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Integrated store service quality Integrated

store service
measurement scale in quality

omni-channel retailing
Min Zhang, Yiwei Li, Lin Sun and Farouk Adewale Moustapha 839
Tianjin University, Tianjin, China
Received 4 February 2021
Revised 12 February 2021
Abstract 9 March 2021
25 October 2021
Purpose – Brick-and-mortar store is an essential channel to deliver a seamless shopping experience and meet Accepted 4 January 2022
customer’s dynamic needs in omni-channel retailing. This paper aims to understand customers’ expectations of
the integrated stores and develop a measurement scale to assess in-store service quality in omni-channel
retailing.
Design/methodology/approach – Grounded theory methodology (GTM) is employed to obtain a clear
picture of consumer expectations and preferences regarding the omni-channel brick-and-mortar integrated
stores. Then, an integrated store service quality scale is proposed, refined and validated using a questionnaire
survey and structural equation model (SEM).
Findings – The measurement scale is set to include seven dimensions: in-store environment, in-store
technology, product information consistency, employee assistance, personalization, channel availability and
instant gratification and return. The relationships among these seven dimensions and customer satisfaction
and loyalty are also verified. According to SEM, product information consistency is more important for
customer satisfaction while personalization contributes more to customer loyalty. The results demonstrate that
by analysing the seven dimensions, retailers can better understand customers and further improve service
quality.
Originality/value – This paper proposes a sufficient measurement scale for in-store service quality and fills
the gap in omni-channel retailing by capturing its integration attribute.
Keywords Brick-and-mortar store, Omni-channel, Service quality, Measurement scale
Paper type Research paper

1. Introduction
The booming online channels and ongoing digitalization give rise to omni-channel retailing
(Verhoef et al., 2015), which has become a predominant norm of the retail industry (Zhang
et al., 2020). Meanwhile, the COVID-19 pandemic is accelerating seamless omni-channel retail,
with frictionless business trend permeating many aspects of the consumer journey. Retailers
who provide an integrated shopping experience merging the benefits of brick-and-mortar
stores with the online platform are known as omni-channel retailers (Rigby, 2011). They tend
to integrate activities within and across channels to suit the consumers’ shopping way
(Ailawadi and Farris, 2017). For the retailers, it is crucial to decide whether and to what extent
they may integrate the various channels (Cao and Li, 2018), as integration is the most
important factor affecting consumers’ perception of omni-channel retail service quality
(Zhang et al., 2019). Customers can benefit from online shopping, such as nearly limitless
selection, transparent price structure and product reviews. In the meantime, they also benefit
from brick-and-mortar store engagement, such as face-to-face interactions with the salesman,
available products for testing or trying on and the social experience of shopping as an event
(Rigby, 2011).
The evolution of retail formats is towards reducing friction in the customer journey and
enhancing customer experience, during which brick-and-mortar stores are constantly being
redefined (Gauri et al., 2021). Brick-and-mortar stores have been recognized as an important International Journal of Retail &
Distribution Management
Vol. 50 No. 7, 2022
pp. 839-859
This work was supported by the National Natural Science Foundation of China (grant number 72171166, © Emerald Publishing Limited
0959-0552
71572122). DOI 10.1108/IJRDM-02-2021-0056
IJRDM retailing channel with the majority of retail sales and close customer connections (Alexander
50,7 and Cano, 2020). In-store service is considered as the multichannel integrated service which
customers value the most.
Brick-and-mortar stores in a modern and multifaceted omni-channel environment are
significantly different from traditional stores (Li et al., 2020). Consumers who patronize a
brick-and-mortar store usually have been bombarded with rich information regarding goods
and services from other retailing or advertising channels (Grewal et al., 2017). However,
840 current research in service quality measurement focuses on the separate shopping
encounters of the online store or brick-and-mortar store. For example, Dabholkar et al.
(1996) proposed an instrument for measuring the service quality of the physical store, and
others paid attention to measuring the service quality of online service (Blut, 2016). Their
study may fail to give an appropriate scale for the store service quality without capturing the
integration attributes in omni-channel retailing. To fill this gap, our research aims to answer:
(1) what services do consumers really expect for brick-and-mortar stores under the omni-
channel retailing environment? (2) how will the perceived in-store service quality influence
customer satisfaction and loyalty?
The structure of this paper is as below. First, we review the literature on integrated store
and service quality measurement. Second, we utilize the grounded theory to identify the core
requirements of omni-channel retailing customers in an integrated store. Third, based on the
qualitative outcomes, we further propose a scale through items generating, refinement and
validation process to measure the integrated store service quality. Fourth, we test the
relationships among service quality, customer satisfaction and customer loyalty. Lastly, we
summarize this paper and give theoretical and managerial implications.

2. Literature review
2.1 Integrated store in omni-channel retailing
The experience value created by brick-and-mortar stores for consumers has irreplaceable
advantages, but the development of interactive technology in online channels brought a great
shock on traditional retail settings (Ayotunde et al., 2021). In response to the fierce
competition and the change of consumer demands, traditional brick-and-mortar stores seek
to integrate with online and mobile channels and transform into integrated stores in omni-
channel retailing. The brick-and-mortar store can link all sales channels and provide an
integrated shopping experience (Piotrowicz and Cuthbertson, 2014), which further provides
interactive contact points to create and complete services, enhancing consumers’ perception
of service quality (Pantano and Viassone, 2015). The integrated store in omni-channel
retailing provides a place where different channels interconnect, and functions of
differentiated channels are integrated to perform service outputs, enabling consumers to
trigger omni-channel interactions (Zhang et al., 2019).
The advanced technology used in brick-and-mortar stores changes the traditional store
atmosphere in the domain of omni-channel retailing (Park et al., 2021). Advanced technology
deployment provides brick-and-mortar retailers with effective means to add value to the
consumer experience and improve service quality (Ayotunde et al., 2021; Grewal et al., 2020).
In the integrated store, customers connect with omni-channel retailers through several
channels, e.g. Internet, mobile device and brick-and-mortar stores within the same point of
sale (Paul et al., 2019). The quality of the channel integration affects customer engagement
which is related to repurchase intention (Lee et al., 2019). Thus, integrated stores win a
competitive edge by providing the opportunities of having synergies across channels. Some
studies also discussed the significance of integrated experiences in brick-and-mortar stores.
For example, Poncin and Mimoun (2014) investigated how to integrate new technologies into
brick-and-mortar stores and the impact on positive affective reactions. Bell et al. (2017) found
that showrooms in omni-channel retailing can attract customers and generate spillover Integrated
effects to the other channels, like increasing online shopping intention related to product and store service
financial risk (Johnson and Ramirez, 2020). Through mitigating consumer fit uncertainty,
physical showrooms provide shoppers with a complete and satisfactory experience (Li et al.,
quality
2020). To sum up, consumers’ perceived service quality in the integrated store is of vital
importance in shaping omni-channel consumption experience. However, current researches
rarely focus on service quality measurement in such integrated store.
841
2.2 Service quality measurement
A number of studies provided service quality measurement scales of brick-and-mortar stores
in both traditional retailing and online retailing. On the basis of the classical SERVQUAL
model established by Parasuraman et al. (1988), an RSQS measuring instrument offering mix
of services and goods was developed (Dabholkar et al., 1996). For the online retailing
environment, some e-service quality measurement scales have been empirically developed to
highlight the interaction between customers and websites. For instance, Kim and Stoel (2004)
proposed a six-dimension quality measurement scale for retail websites. Parasuraman et al.
(2005) provided the E-S-QUAL scale and E-RecS-QUAL scale. Collier and Bienstock (2006)
constructed a measurement for online retailing service quality. Blut (2016) studied a
hierarchical scale and Theodosiou et al. (2019) developed the e-SQ scale. With the
development of online platforms and new digital channels, retailers now provide more than
one retailing channel to offer competitive service. Sousa and Voss (2006) conceptualized
service quality for multi-channel retailing. Seck and Philippe (2013) empirically identified the
quality factors which can influence the overall customer satisfaction in multichannel service
distribution. Huang et al. (2015) proposed and empirically tested a multidimensional M-S-
QUAL scale to evaluate the mobile shopping experience for virtual and physical products.
Acquila-Natale and Iglesias-Pradas (2020) evaluated perceived quality in multi-channel
contexts. Patten et al. (2020) examined service quality in multichannel retailing of fashion by
evaluating physical service quality and electronic service quality.
Besides, technology development has closely embraced human and technology
interaction into service delivery systems known as the hybrid service system. Nasr et al.
(2012) explored the consumer value chain framework through various purchase phases in
hybrid contexts and finally came up with 18 dimensions to assessing service quality in the
hybrid delivery system. Ganguli and Roy (2013) evaluated service quality within hybrid
service settings.
As consumers are more inclined to look and experience the products they are buying, the
retailer’s brick-and-mortar store, in conjunction with its other channels, is an important part
of meeting customers’ multidimensional and dynamic needs of omni-channel shopping.
Measuring and improving the in-store service quality is crucial to deliver outstanding service
for customers. However, the literature reviewed above provides us with a better
understanding of service quality measurement in traditional stores and online retailing,
respectively. They seem to leave a research gap regarding the integrated characteristics of
retail stores. Furthermore, Zhang et al. (2019) developed the customer-perceived service
quality scale in the omni-channel retail context, but its global perspective failed to provide
specific guidance for service quality improvement of integrated stores. Thus, it is necessary
to propose a measurement scale of integrated store service quality in omni-channel retailing
environment.

3. Study 1-Grounded theory deployment

Grounded theory is a methodology to discover a theory through a qualitative data analysis
process (Cao and Li, 2015). It has been widely employed in several research fields such as
IJRDM sociology, business management and so on (Keaveney, 1995). The three-step data analysis
50,7 process proposed by Corbin and Strauss (1990) is one of the most popular approaches that
will be adopted in our study. In detail, open coding is the first step and is used to label data line
by line. Then axial coding is employed to determine the relationship between categories.
Finally, selective coding finds out one or more core categories to conceptualize the
phenomena.
842
3.1 Data collection
Data were collected in two ways. First, we search such data from survey reports of worldwide
famous consulting companies such as McKinsey, annual self-report of well-known retailing
chains, magazine insights, journal papers and books (see Table 1). At last, we have a total of
48 reports. Then, we extract the related sentences that illustrate customer expectations for an
omni-channel retailing store. The second part includes the in-depth interviews with six
employees in the integrated stores and six customers having rich omni-channel shopping
experiences. Employees are asked some questions such as “how do you understand the
customer’s shopping journey?” and “please describe your perception of interaction with
customers during shopping journey”. Customers are asked some questions such as “how do
you get product information before coming to the store?”, “what kind of in-store services are
hopefully provided by the retailer?” and “what services should the retailer improve in-store
shopping activities?”.

3.2 Findings
Once the data is collected, grounded theory analysis is deployed by the basic steps including
open coding and axial coding as shown in Table 2. Finally, seven categories are identified as
in-store environment, in-store technology, product information consistency, employee
assistance, personalization, channel availability, instant gratification and return
respectively. Next, we will discuss these seven categories in detail.
3.2.1 In-store environment. Store atmosphere or physical attractiveness of the store has an
impact on affective and sensory store experiences and satisfaction (Bhatt et al., 2020). Prior
research identified five dimensions for measuring service quality in which tangible (physical
facilities) is an important factor of service quality (Parasuraman et al., 1988). Physical
environment encounters play an important role in omni-channel experiences, and the
diversity, aesthetics and comfort of the physical environment would have a positive impact
on consumers’ behavioural intentions (Ameen et al., 2021). Once omni-channel shoppers
arrive at a brick-and-mortar store, they are in contact with the retailer’s environment, and
their first impression could influence the customer purchase decision. Customers seek
physical stimulation from the in-store environment, specifically, from store design, visual
merchandising and haptics (Patten et al., 2020). The perceived store environment is also
positively associated with customers’ pleasure, arousal and shopping enjoyment (Hashmi
et al., 2020). From our grounded theory analysis, the finding that “customers are attracted by
the store environment” indicates that customers are more satisfied with the store if retailers
could provide an attractive and relaxing shopping environment.
3.2.2 In-store technology. In-store technology is mainly about digital terminals and tools
which have been implemented in brick-and-mortar stores to break the barriers between
physical and online stores for providing a frictionless shopping experience. In-store
technology is reshaping retailing (Shankar et al., 2020). Technology infused in stores aims to
increase customer in-store shopping experiences, especially that evoke high levels of
convenience and social presence would elicit higher levels of imagery, involvement and
elaboration (Grewal et al., 2020). The presence of technology also contributes to retail
environment design in optimizing customer experience (Alexander and Cano, 2020).
Report
Integrated
categories Title Year Source Links store service
quality
Survey On solid ground: brick and 2014 A.T. Kearney https://www.kearney.com/
mortar is the foundation of documents/20152/924670/
omni-channel retailing OnþSolidþGround.pdf/
1958eca8-df9f-da6e-a02d-
82f2039bbd63? 843
t51512665293410
The future of retail: How to 2014 McKinsey and https://www.mckinsey.com/
make your bricks with click Company business-functions/marketing-
and-sales/our-insights/the-
future-of-retail-how-to-make-
your-bricks-click
Building omni-channel 2017 McKinsey and https://www.mckinsey.com/
excellence Company industries/consumer-packaged-
goods/our-insights/building-
omnichannel-excellence#
Omni-channel consumer 2019 Accenture https://www.accenture.com/us-
experience boosts growth en/case-studies/consumer-goods-
services/omnichannel-consumer-
experience
Scaling the Store of the 2020 Boston https://www.bcg.com/zh-cn/
Future Consulting Group publications/2020/scaling-store-
of-future.aspx
Self-report Connected retail: How the 2013 EE Limited https://ee.co.uk/content/dam/
connected consumer is everything-everywhere/
reinventing retail documents/Connected-Retail.pdf
Walmart Inc. 2020 Annual 2020 Walmart Inc. https://s2.q4cdn.com/056532643/
Report files/doc_financials/2020/ar/
Walmart_2020_Annual_Report.
pdf
Insight Macy’s invests in new omni- 2014 Retail Touch http://www.retailtouchpoints.
channel strategies Points com/features/news-briefs/macy-
s-invests-in-new-omnichannel-
strategies
Lagging In-Store 2017 Retail Touch https://retailtouchpoints.com/
Personalization Cost Points topics/customer-experience/
Retailers $150 Billion In 2016 lagging-in-store-personalization-
cost-retailers-150-billion-in-2016
Consumers want “omni- 2018 Retail World https://retailworldmagazine.com.
channel” shopping au/consumers-want-
experience omnichannel-shopping-
experience/
Just How Mature Do You 2020 European https://www.esmmagazine.com/
Think Your Omni-channel Supermarket retail/just-mature-think-
Offering Really Is? Magazine omnichannel-offering-really-
92687
What’s in store for 2020 Accenture https://www.accenture.com/us-
shopping? en/blogs/business-functions-
blog/whats-in-store-for-shopping
Journal Competing in the age of 2013 MIT Sloan http://sloanreview.mit.edu/
paper and Omni-channel retailing Management article/competing-in-the-age-of-
book Review omnichannel-retailing/ Table 1.
Part source of surveys
(continued ) and reports
IJRDM Report
50,7 categories Title Year Source Links

Flatlined: Combatting the 2019 Business https://www.sciencedirect.com/

death of retail stores Horizons science/article/pii/
S0007681318301411
Operations in an Omni- 2019 Springer https://link.springer.com/
844 channel World chapter/10.1007/978-3-030-
20119-7_1
Futurising the Physical 2019 Springer https://link.springer.com/
Store in the Omni-channel chapter/10.1007/978-3-319-
Retail Environment 98273-1_9
Omni-channel management 2020 International https://www.sciencedirect.com/
in the new retailing era: a Journal of science/article/pii/
systematic review and Production S0925527320301195
future research agenda Economics
Disentangling the impact of 2020 MIS Quarterly https://www.misq.org/
omni-channel integration on disentangling-the-impact-of-
consumer behaviour in omnichannel-integratoin-on-
integrated sales channels consumer-behavior-in-
Table 1. integrated-sales-channels.html

For example, emerging AR and VR technologies help create immersive, vivid and interactive
shopping experiences, while AI provides intelligent service delivery solutions (Caboni and
Hagberg, 2019; Cai and Lo, 2020). Seamlessly inserting these technologies into experiential
contexts is the key factor for the brick-and-mortar store. With the advancements of
technology, retailers may offer more personalized and detailed shopping recommendations
and provide a more comprehensive product guide to their customers. Technology
empowerment plays a decisive role in improving consumers’ perceived in-store service
quality.
3.2.3 Product information consistency. In the omni-channel retailing context, customers
usually use all channels simultaneously as they search, buy and get support. In the shopping
process of interacting with multiple touchpoints, retailers need to consider the channel
holistically and provide a unified shopping experience for them (Savastano et al., 2019).
Customers can easily access countless online information for products inside a brick-and-
mortar store. As they travel interchangeably among channels, consistent, accurate and
timely product information can instil trust and brand identity and reduce customer loss due
to free-riding behaviour. Thus, the consistency of product information across channels is
very critical to achieve long-term customer loyalty.
3.2.4 Employee assistance. The omni-channel retailing business model will create very
knowledgeable consumers. For omni-channel shoppers, they head to the brick-and-mortar
store with online product information but the uncertainty of products. This means that the
store employees should be increasingly knowledgeable about the merchandise and online/
offline purchase procedures. Service excellence provided by store employees would affect
customers’ perceived value of transactions and improve service quality (Ameen et al., 2021;
Ertekin et al., 2020). The help and recommendation from store employees can be an important
propeller of both information confirmation and alternative product assessment of the buying
decision, and then decrease the perceived purchase uncertainty for customers (Conchar et al.,
2004). Sometimes, we might observe some loyal consumers who request more product
information from the salesman to confirm what he has obtained online before coming to the
store. By providing more accurate product details, the employee increases customer
knowledge and patronage intention, thereby the customer feels satisfied with the service.
Quotations Open coding Axial coding
Integrated
store service
“Transporting digital world into stores” In-store digitalization In-store technology quality
“Able to browse product ranges and order items Browsing through digital
through digital terminal while shopping in store” terminal in-store
“Touch screens become key components to the Order via digital terminal
in-store experience (kiosk and digital signage)” Important digital terminals in-
store 845
“Use smartphone while shopping in store to Learning more about product Product information
scan/tap to learn more about the product” Up to date product consistency
“Provide shoppers up-to-date product information and discount
information and coupons discounts” Product information
“Online and offline product information are consistency both online and
consistent” offline
“Customers check affordable price on a mobile Affordable price Price (Product
while in a store” Consistency of product price information consistency)
“Product price is consistent online and offline” (online and offline)
“Scan the bar code on the smartphone to verify
the price”
“Store provides in-store instant gratification, Providing instant Instant gratification
convenience” gratification
“Customer can buy online, but pick up in the Buying online and picking up
store” in-store
“Integrated store offers same day delivery” Same day delivery
“Able to return product to the nearest store” Returning product in-store Instant return
“Customer can buy online and return the item to Able to buy online and return
the store” in store
“Use physical and online stores during the Using meantime both online Channel availability
shopping journey” and offline
“Easy online access while shopping in store” Easy online access when in
“Stores advertise their websites at their local store
store (vice-versa)” In-store website
advertisement
“Retailers give personalized offer while entering Giving personalized offer in- Personalization
the store” store
“Customers receive special offers on their phone Offering special offers
while enter the store” Offering ads based on
“Store offers ads takes into account consumer’s consumer’s purchase history
previous purchase history”
“Employee assistance while shopping in store” Employee assistance Employee assistance
“More help from store employees when equipped More helpful when equipped
with tablets” with digital terminal
“Customers have employees assistance about Employee assistance about
the usage of website while shopping in store” online usage
“Customers are attracted by the store Attracting store environment In-store environment
environment” Providing a new store
“Store provides an environment that supports environment Table 2.
product discovery in a delightful, fun and Examples of the coding
relaxing way procedure

3.2.5 Personalization. Nowadays retailers are not only selling products but also keep in touch
with the customers to understand what they really need. Undoubtedly, modern omni-channel
consumers enjoy a personalized shopping experience, such as tailored offers that match their
buying habits. Personalization is an essential part of the shopping experience and has a
positive relationship with the cognitive and affective components of the shopping experience
IJRDM (Tyrvinen et al., 2020). Personalized incentives, including personalized consumer information,
50,7 services and rewards, are positively related to customers’ situational participation in omni-
channel retailing, thus creating usability and hedonic experiences (Hsia et al., 2020). Some
stores are using data-mining techniques and apps to assist their employees to accomplish
these kinds of activities for their customers. The technology-assisted personalization of
customers’ shopping experience has a positive effect on customer behaviour intention and
service quality evaluation (Ameen et al., 2021).
846 3.2.6 Channel availability. In omni-channel retailing, the natural boundaries between
channels become blurred and could be interchanged and used seamlessly in the whole
customer journey (Verhoef et al., 2015). The integration of websites and brick-and-mortar
stores has been considered as consumer engagement in cross-channel shopping. Omni-
channel consumers cross channels inherently during a single shopping experience, often
back and forth without even thinking they have done so. They do expect a unique shopping
experience by operating all channels together and require a consistent experience from a
retailer regardless of channels. The retailer embraces new technologies and channels to
provide seamless interactions between it and its customers. Each interaction is a part of the
overall customer experience with a retailer. Consistent experience may create trust in the
retailer.
3.2.7 Instant gratification and return. This dimension is subdivided into two types of
services: instant gratification (also known as Buy Online and Pick up in-Store “BOPS”) and
instant return (also known as Buy Online and Return in-Store “BORS”). Consumers can view
and pay online, then pick up goods at a brick-and-mortar store to have the tactile experience
of seeing and touching products and forgo delivery wait times. Many companies such as
Amazon, an absolute e-commerce retailer, are opening brick-and-mortar stores in some major
cities to fulfil the immediate gratification of omni-channel consumers. Although we hope that
the omni-channel purchase process is frictionless, it also can lead to the return for several
reasons, such as wrong item, wrong size or finding a defect. Omni-channel consumer coming
back to a brick-and-mortar store prefers the quick response and support from the retailer
concerning his/her return or exchange across any touchpoint as he/she likes (de Borba
et al., 2020).

4. Study 2-Measurement scale establishment

In study 1, we identify the seven key dimensions of the integrated brick-and-mortar service
for omni-channel consumers based on the grounded theory. However, can these dimensions
truly represent the brick-and-mortar store service quality? Will they affect customer
satisfaction and customer loyalty? Next, we will conduct a questionnaire survey to answer
these questions with the use of the measurement scale originating from the qualitative
analysis findings and prior scales.

4.1 Service quality scale development

4.1.1 Items generation. Based on the grounded theory findings, the integrated store service
expected by omni-channel consumers can be summarized into seven dimensions. There are
49 items in our questionnaire, wherein these seven dimensions contain 43 items of the
integrated store service quality scale from the qualitative analysis and prior retailing service
quality scale, and 6 items for measuring customer satisfaction and loyalty (Caruana, 2002;
Zeithaml et al., 1996). Because our target survey respondents are Chinese, we follow the back-
to-back translation procedure (Yang et al., 2013). Then, we evaluate this scale with two senior
managers in famous retailing companies and four omni-channel consumers to eliminate
redundant items and rephrase items to improve clarity. The revised scale is a 7-point scale
varying from 1 (strongly disagree) to 7 (strongly agree) and it includes 40 items for integrated Integrated
store service quality and 6 items for customer satisfaction and loyalty. store service
4.1.2 Data collection and sample profile. In order to ensure that participants have a real
consumption experience of the integrated store in omni-channel retailing, we randomly
quality
sampled consumers at the site of integrated stores. The survey is mainly conducted face-to-
face with a pencil-and-paper questionnaire in three omni-channel retailers’ stores in China.
The participants are first asked if they have used both channels (online and offline) of the
same retailer during a shopping process to further screen participants whose consumer 847
experience took place in an omni-channel context. Participants who have used these channels
are invited to fill out our questionnaire and can get a small gift as an incentive at the end. At
last, 250 questionnaires are collected and 27 invalid questionnaires are excluded because of
missing item scores or being rated as the same scores. Finally, 223 valid questionnaires are
obtained. 61.9% of the participants were males. Young consumers aged 25 or less made up
the highest percentage of participants at 60%. Participants also varied in education and
occupation. The detailed sample profile is displayed in Table 3.
4.1.3 Exploratory factor analysis (EFA). To eliminate non-significant scale items and
identify the number of factors, we first conduct exploratory factor analysis with 40 initial
items scale for integrated store service quality. We use SPSS 22 to run principal components
analysis with varimax rotation. Non-significant items are deleted according to the following
criteria: (1) loading value is less than 0.500, (2) cross-loading value is over 0.500 and (3) item-to-
total correlation is smaller than 0.400 in reliability analysis (Hair et al., 2010). Consequently, 11
items are dropped and 29 items are left on our scale. Seven factors are extracted clearly which
are consistent with the grounded theory findings. The total variance explained by the seven
factors is 67.817%. According to the grounded theory analysis, the seven factors can be
labelled as: in-store environment, in-store technology, product information consistency,
employee assistance, personalization, channel availability, instant gratification and return.
Finally, all the Cronbach’s α values vary from 0.733 to 0.874, which shows good internal
consistency among items (Hair et al., 2010). EFA results are shown in Table 4.

Characteristic Frequency Percent (%)

Gender
Female 85 38.1
Male 138 61.9
Age
25 years or less 134 60
26–35 years 82 36.8
36–45 years 7 3.2
46 years or above / /
Level of education
High School or below 10 4.5
Junior college 40 17.9
Bachelor degree 132 59.2
Master degree or above 41 18.4
Occupation
Student 87 39.0
Enterprise employee 79 35.4 Table 3.
Institution staff 36 16.1 Sample
Else 21 9.5 profile (n 5 223)
IJRDM EFA CFA
50,7 EFA Item-to-total
Factors/Items Cronbach’s α loadings correlation Loadings p-value

In-store environment 0.874

IE1 0.583 0.690
IE2 0.766 0.699
848 IE31 0.786 0.706 0.698 0.000
IE41 0.688 0.644 0.668 0.000
1
IE5 0.635 0.652 0.789 0.000
IE61 0.639 0.676 0.761 0.000
In-store technology 0.866
IT11 0.660 0.674 0.811 0.000
IT21 0.767 0.753 0.853 0.000
IT31 0.778 0.756 0.828 0.000
IT41 0.719 0.618 0.615 0.000
IT5 0.766 0.700
IT6 0.613 0.503
Product information 0.862
consistency
PIC11 0.777 0.704 0.783 0.000
PIC21 0.828 0.790 0.887 0.000
1
PIC3 0.801 0.725 0.808 0.000
Employee assistance 0.799
EA11 0.637 0.574 0.706 0.000
EA21 0.788 0.756 0.874 0.000
1
EA3 0.741 0.608 0.724 0.000
Personalization 0.763
P11 0.739 0.577 0.695 0.000
P21 0.756 0.648 0.774 0.000
1
P3 0.616 0.562 0.700 0.000
Channel Availability 0.848
CA11 0.684 0.671 0.754 0.000
CA21 0.640 0.703 0.833 0.000
CA3 0.695 0.589
CA41 0.695 0.696 0.739 0.000
CA51 0.740 0.628 0.665 0.000
Instant Gratification and 0.733
return
Table 4.
Results of exploratory IGR11 0.717 0.508 0.643 0.000
factor analysis and IGR21 0.735 0.653 0.806 0.000
confirmatory factor IGR31 0.603 0.523 0.666 0.000
analysis Note(s): 1 Items in bold compose the final scale. The detailed items are shown in Appendix

4.1.4 Confirmatory factor analysis (CFA). A repetition of confirmatory factor analysis is

conducted to demonstrate the factor structure of our scale with the use of AMOS 22.0. We
further delete five items step by step according to the modification indices (MIs) in output and
item loading lower than 0.600 (Chin, 1998). Finally, 24 items are retained on the scale. The item
loadings are shown in Table 4, which range from 0.615 to 0.887. Our model shows a good
model fit with χ 2/df, goodness of fit index (GFI), adjusted goodness of fit index (AGFI),
comparative fit index (CFI) and root mean square error of approximation (RMSEA) values of
1.541, 0.885, 0.85, 0.951 and 0.049, respectively. Thus, according to the results of EFA and
CFA, a seven-dimension scale with 24 items for integrated store service quality measurement
is obtained till now, which is represented in Appendix. We will discuss these seven
dimensions next.
4.2 Service quality scale validation Integrated
4.2.1 Reliability and construct validity. Based on the 227 valid questionnaire results, we can store service
work out the Cronbach’s α coefficients varying from 0.733 to 0.862 and composite reliability
(CR) changing from 0.750 to 0.866. The detailed values are provided in Table 5. Because the
quality
above values are larger than the recommended threshold of 0.700, the reliability of our scale is
acceptable (Hair et al., 2010).
Then we will conduct the convergent and discriminant validity to verify the construct
validity of this seven-dimension scale. It can be seen that all the factor loadings are significant 849
(p < 0.001) and the average variance extracted (AVE) values meet the recommended 0.500
(Fornell and Larcker, 1981). Thus, the convergent validity is acceptable. Then, the square
roots of AVEs exceed pairwise correlations between the seven dimensions which are
represented in Table 6. Therefore, the discriminant validity is also confirmed according to
Fornell and Larcker (1981). In sum, our integrated store service quality scale has good
reliability and construct validity.
4.2.2 Nomological validity. Prior studies reveal that service quality impacts customer
satisfaction and loyalty positively in traditional and electronic services, respectively.
Therefore, to examine the nomological validity of the integrated store service quality scale,
we test the relationships between the overall integrated store service quality and customer
satisfaction and loyalty by employing the structural equation model (SEM) using AMOS 22.0.
In the questionnaire survey we conducted, items measuring these two variables have already
been involved. The detailed items are illustrated in Appendix. In this study, it has been
suggested that the overall service quality has positive effects on customer satisfaction and
loyalty. Furthermore, we suppose that customer satisfaction is the mediator of overall service
quality and customer loyalty. Because of the early stage of omni-channel retailing and
integrated store service, we use item parcels (using the mean of each dimension) as indicators
of integrated store service quality to carry out the model (Hau and Marsh, 2004).

Reliability Convergent validity

Dimension Cronbach’s α CR AVE

In-store environment 0.818 0.820 0.534

In-store technology 0.858 0.862 0.613
Product information consistency 0.862 0.866 0.684
Employee assistance 0.799 0.814 0.595
Personalization 0.763 0.767 0.524 Table 5.
Channel availability 0.835 0.836 0.563 Reliability and
Instant gratification and return 0.733 0.750 0.502 convergent validity

AVE IE EA P IGR CA PIC IT

1
In-store environment 0.534 0.731
Employee assistance 0.595 0.590 0.7711
Personalization 0.524 0.666 0.603 0.7241
Instant gratification and return 0.502 0.607 0.516 0.593 0.7091
Channel availability 0.563 0.498 0.641 0.583 0.609 0.7501
Product information 0.684 0.626 0.499 0.484 0.416 0.504 0.8271
consistency
In-store technology 0.613 0.562 0.482 0.567 0.495 0.616 0.472 0.7831 Table 6.
Note(s): 1 Square root of AVEs Discriminant validity
IJRDM Corresponding results of SEM are represented in Figure 1. The effect of integrated store
50,7 service quality on customer satisfaction is positively significant. We further evaluate the
relationships between integrated store service quality and customer loyalty, as well as the
mediating factor of customer satisfaction. Following the approach described by MacKinnon
(2008), the mediated impact is decomposed into total effect, indirect effect and direct effect
shown in Table 7. From Table 7 and Figure 1, it is obvious that the total effect between
integrated store service quality and customer loyalty is significant (z-value of estimate >1.96,
850 p-values of 95% CI < 0.05), thus providing support for the effect of integrated store service
quality on customer loyalty. The results also indicate that customer satisfaction is the
significant mediator of integrated store service quality and loyalty (indirect effect has a
z-value of estimate >1.96 and p-values of 95% CI < 0.05). However, the relationship between
service quality and loyalty becomes non-significant when the significant effect of satisfaction
is included (direct effect has a z-value of estimate <1.96 and p-values of 95% CI > 0.05),
indicating indirect-only (full) mediation. These results confirm the nomological validity of our
service quality measurement scale.
4.2.3 Relative importance of each dimension. To clearly understand the relative importance
of each dimension, two multiple regression analyses are used. Orthogonal factor-score
measures of seven dimensions are calculated to act as independent variables, because each
factor-score is made up of all 24 items and represents its dimension better than its mean score.
The regression results are shown in Table 8. All dimensions of integrated store service
quality significantly contribute to both customer satisfaction and loyalty. Specifically, in-
store environment is the most crucial dimension influencing customer satisfaction and
loyalty. And product information consistency contributes a lot to customer satisfaction, while
personalization contributes more to customer loyalty.

5. General discussion
We develop a seven-dimension measurement scale to assess in-store service quality in omni-
channel retailing, including in-store environment, in-store technology, product information

In-store environment
Sat1

In-store technology
Consumer
Sat2
satisfaction
Product information
consistency 0
Sat3
Integrated store
Employee assistance 0.794***
service quality
Loy1
0
Personalization
Customer
Loy2
loyalty
Channel availability

Loy3
Instant gratification
and return

Figure 1. Note(s): *p < 0.05, **p < 0.01, ***p < 0.001 (two-tailed)
SEM results for Model fit statistics: Chi-square/df = 2.857, GFI = 0.890, AGFI = 0.838, CFI = 0.937,
nomological validity
RMSEA = 0.091
 Bias-corrected 95% Percentile 95%
Integrated
confidence interval (CI) confidence interval (CI) store service
Variables Estimates SE z-value Lower Upper p-value Lower Upper p-value quality
Total Effects
Service 0.865 0.085 10.176 0.699 1.031 0.001 0.698 1.030 0.001
quality → Customer
loyalty 851
Indirect Effect
Service 0.700 0.146 4.795 0.468 1.074 0.000 0.433 1.001 0.001
quality → Customer
loyalty
Direct Effects
Service 0.166 0.164 1.012 0.164 0.497 0.259 0.164 0.497 0.259 Table 7.
quality → Customer Mediated effects in the
loyalty nomological model

Dependent variables
Independent variables Customer satisfaction Customer loyalty

In-store environment 0.560*** 0.479***

In-store technology 0.208*** 0.236***
Product information consistency 0.395*** 0.304***
Employee assistance 0.208*** 0.172***
Personalization 0.130** 0.324***
Table 8.
Channel availability 0.209*** 0.104* Regression analyses of
Instant gratification and return 0.262*** 0.210*** service quality,
Adjusted R2 0.674 0.553 customer satisfaction
Note(s): *p < 0.05, **p < 0.01, ***p < 0.001 (two-tailed) and customer loyalty

consistency, employee assistance, personalization, channel availability, and instant gratification

and return. All these dimensions have a positive effect on customer satisfaction and customer
loyalty. According to the results, product information consistency has a greater impact on
customer satisfaction while personalization is more about customer loyalty.

5.1 Theoretical implications

First, we focus on the consumer-perceived service quality of the integrated store in omni-
channel retailing. Brick-and-mortar stores hold strong appeal to omni-shoppers (Zhang et al.,
2019). Particularly, brick-and-mortar stores play a key role in building brand loyalty. Many
pure online companies are opening brick-and-mortar stores to provide the tactile experience
of touching and trying products before their customers decide to purchase, as well as the
convenience of returning products. Thus, having a brick-and-mortar store is more important
than ever for omni-channel retailers. However, the theoretical research lacks attention to
brick-and-mortar stores in omni-channel context, that is, the integrated store in omni-channel
retailing. As the main place of channel integration, the integrated store occupies an important
position in the omni-channel retail system because of its experience value and physical
advantages. We capture the key value of integrated store service delivery for consumers’
omni-channel experience and provide an effective service quality evaluation method from the
perspective of consumer service quality perception.
IJRDM Second, a seven-dimension scale with 24 items for measuring the integrated store service
50,7 quality in omni-channel retailing is developed and verified, which are in-store environment,
in-store technology, product information consistency, employee assistance, personalization,
channel availability, instant gratification and return. All these seven dimensions significantly
affect customer satisfaction and customer loyalty which shows the effectiveness of our scale
in predicting customer attitudes. Although some dimensions have been proposed in prior
literature, such as in-store environment (Nasr et al., 2012), employee assistance (Bitner, 1992)
852 and instant gratification and return (Gao and Su, 2016), the items in such dimensions
identified in our scale take into account the omni-channel consumer expectations and
behaviours, which are different from the prior ones. For example, employee assistance is
considered a critical factor that affects the brick-and-mortar service quality (Dabholkar et al.,
1996). Omni-channel consumers usually search the product information online at home before
purchasing and are well-informed. When they enter a store, they need to get personalized
recommendations and information from knowledgeable employees, especially when the
product is expensive or technical. Thus, the employees in the integrated store should be well
trained with face-to-face interaction skills consistent with the prior findings (Seck and
Philippe, 2013), and new competencies such as skilful usage of in-store equipped devices to
provide timely and personalized recommendations for their customers.
Third, we also identify some new dimensions in our scale considering the characteristics
of omni-channel retailing, such as in-store technology, product information consistency,
personalization and channel availability. The deployment of in-store technology helps to blur
channel boundaries, achieve seamless interaction and further increase the experience value of
consumers. Product information consistency can convey a unified, standard and trustworthy
store image, and reduce the search cost for consumers to compare information among
channels. Personalization is a necessary aspect of establishing close contact with consumers
and improving consumers’ in-store experience. Channel availability reflects the essential
characteristics of in-store channel integration.

5.2 Managerial implications

Many retailers have started implementing the omni-channel retailing business model to
provide a more convenient and seamless experience to their customers. In channel
integration, retailers with brick-and-mortar stores have a physical advantage, yet the
evidence of success is still patchy (Herhausen et al., 2015). Therefore, it is of great practical
significance to guide retailers to improve the service quality of the integrated stores. Our
integrated store service quality scale may clarify omni-channel consumer expectations to
help the retailers better evaluate and further improve their in-store service.
First, it is proved in our research that the integrated store service quality has positive
relationships with customer satisfaction and loyalty. Satisfied and loyal customers are
valuable treasures for any retailer. Combined various channels in omni-channel retailing
allow customers to reach a product on their smartphones, see it in person at a store and then
make a purchase from any channel they prefer without any gaps and barriers. A brick-and-
mortar store in omni-channel context, as the integration and bridge of multi-channels, is a
critical and interactive channel for omni-channel consumers. The integrated stores are
important in the omni-channel retail system, accompanied by high operating costs.
Consumers’ dissatisfaction with in-store services would make retailers face huge economic
losses, and even threaten the construction of the whole omni-channel retail system. Thus,
omni-channel retailers should evaluate the service quality of integrated stores based on our
scale and improve their service to better provide a seamless experience for their customers.
Second, for the service quality evaluation dimensions consistent with traditional retail
stores in the scale (i.e., in-store environment, employee assistance, instant gratification and
return), retailers should pay attention to the differences in the context of omni-channel Integrated
retailing. For example, in terms of instant gratification and return, the integrated store will store service
expand its service beyond traditional brick-and-mortar stores, as some consumers may
expect offline return services for online purchases (Trenz et al., 2020; Xu and Jackson, 2019).
quality
Besides, retailers should also concern the potential effects of the new dimensions in the scale
(i.e., in-store technology, product information consistency, personalization and channel
availability) on these traditional dimensions. For example, through in-store technology
innovation to optimize the in-store environment, improve employee assistance, help 853
consumers achieve instant gratification and return.
Third, in-store technology, product information consistency, personalization and channel
availability are essential factors for customer satisfaction and customer loyalty, through
which retailers need to show the unique competitiveness of integrated stores. Retailers should
improve service quality through technology enablement, as technology-assisted service
delivery in integrated stores creates appealing practical and experiential value for
consumers. To avoid brick-and-mortar stores becoming showrooms, retailers who are
implementing omni-channel retailing strategy should place a significant amount of effort on
ensuring that their product information contents are accurate and consistent across all
channels and touchpoints. Product information should be shared among all internal
departments and connected closely with their external partners and suppliers to establish a
trusted environment for their customers. Personalization is “the future” and a strategic
priority in omni-channel retailing to retain more loyal customers. With the advancements of
technology, retailers can gather actual customer browsing and purchasing data easily, then
offer more personalized and detailed shopping recommendations and assist their customers
to shop with ease. Finally, integration is always at the core (Mirzabeiki and Saghiri, 2020).
Through channel integration to ensure the channel availability of consumers, the integrated
store can really become a friction-free place for consumer experience.

5.3 Limitations and future research

More and more retailers are adopting the omni-channel retailing business model, in which the
brick-and-mortar store is an important channel. In this research, we first identify the omni-
channel consumer expectation for an integrated store with the use of grounded theory, then
develop and test a measurement scale with seven dimensions and 24 items. However, there
are also several limitations in our study. First, this research is mainly conducted with some
omni-channel retailers in China. Omni-channel retailing is still at its early stage in China, as
we have noticed during our survey for data collection. The results may have limited
generalizability. Thus, the scale proposed in our study needs to be improved when it is used to
assess the integrated store service quality of other countries. Second, we do not take product
categories into consideration. Different types of goods, such as electronics apparel and
dressing clothes, might influence customer familiarity with the store activities and service
quality perception. Further research can explore if there is an effect of product categories on
service quality perception. Finally, we just verify the nomological validity of the integrated
store service quality in predicting customer satisfaction and loyalty and ignore its effect on
omni-channel retailer sales. As a result, further study can investigate the cross-channel
customer behaviour in the omni-channel context, for example, the relationship of integrated
store service and online omni-channel retailer performance.

6. Conclusion
For omni-channel consumers, what really matters is the experience that they have with the
shopping process. As an important channel in omni-channel retailing, brick-and-mortar
stores can strengthen customer awareness and loyalty for many brands in meeting
IJRDM customers’ multidimensional and dynamic shopping needs. Although some scales for
50,7 measuring brick-and-mortar service quality have been proposed, none of them can capture
the new endowed features of brick-and-mortar stores in omni-channel retailing. Based on the
grounded theory findings and prior literature, our research constructs, refines and tests a
seven-dimension instrument for assessing integrated store service quality in omni-channel
context. The relationships among service quality, customer satisfaction and loyalty are
explored. This scale can fill out the research gap in service quality measurement and clarify
854 customer expectations to help the omni-channel retailers better evaluate their in-store
services.

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IJRDM Appendix
50,7
Item details of the integrated store service quality scale

In-store environment (Dabholkar et al., 1996)

IE3 The physical facilities at this store are visually appealing
858 IE4 Materials associated with this store’s service (such as shopping bags, catalogues or statements) are visually
appealing
IE5 This store has clean, attractive and convenient public areas (such as restrooms, fitting rooms)
IE6 The store layout at this store makes it easy for customers to find what they need
In-store technology
IT1 This store uses some advanced digital terminals (such as computer, laptop, scanning apparatus)
IT2 Digital terminals provided by this store are easy to operate
IT3 Digital terminals provided by this store make shopping more convenient
IT4 I feel safe in my transactions with this store’s digital terminals
Product information consistency
PIC1 The product information are consistent in both online and offline channels
PIC2 The products prices are consistent in both online and offline channels
PIC3 The product promotion details are consistent in both online and offline channels
Employee assistance
EA1 Employees in this store can provide me with prompt service with the assistance of digital terminals
EA2 Employees in this store have the knowledge of online product information
EA3 Employees in this store can help me complete an online order
Personalization
P1 This store makes recommendations to me based on my past online and offline purchases
P2 This store offers appropriate discount based on my online and offline purchase
P3 This store provides customized service based on my purchase history
Channel availability
CA1 I can access the retailer’s website while shopping in this store
CA2 I can get full product information from both online and offline channels in this store
CA4 I can get information of online product promotion in this store
CA5 I can get interactive access to online customer service assistance in this store
Instant gratification and return
IGR1 I can pick up the products ordered online in this store
IGR2 This store provides same-day delivery service
IGR3 I can return, repair or exchange the products that I purchased online in this store

Item details of customer satisfaction and loyalty intention

Customer satisfaction (Caruana, 2002)

Sat1 I felt pretty positive about the service this store provided
Sat2 I was satisfied with the service this store provided
Sat3 I was pleased with the quality of the store service in general
Customer loyalty (Zeithaml et al., 1996)
Loy1 I will continue to shop in this retailer in the coming years
Loy2 I will encourage friends and others to purchase from this retailer
Loy3 I will recommend this retailer to someone who seeks my advice
About the authors Integrated
Min Zhang is a Professor in College of Management and Economics, Tianjin University, China. Her
research interests focus on social media and service quality. She has published more than 40 refereed store service
articles in research journals including Journal of Business Ethics, Information Systems Frontiers, Journal quality
of Services Marketing, Electronic Commerce Research and Applications et al.
Yiwei Li is a Ph.D candidate in College of Management and Economics at Tianjin University in China.
Her research interests focus on social media and service quality.
Lin Sun is a Ph.D candidate in College of Management and Economics at Tianjin University in China. 859
Her research interests focus on social media and service quality. Lin Sun is the corresponding author and
can be contacted at: sunlin@tju.edu.cn
Farouk Adewale Moustapha is a graduate student in College of Management and Economics at
Tianjin University in China. His research interests focus on service quality.

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