A review of Perceived Service Quality - DiVA portal531619/FULLTEXT01.pdf · A review of Perceived...

A review of Perceived Service Quality: An empirical investigation of grocery stores’ customers in

Växjö, Sweden

Authors: George Panteloukas891202-H550 Albert Mbu Etonga Asopo 770917-9019 Roland Buwag 800207-2570

Tutor: Sarah Philipson

Examiner: Rana Mostaghel

Subject: Strategic Marketing

Level: Bachelor thesis

Year of publication: Spring 2012

Bachelor Thesis 15hp (2FE07E; 2FE10E) School of Business and Economics

Abstract Service quality and customer satisfaction are important concepts to grocery

industry. It is therefore important for companies to know how to measure this

construct of expectations and perceptions because consumers’ expectations of service

quality are increasing and people are becoming more and more critical of the quality

of service they experience. The service quality model SERVQUAL is discussed in

this study and how it can be applied in the context of grocery stores. The data in use

were gathered from consumers in a southern Swedish town, called Växjö and the goal

was to measure their expectations and perceptions of the services provided to them.

After going through a significant number of articles and literature, the SERVQUAL

model was altered by adding more variables (products, location, and waiting time) to

its five dimensions. The aim was to find out if consumers are satisfied with the

services been provided to them by grocery stores.

Purpose – The purpose of the paper was to identify the dimensions influencing

consumers’ perceived service quality in the grocery retailing.

Method/approach – Using a sample of 200 respondents, a self-completion

questionnaire was given out to consumers in Växjö, to determine their expectations

and perceptions of service quality in grocery stores.

Findings – The results show that expectations exceeded perceptions, denoting gaps in

service quality, which means that grocery stores do not provide the level of service

demanded by customers. This entails that customer satisfaction is rather low and that

there is still room for grocery stores to improve on their performance.

Managerial implications – The findings show that the SERVQUAL model can be a

very useful instrument in measuring service quality in grocery stores. The additional

variables proposed show a strong correlation to customer satisfaction, with products

and waiting time being of high importance to overall service quality. Managers can

use this tool to understand how customers assess service quality in grocery stores and

in turn enhance their service experience.

Originality/value – We introduce three new variables in the SERVQUAL model

which, we believe, complete the assessment of service quality in the context of

grocery stores.

Key words – Service quality, customer satisfaction, SERVQUAL and grocery stores

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Acknowledgements We like to sincerely thank our supervisor, Dr Sarah Philipson for the kind gesture and

support she has gave us to produce this work. It was particularly interesting to our

independence in judging and handling knowledge in different scientific articles and

readings. Three seminars were held to check the progress of the work and to guide us

in getting things right and improve on the quality of the research. In the seminars,

there were lots of interesting discussions and feedback from all the participants. We

want also to thank our examiner Dr Rana Mostaghel for guiding us through these

seminars, as well as Dr Magnus Hultman for his contribution to our paper with his

lectures. Last but not least, we want to give special thanks to all our respondents for

giving answers to our questionnaires. We really appreciate their support in all this

effort.

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Table of contents Abstract…………………………………………………………………...2

Acknowledgements……………………………………………………....3

List of figures…………………………………………………………….6

List of tables……………………………………………………………...6

1 Introduction…………………………………………………………...7

1.1 Background……………………………………………………….7

1.2 Problem discussion……………………………………………….9

1.3 Purpose…………………………………………………………..11

1.4 Delimitations…………………………………………………….11

1.5 Disposition………………………………………………………12

2 Literature review…………………………………………………….13

2.1 Service quality………….………………………………………..13

2.2 Expectations vs perceptions……………………………………..14

2.3 Customer satisfaction……………………………………………15

2.4 Service quality and customer satisfaction……………………….16

2.5 Service quality models…………………………………………..17

2.5.1 The SERVQUAL model…………………………………….19

2.5.2 Criticism of SERVQUAL model……………………………20

2.6 State of the art…………………………………………………...21

2.6.1 Adapted SERVQUAL model………………………………..22

2.7 Research question and hypotheses………………………………23

3 Methodology………………………………………………………...24

3.1 Research approach………………………………………………24

3.2 Research design…………………………………………………25

3.3 Data sources……………………………………………………..26

3.4 Research strategy………………………………………………..26

3.5 Data collection method………………………………………….27

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3.6 Data collection instrument………………………………………28

3.6.1 Operationalization and measurement of variables…………..28

3.6.2 Questionnaire design………………………………………...32

3.6.3 Pretesting…………………………………………………….34

3.7 Sampling…………………………………………………………34

3.8 Data analysis method…………………………………………….35

3.9 Quality criteria…………………………………………………...37

3.9.1 Validity………………………………………………………37

3.9.2 Reliability……………………………………………………37

4 Empirical results and analysis……………………………………….39

4.1 Demographics……………………………………………………39

4.2 Reliability testing………………………………………………...40

4.3 Expectation, perception and gap scores………………………….41

4.4 Regression……………………………………………………….44

4.5 Analysis………………………………………………………….47

5 Conclusions……………………………………………………….....50

5.1 Discussion……………………………………………………….50

5.2 Implications……………………………………………………...51

5.3 Limitations……………………………………………………….51

5.4 Suggestions for future research………………………………….52

6 Reference list………………………………………………………...53

Appendix………………………………………………………………..60

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List of figures Figure 1: Thesis disposition……………………………………………12

Figure 2: Brady & Cronin’s model…………………………………….18

Figure 3: Dabholkar, Thorpe & Rentz’s model………………………..18

Figure 4: Parasuraman, Zeithaml & Berry’s model…………………....19

Figure 5: Adapted SERVQUAL model…….…………………………..22

Figure 6: Research strategies…………………………………………...26

List of tables Table 1: Measurement and scaling of constructs……………………….29

Table 2: Research constructs and their definitions……………………..31

Table 3: Demographic frequencies …………………………………….39

Table 4: Reliability of expectation items……………………………….40

Table 5: Reliability of perception items………………………………..41

Table 6: Expectation-perception means and gap scores………………..43

Table 7: Regression analysis for products……………………………...44

Table 8: Regression analysis for location………………………………45

Table 9: Regression analysis for waiting time………………………….46

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1. Introduction In this chapter, we introduce the reason for choosing the area of study. We

present some information about service quality in the background, our choice of

study, next we proceed to our problem discussion and a purpose for this study

follows. The delimitations are also stated, as well as the continued disposition of

the study, which ends the first chapter.

1.1 Background Service quality has gained significant importance in the last two decades, due to the

unique characteristics of services involving intangibility (services can not be seen,

tasted, heard, smelt or felt), inseparability (services can not be separated from their

providers), variability (the quality of services varies due to who provides them, where,

when and how they are provided) and perishability (services can not be held/stored

and they must be consumed when offered). These characteristics make the process of

service purchase and delivery very complex for both customer and seller and for most

types of services. Indeed, there is no consensus in the measurement and definition of

service quality and this is why the concept has much attention in the marketing

literature (Wisniewski, 2001; Schneider & White, 2004).

As stated by Howcroft (1991), service quality entails constant anticipation of what

customers expect from the service provider. Service quality has been emphasised in

many dimensional advantages leading to customer’s satisfaction (Raddon, 1987;

Buzzell & Gale, 1987). Parasuraman, Zeithaml & Berry (1988) emphasize that there

is credibility in the sales force if the quality of service provided is high. They further

observed that, in the context of grocery stores, the longer such a store keeps

improving on its service performance, the more it meets the expectations of

customers. If customers perceive quality as unsatisfactory, they may divert their

attention elsewhere. Thus, as stated by Balachandran, Voelker & Bahl (2003),

providing high service quality, means achieving success in competing services. More

importantly, in the case of grocery stores which offer identical services,

differentiation through services is of high competitive advantage (Ibid.).

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For a long time, there has been low competition and low customer satisfaction in the

Swedish grocery retail sector (Andersson, Fornell & Rust, 1997; Elg & Johansson,

1992). However, there have been significant changes in the last twenty years, due to

the high demand for service quality improvement by customers. Presently, there is an

increased market share consisting of discount stores, foreign store chains and also a

growing number of clear-cut supermarket concepts and convenience stores

(Anselmsson, 2006). However, consumers need something more than convenient

store solutions and enhanced products. Differentiation through service has

traditionally been a forceful competitive tool (e.g. Parasuraman et al., 1988; Mazursky

& Jacoby, 1986) and according to numerous marketing researchers the offering of

high service quality is often said to be of fundamental importance in retailing (Berry,

1986; Reichheld & Sasser, 1990; Dabholkar, Sheperd & Thorpe, 2000; McGoldrick,

2002). Since grocery stores provide consumers with basic commodities, there is need

for retailers to focus in delivering superior service quality so they can achieve high

levels of customer satisfaction (Anselmsson, 2006). To, therefore, maintain a high

quality image, it is important to measure service quality and find out the expectations

and perceptions of consumers in order to know which dimensions of service need

improvement (Ibid.). The interest of this study was directed towards finding these

dimensions that influence grocery retailing services.

Moreover, as a consequence of the increasing competition and major changes in

retailing, it is important to understand what service signifies from a customer

perspective and what impact service has as a means of competition in the retailing

sector. There has been much research on service quality and which attributes of

service quality are needed to meet the expectations of customers (Anselmsson, 2006).

In recent times there has been much research on how to establish an operational scale

and measurement for the evaluation and monitoring of service quality. The most well-

renowned is the SERVQUAL-scale, an instrument for measuring customer

perceptions of service quality (Parasuraman et al., 1988). However, as McGoldrick

(2002) states, a limitation of the SERVQUAL in the retailing context is that its scale

has been developed and tested mainly in pure service settings, not for profit settings.

He argues that the model has not been developed in retail business settings. Scales

have not been specifically developed to capture the essence of service quality in

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grocery retailing and as a result, more research is needed (Mehta, Lalwani, & Han,

2000).

1.2 Problem discussion As stated by Lovelock & Wirtz (2007), customers have become more and more aware

of their requirements and they demand higher standards of services. Customers’

perception and expectations are continuously evolving, making it difficult for the

service provider to measure and manage services effectively. It is therefore important

for the service provider to pay attention to the most critical service

attributes/dimensions as a part of customer service management (Sachdev & Verman,

2004). It is also important to understand how sensitive customers respond to the

different service attributes or dimensions. Service providers should allocate their

resources in a way consistent with customer priorities, enhancing the effectiveness of

service operations.

In such context, customer satisfaction is one of the most prominent objectives for

service providers. Rust & Oliver (1994) define satisfaction as the “customer fulfilment

response”. Satisfaction is an evaluation as well as an emotion-based response to a

service (Ibid.). According to Geetika & Ashwini (2008), to Sachdev & Verma (2004),

to Ekinci (2003) and Czepiel (1990), customer satisfaction has been commonly

accepted as a major indicator of service quality. Grönroos (1984), states that,

satisfaction from service quality is usually evaluated in terms of technical and

functional quality. Donabedian (1980), however, gives emphasis on the fact that

customers do not get much about the technical aspects of a service and so functional

quality forms their perceptions of service quality.

Perceived service quality has been proven to be a difficult concept to measure. Some

researchers in this area, such as Parasuraman et al. (1985), referred to the concept as

“elusive” and considered as still unsolved, meaning it is “far from conclusive”. Other

researchers, such as Czepiel (1990), defined service quality as the customer

perception of how well a service meets or exceeds the expectations of customers.

Sachdev & Verma (2004) claim it can be measured in terms of customer expectation,

customer perception, customer satisfaction and customer attitude. However, the

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conceptualization and measurement of service quality is a debated and controversial

issue in the service marketing literature. There is still need to examine the

dimensionality of the service quality concept (Parasuraman et al., 1985).

There are several service quality models helping researchers and practitioners to

identify and improve the efficiency and profitability of the overall performance of

services. Indeed, there are two major conceptualizations of the service quality concept

mentioned in the literature. One perspective is the Nordic school by Grönroos (1984)

who defines the dimension of service quality in a global term as consisting of a

functional dimension and a technical dimension of perceived service quality. The

second perspective is the American school by Parasuraman et al. (1988), who use

terms that describe service encounter characteristics, such as tangibles, reliability,

responsiveness, assurance and empathy (explained in chapter 2.5.1) to formulate a

service quality framework, the SERVQUAL. In a different model, Brady & Cronin

(2001) attempt a hierarchical approach of service quality, which describes three

primary dimensions as the basic determinants of service quality, namely interaction,

physical environment and outcome, dividing each in three more sub-dimensions (in

total nine). Other scholars have considered different dimensions of service quality,

such as Lehtinen & Lehtinen (1982) who consider interactive, physical and corporate

quality or Hedvall & Paltschik (1989) who focus on willingness/ability to serve and

the physical/psychological access to the service.

Though the American school of thought dominates the literature of perceived service

quality, a consensus has not been reached as to which approach is appropriate and no

attempt has been made to consider how the different conceptualizations are related

(Brady & Cronin, 2001). It is thus evident that perception of service quality is

generally based on many dimensions, however there is no general agreement on the

nature of these dimensions.

Another model that is mentioned in the literature of service quality is the one of

service quality gap. Compared to the traditional models, this one involves five

additional components and eight additional gaps (Shahin & Abolhasani, 2008). This

model deals with if a service meets or exceeds customer needs and expectations. A

service quality gap can be defined as the difference between customer expectations

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and perceptions of service quality. Hence, if expectations are higher than what is

delivered, the perceived quality is less than satisfactory and the customer gets

disappointed with the service, which implies that the customer will switch to a

competitor (Parasuraman et al., 1985; Lewis & Mitchell, 1990).

It is therefore important to understand the role of expectations because consumers’

expectations of service quality are increasing and people are becoming more and more

critical of the quality of the service they experience (Philip & Hazlett, 1997). Ekinci

(2003) indicates that customer satisfaction comes from the evaluation of service

quality. However, service quality evaluation is a highly complex process that may

operate on several levels of abstraction (Carman, 1990). The literature shows that

there is no consensus on the determinants of service quality and that there is no

unified theory or conceptualization which reflects the complexity and the nature of the

concept (Brady & Cronin, 2001).

1.3 Purpose To identify the dimensions influencing consumers’ perceived service quality in the

grocery retailing.

1.4 Delimitations This study is limited to grocery stores in Växjö, Sweden. It is assumed that the

services offered to the customers by these grocery stores are almost the same, based

on the product and services they offer. The aim of this study is not to look on a single

case or make comparisons between grocery stores. Instead, it seeks an average

opinion for all the grocery stores visited by consumers in Växjö.

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1.5 Disposition Chapter 1 introduces the background and reasons for choosing the area of research.

Chapter 2 presents our theoretical framework that constitutes the foundation for this

study and the solution to our problem discussion. Conceptual models are also

presented in this chapter. Then, chapter 3 describes the chosen methodology, our way

of approaching this research. The empirical data collected from the subjects of this

study are publicized in chapter 4. An analysis of the empirical findings and a

comparison with the theoretical framework is made in the same chapter. Conclusions

can be found in chapter 5, drawn from the discussion in the previous chapters and also

our research question is answered in this chapter. Finally, managerial implications are

presented as well as limitations and directions for future research.

Figure 1: Thesis disposition

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2. Literature review In this chapter, we review literature relevant to our topic. We discuss issues of

service quality, expectations and perceptions, customer satisfaction, relationship

between service quality and customer satisfaction, service quality models and

define relevant concepts to enhance our understanding of the chosen topic and

provide answers to our research question.

2.1 Service quality Authors and researchers have given different definitions of service quality over time.

Zeithaml & Bitner (2003) and Bitner & Hubert (1993) defined service quality as a

comparison of what the customers feel a service provider should offer (expectations).

Oliver (1993) and Bitner (1995) state that service quality perceived by customers, is

the difference between customers’ perceptions and expectations of service quality. In

marketing literature, Parasuraman et al. (1985) have defined service quality as the

extent to which a service meets or exceeds customer expectations. Parasuraman et al.

(1988), however, suggest that customers perceive service quality in different ways.

The first level is expected/desired service, which is the level of service the customer

hopes to receive by the service provider. The second level is adequate service, which

is the level of service the customer will accept (Ibid.). Therefore, it is important for

management to understand the basic concept of this construct because customers are

very sensitive especially if what they get, doesn’t meet their expectations (Ibid.).

Presbury, Fitzgerald & Chapman (2005) emphasize that it is vey important to provide

service quality that meets the expectations of customers. Antony, Antony & Ghosh

(2004) refer to service quality as the concept of meeting and exceeding the

expectations of customers and if these expectations are not exceeded, then service can

be seen as ordinary or inferior. It is thus important for service providers to offer good

quality service to customers so that the conception of quality can be influenced not

only by the service outcome but also by the service process (Ibid.).

Indeed, service quality has turned out to be the leading element in the grocery

retailing these days. Ghobadian, Speller & Jones (1994) state that the interest in

service quality has increased noticeably because it is one of the requirements needed

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to survive in the contemporary, competitive business environment. The nature of the

service is such that the customer is present in the process. He further states that

service quality, in business context, is the measure to which the service delivered

meets customer expectations. So, service quality is achieved through meeting

expectations (Ibid).

2.2 Expectations vs perceptions It is important for marketers to understand the needs of their customers and provide

goods and services that meet their needs better than their competitors. Therefore, it is

important to understand the expectations of the customer because customers make

their purchases by thinking critically of their requirements. As Parasuraman et al.

(1988) state, expectations are predictions by customers about what is going to happen

during a particular transaction, what the customer thinks the transaction is going to

look like.

There has been frequent research on service quality, to an extent on which attributes

are necessary to satisfy customer expectations, because of the slow growth rate in the

grocery retail sector; the pursuit of market share is the objective of managers in these

sectors (Uusitalo, 2001). According to Parasuraman et al. (1988) and Mazursky &

Jacoby (1986), it is important for retail shops to offer and supply high service quality.

Therefore, expectations may concern a particular category of retail shop that will

guide the consumers’ perception, leading to an overall evaluation of a store, as well as

making a choice (Parasuraman et al., 1988; Mazursky & Jacoby, 1986).

As stated by Birtwistle, Clarke & Freathy (1999), it is important to improve the

understanding of customers’ perceptions because managers have different views on

their retail image from what customers have. Another author, Wilkie (1994), states

that consumers’ perceptions comprise of three stages which are: sensing, selecting and

interpreting. Therefore, interpreting in this sense means how consumers give meaning

to a perceived object, for example a store. As stated by Sujan (1985), consumers

categorize a structure in their minds about how a retail store should look like. Their

expectations concerning what a grocery store should possess and what performance

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level can be expected from these stores is of great importance to the success of

grocery stores (Ibid.).

Grönroos (1984) and Parasuraman et al. (1985) state that consumers’ perception of

service quality is based on the differences between expectations and perceptions of

service quality. According to Parasuraman et al. (1988), expectations are what the

customer thinks that he/she should have from a service provider and that is the type of

service that the store should offer; perceptions are what a service provider really

offers. The implication is that when these providers do not meet the expected service,

this leads to customer dissatisfaction. On the other hand, when customer’s

expectations are met, this will lead to customer retention as well as customer loyalty

(Ibid.).

2.3 Customer satisfaction Customer satisfaction has been the subject of much debate in the field of marketing

literature. According to Cronin & Taylor (1992), the meaning of customer satisfaction

is based on the customer’s experience in a particular service encounter. Some authors,

like Jones & Suh (2000), consider customer satisfaction as an accumulative concept

based on the overall evaluation of a service experience. Na, Marshall & Keller (1999)

view satisfaction as a consequence of strong associations or images. Satisfied

customers experience “a pleasurable level of consumption-related fulfilment” (Hunt,

1977, p. 459-460). Fornell (1992, p. 11) defines customer satisfaction as “an overall

post-purchase evaluation”, while Day (1984, p. 496) defines customer satisfaction as

“the consumer’s response to the evaluation of the perceived discrepancy between

prior expectations and the actual performance of the product as perceived after its

acquisition”. However, the definitions mentioned above consider satisfaction as a

post-purchase response, because customers evaluate service quality after the service

encounter.

Yi (1990) states that, customer satisfaction is considered as an attitude. In the case of

grocery shops, the shopping experience is important in evaluating customer

satisfaction. In this regard, customer satisfaction is evaluated based on the multiple

interactions the customer has with the service provider (Ibid.). According to Wicks &

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Roethlein (2009, p. 83), “organisations that consistently satisfy their customers, enjoy

higher retention levels and greater profitability”. It is crucial then to keep customers

satisfied.

However, since perceptions of satisfaction appear to be influenced by pre-existing

expectations, this will mean that satisfaction results from a “disconfirmation

judgement”, as to the difference between expectations of the service provided and the

perceptions of the actual service performance (Rust & Oliver, 1994). Therefore, the

problem with the disconfirmation paradigm exists with respect to satisfaction. In this

case, satisfaction will be considered as “part of the overall attitude towards a service

provider in certain number of measures” (Levesque & McDougall, 1996, p. 14). It is

thus important to evaluate service quality by considering the important quality

attributes that firms can take improvement actions, especially those attributes that

have lower satisfaction level.

2.4 Service quality and customer satisfaction In the past few years, the relation of customer satisfaction and service quality has

received considerable academic attention (Spreng & Mackoy, 1996). Marketing

literature and practice hold the concepts of service quality and customer satisfaction at

the pick of important objectives (Ibid.).

The key for grocery retailing stores lies on delivering high quality service that can in

turn result to customer satisfaction (Shemwell, Yavas & Bilgin, 1998). In the case of

grocery stores, customer satisfaction is considered a prerequisite for customer

retention and loyalty and this obviously helps in realizing economic goals like

profitability and market share (Scheuing, 1995; Reichheld, 1996; Hackl & Westlund,

2002). Different arguments, concerning service quality and customer satisfaction,

claim that these concepts may be conceptually distinct but they are closely related

constructs (Parasuraman et al., 1994; Dabholkar, 1995; Shemwell et al., 1998).

Their relation, as stated by Bitner & Hubert (1994), shows that although there is a

strong correlation between service quality and customer satisfaction, the two concepts

are indeed different, which means that it becomes imperative for service providers to

16


view the two constructs separately. Customer satisfaction reflects the customer

feelings when he or she enters a grocery shop in multiple encounters such as

experience. Service quality is more abstract and is likely to be influenced by external

factors such as advertising and other forms of communication (Bitner et al., 1994).

While customer satisfaction is a broader concept, service quality targets on identifying

dimensions of service (Zeithaml, Bitner & Gremler, 2006). Based on these views,

service quality is a component of customer satisfaction and the two are closely

connected to each other (Ibid.).

2.5 Service quality models Seth, Deshmukh & Vrat (2005) state that researchers and managers are in constant

purchase of the components of service quality that lead to customer satisfaction and

increased profitability. They specifically stress that models can assist managers in not

only identifying and learning about these components, but also in providing directions

for improvement. Conceptual models are a simplified way of describing real-life

situations and thus a way of identifying quality problems and enhancing what an

organization has to offer; thereby improving efficiency, profitability and overall

performance) (Ibid.).

Literature has developed various models over the years, reporting more than 25

conceptualizations, one building on the other and each adding some value to the

service quality concept (Sangeetha & Mahalingam, 2011; Seth et al., 2005). For this

study, three models are shortly introduced, which also helped in the construction of

our questionnaire (see chapter 3.6). However, more emphasis will be given on the

work of Parasuraman et al. (1988) since this served as the core model for this

research. The models used are:

Brady & Cronin’s model illustrates a hierarchical approach of service quality and it

identifies nine subdimensions that define the three direct determinants of service

quality; interaction, environment, and outcome. These reflect the composite set of

factors customers consider when they evaluate the quality of the service (Brady &

Cronin, 2001).

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Source: Brady & Cronin (2001)

Figure 2: Brady & Cronin’s model

In the retail store context, Dabholkar, Thorpe & Rentz’s model presents a hierarchical

factor structure of retail service quality and it identifies five dimensions of the retail

service quality; physical aspects, reliability, personal interaction, problem solving and

policy. The first three dimensions have two more sub-dimensions as shown in the

figure and the whole model depicts the dimensions important to retail customers

(Dabholkar et al., 1996).

Source: Dabholkar, Thorpe & Rentz (1996) Figure 3: Dabholkar, Thorpe & Rentz’s model

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2.5.1 The SERVQUAL model

SERVQUAL is a 22-item subsequent scale for measuring consumers’ expectations

and perceptions of service quality. Originally, Parasuraman et al. (1985) identified

five organizational gaps within the process of service design/delivery that cause

deficits in quality and leading to dissatisfied customers. However, they refined their

research and the original ten dimensions of service quality (proposed in their work in

1985), became five (Parasuraman et al., 1988). As Parasuraman et al. (1988) describe

in their work, these dimensions are: tangibles (the environment of the company and

how the working staff appears to be), reliability (ability to serve customers in a

dependable way), responsiveness (a company’s tendency to serve customers willingly

and promptly), assurance (making the customers feel safe and easy around the

company’s environment) and empathy (ability to understand the needs of the

customer).

Source: Parasuraman et al. (1988)

Figure 4: Parasuraman, Zeithaml & Berry’s model

SERVQUAL’s basic idea is the difference between a customer's expectations for a

service to be used and his or her perceptions of the service received (Parasuraman et

al., 1988). This difference is called a “gap” (gap 5 as shown in figure 4) and it is

referred to as “perceived service quality”. External factors may, however, influence

the expectations of customers, which are not under the control of the service provider

(Ibid.). This study has a focus on this gap and tries to identify the difference between

expectations and perceptions.

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2.5.2 Criticism of SERVQUAL model

According to Buttle (1996), there are some criticisms of SERQUAL, both theoretical

and operational. In the theoretical criticism, the author states that SERVQUAL is

based on a disconfirmation paradigm instead of an attitudinal paradigm and that it

does not draw on established economic, statistical and psychological theories.

Secondly, using the gap model, there is little evidence that customers will assess

service quality in terms of P-E gaps (perceptions-expectations). The author continues

by stating that the process orientation of SERVQUAL focuses on the process of

service delivery and not on the outcome of the service encounter. Using the five

dimensions, the author states that they are not universal and that there is a high degree

of interrelation between the dimensions (Ibid.).

In the operational criticism, Buttle (1996) argues that the term “expectations” has

different definitions and that consumers use other measures than sole expectations to

evaluate service quality. In item composition the author says the five items can not

capture the variability within each service quality dimension. Customers may assess

service quality in various ways from the “moment of truth” (time of interaction of a

service encounter between the two parties). Finally, he states that the SERVQUAL

instruments of expectations and perceptions can cause confusion (Ibid.).

Even though it has some weaknesses and despite the criticisms, Buttle (1996) still

supports the model to be a very good tool in understanding customers’ expectations

and make improvements in service. He states that the extensive use of this model has

proved SERVQUAL to be very reliable and for this reason we believe that this model

can be applied in the context of grocery stores.

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2.6 State of the art

Over a decade, researchers have proposed and evaluated alternative service quality

models and instruments for measuring service quality. Among these models,

SERVQUAL (Parasuraman et al., 1988) is the most dominant and the most widely

used. The model is based on the comparison of performance with expectations. Good

service quality means that the customers’ perceptions of service performance meet or

exceed their expectations of what the service firm should provide (Ibid).

Through in-depth interviews and focus group discussions with firms in four different

service industries, Parasuraman et al. (1988) identified the five determinants of

service quality (stated in chapter 2.5.1) and provided the basis for the measurement of

customer satisfaction. Since then, the SERVQUAL scale has been widely used to

measure service quality in different service contexts, such as professional services

(Freeman & Dart, 1993), health care (Lam, 1997), tourism (Tribe & Snaith, 1988),

business school (Pariseau & McDaniel, 1997) and information systems (Kettinger &

Lee, 1994).

It has also been widely tested for its validity and reliability (Babakus & Boller, 1992;

Bolton & Drew, 1991; Cronin & Taylor, 1992; 1994). Despite that some of these

studies failed to support the SERVQUAL model, Parasuraman et al. (1993) defended

their structure on both conceptual and practical grounds.

Considering the strengths and weaknesses of SERVQUAL and related instruments,

the issue of how best to conceptualize and operationalize service quality is still a

subject of heated debate (Cronin & Taylor, 1994; Parasuraman et al., 1993; Teas,

1994). However, it is generally agreed that SERVQUAL is a multi-dimensional/multi-

attribute construct instrument of being valid and reliable. This study finds the

instrument to be valid and reliable for measuring retail service quality and applicable

for research in Växjö. Based on a modified SERVQUAL, the authors of this study

estimate that this service quality instrument can be applied in measuring service

quality in the field of grocery retailing.

21


2.6.1 Adapted SERVQUAL model

For the purpose of this research, we want to present an adapted SERVQUAL model,

which we believe is more fitting to the context of grocery stores. We essentially use

the basic SERVQUAL model with some additions. As Parasuraman et al. (1993)

suggest, with minor modification, SERVQUAL can be adapted to any service

industry. Thus, we apply the main quality dimensions proposed by Parasuraman et al.

(1988) and we add three more variables; “products”, “location” and “waiting time”.

Products will be looked in the light of variety and quality, which means the different

variations of a product-brand a grocery store offers (flavours, sizes, etc) and their state

when purchased (fresh, not expired, not broken, etc). Location will be looked as the

place of the store, either centrally located or in the outskirts of a city/town and waiting

time as the time spent while shopping, including the waiting time for payment. We,

thus, adopt a modified SERVQUAL model with eight dimensions; tangibles,

reliability, responsiveness, assurance, empathy, products, location and waiting time.

Figure 5: Adapted SERVQUAL model

For this model, the initial 22 items of the SERVQUAL model were modified, some of

them were excluded and other items were included. This model is a summary of items

used from basically three major studies, the ones of Parasuraman et al. (1988),

Dabholkar et al. (1996) and Brady & Cronin (2001). Items of our own making were

also constructed to complete the questionnaire of this study, all based on the literature

gathered and relevant to the concepts we address to our respondents. The aim was to

measure the service quality gap between the expectations respondents have from a

22


grocery store and the actual service they experience. Furthermore, we were interested

in finding out the overall service quality perceived by customers and with which

dimensions respondents are mostly satisfied with.

2.7 Research question and hypotheses

Owing to the fact that customers are sensitive to services provided to them, we look

on the dimensions that customers value the most. We are interested in contributing to

the service quality concept of grocery stores’, adding more value to the

dimensionality of service quality. We will therefore like to answer the following

question in our study:

• Are consumers satisfied with service quality offered by grocery stores?

To answer our research question, we formulate a hypothesis based on the adapted

SERVQUAL model we use:

H1: The smaller the gap between expectations and perceptions, the higher customer

satisfaction is

Also, since the five dimensions of the SERVQUAL have already been widely tested

for their applicability, we are mostly interested in the relation between the three

variables proposed in this study with customer satisfaction and for that reason we

would like to test the following hypotheses:

H2: The good physical condition and variety of a grocery store’s products lead to

customer satisfaction

H3: The location of the grocery store plays a big role to customer satisfaction

H4: The time spent in the grocery store is of high importance to customer

satisfaction

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3. Methodology In this chapter, we present and motivate our choice of method in collecting and

analysing the data of this study. We present both theoretical and practical point

of view and then compare the advantages and drawbacks of other alternative

methods that may be less appropriate to the context of the study.

3.1 Research approach The two research approaches according to Bryman & Bell (2011) are the inductive

and deductive: inductive means that according to the implications of his findings, a

researcher infers a new theory; deductive is when a researcher deduces a hypothesis

or a problem, based on an already known theoretical background in a certain area of

expertise, which then tests with an empirical investigation (Ibid.).

The approach this study follows is the deductive. The interest of the study initiated by

looking at different dominating theories and aspects of service quality and customer

satisfaction that can be applied in the grocery retailing and eventually reaching to our

research question. The aim is to answer this question by undergoing an empirical

investigation.

To accomplish that, there are two ways, the quantitative or the qualitative approach

(Bryman & Bell, 2011): a quantitative research has to do with collecting results which

are measurable and presentable in the form of numbers and statistics, by testing

variables in a large population. Its purpose is to make generalizations based on the

processed results of the investigation; a qualitative research strives to gain a deeper

and more complete understanding of the studied problem by testing several variables

in a smaller population (Ibid.).

For this study, the quantitative approach was chosen, as we want to test some aspects

and dimensions of service quality on a large sample of the population. The

dimensions tested were the ones most relevant to the grocery stores’ service and the

objective is to get a view about customer satisfaction dimensions from a relatively

large number of consumers, in order to be able to generalize the results to the

population as a whole. Furthermore, the qualitative approach would be a more

24


subjective analysis from our part and aim is to gather tangible information to support

our case.

3.2 Research design A research design, as stated by Bryman & Bell (2011, p. 40), “provides a framework

for the collection and analysis of data”. According to Malhotra (2010), it is a

blueprint that includes details of all the procedures needed to solve marketing research

problems. The decision of which research design to choose, is determined by if the

researcher wants to express connections between variables, generalize results to a

population, understand behaviour or compare current with old results (Bryman &

Bell, 2011).

There are three types of research designs according to Malhotra (2010): the

exploratory research design, the descriptive research design and the causal research

design. The exploratory research design gives the researcher an initial understanding

of the problem at hand and provides insights before an approach can be developed.

The descriptive research design is used to describe market characteristics of functions

or make comparisons of variables and make predictions. The causal research design is

employed when a researcher wants to find out which of his or her studied variables is

the cause (independent variables) is and which are the effect (dependent variables) of

the phenomenon he or she studies and tries to obtain evidence regarding this cause-

and-effect relationships (Ibid.).

The design followed in this study is the descriptive because the goal was to look in

some characteristics of the grocery store service and make assumptions and inferences

about them. To be more explicit, the approach followed was the single cross-sectional

design (part of the descriptive design). This design involves the collection of data

from only one sample of a population (Malhotra, 2010). Indeed, one sample was

chosen from our population, so this design best suited the study, primarily due to time

constraints.

25


3.3 Data sources Data can be collected either from primary data sources or secondary: Malhotra (2010)

refers to primary data simply as information collected for the research needs at hand.

Bryman & Bell (2011) refer to them as information collected first-hand, up-to-date

and tailor-made to answer specific research questions. Secondary data are information

collected for reasons other than helping to solve the exact problem at hand and they

are gathered more to provide some background or alternatives to the main research

problem (Ibid.).

For the needs of this research, primary data were found more appropriate, since the

focus is to find current information about the preferences of consumers and which

relate directly to our research questions. This choice was made because secondary

data could prove insufficient or inaccurate since the study was undertaken in Växjö

and probably they couldn’t be generalizable to answer the problem at hand.

3.4 Research strategy According to Yin (2009), there are five major research strategies to follow in a study,

namely experiment, survey, archival analysis, history and case study. These strategies

are presented in figure 6, describing briefly where each focuses:

Source: Yin (2009)

Figure 6: Research strategies

26


Our study followed the survey strategy, as it takes a sample of the grocery stores’

population and tries to make statistical inferences about this population. It could not

take a history or archival analysis path because we primarily test the contemporary

beliefs of the consumers in Växjö and secondly not just observe/examine accumulated

documents, which may not even have any specific relevance to our own work. An

experiment was also ruled out due to the difficulty to run. A case study was excluded

too because the aim was to take data from a large number of units and not just an

individual unit (company, person/group, event). Thus, a survey serves the interest of

this study more adequately since in this way we can answer our research question

with more accuracy.

3.5 Data collection method There are several methods for collecting the data required for a study. The most

common of them are interviews, focus groups, content analysis, different types of

surveys and observations (Bryman & Bell, 2011). Interviews and focus groups are a

good way of getting an in-depth insight of the study object but they tend to be more

subjective in the interpretation and examine a smaller part of a population (Ibid.) and

our focus is firstly to get the most realistic view and secondly from a larger sample.

Furthermore, since the study is quantitative, a survey is more suitable. The reason is

that, since we examine the effect of specific dimensions of grocery stores’ service

quality, the use of collected data from a rather big sample, to give organized statistics

and results, complies perfectly with the purpose of this study.

The different types of surveys include four different contact methods, which means

reaching a test-subject via mail, internet/email, telephone or personal approach

(Bryman & Bell, 2011). For this study, the personal approach was chosen mainly

because we wanted a face-to-face “communication” with our respondents. By

personal or face-to-face, we mean a more direct approach than the other methods. We

wanted essentially to be able to clarify any problems/questions our subjects could not

understand, which would be difficult especially in the case of mails or emails. Also,

we achieved a better response rate with this approach, because of the personal

involvement and chance we had to explain everything to our respondents. The speed

of data collection was likewise very good and depended on us mostly and not just on

27


waiting for answers on mails or emails. For these reasons, a personal contact method

was used to serve the purpose of this research.

3.6 Data collection instrument

To know how customers perceive service quality, self-completion questionnaires were

used for this study. The reason was to collect anonymous answers that could really get

the data we were interested in.

According to Bryman & Bell (2011), self-completion questionnaires are

questionnaires that can be answered without the aid of an interviewer. The author

gives a couple of reasons to support the use of self-completion questionnaires as well

as some of their drawbacks. Advantages include that self-completion questionnaires

are cost effective, meaning they are easy to distribute and without many expenses.

Also, they don’t take a long time to administer (compared to interviews), since they

can be filled in at the same time by many respondents. Additionally, self-completion

questionnaires give respondents convenience and autonomy to respond to questions

when they want and at any speed they want. On the other hand, the main drawbacks

of self-completion questionnaires include low response rate, questionnaires not being

completely answered and biased responses (Ibid.).

Despite the drawbacks cited above, we endeavoured to overcome them by checking

each questionnaire when respondents handed them in. Therefore, by doing so, our

response rate was really high. We even tried to explain the questionnaire to the

respondents in brief to avoid any confusion. The questions-statements were structured

so as to get the respondents’ expectations about the grocery stores in Växjö and their

experiences (perception) of these stores. The statements used seek to find out the

customers’ preferences and identify which of the different dimensions of our adapted

SERVQUAL model actually matter to them.

3.6.1 Operationalization and measurement of variables

Operationalization is the process of defining variables into measurable factors. The

process defines fuzzy concepts and allows them to be measured, empirically and

quantitatively. It is basically how a concept is to be measured in a research and,

28


according to Bryman & Bell (2011), all concepts that have been implemented in a

quantitative research have to be measured.

Table 1 presents the indicators used in the questionnaire, by displaying the concepts,

the type of scale and its construction, the items used and their references. To ease our

analysis of the data collected, we also coded our main variables from the adapted

SERVQUAL model.

Table 1: Measurement and scaling of constructs

Concept

Type of scale & its

construction Items used Adopted

from

Tangibles (TN) TN1: The store has modern-looking equipment

Dabholkar, Thorpe &

Rentz, 1996 TN2: The store has clean and convenient physical facilities

Das, Kumar & Saha, 2010

2 items, 7-point Likert scale

anchored by: (1) Strongly

disagree and (7) Strongly agree TN3: The physical facilities of the

store are visually appealing Brady &

Cronin, 2001

Reliability (RL) RL1: The store has merchandise available when the customers want it

Dabholkar, Thorpe &

Rentz, 1996

RL2: The store provides its services at the time it promises to do so

Parasuraman, Zeithaml & Berry, 1988



disagree and (7) Strongly agree RL3: Customers can count on the

employees taking actions to address their needs

Brady & Cronin, 2001

Responsiveness (RN)

RN1: Employees of the store are able to handle customer complaints directly and immediately

Dabholkar, Thorpe &

Rentz, 1996 RN2: It is okay if the employees are too busy to respond to customer requests promptly




disagree and (7) Strongly agree RN3: Employees of the store respond

quickly to customer needs Brady &

Cronin, 2001

Assurance (AS) AS1: Customers are able to trust employees of the store


AS2: Customers feel safe in their transactions with the store


2 items, 7-point Likert scale anchored by:

AS3: Employees in the store are consistently polite with customers

Das, Kumar & Saha, 2010

29


Empathy (EM)

EM1: The behaviour of the employees indicates that they understand customer needs


EM2: It is realistic to expect employees to know what the needs of their customers are




disagree and (7) Strongly agree

EM3: Employees of the store give customers personal attention


Products (PR)

PR1: The groceries (e.g. vegetables, fruits, meat, milk, etc) are always fresh and not expired

Own

PR2: The products are always in a good condition (not broken, etc) Own




PR3: The store offers the variations of a product-brand the customer needs (e.g. all flavours, sizes, etc)

Own

Location (LC) LC1: The store is located in the outskirts of the town/city

Own

LC2: The store is located in a central area Own



disagree and (7) Strongly agree LC3: The store provides plenty of

convenient parking for customers

Dabholkar, Thorpe &

Rentz, 1996

Waiting time (WT)

WT1: The store layout makes it easy for customers to find what they need

Dabholkar, Thorpe &

Rentz, 1996 WT2: The store understands that waiting time is important to the customer (waiting time: the whole time spent in the store, including the time waiting for payment)





WT3: The store tries to keep the customer's waiting time to a minimum


Customer satisfaction

(CS)




CS: Are you satisfied with the store you usually visit? Own

Table 2 firstly presents the conceptual definition of each concept, which is the

established theory from the literature investigation. Then, the operational definition

follows which is the definition built for the matters of this study, in order to make it

understandable to all readers.

30


Table 2: Research constructs and their definitions

Concept Conceptual definition Operational definition

Tangibles (TN)

“Physical facilities, equipment and appearance of personnel” (Parasuraman et al., 1988, p. 23)

Ambiance of the grocery store and how the working staff appears to be

Reliability (RL)

“Ability to perform the promised service dependably and accurately” (Parasuraman et al., 1988, p. 23)

Ability to serve customers adequately and in time

Responsiveness (RN)

“Willingness to help customers and provide prompt service” (Parasuraman et al., 1988, p. 23)

The grocery store's tendency to serve customers fast and with verve

Assurance (AS)

“Knowledge and courtesy of employees and their ability to inspire trust and confidence” (Parasuraman et al., 1988, p. 23)

Making the customers feel safe and easy around the grocery store environment

Empathy (EM)

“Caring individualized attention the firm provides to its customers” (Parasuraman et al., 1988, p. 23)

Ability to understand the needs of the customer, to get in the “shoes” of the customer

Products (PR) Variety and product quality

The different variations of products-brands the grocery store offers (flavours, sizes, etc) and their state when purchased (fresh, not expired, not broken, etc)

Location (LC) Place of the store

If the grocery store is centrally located or in the outskirts of a city/town

Waiting time (WT) Time spent in a store

Time spent while shopping, including the waiting time for payment

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3.6.2 Questionnaire design

The questionnaire is comprised of three parts and it includes 29 questions (see

Appendix). The main part of the questionnaire is divided in two sections, one for

expectations and one for perceptions. The respondents had to evaluate the same

statements-items, firstly in the light of expectations and secondly in the light of

perceptions.

The first part of the questionnaire aims at measuring the respondents’ expectations of

service quality in grocery stores. It requires from respondents to show the extent to

which they believe grocery stores “should” possess the features stated. In other words,

its purpose is to picture the ideal service people want from a grocery store and express

their desire for a particular attribute of service quality.

The second part aims at measuring respondents’ perceptions. Respondents were

requested to show the extent to which the statements reflect their experience from

grocery stores in Växjö. In this part, they were asked to picture the store in Växjö they

visit the most and answer accordingly.

After completing these two sections of the questionnaire, having 24 questions, the

respondents were asked to fill one question about the overall satisfaction they get

from grocery stores in Växjö. This question intends to measure their opinion

regardless their expectations and perceptions.

In the last part of the questionnaire, we accumulated some demographic

characteristics, like gender, age, level of education and their monthly expenditure in

grocery stores. Monthly expenditure was calculated in Swedish currency, the Swedish

Kronor.

As stated in section 2.6.1, most of the statements used in this study were originally

developed by Parasuraman et al. (1988), Dabholkar et al. (1996) and Brady & Cronin

(2001). This research has changed the original SERVQUAL instrument, but we have

tried to bring in some new dimensions and rephrased the statements to be context-

relevant. To ensure content validity, we have added three new dimensions, product,

location and waiting time (described in section 2.5.2). All eight dimensions included

32


three items each. We have therefore employed 24 statements to measure our

dimensions. Questions 1 to 3 will be used to measure the tangibility aspect of grocery

stores in Växjö. The reliability dimension will be measured in statement 4 to 6, while

the responsiveness dimension will be measured in statement 7 to 9. The assurance and

empathy dimensions will be measured in 10 to 12 and 13 to 15 respectively. The

product dimension will be measured in statement 16 to 18. Lastly, the location and

waiting time dimensions will be measured in statements 19 to 21 and 22 to 24

respectively. Question 25 measures if the respondents are satisfied in the whole from

the grocery store they visit. Finally, questions 26 to 29 are devoted to demographic

features as explained above.

The questions are close-ended. By being such, the results of the questions are easy to

complete by respondents and process and compare for researchers (Bryman & Bell,

2011). They are easy and quicker to analyze and reduce the probability of

misinterpreting the questions by giving respondents a set of possible answers (Ibid.).

The scale in our survey questions is the 1 to 7 Likert-type scale, originally developed

by Rensis Likert, with 1 denoting ‘I strongly disagree’ and 7 denoting ‘I strongly

agree’.

All in all, the adapted SERVQUAL model was used to assess consumers’

expectations and perceptions of grocery stores service. Both were measured using the

7-point Likert scale to rate the level of agreement and disagreement, through which

the higher number indicated a high level of expectations and perceptions.

Expectations are based on past experiences and information while perceptions are

based on the actual service received in grocery stores. As Parasuraman et al. (1985)

suggest, service quality scores are measured as the difference between perceptions (P)

and expectations (E) scores and this is how measurement was made in this study, with

the only difference it was thought as expectations minus perceptions. What we are

more interested in, is the absolute difference between expectations and perceptions;

the signs (+) or (–) just indicate which one is higher. This score measures the degree

to which expectations exceed perceptions. The more positive this P-E score, the

higher the level of service quality, leading in turn to a higher level of customer

satisfaction (Ibid.).

33


We could therefore assume based on the above that, in most cases, when expectations

and perceptions are equal, then service quality leads to satisfaction. This is actually

the, based on discrepancy theories, disconfirmation paradigm (Oliver, 1977). As this

theory suggests, consumers judge satisfaction as a result of their expectations and

perceptions. Therefore, positive disconfirmation leads to increased satisfaction and

negative disconfirmation leads to decreased satisfaction (Ibid.). We therefore kept in

mind this theory when developing the questionnaire, which can be seen in the

Appendix.

3.6.3 Pretesting

To ensure that our questionnaire is field-ready, we followed some pretesting of the

questionnaire. Testing the questionnaire helps researchers determine whether the

questionnaire is able to capture the required data to answer the purpose of the

research. It helps firstly in making the questions understandable to all respondents and

secondly making it easy for the researchers to document the information gathered

(Bryman & Bell, 2011).

For these reasons, experts in the field as well as parts of the survey population were

needed to examine the items of our questionnaire. Our test “pilots” for the

questionnaire was our tutor, our examiner and students from our university. The

questionnaire was at first discussed with our tutor and examiner and necessary

adjustments were made to the initial version. After that, the questionnaire was handed

out to students studying in fields outside Marketing, to ensure that everyone,

regardless of study-field, can understand the questions. Based on the feedback we got

from the test pilots, changes and improvements were made accordingly and the

questionnaire was ready to hand out to our real sample.

3.7 Sampling A survey can examine either every element of the population (census survey)

(Bryman & Bell, 2011), or in our case, a sample of the population (sample survey). A

census survey cannot be a viable option and so a sample survey had to meet the

expectations of this study because of its time, cost and resource saving characteristics.

34


Our study was carried out in Växjö Sweden and we are interested to find out how

consumers in this town perceive service quality in grocery stores. Växjö is a town

located in the south of Sweden with a population of approximately 80,000 inhabitants

and it is considered as the administrative headquarter of Kronoberg County (Växjö

Kommun Statistics, 2012). Our sample was from the inhabitants of Växjö, being

either Swedish or any other nationality living in town. To determine that sample, we

used the statistical method/formula (see below) and we calculated our sample size

target to be at 382 inhabitants.

n= {2500 x N x Z2}/ {[25 (N-1)] + [2500 x Z2]}

n= sample size,

N= population size,

Z= number of standard errors (1.96 for 95% confidence level)

However, due to time constraints, our sample was decreased to 200 respondents of

this population. We believe that this sample is sufficient to meet the objectives of this

study.

To gather this sample, we situated ourselves in front of different grocery stores in

Växjö so as to reach a large number of consumers. We approached any person who

had a shopping experience of the store we were outside from. Lastly, we shared the

questionnaires with everyone, without being biased and gave it to anyone who was

willing to answer.

3.8 Data analysis method For this quantitative research, the use of statistical tools was needed to help us do

some analyses. The SPSS program (Statistical Package for Social Sciences) was used

for the analysis of our data, as well as the Excel program to present tables and figures

of our results. We used descriptive statistics, mainly involving percentage frequencies

and arithmetic mean. The Cronbach's alpha test was also employed as well as a

regression analysis to test our different concepts. The tools used are briefly described

below:

35


The arithmetic mean is the total of all the values in a distribution, divided by the

number of these values (Bryman & Bell, 2011). Whenever answers were missing

from a statement of a questionnaire, a means/average was computed from the rest of

the answers of that same statement, in order to have a complete list of data to add in

the SPSS.

Cronbach's alpha is a test for a model or survey's internal consistency. It is widely

used to test internal reliability. Cronbach's alpha assesses the reliability of a rating

extracted from a multi-point formatted questionnaire or scale, summarizing a group of

survey answers which measure a specific concept (Blumberg, Cooper & Schindler,

2008; Bryman & Bell, 2011). A computed alpha coefficient varies between 1 (perfect

internal reliability) and 0 (no internal reliability). To have an acceptable level of

internal reliability, the figure 0.8 is typically employed, meaning “α” must be equal or

higher than this figure; α=>0.8 (Ibid.). However, in this study and in accordance with

our tutor, the figure used to denote acceptable level of reliability was α=>0.6.

Regression analysis is a statistical tool for the investigation of relationships between

one dependent variable (criterion) and one or more independent variables (predictor)

(Malhotra, 2010). The results of a regression analysis are assessed by looking at three

key factors; R-square, Beta value and significance. R-square ranges between 0 and 1

and indicates the proportion of the variance in the dependent variable which is

accounted for by the model. An example of R-square=0.357 means that 35.7% of the

variance is explained by the model. The Beta variable is a measure of how strongly

the independent variable influences the dependent variable. The higher the beta is, the

greater the impact of the dependent variable on the independent variable (Field,

2009). Lastly, significance is about how confident a researcher can be that his/her

findings can be generalized from a sample to a population (Bryman & Bell, 2011). If

a significant score is greater than 0.1, then the results are not significant or differently,

they do not support a hypothesis. If it is equal to 0.1 or greater than 0.05, then the

results are significant at 10% level of significance and support a hypothesis at p<0.1.

If it is equal to 0.05 or greater than 0.01, then the results are significant at 5% level of

significance and support a hypothesis at p<0.05. Finally, if a significance score is 0.01

36


or less, then the results are significant at 1% level of significance and support a

hypothesis at p<0.01, which is the highest level of significance (Ibid.).

3.9 Quality criteria The two main quality criteria for business research are validity and reliability. Next

follows a brief explanation of what these concepts stand for and the reasons we

believe that they characterize this study.

3.9.1 Validity

Bryman & Bell (2011, p. 42) define validity as “the concern with the integrity of the

conclusions that are generated from a piece of research”. In simple words, validity

concerns the accuracy of the study, whether a researcher measures the things that

he/she was supposed to measure. Validity can be seen from an external and an

internal perspective according to several authors (Bryman & Bell, 2007; Miles &

Huberman, 1994). External validity describes the degree of generalisation of the

results. Internal validity refers to the congruence of the observations and the

theoretical ideas (Bryman & Bell, 2007). According to LeCompte & Goetz (1982),

internal validity is seen as a strong point in quantitative research because the concept

and the observation match together.

We are inclined to believe that our work is valid and relevant and it can measure the

concepts we are addressing to our respondents. The items used in our questionnaire

have already been tested in practice by other researchers and have been proven to give

answers to the same concepts we measure in our study. For this reason, we believe

that with this questionnaire, it is possible to gather the data to answer our research

question.

3.9.2 Reliability

The consistency or the degree to which a research is replicable is expressed in the

term of reliability. The reliability is estimated high when an instrument measures the

same results under the same conditions monitoring the same subject. According to

Miles & Huberman (1994, p. 278), a reliable study is “consistent and reasonably

stable over time and across researcher and methods”. Problems with the reliability of

37


quantitative research are likely to occur because of change of the settings in which the

study is embedded (Bryman & Bell, 2007).

We believe that our work is reliable and if a future research would be undertaken, it

would give the same or almost the same results with us. The items we used in the

questionnaire are easy to comprehend and could be answered in any point in time.

Considering also that the questions are close-ended, this means that the responses are

limited. There is a chance though that results collected in another point of time could

change because consumers’ expectations are always changing. However, in the

whole, we think that if this study is carried out again, the results will be almost similar

to our own, especially because the answers are limited and specific.

38


4. Empirical results and analysis In this chapter we present the results of the study and analyse the primary data

we collected with our questionnaire. We present tables to demonstrate the results

and we interpret these results in compliance with the theories gathered.

4.1 Demographics To start the empirical chapter and give some information about our respondents, the

authors present their demographic characteristics in percentages. Our sample was

almost half divided with female respondents up to 52% and male up to 48%. The age

parameter counted 76.5% respondents being of 20-30 years old, 14.5% below 20 and

8.5% of 31-40 years old. Their level of education was in high percentage, having

93.5% respondents of university education and 4.5% of high school. Lastly, from

income expenditure, 40% of the respondents claimed to spend per month between

1001-2000Kr of their incomes in grocery stuff, while 26.5% claimed they spend 500-

1000Kr and 28% spend above 2000Kr). The percentages are summarized in table 3:

Table 3: Demographic frequencies

Characteristics Percentage Gender Male 48%

Female 52% Age <20 14.5%

20-30 76.5% 31-40 8.5%

41-50 0.5% Level of education Secondary school 2%

High school 4.5% University 93.5%

Monthly expenditure <500Kr 5.5% 500 – 1000Kr 26.5% 1001 – 2000Kr 40%

>2000Kr 28%

39


4.2 Reliability testing To check the reliability of our adapted SERVQUAL model, the Cronbach’s alpha was

computed for each of the eight dimensions, both in expectations and perceptions. The

level of acceptance employed, as explained in chapter 3.8, was α=>0.6. Table 4 shows

the reliability scale for all eight dimensions. The reliability scale was also calculated

when each item was deleted from each dimension, in order to see if the deleted item is

affecting the outcome or not. Whenever Cronbach’s alpha increases when an item is

deleted, it shows that item is not the most appropriate to measure that dimension

(Bryman & Bell, 2011). From the table, it can be realized that all the items showed a

lower value of reliability when deleted. By checking the internal reliability of this

result, it helps to determine the credibility of the findings since we are dealing with

multiple items (Ibid.).

Looking at the reliability coefficients (α) of all eight dimensions of expectations,

some dimensions have coefficients slightly above 0.6, like reliability (0.604) and

responsiveness (0.606), which is sufficient based on the α value being =>0.6.

Empathy (0.694) and waiting time (0.672) had higher scores of 0.694 and 0.672

respectively. Other dimensions like assurance and products showed coefficients

higher than 0.7 (0.714 and 0.741 respectively), meaning these dimensions show a true

measure of service quality. The location dimension, on the other hand, had a rather

low reliability coefficient of 0.531 when computed for all of its items. In this case, the

results reported that item LC1 yielded a higher α to the dimension when deleted from

the calculations and so that α, of 0.603, was adopted. Next follows the table with the

results of the Cronbach’s alpha test:

Table 4: Reliability of expectation items

Dimension Cronbach's alpha

for dimensions Tangibles (TN) 0.606 Reliability (RL) 0.604

Responsiveness (RN) 0.606 Assurance (AS) 0.714 Empathy (EM) 0.694 Products (PR) 0.741 Location (LC) 0.603

Waiting time (WT) 0.672

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The next table shows the reliability testing for the items of perceptions. It can be seen

that all items showed a lower value of reliability when deleted, except for WT1 (the

store layout makes it easy for customers to find what they need) which had a higher

value of 0.756, showing it is not the best measure under that dimension. Consequently

that α was adopted. The reliability coefficients of five of the dimensions were in the

desirable frame of α=>0.6, for instance tangibles (0.653), reliability (0.603),

responsiveness (0.613), empathy (0.648) and products (0.666). The location

dimension had, however, a lower reliability coefficient of 0.585, denoting low internal

reliability as in the expectations reliability testing. In this case, the results reported

that item LC2 yielded a higher α to the dimension when deleted from the calculations

and so that α, of 0.616, was adopted. The results can be seen below:

Table 5: Reliability of perception items

Dimension Cronbach's alpha

for dimensions Tangibles (TN) 0.653 Reliability (RL) 0.603

Responsiveness (RN) 0.613 Assurance (AS) 0.609 Empathy (EM) 0.648 Products (PR) 0.666 Location (LC) 0.616

Waiting time (WT) 0.658

4.3 Expectation, perception and gap scores In this part, we computed the arithmetic means for all the items of both expectations

and perceptions. The aim was to measure the gap that exists between expectations and

perceptions.

The items with the highest expectation scores were PR1 (freshness of the groceries)

with 6.33, AS2 (safety of customer transactions with the store) with 6.31 and PR2

(good condition of the products) with 6.27. The lower mean was 4.14 of the RN2 item

(it is okay if the employees are too busy to respond to customer requests promptly).

The overall mean of expectations was computed too and the result was at 5.8,

meaning that expectations of the sample taken are quite high.

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The items with the highest perception scores were AS2 (safety of customer

transactions with the store) with 5.85, RL2 (the store provides its services in time)

with 5.37 and LC3 (offer of convenient parking) with 5.27. The lower mean was 4.21

of the RN2 item (it is okay if the employees are too busy to respond to customer

requests promptly). The overall mean of perceptions was at 4.81, which means that

the actual service perceived by the respondents is quite low. It can be seen that

perceptions in general are lower than expectations, which was anticipated as

Parasuraman et al. (1988) also suggested.

To find out which dimensions of service quality consumers are more satisfied with,

gap scores were computed. According to Parasuraman et al. (1985), the more positive

the P-E score, the higher the level of service quality, and to this extent a higher level

of customer satisfaction. In this regard, the gap scores were computed based on the

difference between consumers’ expectations and perceptions, with the only difference

it was thought as expectations minus perceptions in the calculations (explained in

chapter 3.6.2).

The largest gaps scores were clearly reported on the dimension of waiting time with

1.39, 1.47 and 1.51 scores in each of the three items employed. Other big gaps were

reported in the products dimensions PR1 (freshness of groceries) and PR2 (good

condition of products), scoring 1.32 and 1.14 respectively. In the responsiveness

dimension, RN1 (employees able to handle customer complaints) scored 1.23 and in

the reliability dimension, RL3 (customers counting on employees) scored 1.07.

Lastly, from the assurance dimension, AS3 (politeness of employees) scored 1.08.

The smallest gap was found in item AS2 (safety in transactions with store) scoring

0.46. EM2 (expect employees to know customers’ needs) and LC3 (offer of

convenient parking), both scored 0.49, denoting small gaps as well.

Negative scores were found only in the responsiveness dimension RN2 (okay if

employees are too busy to respond to respond to customers), which scored -0.07 and

location dimension LC1 (stores located in the outskirts of a town/city), which scored -

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0.08. The negative sign in this case means that perceptions score was higher than the

score of expectations. Table 6 shows all means and gap scores:

Table 6: Expectation-perception means and gap scores

Dimension Statements Expectations

scores Perceptions

scores Gap scores Tangibles (TN) TN1 5.18 4.59 0.59

TN2 6.14 5.05 0.65 TN3 5.49 4.71 0.78

Reliability (RL) RL1 6.03 5.01 1.02 RL2 6.05 5.37 0.68

RL3 6.04 4.97 1.07 Responsiveness (RN) RN1 5.71 4.48 1.23

RN2 4.14 4.21 -0.07 RN3 5.88 4.93 0.95

Assurance (AS) AS1 5.90 5.14 0.76 AS2 6.31 5.85 0.46

AS3 6.14 5.06 1.08 Empathy (EM) EM1 5.69 4.83 0.86

EM2 5.10 4.61 0.49 EM3 5.10 4.38 0.72

Products (PR) PR1 6.33 5.01 1.32 PR2 6.27 5.13 1.14

PR3 5.90 5.03 0.87 Location (LC) LC1 4.55 4.63 -0.08

LC2 5.73 5.12 0.61 LC3 5.76 5.27 0.49

Waiting time (WT) WT1 6.06 4.67 1.39 WT2 5.90 4.43 1.47 WT3 6.04 4.53 1.51

Overall means 5.80 4.81 1.02

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4.4 Regression To test our hypotheses concerning the three proposed variables, a regression analysis

was employed for each of the dimensions. The dependent variable (criterion) for this

analysis was the customer satisfaction item (see table 1, chapter 3.6.1) and as

independent variables (predictors) were each time one of the dimensions. Because of

the fact that each dimension has three items, a mean was computed for each of the

dimensions and this mean was used in each test. The names adopted for these means

were PR, LC and WT. Also, this analysis was based on the answers of perceptions

since our interest revolves around the real experience. The hypotheses are presented

below, in parallel with the tables, so as to base the arguments of whether they are

supported or not:

H2: The good physical condition and variety of a grocery store’s products lead to

customer satisfaction

Table 7: Regression analysis for products

Model Summary

Model R R

Square

Adjusted R

Square

Std. Error of the

Estimate 1 0.424a 0.180 0.176 0.972a. Predictors: (Constant), PR

ANOVAa

Model Sum of Squares df

Mean Square F Sig.

Regression 41.000 1 41.000 43.441 0.000b Residual 186.875 198 0.944

1

Total 227.875 199 a. Dependent Variable: CS Are you satisfied with the store you usually visit? b. Predictors: (Constant), PR

Coefficientsa Unstandardized

Coefficients Standardized Coefficients

Model B Std.

Error Beta t Sig. (Constant) 3.303 0.337 9.815 0.000 1 PR 0.430 0.065 0.424 6.591 0.000

a. Dependent Variable: CS Are you satisfied with the store you usually visit?

44


The results for the products dimension indicate that the independent variable is a

rather strong predictor of the criterion variable (customer satisfaction). The R-square

of 0.180 shows a good correlation between the two variables. Beta value of 0.424

shows a positive correlation between the variables, indicating a rather good

contribution to explaining the dependent variable. The significance shows that this

dimension made a statistically significant contribution to the variation of the

dependent variable. PR is statistically significant at the 1% significance level, in other

words, results support the hypothesis H2 at p<0.01 level, reaching the highest level of

significance. The ranges of R-square, Beta value and significance are explained in

chapter 3.8.

H3: The location of the grocery store plays a big role to customer satisfaction

Table 8: Regression analysis for location

Model Summary

Model R R

Square

Adjusted R

Square

Std. Error of the

Estimate 1 0.262a 0.069 0.064 1.035a. Predictors: (Constant), LC

ANOVAa


Mean Square F Sig.


1

Total 227.875 199 a. Dependent Variable: CS Are you satisfied with the store you usually visit? b. Predictors: (Constant), LC



Model B Std.

Error Beta t Sig. (Constant) 4.038 0.382 10.561 0.000 1 LC 0.287 0.075 0.262 3.828 0.000


45


The results for the location dimension indicate that this independent variable is overly

a moderate predictor of the criterion variable. The R-square of 0.069 shows a rather

small correlation between the two variables. On the other hand, the Beta value of

0.262 shows a positive correlation between the variables, indicating a rather good

contribution to explaining the dependent variable. The significance also shows that

this dimension made a statistically significant contribution to the variation of the

dependent variable. LC is statistically significant at the 1% significance level and that

means the results support the hypothesis H3 at p<0.01 level (highest level of

significance).

H4: The time spent in the grocery store is of high importance to customer satisfaction

Table 9: Regression analysis for waiting time

Model Summary

Model R R

Square

Adjusted R

Square

Std. Error of the

Estimate 1 0.373a 0.139 0.135 0.995a. Predictors: (Constant), WT

ANOVAa


Mean Square F Sig.


1

Total 227.875 199 a. Dependent Variable: CS Are you satisfied with the store you usually visit? b. Predictors: (Constant), WT



Model B Std.

Error Beta t Sig. (Constant) 3.862 0.293 13.157 0.000 1 WT 0.355 0.063 0.373 5.663 0.000


46


The results for the waiting time dimension indicate that the independent variable is

also a rather strong predictor of the criterion variable. The R-square of 0.139 shows a

good correlation between the two variables. Beta value of 0.373 shows a positive

correlation between the variables, indicating a rather good contribution to explaining

the dependent variable. The significance shows that this dimension made a

statistically significant contribution to the variation of the dependent variable. WT is

statistically significant at the 1% significance level, meaning results support the

hypothesis H4 at p<0.01 level (highest level of significance).

4.5 Analysis The process of the collected data yielded different results which would need some

interpretation to have a better value. It can be seen from table 3 that our sample was

equally divided among men and women, more of 20-30 years old and representing a

high percentage of University education. The equal gender division was made on

purpose, to have a view at both sexes and the range of age was chosen based on the

fact that authors wanted to know the young studying and working population of

Växjö. The monthly expenditure of the respondents on grocery stores also varied,

showing the difference in importance people give in spending a lot or not too much

money on grocery stores.

In checking the reliability of the items used, the results from the Cronbach’s alpha test

were positive in almost all cases. Assurance and products items scored high

coefficients in both expectations and perceptions, which means that they show a true

measure of service quality. Other dimensions such as tangibles, reliability,

responsiveness, empathy and waiting time also scored within the desired measure of

α, meaning they can be used in the context of grocery stores. However, it was

expected to find some low reliability especially because we are dealing with a lot of

items (Bryman & Bell, 2011). The dimension of location was found to have low

internal reliability in both expectations and perceptions and so the α adopted was each

time when an item was deleted from the calculations. It seems that items LC1 and

LC2 were a bit confusing and should probably have a different wording or even a

different statement to represent the location dimension in its entirety or at least as we

define it in chapter 2.6.1.

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On to table 6, it can be easily realized that expectations of the respondents exceeded

their perceptions. According to Parasuraman et al. (1988), it is usual for expectations

to exceed perceptions and that this means that companies should keep improving their

performance. However, there is not much difference between the scores but generally

expectation scores were higher than perception scores.

The largest gaps scores were reported in the dimension of waiting time and secondly

in the dimension of products. That proves that consumers think of the time spent in

the store as very valuable and the result they get in the stores is not the most

satisfying. As Na et al. (1999) state, satisfaction comes as a consequence of strong

associations, in our case of waiting time with service quality. Also, products

dimension seems to be very important for them, especially in terms of freshness and

good condition, which means that stores should pay a lot of attention to the quality

and the variety of products they offer. This comes in line with the technical dimension

of service quality Grönroos (1984) suggested. Altogether, all the dimensions had at

least one item which had a rather high gap score, meaning consumers expect more; in

reliability, counting on the employees, in responsiveness, handling of customer

complaints and in assurance, politeness of employees for instance.

The smallest gap was found in the assurance item AS2 (safety in transactions with the

store). Expectations as well as perceptions in this item were high, which means that

consumers feel safe in their dealings with the grocery stores and really get what they

ask for. The location item LC3 (offer of convenient parking) noted also a small gap

but in this case, expectations as a mean were not that high and neither was the mean

of perceptions. This can be interpreted in terms that consumers do not hold this offer

as the most important service but they would still prefer to benefit from it, as part of

the overall service experience.

In the whole, perceptions did not meet consumers’ expectations, except for two items.

Responsiveness item RN2 (okay if employees are too busy to respond to respond to

customers) and location item LC1 (stores located in the outskirts of a town/city) noted

negative scores, meaning that perceptions in this case were greater than expectations.

As Fen & Lian (2005) suggest, higher perceptions indicate higher satisfaction since

48


service quality and satisfaction are positively related. Consumers seem not to have

many expectations on these two matters but they acknowledge their existence as part

of the service.

To test hypothesis H1 (below) and from the above:

H1: The smaller the gap between expectations and perceptions, the higher customer

satisfaction is

it can be inferred that hypothesis H1 is true. Positive gaps scores in this study signify

that the actual experienced service consumers get is lower than their expectations,

therefore lower customer satisfaction. As Douglas & Connor (2003) state, it is very

important to understand and measure customers’ expectations, to identify these gaps

in delivering service with quality that could ensure satisfaction. These gaps can occur

because of the poor interaction between customer and service provider (in this case

grocery store) and because consumers are becoming more demanding and do not

tolerate shortfalls in the quality of services (Ibid.). Customer satisfaction is higher

only when these gaps are small or when the perceptions exceed expectations.

Lastly, to test hypotheses H2, H3 and H4 (see chapter 2.7), concerning the three

dimensions we proposed, a regression analysis helped in showing if they were

supported or not. It seems from the empirical data that all the hypotheses are

supported, since the levels of significance in each case report the highest levels of p-

values. In particular, the dimensions of products and waiting time show a better

overall correlation to the concept of customer satisfaction than location but all have a

rather good contribution to explaining this dependent variable. It can be inferred, thus,

that all the hypotheses are supported in a good level.

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5. Conclusions In this chapter, we answer our research question by having a general discussion

based on all the literature and findings. Implications are also presented as well as

the limitations of this research. The chapter ends with suggestions for future

research.

5.1 Discussion After going through a literature review and an analysis of the empirical data we

assembled, we can at last proceed in answering our research question:

Are consumers satisfied with service quality offered by grocery stores?

As the literature suggests, customer satisfaction depends on the difference between

expectations and perceptions. The findings indicate that expectations of the

respondents exceeded their perceptions. The overall mean computed in expectations

for all the dimensions, showed that consumers’ expectations from grocery stores are

quite high. The overall mean of perceptions, on the other hand, was low, giving in

turn the gap scores when compared to expectations. In particular, the largest gap

scores were reported in two of the three dimensions added in the SERVQUAL model.

Both waiting time (time spent in the grocery store) and products (quality and variety)

scored high in expectations whereas low in perceptions. This proves that consumers

give high importance to these dimensions. This does not imply that the rest six

dimensions do not report big gaps. On the contrary, these dimensions also report quite

big gaps, which indicate a lack of service quality.

All the above prove hypothesis H1 which entails that the smaller the gap between

expectations and perceptions, the higher customer satisfaction is. Customer

satisfaction can only be high when these gaps are very small or when the perceptions

exceed expectations, which does not happen in our case. In addition, hypotheses H2,

H3 and H4 were also supported by the tests we ran, giving even more proof that

service quality of grocery stores depends on these dimensions as well as the

dimensions of the original SERVQUAL model. We can therefore conclude that the

service quality perceived from grocery stores is not adequate enough, consumers are

not completely satisfied with what they experience and that there is still room for

more improvement.

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5.2 Implications

The analysis of the empirical results showed that the adapted SERVQUAL model can

be used in the context of grocery stores. The additional dimensions proposed, show a

strong correlation to customer satisfaction, with products and waiting time being of

high importance to overall service quality, along with all the original dimensions of

the model. For this reason, we believe that that our adapted SERVQUAL model can

truly contribute to the field of grocery retailing and add more value as a whole in the

marketing literature.

Also, we believe that our adapted model can be of great use to managers in

understanding how customers assess service quality in the grocery store context and

guide them to enhance customers’ service experiences. In looking at the service

quality gaps, managers can diagnose where performance improvement is needed. By

combining the largest gaps with dimensions which report high expectations, a

manager can see which aspect of service performance should be improved. Equally, if

perceptions are higher, then this means that managers use this feature of the service in

a good way.

All in all, grocery stores should focus on all the dimensions of service quality. Efforts

to improve these dimensions can improve performance, which in turn will lead to

higher perceived service quality and customer satisfaction. Managers should,

therefore, regularly measure service quality to acknowledge customers’ satisfaction

standards and hence make necessary adjustments in performance.

5.3 Limitations There are some limitations in this study as in any research project. The results of this

study cannot be generalised in all studies of service quality because the proposed

dimensions have to do with the grocery store context. Also, the sample size consists

of mostly young respondents, who are mostly university students as well. Another

limitation is that different store sizes may yield different results because consumers

may expect more from bigger grocery stores that they do with smaller ones. Cultural

difference is also a limitation to this study because other countries have different

standards of service quality assessment. This means that this study may only be

51


generalized to Sweden or other Scandinavian countries, which seem more close to

these standards. Despite the limitations mentioned above, carrying these kinds of

studies is always important in order to improve the overall service quality perceived

by customers.

5.4 Suggestions for future research We believe that our adapted SERVQUAL model will be useful for future research

because of the three additional dimensions it incorporates, which proved to be adding

value to the service quality concept of grocery stores. A similar study can be carried

out with a larger sample size so that results can be generalised in a larger population.

We also think further studies can be carried out, with similar sample size, in other

areas of Sweden. Further suggestion includes using different statements-items in the

three dimensions proposed in this study to test the reliability of the dimensions.

Furthermore, removing and adding another dimension could be an option, to test if a

new aspect applies on grocery stores. In the whole, we believe that further research

could be conducted in order to enhance the understanding of these concepts, since

they can be really important in every service industry.

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Växjö Kommun (2012), Statistics, webpage: http://vaxjo.se/Kommun--

politik/Statistik-undersokningar-och-kvalitet/Statistik/, accessed 2012-04-22, 10.40

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http://vaxjo.se/Kommun--politik/Statistik-undersokningar-och-kvalitet/Statistik/

http://vaxjo.se/Kommun--politik/Statistik-undersokningar-och-kvalitet/Statistik/


Appendix - Questionnaire

We are Bachelor students in Marketing from Linnaeus University and we are carrying out a study on how consumers perceive service quality in grocery stores in Växjö. We would be very glad if you could help us by answering the following questionnaire. You should answer each statement as follows: Strongly disagree (SD) Strongly agree (SA) 1 2 3 4 5 6 7 Circle your choice of answer. The questionnaire is divided in two sections; expectations, the ideal service for you (left column) and perceptions, your experience of the services you actually receive (right column). Expectations: The left column deals with your opinion of grocery stores. Please, show the extent to which you think grocery stores “should” possess the following features. We are interested essentially in knowing your expectations, the ideal service you would like to get from grocery stores in Växjö. Perceptions: The right column deals with your perception of the services that you actually experience in grocery stores. Please, show the extent to which the statements reflect your experience of service in grocery stores in Växjö. It will be easier to answer this section if you picture your experience from the grocery store you visit most often.

Scores for expectations Statements

Scores for perceptions

SD SA SD SA1 2 3 4 5 6 7 1. The store has modern-looking equipment 1 2 3 4 5 6 7

1 2 3 4 5 6 7 2. The store has clean and convenient physical facilities 1 2 3 4 5 6 7

1 2 3 4 5 6 7 3. The physical facilities of the store are visually appealing 1 2 3 4 5 6 7

1 2 3 4 5 6 7 4. The store has merchandise available when the customers want it 1 2 3 4 5 6 7

1 2 3 4 5 6 7 5. The store provides its services at the time it promises to do so 1 2 3 4 5 6 7

1 2 3 4 5 6 7 6. Customers can count on the employees taking actions to address their needs 1 2 3 4 5 6 7

1 2 3 4 5 6 7 7. Employees of the store are able to handle customer complaints directly and immediately 1 2 3 4 5 6 7

1 2 3 4 5 6 7 8. It is okay if the employees are too busy to respond to customer requests promptly 1 2 3 4 5 6 7

1 2 3 4 5 6 7 9. Employees of the store respond quickly to customer needs 1 2 3 4 5 6 7

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1 2 3 4 5 6 7 10. Customers are able to trust employees of the store 1 2 3 4 5 6 7

1 2 3 4 5 6 7 11. Customers feel safe in their transactions with the store 1 2 3 4 5 6 7

1 2 3 4 5 6 7 12. Employees in the store are consistently polite with customers 1 2 3 4 5 6 7

1 2 3 4 5 6 7 13. The behaviour of the employees indicates that they understand customer needs 1 2 3 4 5 6 7

1 2 3 4 5 6 7 14. It is realistic to expect employees to know what the needs of their customers are 1 2 3 4 5 6 7

1 2 3 4 5 6 7 15. Employees of the store give customers personal attention 1 2 3 4 5 6 7

1 2 3 4 5 6 7 16. The groceries (e.g. vegetables, fruit, meat, milk, etc) are always fresh and not expired 1 2 3 4 5 6 7

1 2 3 4 5 6 7 17. The products are always in a good condition (not broken, etc) 1 2 3 4 5 6 7

1 2 3 4 5 6 7

18. The store offers the variations of a product-brand the customer needs (e.g. all flavours, sizes, etc) 1 2 3 4 5 6 7

1 2 3 4 5 6 7 19. The store is located in the outskirts of the town/city 1 2 3 4 5 6 7

1 2 3 4 5 6 7 20. The store is located in a central area 1 2 3 4 5 6 7

1 2 3 4 5 6 7 21. The store provides plenty of convenient parking for customers 1 2 3 4 5 6 7

1 2 3 4 5 6 7 22. The store layout makes it easy for customers to find what they need 1 2 3 4 5 6 7

1 2 3 4 5 6 7

23. The store understands that waiting time is important to the customer (waiting time: the whole time spent in the store, including the time waiting for payment) 1 2 3 4 5 6 7

1 2 3 4 5 6 7 24. The store tries to keep the customer's waiting time to a minimum 1 2 3 4 5 6 7

25. Are you satisfied with the store you usually visit? 1 2 3 4 5 6 7 Demographics (choose one option) 26. Gender Male Female 27. Age <20 20-30 31-40 41-50 51-60 61-70 >70 28. Level of education Secondary school High school University 29. Monthly expenditure <500Kr 500 – 1000Kr 1001 – 2000Kr >2000Kr

Thank you for your time!

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