende natuurgeluiden) het wachten veraangenaamd
kan worden. Door een onderscheid te maken in bewust en minder bewust
waargenomen omgevingselementen kan de aandacht van mensen in een gewenste
richting gestuurd worden. We hebben gezien dat kleur en lichtintensiteit onbewust
worden waargenomen en muziek en infotainment meer opvallen. Dit betekent dat
kleur en lichtsterkte ingezet kunnen worden om de sfeer van de verblijfsruimte
positief te beïnvloeden en muziek en infotainment kunnen worden ingezet om
mensen afleiding te bieden van het wachten. Aanbevolen wordt om een dynamische
programmering van prikkels te ontwikkelen aangepast aan de drukte en de functie
van de ruimten waarin de reizigers zich bevinden. Dit betekent weinig prikkels in
transfergebieden en veel prikkels in verblijfsgebieden. In wachtruimten en winkels
kunnen bijvoorbeeld warme kleuren en stimulerende muziek worden toegevoegd
aan de omgeving, reizigers ervaren dan meer plezier, maar in transferruimten, zoals
de looproutes, zijn stilte en koele kleuren effectiever voor een prettige beleving.
Geconcludeerd kan worden dat door het toevoegen van de juiste omgevingsprikkels
op het juiste moment het station en de wachttijd positiever worden beoordeeld en
het algemeen oordeel van het perron uitgedrukt in een rapportcijfer met een half tot
een vol punt kan stijgen.

Samenvatting 267
 Dankwoord

U heeft zojuist de kans gehad om in dit proefschrift kennis te nemen van wetens­
waardigheden opgedaan in de ontdekkingsreis naar wachttijdbeleving. Dit
proefschrift is daarmee een reisverslag, waarin alleen de inhoudelijke weergave van
de onderweg verzamelde kennis is weergegeven. Het reisproces zelf komt nauwelijks
aan bod. Toch is een reis niet alleen een functionele en doelgerichte operatie, maar
kan een reis ook een gedenkwaardige belevenis zijn: de reis is de herberg. Met
dit in het achterhoofd had ik me voorgenomen om niet alleen het doel van de reis
voor ogen te houden, maar ook van het reizen zelf te genieten. Dat is gelukt! Maar
uiteraard niet zonder een goede voorbereiding en zonder hulp van veel betrokken
medereizigers. Ik hecht er grote waarde aan om de belangrijkste metgezellen te
bedanken voor hun inspiratie, adviezen, hulp, maar vooral het plezier dat ze mij
onderweg hebben gegeven. Daarbij ontstaat altijd het gevaar dat ik personen die een
bijzondere rol hebben gespeeld vergeet te bedanken, bij deze wil ik de ook niet met
naam genoemde relevante personen hier bedanken.

Als eerste wil ik de reisverkenner, Jan Jurriëns bedanken. Jan je hebt me vanaf
1996 regelmatig de suggestie gedaan, maar eens te gaan promoveren. Ik heb me
daar lang tegen kunnen verzetten, met als belangrijkste reden tijdgebrek… Pas
nadat je Aad Veenman informeerde over dit idee en in diezelfde week Ad Pruyn hét
onderwerp voor onderzoek aanreikte en bereid was dat te begeleiden, wist ik dat
alle bezwaren niet meer zouden opwegen tegen het avontuur. Aad, bedankt voor
de aanmoediging en steun aan het begin van het traject, maar ook aan het eind
door zitting te nemen in de promotiecommissie. Jan, bedankt voor de inspirerende
voortgangsgesprekken, toen het spel eenmaal op de wagen was.
Elke ontdekkingsreis begint met een goede voorbereiding. Zoals in de eerste zin
van mijn proefschrift staat kost een reis geld, tijd en moeite, zo ook deze reis. Door
de financiële steun van NS en Prorail is het mogelijk geweest de verschillende
onderzoeken uit te voeren en het boekje mooi vorm te geven. Daarvoor ben ik in
het bijzonder dank verschuldigd aan Paul Rooijmans, Paul Schulten, Jan-Paul
van Heemskerck, Erik Beenen, Roger Courtens, Jaap Reinders, Peter Krumm en
Mark Bendik. Verder heeft NS mij een dag in de week de tijd gegund om aan mijn
avontuur te wijden, zodat ik meer tijd had om mijn gedachten te verzetten van
regulier werk naar promotieactiviteiten. Daarvoor wil ik graag Maarten Spaargaren,
Maurice Unck, Theo van der Star en Jeroen Gemke bedanken. Jeroen je hebt mij
in de laatste fase van het proefschrift veel ruimte gegeven om het verhaal goed af
te kunnen ronden, omdat je van zeer nabij weet wat dit betekent, hartelijk dank
daarvoor.
Verder hebben getalenteerde studenten van de Universiteit Twente mij veel werk
uit handen genomen en daarmee tijd en moeite bespaard. Ik wil in het bijzonder
die studenten bedanken die voor hun afstuderen invulling wilden geven aan enkele
studies van mijn proefschrift en daarmee de noodzakelijke puzzelstukjes hebben
aangereikt: Pam Roelofs (voorstudie motivationele oriëntatie); Joyce Peters (Virtueel
laboratorium en online studie kleur & licht); Jessica Sauren (veldstudie kleur & licht
en online studie muziek); Elsbeth Boes (veldstudies muziek); Judith Kramer (online
reclame en infotainment studies); Koen van ’t Hof (wachttijdbeleving en veiligheid,
jammer Koen dat er in het boekje geen ruimte meer was voor de interessante
studieresultaten, maar we werken aan een publicatie!). Al deze studenten zijn bij
hun afstuderen begeleid door docenten van de vakgroep Marketingcommunicatie
en Consumentenpsychologie.

In het begin van de reis heb ik veel geleerd van de praktijkkennis van een aantal
deskundigen op het gebied van wachttijd(beleving) werkzaam bij verschillende
dienstverleners. Dank gaat uit naar Hans Bartelds, Marieke den Boer, Kees-Jan
Dosker, Ruud Huitenga, Jolanda van Halteren, Peter Krumm, Hans Martens, Edwin
Okel, Paul Rooijmans, Gideon Ruig, Paul van Vlijmen, Roy de Vries, Olaf Vugts, Irma
Winkenius, Ronald van der Zijl en Rob Zwerink.

Experimenteel onderzoek doen zonder respondenten is onmogelijk, daarom wil ik

alle reizigers en NS panelleden die meegewerkt hebben aan de onderzoeken heel erg
bedanken voor hun deelname. Ook hebben allerlei mensen noodzakelijke hand- en
spandiensten verricht bij de uitvoering van de studies. Mijn naaste collega’s op
het werk – Baudien van ’t Blik, Ineke van Uden, Monique Schalkwijk en Helga
Bosma – wil ik bedanken voor allerlei regelwerk en het inplannen van de nodige
afspraken, maar ook mijn collega’s van MOA/BPO wil ik bedanken, in het bijzonder
Bert de Vries voor zijn adviezen bij SPSS, Adriaan Roeleveld voor de betrokken
gesprekken en kamergenoot Maarten Exel voor de gezelligheid en het aanreiken
van NS data. Voor de ondersteuning bij de verschillende veldstudies wil ik diverse
mensen in willekeurige volgorde bedanken: Eymert van Manen, Willem Boiten,
Toine Schoutens, Michael Sebregts, Jurgen Bal, Peter het Hart, Peter de Jong, Niko
Bakker, Dimphy Geldhof, Robert Jansen, Clara Lieverse en Wim Verheul. Voor het
ontwikkelen van het virtuele station Leiden en de nodige aanpassingen daarin wil
ik Jan Beumer en Pim Greijn van Movares bedanken. Ook Mark Veth, Willem de
Jonge en de rest van het team van Cebra wil ik bedanken voor het online zetten van

270 waiting experience at train stations

de virtuele wereld en het ontwikkelen van nieuwe toepassingen, zoals “streaming”
van muziek en films in de virtuele wereld. Dankzij jullie inzet en aanstekelijke
enthousiasme lukte het steeds om veranderingen op tijd online te hebben voor het
onderzoek, ook al moesten we daarvoor wel eens doorwerken tot het allemaal goed
werkte, zoals tot laat in de nacht op die kerstavond in 2008, waarin de trein maar
niet op tijd wilde komen (ja beste lezer, ook in de virtuele wereld kan een trein te laat
komen…). Ook Koos en Arjan Termorshuizen van Arachnea wil ik bedanken voor het
zorg dragen van de programmering van de online vragenlijsten, het benaderen van
de respondenten en het aanleveren van de databestanden.

Twee reizigers die mij bijzonder hebben geïnspireerd en nu ook bij de aankomst
naast mij staan in de vorm van paranimfen, moet ik speciaal bedanken, Paul
Rooijmans en Maarten Hartveldt. Paul, jij was vanaf het begin direct zo enthousiast
en kreeg zoveel energie van mijn plannen, dat je dit project direct financieel wilde
steunen, vanuit het programma Fens KVS, mits ik andere sponsors zou weten te
betrekken. Dat is gelukt, hartelijk dank voor het vertrouwen, je hulp en de bijpraat-
lunches. Maarten vanaf het eerste moment dat we elkaar spraken was er de bekende
klik en hebben we vaak gediscussieerd over de rol en het effect van beleving, zeker
op het terrein van muziek waar ik ongelofelijk veel van je geleerd heb. Hartelijk dank
daarvoor.

Zonder een goede gids is een dergelijke reis een hachelijke zaak. Ad Pruyn heeft
deze rol uitstekend vervuld. Ad je hebt mij als promotor duidelijk de weg gewezen,
zonder mij de kans te ontnemen zinloze, doch interessante zijpaden te verkennen.
Je 24/7 bereikbaarheid voor hulp en reflectie en constructieve en structurerende
feedback waardeer ik zeer, waardoor het proefschrift een logisch en leesbaar verhaal
is geworden. Mijn tweede gids, Mirjam Galetzka, wil ik hartelijk danken voor alle
tijd en energie die ze gestoken heeft in het wegwijs maken in de academische mores,
het coördineren van de studentenprojecten en het statistisch programma SPSS.
Mirjam ik denk met veel plezier terug aan de sessies in Nijmegen en Deventer, waar
ik erg veel van je leerde en we belangrijke knopen doorhakten. Ook mijn begeleider
binnen NS, Bert Meerstadt, ben ik veel dank verschuldigd voor het houden van de
aansluiting tussen academische wereld en het bedrijfsleven. Bert erg bedankt voor
het lezen van alle tussenresultaten, je waardevolle suggesties, je hulp wanneer ik
vast dreigde te lopen en de prettige doch intensieve gesprekken, waaruit steeds
weer bleek dat in een half uur heel veel besproken kan worden. Ook Diane Ricketts
is als vertaler een waardevolle gids geweest, die voor mij al de Nederlandse teksten
naar keurig Brits Engels heeft omgezet. Diane ik wil je daarnaast bedanken voor je
betrokkenheid, die zich tot op het laatste moment uitte in het minutieus doorlezen
van de tussenstukken en het aanreiken van werkbare suggesties, waardoor de
kwaliteit en leesbaarheid van het hele verhaal sterk is verbeterd.

Dankwoord 271
Het is duidelijk dat gedurende de reis steeds nieuwe mensen instappen en anderen
weer uitstappen. Ook in de laatste fase van de reis stappen weer nieuwe mensen in
die een belangrijke rol spelen bij het bereiken van de bestemming, zoals de leden
van de promotiecommissie. Ik wil jullie hartelijk danken voor de tijdsinvestering en
het voorbereiden van de vragen tijdens mijn verdediging, waardoor het eindpunt van
de reis duidelijk en feestelijk gemarkeerd is.

De broodnodige onthaasting en relativering heb ik steeds kunnen putten uit

afleidende activiteiten, zoals de vakanties met het gezin, carnaval en uitstapjes met
collega’s, de jaarclub, de borrelclub en de buurtvereniging. In het bijzonder wil ik
nog noemen André Emmers, Kees Nederveen en René Leijten, die steeds tijd wisten
te maken voor een ontspannen ‘gesprek’.

Daarnaast wil ik mijn ouders bedanken voor al de goede zorgen in mijn jeugd, waar-
door ik de kans heb gehad mij in alle vrijheid te ontwikkelen naar de persoon die ik
nu ben en daarmee het fundament hebben gelegd om deze reis aan te kunnen.

Last but not least wil ik Iris, Pieter en Hetty hartelijk bedanken voor al hun geduld
en begrip. Ik vind het geweldig hoeveel respect jullie ervoor hadden dat jullie
papa en man weinig tijd had en ‘altijd boven zat’. Iris jou wil ik natuurlijk heel erg
bedanken voor het ontwerpen van de mooie kaft van dit boek en Pieter voor onze
zolder gesprekjes en het diepzinnige doorvragen wat me steeds weer aan het denken
zette. En natuurlijk wil ik jou, Hetty, bedanken voor de tijd en vrijheid die je me de
afgelopen jaren hebt gegeven om me volledig te kunnen concentreren op mijn werk
en promotie activiteiten. Je hebt ons huishouden al die tijd volledig gerund en jezelf
daarmee een aantal jaren weggecijferd. Ik kan niet in woorden uitdrukken hoeveel
bewondering ik voor je heb. Zonder jou was dit proefschrift er nooit gekomen!

Zoals het hoort bij een goed verhaal, komt ook aan deze reis een eind. Ik koester
warme herinneringen aan deze periode, waarbij het proefschrift als tastbaar
aandenken overblijft en naar ik hoop anderen inspireert om ook een dergelijk
avontuur aan te gaan. Van mijn promotor mag dat trouwens in aanzienlijk minder
pagina’s …

272 waiting experience at train stations