491604

research-article2013
JHTXXX10.1177/1096348013491604Journal of Hospitality & Tourism ResearchPike, Bianchi / Destination Brand Equity

DESTINATION BRAND EQUITY FOR

AUSTRALIA: TESTING A MODEL OF
CBBE IN SHORT-HAUL AND LONG-HAUL
MARKETS

Steven Pike
Queensland University of Technology
Constanza Bianchi
Universidad Adolfo Ibáñez and Queensland University of Technology

The study of destination brand performance measurement has only emerged in earnest
as a field in the tourism literature since 2007. The concept of consumer-based brand
equity (CBBE) is gaining favor from services marketing researchers as an alternative
to the traditional “net-present-value of future earnings”’ method of measuring brand
equity. The perceptions-based CBBE model also appears suitable for examining
destination brand performance, where a financial brand equity valuation on a
destination marketing organization’s balance sheet is largely irrelevant. This is the
first study to test and compare the model in both short- and long-haul markets. The
article reports the results of tests of a CBBE model for Australia in a traditional short-
haul market (New Zealand) and an emerging long-haul market (Chile). The data from
both samples indicated destination brand salience, brand image, and brand value are
positively related to purchase intent for Australia in these two disparate markets.

KEYWORDS: destination branding; consumer-based brand equity; destination

loyalty; destination image; Australia; New Zealand

INTRODUCTION

The notion of branding began during the 1700s as a means to identify the
maker of the product. Despite its early roots, the discussion and study of the
concept of branding did not emerge as a central part of the marketing discipline
until well into the 20th century (Bastos & Levy, 2012). Stern (2006) suggested
that the term brand entered marketing discourse in 1922, as an expression of a
trade or proprietary name. The Second World War had a great impact on the
competitive situation in the marketplace, which led to intensive competition and

Authors’ Note: This article was prepared with the assistance of the Services Innovation Research
Program, QUT Business School, Queensland University of Technology.

Journal of Hospitality & Tourism Research, Vol. XX, No. X, Month 2013, 1­–21
DOI: 10.1177/1096348013491604
© 2013 International Council on Hotel, Restaurant and Institutional Education
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proliferation of brands. Since the 1950s, the study of brands and branding grew
gradually, and in the second half of the 20th century the branding concept
expanded in terms of both application and thinking. Gardner and Levy (1955)
pointed out that consumers were confronted with making choices among brands,
often in instances when they could not discern differences among the products.
The first published research related to tourism destination branding did not
appear until the late 1990s (see, e.g., Dosen, Vranesevic, & Prebezac, 1998). A
literature review of the first decade of destination branding publications, from
1998 to 2007 identified 74 publications (see, Pike, 2009). Of these, only four
were concerned with the measurement of brand performance. This is a major
gap in the literature, given the increasing investment in branding initiatives by
destination marketing organizations (DMOs). Traditional financial accounting
means of measuring brand effectiveness, such as the net-present-value of future
earnings on corporate balance sheets, are largely irrelevant for DMOs, with the
possible exception of brand/merchandise licensing revenue. There is a need for
measures of brand performance that are more appropriate for DMOs and their
stakeholders, and in particular indicators that capture effectiveness of past mar-
keting communications as well as pointers to future performance such as con-
sumers’ purchase intent.
Branding emerged as a means to gain differentiation in markets crowded with
competitors offering similar products or services. In the evolution of marketing,
branding explicitly recognizes the competitive requirement to adapt from a sales
orientation to a marketing orientation. A marketing orientation recognizes con-
sumers are spoilt for choice and thus all company decisions should be made with
consumer’s needs in mind. The most common definition of branding, by Aaker
(1991) focuses on the concept of differentiation:

A brand is a distinguishing name and/or symbol (such as a logo, trademark, or

package design) intended to identify the goods or services of either one seller or a
group of sellers, and to differentiate those goods from those of competitors. (p. 7)

However, destination branding is more complex than merely the design of

product names and symbols (see Pike, 2005). Destination branding should (a)
feature DMO marketing communications that consistently reinforce brand iden-
tity elements to differentiate the destination, (b) be based on a small set of deter-
minant attributes that appeal to the needs of the target segment, (c) be supported
and delivered by stakeholders. The aim of destination branding should be to
stimulate intent to visit and revisit, which are indicators of brand loyalty.
In terms of visitation intent, consumers from short-haul destinations might
consider different factors when deciding about a destination preference com-
pared with long-haul travelers which consider mostly airfare costs and travel
time (McKercher, 2008; McKercher, Chan, & Lam, 2008). This implies that
short-haul travelers may visit a preferred destination several times compared
with long-haul visitors. In addition, a few recent studies suggest that short haul

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 Pike, Bianchi / DESTINATION BRAND EQUITY 3

tourists may be a fundamentally different group of people from long haul tour-
ists in terms of income level, sensitivity of demand, and tourism consumer
behavior (Bao & McKercher, 2008; Ho & McKercher, 2012). According to
these studies, short-haul travelers tend to be younger people and more likely
females, with lower income and education, and are more price sensitive com-
pared with long-haul travelers (Bao & McKercher, 2008; Crouch, 1994; Ho &
McKercher, 2012).
Overall, the literature suggests differences between short-haul and long-haul
travelers, yet these studies tend to focus predominantly on demographic and dif-
ferences of tourists using secondary travel data. Little or no emphasis has been
placed on the short and long haul tourist’s perceptions of the elements and fac-
tors of destination brand identity that might lead to destination brand loyalty.
Additionally, to date, little has been published outside the destination image lit-
erature about destination brand performance measures over time (Pike, 2009).
This is essential for destination marketers to reinforce salient brand attributes
that can stimulate on a permanent basis potential tourists to visit and revisit the
destination.
It is proposed in the branding literature that the model of consumer-based
brand equity (CBBE), developed by Aaker (1991, 1996) and Keller (1993,
2003), offers destination marketers a performance instrument with which to
evaluate and measure consumer perceptions of a destination brand. The pro-
posed CBBE model integrates five related dimensions to obtain a measure of
brand equity: brand salience, brand image, brand quality, brand value, and brand
loyalty (Aaker, 1991, 1996; Keller, 1993, 2003). Developing and testing such
measures will offer practical value to DMOs who have been increasing invest-
ment in brand identity development.
Thus, the purpose of this study is to test the suitability of the CBBE model for
benchmarking brand performance of Australia. It was conducted at the time of
the launch of a new brand campaign, and thus provides an opportunity to bench-
mark future performance over time. To test the model we used samples from a
traditional short-haul market (New Zealand) and an emerging long-haul market
(Chile). These two countries were chosen for this study because they are both
located in the southern hemisphere within the Pacific Rim region, and both have
direct flights to Australia, although they are located 9,000 kilometers apart. New
Zealand has traditionally been Australia’s largest single source of visitors. The
country is a 3-hour flight from Australia’s east coast destinations such as Sydney,
Brisbane, and the Gold Coast, and shares a sporting rivalry, and similar language
and culture. Australia is also home to the largest number of New Zealand expatri-
ates. Chile, on the other hand, is more than 16 hours flying time, and the predomi-
nant language is Spanish. Tourism Research Australia (2011) acknowledges that
although visitors from Latin America represent only 1% of total annual arrivals,
Chile is one of the fastest growing. This market has recently emerged as a tourism
market for Australia, with 2009 ushering in a free trade agreement and direct
flights between Sydney and Santiago. The number of Chilean visitors to Australia

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grew 23% for the year 2011 and this market is considered important for Australia
because of its high level of development and growth within the Latin American
region and improved air connectivity (Tourism Research Australia, 2011). Some
aspects of the first stage of the study, which involved only the Chilean sample,
have previously been reported (Pike et al., 2010).

CONSUMER-BASED BRAND EQUITY

Consumer-Based Brand Equity Model Development

There have been relatively few applications testing the CBBE model in rela-
tion to destination branding. Modeling of CBBE in the wider tourism and hospi-
tality literature has included: conferences (Lee & Back, 2008), hotels
(Cobb-Walgren, Beal, & Donthu, 1995; Kayaman & Arasli, 2007; H. Kim, Kim,
& An, 2003; W. G. Kim, Jin-Sun, & Kim, 2008), restaurants (H. Kim & Kim,
2005), wineries (Lockshin & Spawton, 2001), and airlines (C.-F. Chen & Tseng,
2010). The first published journal article related to the measurement of destina-
tion brand equity appears to be that by Kim (2001, cited in S. H. Kim, Han,
Holland, & Byon, 2009). Since then there have been at least eight published
articles: Croatian-based brand equity for Slovenia (Konecnik & Gartner, 2007);
short-break destination brand equity for an emerging destination (Pike 2007);
CBBE for Las Vegas and Atlantic City, in the context of gambling destinations
(Boo, Busser, & Baloglu, 2009); host community brand equity (Pike & Scott,
2009); international visitors to Korea (S. H. Kim et al., 2009); international visi-
tors to Mongolia (C.-F. Chen & Myagmarsuren, 2010); and short-haul interna-
tional travelers to Slovenia (Ruzzier, 2010). This shows that the application and
testing of the CBBE model is in its infancy and needs further work. The CBBE
conceptual model is shown in Figure 1, and features five latent variables: desti-
nation brand loyalty, brand salience, brand image, brand quality and brand value.
These variables are consistent with previous destination studies.

Dependent Variable: Attitudinal Loyalty

There is a compelling argument for using attitudinal loyalty as the dependent

variable in modeling destination brand equity. Destination loyalty is vital for
achieving repeat visitation and positive word of mouth among visitors (Gartner
& Hunt, 1987, X. Li & Petrick, 2008b). Although attracting new customers is
essential, it is more desirable and much less expensive to retain current custom-
ers (Reichheld, Markey, & Hopton, 2000). Research shows that in the short run,
loyal customers are more profitable because they spend more and are less price
sensitive (Reichheld et al., 2000). Loyal customers can also lead to increased
positive word of mouth for the service provider (Jones & Taylor, 2007).
Nevertheless, despite these advantages, few studies attempt to identify the key
determinants of destination brand loyalty for travelers from long-haul markets
(X. Li & Petrick, 2008a).

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 Pike, Bianchi / DESTINATION BRAND EQUITY 5

Figure 1
Proposed Model

Desnaon
brand salience

H. 1

Desnaon
brand H. 2
image A tudinal
desnaon
loyalty

Desnaon H. 3
brand
quality

H. 4

Desnaon
brand
value

Although brand loyalty was first reported in the literature during the early
1900s (Bastos & Levy, 2012; Guest, 1942), only a few studies of destination brand
loyalty are found in the tourism literature before the millennium (Oppermann,
2000). The topic of repeat visitors to destinations has started to attract increased
interest from researchers only in the past decade (Alegre & Cladera, 2006;
J. S. Chen & Gursoy, 2001; Chi & Qu, 1998; Chitty, Ward, & Chua, 2007; X. Li
& Petrick, 2008b; McKercher & Guillet, 2011; Mechinda, Serirat, & Guild, 2009;
Niininen, Szivas, & Riley, 2004; Oppermann, 2000; Yoona & Uysalb, 2005).
These studies assert that the measurement of destination loyalty, especially in a
long-haul travel context, is difficult since the purchase of a tourism product is
often infrequent, or even once in a lifetime, and/or part of a multidestination travel
experience (Martin & Woodside, 2008; Oppermann, 1999). However, following
the conceptual work of Aaker (1991, 1996) and Keller (1993, 2003), the loyalty
construct in CBBE is suitable for application with prospective visitors as well as
previous visitors. Therefore, the aim of this study was to test the appropriateness
of this dependent variable in both long-haul and short-haul markets.
Previous research suggests that the loyalty construct is composed of two dimen-
sions; behavioral loyalty and attitudinal loyalty (Jones & Taylor, 2007; X. Li &

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Petrick, 2008b). Hence, loyalty implies a commitment to the specific brand and
goes beyond repetitive behavior (Jacoby & Kyner, 1973). Behavioral loyalty
refers to the frequency of repeat purchase or relative volume of same brand pur-
chase. Attitudinal loyalty refers to the dispositional commitment or attitude a con-
sumer-traveler has toward a destination, measured by intent to visit and positive
word-of-mouth recommendations. Both items are relevant to prospective visitors
as well as previous visitors. This study uses attitudinal loyalty as the dependent
variable since it is a measure of future travel preference or intent to visit.

Brand Salience

Brand salience is the foundation of the CBBE model (Keller, 2003), with the
aim being to be remembered for the reasons intended rather than just achieve
general awareness per se (Aaker, 1996). Since most consumers will be aware of
a multitude of destinations, we conceptualize destination brand salience as the
strength of awareness of the destination in the mind of an individual when a given
travel situation is considered. Previous studies demonstrate that consumers will
usually only actively consider between two to four brands in their decision set
(Howard, 1963; Howard & Sheth, 1969; Pike, 2006; Thompson & Cooper, 1979;
Woodside & Sherrell, 1977). Brand salience is commonly measured by unaided
awareness or aided brand recall. It is proposed that membership in a consumer’s
decision set for a given travel context, elicited through unaided awareness, repre-
sents a source of competitive advantage. Previous research suggests an indirect
relationship between destination brand salience and destination brand loyalty for
short-haul destinations (Boo et al., 2009). Thus, we propose that destination
brand salience will positively influence destination brand loyalty for short- and
long-haul visitors. Yet we predict that destination brand salience will be stronger
for short-haul travelers because of the geographical proximity:

Hypothesis 1: Destination brand salience will positively influence destination brand

loyalty.

Brand Image

Brand image, in accordance with the associative network memory model

(J. R. Anderson, 1983), is anything linked to a brand in the consumer’s memory
(Aaker, 1991), which consists of nodes and links. A node contains information
about a concept, and is part of a network of links to other nodes. When a given
node concept is recalled, strength of association determines what other nodes
will be activated from memory. A destination can therefore be conceptualized as
a node to which a number of other node concepts are linked. Although destina-
tion image research is well established in the tourism literature, there is no uni-
versally accepted measurement scale index. Following Boo et al. (2009), this
study limits destination image to social and self-image. Using this approach,

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Boo et al. (2009) found a positive relationship between brand image and brand
destination loyalty. This was supported by Chitty et al. (2007), who examined
the antecedents of backpacker loyalty to Australia and found brand image to be
an important predictor. Thus, we propose that destination brand image will posi-
tively influence destination brand loyalty for short and long haul travelers:

Hypothesis 2: Destination brand image will positively influence destination brand

loyalty.

Perceptions of Quality

Brand quality is a key dimension of brand equity for product manufacturers

and service providers (Aaker, 1996; Keller, 2003). Perceived quality is defined
as the “perception of the overall quality or superiority of a product or service
relative to relevant alternatives and with respect to its intended purpose” (Keller,
2003, p. 238). Destination brand quality, therefore, refers to perceptions of qual-
ity of the facilities and nonphysical aspects of the destinations. Previous research
reports that elements of perceived quality, such as destination infrastructure,
affect brand performance (Buhalis, 2000) and have a positive effect on brand
loyalty (Boo et al., 2009). Thus, we propose that destination brand infrastructure
elements of quality will positively influence destination brand loyalty for short-
and long-haul travelers:

Hypothesis 3: Destination brand quality is positively related to destination brand

loyalty.

Perceptions of Value

The perceived value of a service pertains to the benefits customers believe

they receive relative to the costs associated with its consumption (McDougall &
Levesque, 2000). Zeithaml and Bitner (2000) suggest that perceived value is an
overall evaluation of a service’s utility, based on customers’ perceptions of what
is received at what price. Heskett, Sasser, and Schlesinger (1997) argue that high
perceived value is positively associated with satisfaction and loyalty. In a tour-
ism context, Mechinda et al. (2009) examined the antecedents of consumer loy-
alty toward a destination in Thailand and found that destination attitudinal
loyalty was driven mainly by perceived value. This finding was supported by
Boo et al. (2009) and Chitty et al. (2007), who also found a positive relationship
between perceived value and destination loyalty. Thus, we propose that destina-
tion brand value will positively influence destination brand loyalty for short-
and long-haul visitors, yet we predict that destination brand value will have a
stronger effect for short haul travelers:

Hypothesis 4: Destination brand value will positively influence destination brand loyalty.

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METHOD

This section discusses the second stage of the study, which tested the pro-
posed model with a sample of New Zealand residents, to examine CBBE for
Australia in a traditional short-haul market. As indicated, the model was previ-
ously tested in a similar way with a Spanish version of the questionnaire and a
sample of 341 Chilean travelers to examine CBBE for Australia as a long-haul
destination in an emerging market (Pike et al., 2010).
The New Zealand sample consisted of members of a panel from a locally
based marketing research company. Panel members were sent an e-mail invita-
tion to participate in an online survey. As well as the usual benefits that panel
members are offered as an incentive to participate in surveys by the marketing
research firm, an additional $500 travel voucher prize was offered.
No mention of Australia was made on the opening page of the online survey.
Two filter questions were first used to identify: (a) if participants had visited
another country during the previous 5 years and (b) the likelihood of taking an
international holiday during the following 12 months. Next, two open-ended ques-
tions were used to identify unaided destination salience, top of mind awareness
(ToMA) preferred destination, and the other destinations in their decision set.
The next page asked participants to indicate if they had previously visited
Australia and to evaluate the destination on the five dimensions of the CBBE
model using a 7-point scale anchored at 1 = very strongly disagree to 7 = very
strongly agree. Brand salience was measured with five items derived from Boo
et al. (2009) and Konecnik and Gartner (2007). Brand quality was measured
with four items based on Konecnik and Gartner (2007). Brand value was mea-
sured by four items adapted from Boo et al. (2009). Brand image and brand
loyalty were both measured using four items each from Boo et al. (2009),
Konecnik and Gartner (2007), and Chi and Qu (1998).

RESULTS

Data Analysis

The characteristics of the New Zealand and Chilean participants are shown in
Table 1. The New Zealand sample (N = 858) comprised 24% males and 76%
females. Although these characteristics possibly affect the generalizability of the
data, a purposeful sample of residents with international travel experience was
achieved. That is, it is argued that the sample is suitable for assessing the desti-
nation brand equity model given that 764 respondents (89%) had taken a holiday
in another country during the previous 5 years. The mean likelihood of partici-
pants taking a holiday in another country during the following 12 months was
5.8 on a 7-point scale anchored at 1 = definitely not and 7 = definitely. The
majority of participants (84%) were aged between 25 and 64 years.
The Chile sample (N = 845) comprised 76% males and 24% females.
Although the characteristics do not enable the data to be generalized to the wider

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Table 1
Characteristics of Participants

New Zealand (N = 858) Chile (N = 845)

  n Valid (%) n Valid (%)

Gender
 Male 206 24.0 643 76.5
 Female 652 76.0 197 23.5
Age (years)
 18-24 86 10.0 6 0.07
 25-44 339 39.5 514 60.8
 45-64 384 44.8 301 35.6
 65+ 49 5.7 24 3.59
Marital status
 Single 196 22.8 124 14.7
  Married/live in partner 558 65.0 644 76.2
 Divorced/separated/widowed 104 12.1 77 9.1
Number of dependent children
 0 477 55.6 246 29.1
 1-2 299 34.8 329 38.9
 3+ 82 9.6 270 32.0
Household income (US$)
 <25,000 72 8.4 86 10.2
 25,000-50,000 286 33.3 233 27.6
 50,001-99,999 210 24.5 313 37.0
 100,000+ 290 33.8 213 25.2
Education
  High school 300 34.9 3 0.00
 University 243 28.3 450 53.3
 Other 315 36.7 392 46.7

Chilean population, the aim was to achieve a purposeful sample of residents

with recent international travel experience. It is suggested that the sample is suit-
able for destination brand equity model testing, given that 758 participants
(90%) had taken a holiday in another country during the previous 5 years. The
mean likelihood of participants taking a holiday in another country during the
following 12 months was 5.2 on a 7-point scale anchored at 1 = definitely not
and 7 = definitely. The majority of participants (87%) were aged between 25 and
64 years.
Participants’ ToMA-preferred destinations are listed in Table 2. This table
includes the data from the Chilean study as well. Australia was listed as the top
of mind destination by 40% of participants from the New Zealand sample (short
haul). Although it might be expected that Australia would receive a high level of
ToMA elicitation from such a contiguous market, it is important to note that the

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Table 2
Top of Mind Awareness Preferred Destination

Rank New Zealand Sample n % Chile Sample n %

1 Australia 340 39.8 USA 138 16.3

2 United Kingdom 71 8.3 Brazil 114 13.5
3 United States 67 7.8 Mexico 71 8.4
4 Rarotonga 30 3.5 Italy 54 6.4
5 Fiji 28 3.3 Spain 53 6.3
6 Samoa 22 2.6 Argentina 49 5.8
7 Italy 21 2.5 Caribbean 38 4.5
8 Canada 19 2.2 France 27 3.2
9 France 18 2.1 Greece 25 3.0
10 Greece 12 1.4 Australia 24 2.8

majority of participants (60%) identified other preferred destinations. This dif-

fers when looking at the Chilean sample (long haul), where Australia was listed
as the top of mind destination by only 2.8% of participants. The mean number of
destinations in both participants’ decision sets is 3.4, which is consistent with
previous studies reported in the tourism and marketing literature (Woodside &
Sherrell, 1977).
Table 3 presents the destination performance means, standard deviation, and
Cronbach’s alpha scores for each construct for both the New Zealand and Chile
sample. This table also includes the data from the Chilean study for comparative
purposes. The Cronbach alpha coefficients for both samples, which ranged from
.81 to .93, indicate good internal consistency and reliability (Kline, 2005). This
is despite differences in the destination performance means. Brand salience
means for the Chilean sample are lower than the New Zealand sample except for
the item “This destination has a good name and reputation,” which is higher.
Interestingly, the means for brand image and perceived quality were all higher in
the Chilean data, except for the item “Accommodation,” which had a higher
mean in the New Zealand data. Finally, as would be expected, the means for
brand value were lower for the long-haul sample compared with the short-haul
sample.
Item-to-total correlations, standardized Cronbach’s alpha, exploratory factor
analysis (all in SPSS), single measurement models, and confirmatory factor
analysis (using AMOS 16) were used for construct purification. Based on these
analyses, eight measurement indicators from the five constructs were dropped.
The authors tested the proposed model with the refined measures using struc-
tural equation modeling techniques (J. C. Anderson & Gerbing, 1991). Tables 4
and 5 show the correlations, means, and standard deviations for the construct
measures of the New Zealand and Chile samples, respectively. The standardized
regression weights for both the New Zealand and Chile samples are shown in

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Table 3
Destination Performance Means

New Zealand Chile

  M SD α M SD α

Brand salience .82 .81

• This destination has a good name and reputation (Boo, 5.6 1.1 6.1 1.1  
Busser, & Baloglu, 2009)
• The characteristics of this destination come to my mind 5.6 1.2 4.8 1.8  
quickly (Boo et al., 2009; Konecnik & Gartner, 2007)
• This destination is very famous (Boo et al., 2009) 5.3 1.3 4.7 1.6  
• When I am thinking of an international holiday, this 4.8 1.7 2.7 1.6  
destination comes to my mind immediately (Boo et al.,
2009)
• I have seen a lot of advertising promoting Australian 5.6 1.3 3.1 1.6  
holidays (Konecnik & Gartner, 2007)
Perceived quality .93 .93
• High-quality accommodation (Konecnik & Gartner, 2007) 5.8 1.1 5.6 1.3  
• High levels of cleanliness (Konecnik & Gartner, 2007) 5.7 1.1 5.8 1.2  
• High level of personal safety (Konecnik & Gartner, 2007) 5.5 1.1 5.8 1.2  
• High-quality infrastructure (Konecnik & Gartner, 2007) 5.6 1.1 5.9 1.1  
Brand image .92 .92
• This destination fits my personality (Boo et al., 2009) 3.8 1.7 4.0 1.7  
• My friends would think highly of me if I visited this 3.6 1.6 4.3 1.8  
destination (Boo et al., 2009)
• The image of this destination is consistent with my own self 3.7 1.6 4.3 1.7  
image (Boo et al., 2009).
• Visiting this destination reflects who I am (Boo et al., 2009) 3.4 1.7 3.6 1.6  
Brand loyalty .88 .88
• This destination would be my preferred choice for a 4.4 1.7 3.2 1.6  
vacation (Boo et al., 2009)
• I would advise other people to visit this destination (Boo 5.0 1.4 4.0 1.8  
et al., 2009; Chi & Qu 1998; Konecnik & Gartner, 2007)
• I intend visiting this destination in the future (Chi & Qu, 4.6 1.5 4.6 1.9  
1998; Konecnik & Gartner, 2007)
• This destination provides more benefits than other 4.4 1.4 3.5 1.5  
destinations (Konecnik & Gartner, 2007)
Brand value .92 .85
• This destination has reasonable prices 5.2 1.29 3.0 1.3  
• Considering what I would pay for a trip, I will get much 4.9 1.35 3.7 1.5  
more than my money’s worth by visiting this destination
(Boo et al., 2009)
• The costs of visiting this destination are a bargain relative 4.6 1.38 2.8 1.3  
to the benefits I receive (Boo et al., 2009)
• Visiting this destination is good value for money (Boo et al., 4.9 1.30 3.4 1.4  
2009)

Table 6. The estimates are similar in both countries and greater than .6, which
demonstrates convergent validity for the constructs (except for one item of brand
salience which is less than .6 in both countries).

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12   JOURNAL OF HOSPITALITY & TOURISM RESEARCH

Table 4
Means, Standard Deviations, and Correlations: New Zealand Sample

M SD DBS DBQ DBI DBV DBL

DBS 5.54 0.97 1.00 0.27* 0.36* 0.56* 0.56*

DBQ 5.46 1.15 0.27* 1.00 0.10* 0.28* .027*
DBI 3.62 1.47 0.36* 0.10* 1.00 0.44* 0.52*
DBV 4.89 1.19 0.56* 0.28* 0.44* 1.00 0.70*
DBL 5.00 1.31 0.56* 0.27* 0.52* 0.70* 1.00*

Note: DBS = destination brand salience; DBQ = destination brand quality; DBI = destina-
tion brand image; DBV = destination brand value; DBL = destination brand loyalty.
*Correlation is significant at the .01 level (two-tailed).

Table 5
Means, Standard Deviations, and Correlations: Chile Sample

M SD DBS DBQ DBI DBV DBL

DBS 4.32 1.16 1.00 0.45* 0.49* 0.48* 0.66*

DBQ 5.76 1.06 0.45* 1.00 0.38* 0.21* 0.43*
DBI 4.10 1.59 0.49* 0.38* 1.00 0.33* 0.60*
DBV 3.07 1.09 0.48* 0.21* 0.33* 1.00 0.52*
DBL 3.82 1.44 0.66* 0.43* 0.60* 0.52* 1.00

Note: DBS = destination brand salience; DBQ = destination brand quality; DBI = destina-
tion brand image; DBV = destination brand value; DBL = destination brand loyalty.
*Correlation is significant at the .01 level (two-tailed).

To examine the model structure, confirmatory factor analysis, using Amos

16.0, was undertaken. Results from the New Zealand data indicate a good model
fit. The chi-square statistic was significant (χ2/df = 3.99, incremental fit index
[IFI] = .966, Tucker–Lewis index [TLI] = .959, comparative fit index [CFI] =
.966, and root mean square error of approximation [RMSEA] = .059). The
RMSEA was greater than .05, which is considered a reasonably good fit (Bollen,
1989). Furthermore, IFI, TLI, and CFI exceeded the recommended level of .90
(Bollen, 1989). All items are significantly associated with their hypothesized
factors, evidence of convergent validity. In addition, the potential for acquies-
cence bias was minimized by including both positively and negatively worded
items in the questionnaire. Furthermore, a combination of semantic differential
scales and 7-point Likert-type scales were used to reduce common method bias
(Podsakoff, Mackenzie, Lee, & Podsakoff, 2003). Finally, no single factor
accounted for most of the variance in the independent and dependent variables.
This result provides support for the absence of common method bias variance
(Podsakoff & Organ, 1986).

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Table 6
Standardized Regression Weights

New Zealand Chile

Brand salience
  This destination has a good name and reputation .80 .78
  The characteristics of this destination come to my mind .83 .79
  This destination is very famous .75 .79
  I have seen a lot of advertising promoting Australian holidays .57 .56
Perceptions of brand quality
  High-quality accommodation .87 .83
  High levels of cleanliness .94 .92
  High level of personal safety .84 .88
  High-quality infrastructure .95 .93
Brand image
  This destination fits my personality .86 .88
  My friends would think highly of me if I visited this .76 .77
destination
  The image of this destination is consistent with my own .92 .93
self-image
  Visiting Australia would reflect who I am .94 .92
Brand value
  This destination has reasonable prices .78 .77
  Considering what I would pay for a trip, I will get much more .88 .88
than my money’s worth by visiting this destination
  The costs of visiting this destination are a bargain relative to .88 .88
the benefits I receive
  Visiting this destination is good value for money .89 .89
Brand loyalty
  This destination would be my preferred choice for a vacation .77 .76
  I would advise other people to visit this destination .86 .84
  I intend visiting this destination in the future .70 .69

Hypotheses Testing

The results from the hypotheses testing on the New Zealand data indicate that
destination brand salience is significantly and positively related to destination
brand loyalty (β = .34, p < .001). Therefore, the data supports Hypothesis 1. This
is consistent with the Chilean sample (long haul), which found a positive statisti-
cal relationship between destination brand salience and destination brand loyalty
(β = .29, p < .001).
Regarding Hypothesis 2, the data indicate that destination brand quality is not
significantly related to destination brand loyalty (β = .04, p = .60). Therefore,
Hypothesis 2 is not supported in the New Zealand sample. This also matches the
Chilean study, which finds a nonsignificant relationship between destination
brand quality and destination brand loyalty (β = .16, p = .075).

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Furthermore, the results indicate that destination brand image is significantly

and positively related to destination brand loyalty (β = .20, p < .001). Therefore, the
data supports Hypothesis 3 for the New Zealand sample. This is consistent with the
Chilean sample, which also found a positive statistical relationship between desti-
nation brand salience and destination brand loyalty (β = .28, p < .001).
Finally, in reference to Hypothesis 4, the data indicate that destination brand
value is significantly and positively related to destination brand loyalty (β = .56,
p < .001). Therefore, Hypothesis 4 is supported for the New Zealand sample.
This is also consistent with the Chilean sample which also found a positive sta-
tistical relationship between destination brand salience and destination brand
loyalty (β = .23, p < .001).
Overall, three out of four hypotheses were supported by both the New
Zealand (short haul) and Chilean (long haul) data. The final model is shown
in Table 7. It is interesting to note that for Hypothesis 3, the relationship
between destination brand image and destination brand loyalty is stronger for
the Chilean sample than for the New Zealand sample. As predicted, when
looking at destination brand value, the relationship with destination brand
loyalty is much stronger for the New Zealand sample. In fact, destination
brand value is the strongest driver of destination brand loyalty for the New
Zealand data, yet destination brand salience is the strongest driver for the
Chilean data.

DISCUSSION AND CONCLUSION

There has been limited research addressing the drivers and modeling of
destination brand performance. This study contributes to the tourism destina-
tion branding literature by testing a conceptual model of destination brand
performance in two disparate markets. Key constructs from the CBBE model,
championed by Aaker (1991, 1996) and Keller (1993, 2003), were trialed.
The data from both the emerging long-haul market (Chile) and traditional
short-haul market (New Zealand) found brand salience, brand image, and
brand value to be positively related to brand loyalty. In addition, the results of
this study supported our prediction that destination brand salience is higher
and has a stronger effect on destination brand loyalty for short-haul travelers
(New Zealand β = .34), than long-haul travelers (Chile β = .29, p < .001),
mainly due to geographic proximity. The findings also support our prediction
that destination brand value has a stronger effect for short-haul travelers
(New Zealand β = .54) compared with long-haul travelers (Chile β = .23, p <
.001), probably because short-haul travelers tend to be more price sensitive
compared with long-haul travelers (Bao & McKercher, 2008; Crouch, 1994;
Ho & McKercher, 2012).
We argued the case for attitudinal destination loyalty as the dependent vari-
able in the proposed model. This construct measures stated intent to visit and
likelihood of personal recommendations to others. One of the key aims of DMOs

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 Pike, Bianchi / DESTINATION BRAND EQUITY 15

Table 7
Model Goodness-of-Fit and Hypotheses Testing

New Zealand Data (n = 858)

  χ2 df χ2/df RMSEA IFI TLI CFI

Total sample 486.8 142 3.43 .053 .967 .961 .967

**p < .001

Hypotheses Path Directions β t Significance Result  

H1 DBS → DBL .34 6.22 *** Supported  

H2 DBQ → DBL .04 1.57 .598 Not Supported  
H3 DBI → DBL .20 7.53 *** Supported  
H4 DBV → DBL .56 12.72 *** Supported  
Results significant at ***p < .001, **p < .005

Chile Data (n = 341)

  χ2 df χ2/df RMSEA IFI TLI CFI

Total sample 181.4 80 2.27 .061 .964 .946 .964

**p < .001

Hypotheses Path Directions β t Significance Result  

H1 DBS → DBL .29 4.71 *** Supported  

H2 DBQ → DBL .16 2.43 .075 Not Supported  
H3 DBI → DBL .28 5.61 *** Supported  
H4 DBV → DBL .23 3.88 *** Supported  
Results significant at ***p < .001, **p < .005

Note: RMSEA = root mean square error of approximation; IFI = incremental fit index; TLI = Tucker-
Lewis index; CFI = comparative fit index; DBS = destination brand salience; DBQ = destination brand
quality; DBI = destination brand image; DBV = destination brand value; DBL = destination brand
loyalty.

is to stimulate intent to visit and revisit. In this regard, whereas all the constructs
provide performance measures in terms of the effectiveness of past marketing
communications, the intent-to-visit data also provide a future orientation. For
any individual business, strong levels of purchase intent represent a form of
“goodwill” on the balance sheet. For DMOs, intent to visit represents an impor-
tant barometer for future performance.
This is the first study to model and compare a destination’s CBBE in short-haul
and long-haul markets. Most published research in this field has focused on desti-
nation brand initiatives aimed at travelers from geographically close markets
(McKercher, 2008), particularly for Australia (Prosser, 2000), such as China and
Taiwan (e.g., Huang & Gross, 2010; Kao, Patterson, Scott, & Li, 2008; J. W. Li &
Carr, 2004; Pan & Laws, 2003). Attracting visitors from long-haul destinations
entails distinctive challenges; including mitigating higher airfare costs, travel
time, and consumer confidence or risk (McKercher, 2008; McKercher et al.,

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16   JOURNAL OF HOSPITALITY & TOURISM RESEARCH

2008). Long travel distances have an influence on tourism demand due to higher
levels of consumer involvement in planning and expenditure (McKercher &
Lew, 2003). In fact, some studies suggest that many people may be precluded
from long-haul travel because of the longer distances and higher costs
(McKercher, 2008; McKercher et al., 2008). For example, McKercher et al.
(2008) report that relatively few people are willing to travel more than 2,000
kilometers from their home country and as a result, most destinations’ ability to
attract long-haul markets is limited. Indeed it has been suggested that 70% of
international travelers visit only 10 countries, so more than 90 National Tourism
Offices around the world compete for 30% of total international arrivals
(Morgan, Pritchard, & Pride, 2002).
The negative relationship between distance and demand has been termed
distance decay. This is apparent in the results of the brand value scale items,
where the means for the Chile sample were all below the scale midpoint,
whereas the means for the New Zealand sample were all above the scale
midpoint.
On the other hand, Nicolau (2008) contends that the journey itself can lead
to satisfaction and thus, longer distances can sometimes be preferred. This is
consistent with Goh, Law, and Mok (2008), who found that the decision to
traveling to a long-haul destination can also be affected by the consumer’s
perceptions of a destination, its cultural background, and climatic conditions.
As highlighted in Table 2, more than half the New Zealand sample (64%) and
around half the Chilean sample (48%) elicited long-haul destinations as ToMA
preferences for their next international holiday. On a positive note for the tour-
ism industry, Australia was perceived well in both markets across many of the
brand salience and brand quality items. The highest mean (6.1) for any scale
item was Chileans’ respondent’s perception that Australia has a good name
and reputation as a holiday destination. Clearly this image has been formed
organically rather than induced by marketing (see, Gunn, 1988), since the
mean for “I have seen a lot of advertising promoting Australian holidays” was
3.1 for the Chilean sample. This organic image provides a solid base for future
brand building.
The study took place at the commencement of a new brand campaign by
Tourism Australia. The Chilean data were also collected at the same time as the
commencement of direct air services between Sydney and Santiago. The data
therefore provides a performance benchmark, for future studies of Australia’s
performance in this, and the New Zealand market.
Finally, it is important to reflect on the relevance of structural equation mod-
eling for destination marketing practitioners. Although the model we have tested
contributes toward our understanding of the complexities of brand performance
measurement, we do not necessarily advocate this method for tracking perfor-
mance over time. Although structural equation modeling helps identify anteced-
ents of destination loyalty as the dependent variable, we suggest that future
destination brand performance tracking include the following:

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 Pike, Bianchi / DESTINATION BRAND EQUITY 17

1. Unaided awareness questions to elicit ToMA position and decision set composi-
tion. These data identify the competitive set of brands for a travel segment, as
well as provide an indicator of future competitiveness given the higher probabil-
ity of travel to places listed in decision sets.
2. Brand salience, brand image, and brand value scale items should not be mea-
sured for the destination in isolation. Rather, perceptions of the other destinations
in the competitive set are required to provide a relative measure of the brand’s
competitive position in the market.

Limitations and Future Research

Several limitations might have affected the generalizability of the results of

this study. First, this empirical investigation considers only the perceptions of
Chilean and New Zealand consumers with regard to Australia as a holiday
destination. Thus, the analysis was limited to two countries. More research
needs to be undertaken with consumers in other markets of interest to Australia,
such as the Asia-Pacific region. Second, both samples differ in their gender
and educational characteristics; however, we argue that both data sets repre-
sent the typical traveler and holiday decision maker for New Zealand and
Chile. Finally this study only considers attitudinal destination loyalty and not
behavioral loyalty.
Our literature review found scant research on the travel motivations and pref-
erences of Latin American consumers, other than the “purpose of visit” data
published by Tourism Research Australia (e.g., Tourism Research Australia,
2012). Thus, more insights are required into the motivations of long-haul North
and South American as well as European travelers. Replications of this study in
such markets could deliver additional performance indicators for current brand-
ing efforts by Tourism Australia and its stakeholders.

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Submitted September 14, 2012

Accepted April 22, 2013
Refereed Anonymously

Steven Pike, PhD (e-mail: sd.pike@qut.edu.au) is an associate professor in the School of

Advertising, Marketing and Public Relations, QUT Business School at the Queensland
University of Technology, Brisbane, Queensland, Australia. Constanza Bianchi, PhD
(e-mail: constanza.bianchi@uai.cl) is a Professor of International Marketing in the school
of business at Universidad Adolfo Ibáñez, Santiago, Chile, and Adjunct Professor in the
School of Advertising, Marketing and Public Relations, QUT Business School at the
Queensland University of Technology, Brisbane, Queensland, Australia.

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