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An application of retailing service quality practices influencing customer

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Article in Marketing Intelligence & Planning · August 2017

DOI: 10.1108/MIP-09-2016-0178

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 Marketing Intelligence & Planning
An application of retailing service quality practices influencing customer loyalty
toward retailers
Achchuthan Sivapalan, Charles Jebarajakirthy,
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Application of
An application of retailing service RSQ practices
quality practices influencing
customer loyalty toward retailers
Achchuthan Sivapalan
Department of Commerce, University of Jaffna, Jaffna, Sri Lanka, and
Received 29 August 2016
Charles Jebarajakirthy Revised 27 September 2016
11 February 2017
Department of Marketing, Griffith Business School, Griffith University, 12 May 2017
Gold Coast, Australia 8 June 2017
Accepted 10 June 2017

Abstract
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Purpose – Enhancing retailing service quality (RSQ) serves as a basic strategy for gaining competitive
advantage in the retailing industry and enables retailers to make a loyal customer base. The purpose of this
paper is to propose and empirically investigate a comprehensive mechanism for enhancing customer loyalty
to retail stores via service quality practices. This study suggests information on retailers can be the
antecedent of the RSQ and its dimensions, thereby proposing a comprehensive mechanism for enhancing
customer loyalty to retailers.
Design/methodology/approach – The data were collected using questionnaire surveys from
2,375 customers of three main supermarkets in Sri Lanka. After testing the measurement model,
two structural models were run to test hypotheses.
Findings – The findings showed that the RSQ positively influenced customer loyalty. From all the RSQ
dimensions, the store’s physical aspects, personal interaction and policy had a significant influence on customer
loyalty. The findings also demonstrated that information on retailers contributes to enhancing a customer’s
favorable evaluation of the supermarket’s physical aspects, personal interaction and retailing policy.
Research limitations/implications – This study was conducted with supermarket customers in one
country using the cross-sectional data. Hence, the model should be replicated among retail customers in other
countries with the longitudinal data.
Practical implications – Practically, this study recommends to retailers which dimensions of service
quality they need to focus to enhance customer loyalty to their business. The study furthermore recommends
certain dimensions that need to be emphasized while retailers design their promotional and communication
programs.
Originality/value – Information on retailers has been suggested as an antecedent for enhancing
supermarkets’ service quality practices. Thus, this study proposes a comprehensive mechanism for
enhancing customer loyalty to retailers via service quality practices.
Keywords Customer loyalty, Supermarkets, Dimensions of RSQ, Information on retailers,
Retailing service quality (RSQ)
Paper type Research paper

Introduction
The concept of “retailing service quality (RSQ)” has gained a prominent place in the services
marketing literature during the last decade. There are numerous entities operating in the
retailing industry, so intense competition prevails there. Providing high RSQ is considered a
basic retailing strategy for gaining competitive advantage in this industry (Gopalan and
Satpathy, 2013; Bharti et al., 2014). Karjaluoto et al. (2015) suggest that enhancing RSQ will
enable retailers to create greater customer value which would make customers more loyal to
a particular store or retailer.
“Customer loyalty” has emerged as the heart of the consumer marketing literature
(Bowen and Chen McCain, 2015; Blut et al., 2014; Kursunluoglu, 2014). Oliver (1999) defines
customer loyalty as “a deeply held commitment to rebuy or repatronize a preferred product/ Marketing Intelligence & Planning
service consistently in the future, thereby causing repetitive purchase of same-brand or © Emerald Publishing Limited
0263-4503
same brand-set, despite situational influences and marketing efforts having the potential to DOI 10.1108/MIP-09-2016-0178
 MIP cause switching behavior” (p. 34). In the retailing sector, enhancing the RSQ is viewed as the
best strategic tool to make customers loyal to the retailers (organization) or to their stores
(branches or outlets) (Dabholkar et al., 1995; Wong and Sohal, 2003; Sheikh and Lim, 2015).
Generally, retailing is considered different from pure services, such as education and
medicine. Retailing combines both commodities and services. This unique characteristic
marshals researchers’ efforts into using a specific scale to measure RSQ (Dabholkar et al.,
1995; Wong and Sohal, 2003; Sarkar and Sarkar, 2017; Peker et al., 2017). However, scant
research has investigated the influence of RSQ on customer behavioral outcomes, such as
satisfaction, purchase intention, loyalty and retention, in detail. This study addresses this
gap. Thus, the main purpose of this study is to propose and empirically investigate a
comprehensive mechanism for enhancing customer loyalty to retail stores via service
quality practices. First, this study investigates the influence of RSQ on customer loyalty.
Second, this study proposes information on retailers as an antecedent of RSQ, thereby
recommending a comprehensive mechanism for enhancing customer loyalty to retail stores.
This study has both academic and practical importance. It applies RSQ which is an
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emerging form of service quality measure. RSQ is a multidimensional construct, and this
study examines RSQ as a whole construct and at the level of individual dimensions. It also
suggests a comprehensive mechanism for enhancing customer loyalty, and so this study
will significantly contribute to the literature relating to service quality and customer loyalty
with the special emphasis on retailing contexts. The findings of this study will also provide
useful practical implications for the retailers to enhance customer loyalty by improving the
specific dimensions of RSQ.

Literature review
RSQ
Over the decades, both marketing scholars and practitioners have experienced difficulties in
correctly defining and measuring the concept of “service quality” (Parasuraman et al., 1988;
Ananth et al., 2010). However, Parasuraman et al. (1988) have made an attempt to give
seminal definition to this concept. They define “service quality” as a “global judgment or
attitude relating to the overall excellence or superiority of the service.” This definition
proposes a general conceptualization of service quality. However, the general parameters
that define service quality might be inappropriate for the retailing context (Gagliano and
Hathcote, 1994; Hanjunath and Naveen, 2012). In the retailing context, both products and
services are combined. That is, customers come to retailers to purchase products and they
require the services of the retailers. Dabholkar et al. (1995) therefore introduced the concept
of “RSQ”. Marketing scholars suggest the RSQ concept might be used as a basic retailing
strategy for enhancing customer value, satisfaction, retention and loyalty relating to retail
stores (Wong and Sohal, 2003; Demirci-Orel and Kara, 2015).

Customer loyalty
An organization can gain relative advantage over competitors through its loyal customer
base (Oliver, 1999). The concept of “customer loyalty” is defined both from attitudinal and
behavioral perspectives (Oliver, 1999; Zeithaml, 2000). From the behavioral perspective,
customer loyalty is defined as “repeat patronage, that is the proportion of times a consumer
chooses the same product or service in a specific category compared to the total number of
purchases made by the consumer in that category” (Neal, 1999). From the attitudinal
perspective, customer loyalty is defined as “a specific desire to continue a relationship with a
product or service provider” (Zeithaml, 2000). Due to the unique nature of the retail setting,
both perspectives are integrated for the purpose of understanding customer loyalty
(Dick and Basu, 1994; Oliver, 1999; Karjaluoto et al., 2015).
 Theoretical support Application of
Cognitive-motivation-relational (CMR) theory developed by Lazarus (1991) assists in RSQ practices
understanding the association between cognitive evaluation and emotional motivation.
Cognitive orientation occurs when individuals make an evaluation of their environment based
on their goals, beliefs and values which in turn generates emotions relating to the aspects
found in the environment. These emotions contribute to forming an ongoing relationship with
those aspects in the environment. Based on this theory, it can be suggested that there is an
association between service quality and customer loyalty in retail settings. Brady and
Robertson (2001) used the CMR theory to recommend a relationship between service quality
and customer responses, such as customer satisfaction and purchase intention, in the services
marketing context. They suggest service quality is associated with the cognitive evaluation of
services, whereas customer responses, such as satisfaction and purchase intention,
are perceived to be emotional motivations. Satisfaction with a particular retail setting could
make customers loyal to retailers (Bowen and Chen, 2001). The preceding theoretical
standpoints indicate a relationship between RSQ and customer loyalty in retail settings.
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The influence of RSQ on customer loyalty

Loyal customers are regarded as the source for a company’s sustainable competitive advantage
(Sivadas and Baker-Prewitt, 2000; Wong and Sohal, 2003; Yuen and Chan, 2010). Pursuing this
line of argument, it has been suggested that in the retailing sector, marketers focus on enhancing
their service quality for maintaining customer loyalty (Karjaluoto et al., 2015; Sabbir Rahman and
Nusrate Aziz, 2014). If customers have a favorable evaluation of, and attitudes toward certain
retailers, they tend to have loyalty to those retailers (Dick and Basu, 1994; Yuen and Chan, 2010;
Demirci-Orel and Kara, 2015). In support of this view, Zeithaml et al. (1996) and Sivadas and
Baker-Prewitt (2000) suggest a customer’s long-term relationship with a company is strengthened
when that customer makes a favorable assessment about the company’s service quality, and this
relationship is weakened when the customer makes negative assessments about the company’s
service quality. From the foregoing discussion, the following hypothesis is formulated:
H1. RSQ positively influences customer loyalty to retail stores

The dimensions of RSQ and their influences on customer loyalty

Dabholkar et al. (1995) conceptualized RSQ as a multidimensional construct consisting of
five dimensions: physical aspect, reliability, personal interaction, problem solving and
policy. A brief discussion of each of these dimensions and their influences on customer
loyalty to retailers follows.

Physical aspect
Physical aspect refers to the appearance of a supermarket and its staff, the availability of
equipment, facilities and visual materials, store layout and the convenience at
the supermarket (Dabholkar et al., 1995; Siddiqi, 2011). A good store layout and attractive
service materials provide customers with a good impression and attitude toward the
store (Beneke et al., 2012; Kitapci et al., 2013; Wong and Sohal, 2003). This indicates a
possible association between physical aspect and loyalty.

Reliability
Reliability measures the store’s ability to deliver the service that has been promised to
customers, accurately and without error (Vàzquez et al., 2001; Beneke et al., 2012). If a retail
store keeps its promises, it will increase customer confidence in the store (Wong and
Sohal, 2003; Yuen and Chan, 2010) and will gradually build customer loyalty.
 MIP Personal interaction
Personal interaction measures the customer’s perceptions of whether or not the store has
courteous and helpful employees who inspire confidence and trust among customers.
Sales staff play a pivotal role in a customer service situation (Gounaris, 2008). Beneke et al.
(2012) suggest that the more customers receive personalized assistance and attention from
sales staff, the greater the customer satisfaction with and loyalty to the store.

Problem solving
Problem solving means the extent to which a store has the ability to handle potential
problems, such as returns, exchanges and complaints (Swanson and Kelley, 2001; Beneke
et al., 2012). When a customer’s complaints are dealt with or their problems are resolved, they
will feel satisfied with the store, and have credibility and favorable perceptions of the store
(Beneke et al., 2012; Caruana, 2002; Ha et al., 2015). As a consequence, they will continue to
shop at the store, which indicates an association between problem solving and loyalty.
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Policy
The final dimension is policy, which refers to a store’s decisions concerning the depth and
breadth of their merchandise, loyalty programs, credit facilities, operating hours, parking
facilities and additional customer services offered (Beneke et al., 2012). Customers are more
likely to continue purchasing from the stores that are endowed with an effective retailing
policy (Yuen and Chan, 2010), which indicates retailers’ policies hold influence over
customer loyalty.
The preceding discussion indicates a strong connection between RSQ dimensions and
customer loyalty to retail stores. This discussion also suggests the dimensions of RSQ have
unique effects on customer loyalty. Therefore, the following hypotheses are formulated:
H2a. Physical aspect positively influences customer loyalty to retail stores.
H2b. Reliability positively influences customer loyalty to retail stores.
H2c. Personal interaction positively influences customer loyalty to retail stores.
H2d. Problem solving positively influences customer loyalty to retail stores.
H2e. Policy positively influences customer loyalty to retail stores.
Information on retailers as an antecedent of both RSQ and its dimensions. Information on
retail stores can be an antecedent of customer perceptions of service quality (Sultan and
Yin Wong, 2014). Information on retailers refers to the explicit and implicit messages that
customers receive directly and indirectly about retailers prior to consumption (Sultan and
Yin Wong, 2014). Media advertising and other types of communication employed by
retailers can influence consumers to form some expectations and perceptions of their service
delivery prior to consumption (Devlin et al., 2002; Russell, 2005; Teeroovengadum et al.,
2016; Khandeparkar and Abhishek, 2017; Mogaji, 2015). Hence, the following hypothesis
is formulated:
H3. Information on retailers influences RSQ.
Sharing information on retailers can also affect the customer evaluation of the dimensions of
service quality. The first dimension of the RSQ is physical aspect. Customers often expect to
see a convenient and attractive store layout with matching physical facilities when they
contemplate their visit to a supermarket (Russell, 2005). This suggests that sharing
information about the store environment through, for instance, a television advertisement
featuring visuals of the environment, contributes to consumers forming favorable
 evaluations and perceptions of its physical aspects (Dabholkar et al., 1995; Hanjunath and Application of
Naveen, 2012). The next dimension of RSQ is reliability. If the retailers share their RSQ practices
capabilities and exhibit confidence through promotional efforts, such as trade magazines
and periodic catalogues, then customers will believe that retailers will fulfill the promises
they claim to offer.
Another dimension of RSQ is personal interaction. Disseminating information about
courteous and helpful employees in the store will contribute to forming favorable customer
perceptions of the store (Grisaffe and Nguyen, 2011; Kim et al., 2016). The next dimension of
RSQ is problem solving. Communicating the retailer’s capacity and commitment to solving
customer problems enhances the customer’s favorable perceptions of a store (Swanson and
Kelley, 2001; Beneke et al., 2012; Kim et al., 2016). The final dimension of RSQ is retailing
policy. The sharing of information about policy aspects of retailers, enhances customer
awareness and perceptions of policy facts (Sultan and Yin Wong, 2014). They may
propagate this information via billboards, advertisements, their online sites and trade
magazines. The above discussion suggests that efforts to disseminate retailer information
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can be an antecedent of customer perceptions surrounding the dimensions of service

quality, so the following hypotheses are formulated:
H4a. Information on retailers influences customer perceptions of physical aspect.
H4b. Information on retailers influences customer perceptions of reliability.
H4c. Information on retailers influences customer perceptions of personal interaction.
H4d. Information on retailers influences customer perceptions of problem solving.
H4e. Information on retailers influences customer perceptions of policy.

The proposed conceptual models

The aforementioned hypothesized relationships are depicted in Figures 1 and 2. Figure 1
shows hypotheses relating to RSQ excluding its dimensions whereas Figure 2 shows
hypotheses at RSQ dimensions level.

Method
Sample and survey administration
The sample for this study comprised 4,000 customers of supermarkets operating in
Sri Lanka. There are differences between developed and developing countries in terms of
Figure 1.
Conceptual model
Information on H3 Retail Service H1 Customer
1 (without the
Retailers Quality Loyalty dimensions of RSQ)

H4a Physical Aspect H2a

H4b Reliability H2b

Customer
Information on H4c
H2c Loyalty
Retailers Personal Interaction
H2d
H4d Figure 2.
H4e Problem Solving H2e Conceptual model
2 (including the
dimensions of RSQ)
Policy
 MIP customers’ behavior, attitudes, usage and disposition relating to products and services
( Jebarajakirthy and Lobo, 2015). Studies relating to RSQ among supermarket customers in
emerging economies, such as those in Asia and South Asia are at infant level (Mittal et al.,
2015). This indicates that there is insufficient research on RSQ and its effect on customer
behavioral responses, such as customer loyalty, in emerging and transitional South Asian
countries, including Sri Lanka. This suggests a need to investigate RSQ among supermarket
customers in developing countries, such as Sri Lanka. Consistent with the discussion above,
since the end of its civil war, Sri Lanka has achieved an incredible economic rate of growth,
contributing particularly to a flourishing retail sector. The retailing sector is viewed as the
largest sub-category of the service sector in the Sri Lankan economy (Chanaka et al., 2014).
Hence, Sri Lankan supermarkets seem an ideal model setting for investigating RSQ and its
customers an excellent choice to survey.
A paper-based survey questionnaire was used to collect the data from sample
respondents. Participants were the customers of three leading supermarkets in Sri Lanka.
The survey was administered in six supermarket outlets. In each of these outlets, the survey
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was administered on a weekday and one day of the weekend. The survey was administered
during February-March 2016. Participants were approached on the entrance ( foyer) of each
outlet. While administering the survey, we asked the sample customers to respond to
it based on their experience of that particular supermarket they were in on that day.
Participants had the option of responding to the survey either immediately or at a time of
their own convenience. We gave postage paid self-addressed envelope to those respondents
who were unable to immediately return the survey. We distributed 4,000 survey
questionnaires, and out of this number, 2,375 surveys were returned. Of these, 83 surveys
had missing data, and were accordingly discarded.
The respondents comprised 54 percent male and 46 percent female. Regarding their age,
32 percent were aged between 18 and 30 years, 51 percent were aged between 31 and
45 years, 9 percent were aged between 46 and 60, and the rest were above 60 years.
Approximately 25 percent of the respondents had a monthly family income of less than
USD230, around 45 percent had an income between USD231-USD500, around 19 percent
had an income between USD501-USD750 and the rest had income above USD750. Finally,
in regards to their educational qualification, 44 percent had secondary or below
qualification, 22 percent had two-year college or associate degree, 18 percent had Bachelor’s
degree and 16 percent had Postgraduate degree or higher.

Measures and instrument development

A paper-based survey instrument was designed from previously validated scales. However,
these scales were modified to suit the retailing and supermarket context, where appropriate.
The scales of RSQ included 30 items under the five dimensions: physical aspect, reliability,
personal interaction, problem solving and policy. This means that the physical aspect was
operationalized using six items; reliability, using six items; personal interaction, using ten
items; problem solving, using three items; and policy, using five items. Of the 30 items,
28 items were adopted from Dabholkar et al. (1995) and two from Verma and Duggal (2015).
Customer loyalty was measured using the scales developed by Kim and Niehm (2009) and
Zeithaml et al. (1996). The measures of customer loyalty comprise both attitudinal and
behavioral aspects. The measures of attitudinal loyalty included three items adapted from
Kim and Niehm (2009) whereas behavioral loyalty was operationalized using three items
obtained from Zeithaml et al. (1996). Of the three items operationalizing the information on
retailers construct, the first two were obtained from Sultan and Yin Wong (2014) whilst the
remaining was developed for this study with the support of the literature (Dabholkar et al.,
1995; Wong and Sohal, 2003, Beneke et al., 2012). The items operationalizing all the
constructs were measured with the seven-point Likert type scale ranging from 1 for
 “Strongly disagree” to 7 for “Strongly agree.” Age, income and educational qualification also Application of
influence customer loyalty in retail setting (Oly Ndubisi, 2006; Cooil et al., 2007; Kuruvilla RSQ practices
and Joshi, 2010). They were not considered for hypotheses development, but instead
assumed to be control variables in this study. The data concerning these control variables
were also sought through this survey instrument.
To ensure content validity, the survey instrument was vetted by five academics with
expertise in the marketing field. The survey instrument, originally written in English, was
translated into Sinhalese and Tamil, the respondents’ local languages. Each translated
version of survey instrument was translated back into English and was cross-checked by
two other bilingual researchers to ensure the reliability and validity of translation.
The respondents had the option of responding to either the English or Sinhalese or
Tamil language survey based on their language proficiency. The survey instrument was
pretested using three focus groups, each comprising six customers of the three supermarket
chains considered for this study. Based on their feedback, some minor changes were
incorporated into the wording and format of the survey instrument.
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Analysis and results

Measurement model
Confirmatory factor analysis (CFA) was performed to test the measurement properties of all
the constructs. First and second-order CFA seemed appropriate to determine the
dimensionality, reliability and validity of all the study constructs. Physical aspect,
reliability, personal interaction, problem solving and policy were considered first-order
constructs, whereas customer loyalty was regarded as a second-order construct, which
consists of two dimensions. In arriving at the final set of items for each construct, five items
were deleted based on item to total correlations and the standardized residual values
(Byrne, 2009) (one item from physical aspect, one from reliability and three from personal
interaction). The deleted items were examined and compared with the original conceptual
definitions of the constructs. In each case, deleting the items did not significantly change the
make-up of the construct as initially conceptualized. The resulting pool of items was
subsequently subjected to CFA. A completely standardized solution produced by AMOS
version 21 using the maximum likelihood method shows that all the remaining items load
highly on their corresponding factors. This confirms the unidimensionality of the constructs
and provides strong empirical evidence of their validity.
The results of the CFA are presented in Table I. The CFA results showed that the factor
loadings of all the constructs were significant ( po0.01) and above 0.5, the minimum
threshold value, and the average variance extracted (AVE) values of all the constructs were
also above 0.5, both of which are indicative of the convergent validity of measures (Hair and
Anderson, 2010). The discriminant validity of the study constructs was tested as suggested by
Fornell and Larcker (1981). Thus, the square root of the AVE values presented in the upper
diagonal of Table II for each construct were greater than the construct’s correlation
coefficients with other constructs. This is indicative of discriminant validity among constructs
(Fornell and Larcker, 1981). In addition, Cronbach’s α coefficients of each construct presented
in Table I were above 0.7, indicating the reliability of constructs’ measures.
Table II presents the mean, standard deviation and correlations for the study constructs.
The results show that the majority of the constructs are significantly correlated with each
other as correlation regressions range from 0.1 to 0.57. However, all correlations are less than
0.9, thus suggesting there is no multicollinearity between these constructs (Tabachnick and
Fidell, 2012). Of the control variables, only income and education had significant relationship
with the study constructs: income was positively correlated with policy (r ¼ 10*) and
customer loyalty (r ¼ 15**) whereas educational level was positively correlated with reliability
(r ¼ 10*), personal interaction (r ¼ 11*) and information on retailers (r ¼ 11*).
 MIP Construct Statements FL

Physical aspect This supermarket has modern-looking equipment and fixtures 0.59
AVE (0.77), CR (0.89), The physical facilities at this supermarket are visually appealing 0.78
α ¼ 0.87 This supermarket has clean, attractive and convenient areas 0.80
The layout of this supermarket makes it easy to find what I need 0.80
The layout of this store makes it easy to move around within the store 0.69
Reliability In this supermarket, I am able to get goods and services when I require them 0.64
AVE (0.69), CR (0.78), This supermarket provides its services at the time it promises to do so 0.77
α ¼ 0.77 This supermarket accepts the suggestions made by customers and works on them 0.75
This supermarket provides the right service in the first instance 0.57
This supermarket insists on error-free sales transactions and records 0.66
Personal interaction Employees in this supermarket have the knowledge to answer my questions 0.64
AVE (0.58), CR (0.75), The behavior of employees in this supermarket instills confidence in me 0.71
α ¼ 0.74 I feel safe while doing transactions with this supermarket 0.63
Employees in this supermarket give me prompt service 0.51
This supermarket gives individual attention on me 0.57
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Employees in this supermarket are consistently courteous with me 0.51

Employees of this supermarket treat me courteously on the telephone 0.52
Problem solving This supermarket willingly handles returns and exchanges 0.84
AVE (0.75), CR (0.75), When I have a problem, this supermarket shows sincere interests in solving it 0.77
α ¼ 0.73 Employees of this supermarket are able to handle my complaints immediately 0.54
Policy This supermarket offers high quality merchandise 0.55
AVE (0.69), CR (0.74), This supermarket provides plenty of convenient and free parking for customers 0.74
α ¼ 0.72 The operating hours of this supermarket are convenient to their customers 0.67
This supermarket accepts most major credit cards 0.62
I could enjoy special privilege from this supermarket using its loyalty points system 0.59
Information on Overall, information provided by this supermarket helps me find service attributes 0.64
retailers Information provided by this supermarket makes promises about the quality of
AVE (0.68), CR (0.73), their service 0.64
α ¼ 0.71 This supermarket provides information on its attributes via various sources 0.76
CL AVE (0.71), CR (0.82), α ¼ 0.80
AL I consider myself a loyal patron of this supermarket 0.78
AVE (0.72), CR (0.78), I would say positive things about this supermarket to other people 0.74
α ¼ 0.75 I would recommend this supermarket to someone who seeks my advice 0.68
BL I would consider this supermarket my first choice for the purchase of
AVE (0.85), CR (0.90), convenient goods 0.84
α ¼ 0.87 I would do more business with this supermarket in the next few years 0.94
I would do less business with this supermarket in the next few years (reverse coded) 0.84
Notes: Fit indices χ2(504) ¼ 897.12, (p o0.001), CFI ¼ 0.95, TLI ¼ 0.95, RMSEA ¼ 0.038. CL, customer loyalty;
Table I. AL, attitudinal loyalty; BL, behavioral loyalty; FL, factor loading; CR, construct reliability; AVE, average
Summary of the variance extracted; CFI, comparative fit index; TLI, Tucker-Lewis index; RMSEA, root mean square error of
measurement model approximation

Mean SD 1 2 3 4 5 6 7

1. Physical Aspect 4.63 1.35 0.88a

2. Reliability 4.76 1.55 0.22** 0.83a
3. Personal Interaction 4.75 1.49 0.44** 0.27** 0.76a
4. Problem Solving 4.55 1.43 0.22** 0.29** 0.23** 0.87a
Table II.
5. Policy 4.99 1.76 0.35** 0.23** 0.31** 0.16** 0.83a
Descriptive statistics
and correlation matrix 6. Customer Loyalty 4.28 1.24 0.44** 0.03 0.25** 0.04 0.48** 0.84a
for the study 7. Information 4.71 1.45 0.57** 0.31** 0.05 0.06 0.44** 0.45** 0.82a
constructs Notes: aDiagonal value indicates the square root of AVE of individual latent construct. **po 0.01
 Common method bias Application of
Because the data relating to both independent and dependent constructs were collected from RSQ practices
the same respondents, a common method bias may occur. This potential problem was
checked with the Harman one-factor test (Podsakoff and Organ, 1986). A factor analysis of
eight focal constructs resulted in an eight-factor solution, which accounted for 79.76 percent
of the total variance; and factor one accounted for 17.55 percent of the variance. Because a
single factor did not emerge and factor one did not explain most of the variance, a common
method bias is unlikely to be a concern in this data. Single latent factor model was also used
to detect common method bias. If common method bias poses a threat, a single latent factor
model should yield a better fit than the multifactor model (model proposed for the study
based on the theory) (Podsakoff et al., 2003). The comparison of the single latent factor
model with the eight-factor model showed that a common factor bias was not a serious
threat. The fit of the single latent factor model is unacceptable and significantly worse
( χ2 ¼ 1,172.65; df ¼ 499; χ2/df ¼ 2.35; CFI ¼ 0.86, TLI ¼ 0.85, RMSEA ¼ 0.058, Δχ2 ¼ 312.4;
Δdf ¼ 34; p ⩽ 0.001) than that of the multidimensional model (model proposed for the study
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based on the theory).

Hypothesis testing
Two structural models were run to test the hypotheses. Fit indices suggest an acceptable
level of fit for both models with the sample data. In both structural models, the variance
inflation factor value was below cut-off value 5.0, indicating the absence of multicollinearity
in the models.
Table III depicts the results of the first structural equation model. In this analysis, both
RSQ and customer loyalty were considered second-order factors with summated first-order
indicators. This avoided the analysis of the individual dimensions of the RSQ. Along with
the control variables, RSQ explained 73.5 percent of variance in customer loyalty.
The results in Table III suggest, RSQ ( β ¼ 0.72, p o0.001) had significant positive influence
on customer loyalty. So, H1 was accepted. In this structural model, information on retailers
was considered an antecedent to the RSQ. The results in Table III also show that
information on retailers had significant and positive influences on RSQ ( β ¼ 0.64, p o0.001).
So, H3 was accepted. information on retailers explained 47 percent variance in RSQ.
The results of the second structural equation model are presented in Table IV. In this
analysis, customer loyalty was considered a second-order dependent factor with summated
first-order indicators. This structural equation model shows the analysis of the individual
dimensions of the RSQ. The five dimensions of RSQ, along with the control variables
explained 74.5 percent of the variance in customer loyalty. The results in Table IV show that
of the dimensions, physical aspect ( β ¼ 0.56, p o0.001), personal interaction ( β ¼ 0.34,
p o0.01) and policy ( β ¼ 0.63, p o0.001), had significant positive influences on customer
loyalty. Hence, H2a, H2c and H2e were accepted. However, reliability ( β ¼ 0.05, p W0.05) or

Proposed hypothesis/path relationships Coefficient ( β) t-value

H1: RSQ → customer loyalty 0.72 10.69***

H3: information on retailers → RSQ 0.64 10.64***
Age → customer loyalty 0.04 0.64ns
Income → customer loyalty 0.11 2.53*
EQ → customer loyalty 0.05 1.02ns
Notes: ns, not significant; RSQ, retail service quality; EQ, educational qualification; CFI, comparative fit Table III.
index; TLI, Tucker-Lewis index; RMSEA, root mean square error of approximation. Fit indices χ2 (614) ¼ The results of first
1,043.82, (p o0.001), CFI ¼ 0.90, TLI ¼ 0.94, RMSEA ¼ 0.048. *p o 0.05; ***p o 0.001 structural model
 MIP Proposed hypothesis/path relationships Coefficient (β) t-value

H2a: physical aspect → customer loyalty 0.56 10.53***

H2b: reliability → customer loyalty 0.05 0.82ns
H2c: personal interaction → customer loyalty 0.34 5.17**
H2d: problem solving → customer loyalty 0.08 1.23ns
H2e: policy → customer loyalty 0.63 11.35***
H4a: information on retailers → physical aspect 0.79 13.88***
H4b: information on retailers → reliability 0.56 11.03***
H4c: information on retailers → personal interaction 0.08 1.35ns
H4d: information on retailers → problem solving 0.09 1.54ns
H4e: information on retailers → policy 0.68 12.43***
Age → customer loyalty 0.04 0.66ns
Family income → customer loyalty 0.11 2.95*
Table IV. EQ → customer loyalty 0.06 1.27ns
The results of second Notes: ns, not significant; EQ, educational qualification. Fit indices χ2 (611) ¼ 1,025.38, ( p o0.001), CFI ¼
0.92, GFI ¼ 0.94, RMSEA ¼ 0.045. *p o0.05; **p o0.01; ***p o0.001
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structural model

problem solving ( β ¼ 0.08, pW 0.05) did not have significant effects on customer loyalty.
Hence, H2b and H2d were rejected. In this structural model, information on retailers was
considered antecedent to the dimensions of the RSQ. The results in Table IV also show that
information on retailers had significant and positive influences on physical aspect ( β ¼ 0.79,
p o0.001), reliability ( β ¼ 0.56, p o0.001) and on policy ( β ¼ 0.68, p o0.001). So, H4a, H4b
and H4e were accepted. However, information on retailers did not have any significant
effects on personal interaction ( β ¼ 0.08, p W0.05) or on problem solving ( β ¼ 0.09, pW0.05).
Thus, H4c and H4d were not accepted. Information on retailers explained 63, 32, 11, 13 and
46 percent variance in physical aspect, reliability, personal interaction, problem solving and
policy, respectively.
Information on retailers indirectly affects customer loyalty through RSQ and its
dimensions. The examination of the indirect effects is essential in developing a
comprehensive understanding of the current findings. Cheung and Lau (2008) suggest
performing bootstrapping to test indirect effects and to determine their statistical
significance. Bias-corrected bootstrapping was conducted for 2,000 resamples, with a
95 percent confidence interval to evaluate indirect effects on customer loyalty. The results of
this test showed that information on retailers ( β ¼ 0.46, p o0.001) had significant indirect
effects on customer loyalty via RSQ and its dimensions.

Discussions
The results showed that RSQ ( β ¼ 0.72, p o0.001) had a significant positive influence on
customer loyalty in the retail supermarket context. This finding indicates that maintaining a
higher level of RSQ in supermarkets enhances customer intention to repurchase from those
supermarkets and to maintain a long-term relationship with them. Additionally,
maintaining satisfactory RSQ level contributes to providing customers with favorable
experience with supermarkets, which makes it less likely for them to switch to rival
supermarkets.
This study also investigates the influence of the dimensions of RSQ on customer loyalty
to supermarkets. The findings show that physical aspect ( β ¼ 0.56, p o0.001), personal
interaction ( β ¼ 0.34, p o0.01) and policy ( β ¼ 0.63, p o0.001) had significant positive
effects on customer loyalty to supermarkets. These findings are consistent with those
reported in the literature (Beneke et al., 2012; Gounaris, 2008; Kitapci et al., 2013;
Siddiqi, 2011; Yuen and Chan, 2010). Reliability ( β ¼ 0.05, p W0.05) had no significant
 influence on customer loyalty to supermarkets. One possible explanation to this scenario may Application of
be this dimension includes measures, such as delivering promised and accurate services at the RSQ practices
promised time and ensuring error-free sales transactions, which most supermarkets provide in
the normal course of business. Most customers do not normally expect additional services
while shopping in supermarkets. Also, timely delivery of services seems more important for
online shopping than in-store shopping in supermarkets. Therefore, supermarkets should
extend their focus beyond reliability measures to enhance their customer loyalty.
Problem solving ( β ¼ 0.08, p W0.05) had no significant influence on customer loyalty to
supermarkets. This is possibly because in the supermarket context, not all customers
encounter problems during or after purchase. They normally purchase convenience goods
in supermarkets with which they are unlikely to face issues, such as returns, exchange or
complaints. Problem solving might be a more serious concern in an electronic supermarket
context, as customers may need to return or exchange electronic goods and may make
complaints about them.
This study considered “information on retailers” the antecedent of RSQ. The results show
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that information on retailers had significant positive effects ( β ¼ 0.64, po0.001) on RSQ. This
finding indicates that disseminating information about retailers, with an emphasis on their
unique service attributes, can lead customers to make a favorable evaluation of service quality
of retail stores. The findings also show that information on retailers had significant positive
effects on customer evaluation of physical aspects in retail stores ( β ¼ 0.79, po0.001),
reliability of the retailers ( β ¼ 0.56, po0.001) and retailing policy of the retailers ( β ¼ 0.68,
po0.001). These findings are consistent with the arguments in previous studies that were
documented in the literature review section of this paper. However, sharing information on
retailers did not have significant influence either on customer evaluation of personal
interaction ( β ¼ 0.08, pW0.05) or problem solving ( β ¼ 0.09, pW0.05). This is possibly
because customers evaluate both personal interaction and problem solving based on their
experience with purchase situations, such as returns and exchange, and based on their
interactions with sales staff. Customers are unlikely to evaluate both these dimensions based
purely on the information shared via different channels.

Academic and practical implications

This study makes many academic contributions. First, this research investigates the influence
of RSQ on customer loyalty to retail businesses, particularly to supermarkets. It also shows
that the dimensions of RSQ variably influence the enhancement of customer loyalty to
supermarket outlets. Moreover, this study has incorporated “information on retailers” as an
antecedent of the RSQ, thereby suggesting a comprehensive mechanism for enhancing
customer loyalty to retailers. It is also important to note this study was carried out in
Sri Lanka, as insufficient research exists on RSQ and its influences on customer behavioral
outcomes in developing countries, such as Sri Lanka. Hence, this study and its findings can
significantly contribute to the literature relating to services marketing, service quality,
retailing and customer behavior – in particular customer loyalty. Second, we have used CMR
theory developed by Lazarus (1991) to theoretically argue a relationship between RSQ and
customer loyalty. This theoretical argument also makes a contribution to the literature.
Third, this study has modified the items measuring RSQ and customer loyalty to suit the
supermarket context, and we have also refined the items measuring “information on
retailers” by including an additional statement that emerged from the literature review.
Future researchers can readily apply these items for investigating RSQ, customer loyalty
and their dimensions in supermarkets and other retail businesses.
Besides making academic contributions, the findings of this study have several practical
marketing implications for supermarkets. From the broader perspective, of the
five dimensions of RSQ, policy, physical aspects and personal interaction significantly
 MIP enhance customer loyalty, which suggests that strengthening and improving these areas or
dimensions in supermarkets would increase their customer loyalty. Particularly, of the
dimensions, policy is the main determinant of customer loyalty. Therefore, supermarkets
should consider adopting a retailing policy of stocking high-quality merchandise, operating
during convenient hours of the day, providing convenient and free parking facilities, accepting
major credit cards and issuing loyalty point cards in the interest of retaining customers.
Personal interaction also enhances customer loyalty to supermarkets. Hence, to enhance
customer loyalty, supermarkets can interact fairly with their customers. To effectively
achieve this, supermarkets should foster their staff’s knowledgeability, helpfulness,
courtesy and personal attention to customers. Supermarkets can judiciously consider
incorporating these aspects into their HR policies (e.g. policies relating to recruitment and
selection of sales staff ). Finally, physical aspects had a positive influence on customers’
loyalty to supermarkets. Therefore, to enhance customers’ favorable impressions of the
store’s physical aspect, the management of supermarkets should establish modern-looking
equipment and fixtures, visually appealing physical facilities, convenient layout,
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well-designed staff uniforms, as well as service materials such as catalogues.

The findings have also shown that information on retailers significantly influences
customers to favorably evaluate psychical aspects, reliability and policy relating to
supermarkets. However, of these RSQ dimensions, only the psychical aspect and policy
significantly enhance customer loyalty to supermarkets. This suggests retailers and
supermarkets can enhance customer loyalty by laying a strong emphasis on their physical
aspects and retailing policy while designing their communication and promotional
programs. Retailers and supermarkets can utilize television advertisements, business
magazines, newspapers, catalogues, brochures and leaflets, to visualize physical aspects
(e.g. modern-looking equipment and fixtures) and to make customers aware of their retailing
policy (e.g. convenient operating hours).

Limitations and directions for future research

This study was confined to supermarkets in Sri Lanka. Therefore, to better generalize the
findings of this study, it needs to be replicated with supermarkets in other countries,
especially in other emerging and transitioning economies. In addition, the data for this
study was cross-sectional. However, due to the rapid changes adopted by supermarkets –
such as technological developments and innovative marketing practices – customers’
attitudes, perceptions and evaluations of supermarkets are likely to change overtime.
This indicates that replicating this study with the longitudinal data could reveal more
interesting results.
This study opens multiple avenues for further research. First, there may be moderating
factors in the relationship between RSQ and customer loyalty. Future researchers can
identify these moderators through the literature review and expand this study. Second, this
study has considered only information on retailers as the antecedent of RSQ, while there
may be other antecedents of the RSQ; for example, past experience (Sultan and Yin Wong,
2014) with the retailer (supermarket). Future researchers can identify and incorporate these
additional antecedents into this study and improve on it. Third, this study has examined the
influence of RSQ on customer loyalty, which is a customer behavioral outcome.
Other customer behavioral outcomes may be considered, such as customer retention and
purchase intention, so that the influence of RSQ on these customer behavioral outcomes can
be investigated in future research.
Finally, the findings of our study have demonstrated that providing information on
retailers does influence a customer’s evaluation of RSQ and its dimensions, so we suggest
future researchers investigate which types of information (e.g. advertisement, billboards,
etc.) most influence each RSQ dimension.
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About the authors

Achchuthan Sivapalan is based in the Faculty of Management Studies and Commerce at the University
of Jaffna, Sri Lanka. His research interests are in the areas of consumer behavior, social marketing and
business ethics. Achchuthan’s research has been published in the Asian Social Science, International
Journal of Business and Management, Asian Journal of Empirical Research and Corporate Ownership
and Control among others.
Dr Charles Jebarajakirthy is a Lecturer in Marketing in Griffith Business School, Gold Coast, Australia.
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His research interests are in the areas of consumer behavior, services marketing and retailing. Charles’s
research has been published in the Journal of Retailing and Consumer Services, Journal of Strategic
Marketing, Asia Pacific Journal of Marketing and Logistics, International Journal of Consumer Studies,
Journal of Young Consumers, International Journal of Nonprofit and Voluntary Sector Marketing, and
International Journal of Bank Marketing among others. Dr Charles Jebarajakirthy is the corresponding
author and can be contacted at: c.jebarajakirthy@griffith.edu.au

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