Investigation and Identification of Quality Dimensions in e-Business

Prodromos D. Chatzoglou

1,2

, Antonios Christidis

Vasileios Aggelidis

and Symeon Symeonidis

Dept. of Production and Management Engineering, Democritus University of Thrace, 12 Vas. Sofias Str., Xanthi, Greece

Business School, Hellenic Open University, 18 Parodos Aristotelous Str., Patras, Greece

Keywords: Website Design, Website Usability, Information Quality, Service Reliability, Trust, Service Quality,

Customer Satisfaction.

Abstract: This paper attempts to develop and empirically test a research model that examines the relationship between

various e-service quality dimensions and overall service quality, customer satisfaction and purchase

intension. The adopted quality dimensions are based on SERVQUAL and its extensions proposed by

various researchers which refer specifically to some of the critical factors of electronic services provided by

e-shops. A structured questionnaire has been constructed and electronically distributed. Three hundred and

sixty usable questionnaires were received. SEM (structural equation modeling) was mainly used to analyse

the gathered data and test the validity of the proposed research model. The results showed that the

dimensions of web site design, web site usability, information quality, service reliability, responsiveness,

trust, and personalization are some of the most important dimensions of quality. Almost all of them have

direct or indirect relationship with overall service quality and customer satisfaction which, in turn, have a

strong relationship with purchase intentions. Overall, the results suggest that e-shops should develop

specific marketing strategies to better address the proposed dimensions of e-services.

1 INTRODUCTION

The last few years, companies are experiencing a

huge increment of their electronic transactions

through PCs, tablets, mobile phones. Companies

with experience in e-commerce are starting to realize

that their business success is not depending only on

the prices of their products or the design of their web

site but, also, on the quality of their e-services.

The Greek economy and Greek market are

operating in the maelstrom of an economic crisis

which can be considered worse than the Great

depression at US (Liz Alderman, 2015). On the

other hand, the unlucky decision for capital controls

in July of 2015 (Maliara, 2015) have made the

operation of e-business and especially e-shops one-

way road and a necessity for many Greek companies

in order to find a way out of the limited, because of

austerity measures, market and to show the Greek

products and innovating ideas to the rest of the

world. As a result, online shopping of Greek

consumers is growing (5% in 2015 according to

Kassimi, 2016), despite the fact that they are not

allowed to purchase from foreign firms operating

outside Greece.

In order for e-shops to be competitive in such

local environment and, also, to be competitive with

e-shops from all over the world, they must adopt an

e-business profile that enhance the quality of the e-

services provided to customers. Due to the fact that

quality is an abstract idea which is difficult to be

measured, this research attempted to investigate the

quality dimensions of e-business and especially of e-

shops.

Thus, one of the most important requirements for

the even broader spread of e-business is to ensure a

high level of quality in electronic transactions,

something that will allow companies and users-

consumers realize the advantages of e-business.

Needless to say, there are several questions

regarding the meaning of e-business quality, with

the most important one probably being. "What are

the main criteria that should be used to evaluate the

quality of e-business transactions?"

This paper will attempt to give an answer to each

one of these questions. More specifically, its main

target is to evaluate the quality dimensions of e-

business (especially for e-shops) and to explore

ways to improve them.

Chatzoglou, P., Christidis, A., Aggelidis, V. and Symeonidis, S.

Investigation and Identiﬁcation of Quality Dimensions in e-Business.

DOI: 10.5220/0008167501130119

In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019), pages 113-119

ISBN: 978-989-758-382-7

113

2 LITERATURE REVIEW

Service quality is an elusive and abstract construct

and it is difficult to be measured. The SERVQUAL

model, which was proposed in 1988 by Parasuraman

et al., (2005) is the most used model for measuring

service quality, but it is not the only one.

Nevertheless, most of them tried to measure quality

based on the traditional idea of service without

taking into consideration the realities of e-services.

This also applies to SERVQUAL, but it should be

stressed that, relatively recently, some researchers

extended the dimensions of SERVQUAL in order to

more accurately measure service quality in e-

business as well).

The procedures for providing e-services (e-

business is consisted from a set of e-services) are

considered as quality ones when customers' total

experience (as perceived by each one of them) is

close to their initial expectations. With the explosion

of internet and the number of electronic devices

connected to it, many researchers have tried to give

a clear definition and to propose a valid and reliable

scale for measuring e-service quality. According to

Parasuraman (2005), the definition of e-service

quality (e-SQ) is described as “extend to which a

website facilitates efficient and effective shopping,

purchasing and delivery”.

According to Zeithaml, Parasuraman and

Malhotra (2000), a customer’s opinion regarding an

electronic transaction includes not only the

transaction but, also, post interaction services. For

these reasons, the e-SQ definition includes all phases

of a transaction. The three researchers proposed

many different features, from specific cues to more

general perpetual attributes, to broad dimensions

and, finally, to higher abstractions. Having in mind

mostly web sites, they identified many features and

categorized them into 11 e-SQ dimensions:

(Reliability, Responsiveness, Access, Flexibility,

Easy of navigation, Efficiency, Assurance, Security,

Price knowledge, Site aesthetics, Customization /

personalization).

Parasuraman et al (2005) claims that Zeithaml,

Parasuraman and Malhotra (2000) evaluated service

quality using the 11 dimensions of e-SQ and they

noticed that many customers didn’t answered

questions regarding service recovery (product

returns, problems and how to deal with them and

ways to reach company), mainly because many of

them had never faced any problems and, thus, they

had no experience in service recovery. For these

reasons, they set aside the service recover

dimensions and defined and e-core service quality

scale (E-S-QUAL), which has 4 dimensions

(Efficiency, Fulfillment, System availability,

Privacy). The other three dimensions

(Responsiveness, Compensation, Contact), concern

service recovery, were used for the creation of an e-

recovery service quality scale (E-RecS-QUAL).

The Chaffey and Edgar (2000) redesigned the 22

quality characteristics of SERVQUAL model to

match the case of e-services (Stiakakis and

Georgiadis,2009). According to Blut et al., (2015),

there are four dimensions in e-service quality (with

different weights): website design, security,

customer service, and fulfillment. These dimensions

can be used to identify service quality, customer

satisfaction and also to predict whether customers

will return back for their future shopping.

Latest surveys (Russotti,2015) shows that 81%

of shoppers do online research, while 60% of them

read product reviews, before they buy a product.

The above numbers provide an example of why

quality is so important for electronic transactions.

3 RESEARCH HYPOTHESES

Since SERVQUAL is not a model that was created

for e-services, so remains insufficient to provide a

conceptual model of e-service quality. The 11

dimensions of e-service quality, proposed by

Zeithaml, Parasuraman and Malhotra (2000), and the

e-SQ model, provide an explanation to why most

companies that provide e-services usually cannot

satisfy their customers' demands. This method can

help e-services companies to identify problems and

gaps that can be created in the procedures of an

electronic transaction and propose ways to eliminate

them. The E-S-QUAL and E-RecS-QUAL models

can be considered as more specific, to services and

service recovery, e-SQ methods, and it is a

separation of e-SQ dimensions in two different

sections of e-services: the core e-services and

service recovery.

Thus, empirical research improvements,

proposed by other researchers have been considered

in order to propose a new and improved research

model. Following the guidelines of Voss (2003), the

proposed e-service quality dimensions used by this

research are web design, website usability,

information quality, reliability, responsiveness, trust,

and personalization (it is not claimed that these

dimensions are the only important ones). The

relationship between the proposed e-service quality

dimensions, overall service quality and customer

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satisfaction and, in turn, their influence on

customers; purchase intensions is discussed below.

3.1 Website Design

Web site design is very important (Than and

Grandon, 2002) for online stores. It is the first

picture that a customer has and, many times, the

quality of the web site helps in the creation of a

better e-shop image. Web site design is a description

of the appeal that user interface design presents to

customers (Kim and Lee, 2002). A study that was

performed by Wolfinbarger and Gilly (2003) has

shown that web design related factors are strong

predictors of customer judgment regarding quality,

overall satisfaction and loyalty. The following

hypotheses are then proposed:

H1a. Web site design in an e-shop positively

influences its overall service quality

H1b. Web site design in an e-shop positively

influences customer satisfaction

3.2 Website Usability

The usability of a web site (user friendliness) is also

a very important factor for determining customers'

opinion regarding service quality of an e-shop. The

site must be easy to navigate with the minimum of

scrolling and availability of instructions of

navigation. Parasuraman et al (2005) included

website usability as one of the four dimensions of

his proposed E-S-QUAL model. The following

hypotheses are then proposed:

H2a. Web site usability in an e-shop positively

influences its overall service quality

H2b. Web site usability in an e-shop positively

influences customer satisfaction

3.3 Information Quality

Another very important factor that influences

customer opinion regarding an e-shop has to do with

the information presented in the site (how useful,

accurate and up dated is that information). Li et al

(2002) consider that information quality is very

important as far as the quality that customers receive

from a web site is concerned. The following

hypotheses are then proposed:

H3a. Web site information quality in an e-shop

positively influences its overall service

quality

H3b Web site information quality in an e-shop

positively influences customer satisfaction

3.4 Reliability

It represents the ability of the web site to fulfill

orders correctly, to deliver them promptly and,

probably the most important nowadays, to keep

customers' personal information secure (Kim and

Lee, 2002). For Zhu et al (2002), online stores must

provide error free services and secure financial

transactions in order customers to feel secure and

comfortable when using the e-shop site for

shopping. The following hypotheses are then

proposed:

H4a. Reliability in an e-shop positively

influences its overall service quality

H4b. Reliability in an e-shop positively

influences customer satisfaction

3.5 Responsiveness

Customers expect that e-shops will respond to their

inquiries as soon as possible. Automated or human

initiated emails answering customers' specific

questions, and showing an interest from e-shop to

solve customer problems, are part of this. It

describes how often e-shop provides services, like

customer inquiries and information retrieval, that are

important for its customers (Parasuraman et al.,

1988, Kim and Lee, 2002). The following

hypotheses are then proposed:

H5a. Responsiveness in an e-shop positively

influences its overall service quality

H5b. Responsiveness in an e-shop positively

influences customer satisfaction

3.6 Trust

Many studies have emphasized the importance of

trust between customers and e-shops (McKnight et

al., 2002). According to Kimery and McCard (2002),

trust is defined as customers’ willingness to accept

vulnerability in a transaction, between him and the

e-shop, based on their positive expectations

regarding future e-shop behaviors. The following

hypotheses are then proposed:

H6a. Trust in an e-shop positively influences its

overall service quality

H6b. Trust in an e-shop positively influences

customer satisfaction

3.7 Personalization

This is customers’ perception of the individual

attention and differentiated service that are created

to meet customers' individual needs and preferences.

Investigation and Identiﬁcation of Quality Dimensions in e-Business

115

An example of this is the personalized website

pages, the personalized contents and the customized

products. Also, the lack of real time interactions can

be a reason which will prevent potential customers

from buying from an e-shop (Yang and Jun, 2002).

Wolfinbarger and Gilly (2003) have also studied this

issue and showed that customer service influences

customer satisfaction. The following hypotheses are

then proposed:

H7a. Personalization in an e-shop positively

influences its overall service quality

H7b. Personalization in an e-shop positively

influences customer satisfaction

3.8 Purchase Intention

Various studies have suggested that customers’

perception of service quality and satisfaction have

strong influence on positive purchasing intention.

For Rust and Zahorik (1993), overall service quality

and customer satisfaction positively affect

profitability and market share. Llusar et al. (2001)

suggest that customer satisfaction is the mediator

between perceived quality and purchase intensions.

The following hypotheses are then proposed:

H8. Overall service quality in an online store

positively influences customer satisfaction.

H9. Overall service quality in an online store

positively influences customer purchase

intention.

H10. Customer satisfaction with an online store

positively influences purchase intention.

4 RESEARCH METHODOLOGY

A structured questionnaire was constructed in order

to collect the necessary primary data which will

allow researchers to empirically test the validity of

the proposed research model. The scales used to

measure the incorporated factors are adopted from

relevant previous studies with minor changes in

order to comply with the specific research

conditions. Some of the factors (web site design,

reliability, responsiveness) are based on the

SERVQUAL model, taking into consideration the

improvements proposed by other researchers for the

case of e-services (Parasuraman et al, 1998; Kim and

Lee, 2002). All items were measured with a five-

point Linkert scale (ranging from 1= strongly

disagree to 5=strongly agree).

The questionnaire was constructed and uploaded

in Google Forms. This method was selected because

it is easy to construct the survey instrument, while it

can be addressed to multiple recipients in many

different ways at the same time (web link, email,

social media).

Three hundred and sixty valid questionnaires

were collected, number that can be considered

sufficient in order to be used as input for the

statistical analysis. Most of the participants were

men (61%), between 30 and 60 years old, highly

educated and with good to very good electronic

device experience. Most of them (61%) changed

their e-shopping behavior after the enforcement of

capital controls (July 2015).

5 RESULTS

The results (Table 1) show that website design,

information quality, service reliability,

responsiveness, and trust, are recognized by most of

the participants as very important quality factors-

dimensions (mean scores between 4,41 - 4,81).

Especially for trust, the mean is 4,81, very close to

5, which reflects the importance of security and

privacy in electronic transactions. Although

personalization mean score is lower (3,72), it is still

considered as an important quality dimension. It is

important to highlight that the selected quality

dimensions play an important role as far as the

overall perceived, by the customer, service quality

(mean=4,37) and customer satisfaction by an e-shop

(mean=4,36). Finally, the perception of quality

offered by an e-shop influence customers' purchase

intension (mean=4,41).

5.1 Factor Analysis

The measures used to test the validity and reliability

of the scales used are Factor Loading (Son,2011),

Kaiser-Meyer-Olkin (K.M.O) test of adequacy

(Hinton et al ,2004), Total Variance Explained

(TVE) (Nandagopal et al, 2007), Cronbach a-value

(De Vellis, 2003), (Nunnally, 1978). The results of

this analysis (Table 1) support the claim that all

factors are both valid and reliable.

5.2 Correlation Analysis

The results of the correlation analysis (Spearmans' r)

suggest that most of the demographic characteristics

of the participants (gender, age, familiarity with e-

transactions, number of e-transactions after the

capital controls) are not correlated with the factors

incorporated in the proposed model. Only education

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Table 1: Factor Analysis.

Factor Loadings

(min, max)

K.M.O

T.V.E

Cronbach

α-value

Mean

St. Dev

Website Design (WD)

.681 - .882

.628

63.029

.699

4,49

.461

Information Quality (IQ)

.675 - .840

.738

55.033

.789

4,57

.377

Website Usability (WU)

.748 - .856

.760

65.121

.807

4,07

.608

Service Reliability (SR)

.656 - .720

.795

55.916

.700

4,61

.321

Responsiveness (R)

.740 - .852

.659

65.908

.707

4,41

.472

Trust (T)

.738 - .873

.630

65.029

.722

4,81

.312

Personalization (P)

.806 - .902

.689

74.595

.824

3,72

.802

Overall Service Quality (SQ)

.714 - .765

.629

54.443

.681

4,37

.406

Customer Satisfaction (CS)

.836 - .919

.753

85.222

.913

4,36

.647

Purchase Intention (PI)

.804 - .907

.676

73.784

.815

4,41

.575

seems to have a weak relationship with trust and

service reliability.

As far as the correlations between the factors of

the model are concerned, it is very important that

only information quality and trust seems not to be

related with overall service quality, customer

satisfaction and purchase intention. This results is

not necessarily negative. It probably indicates that

since trust level is very high (4,81), it is not play any

role. It is the lack of trust what usually negatively

affects customer satisfaction and their purchase

intention. The same applies for information quality.

Once again, it is found that overall service quality

and especially customer satisfaction are the two

factors that are mainly correlated with purchase

intention (r=,470 and ,626 respectively).

5.3 Structural Equation Modelling

The proposed model was tested using the Structural

Equation Modeling (SEM). The relations of the

research model are presented in Figure 1, where path

coefficients and the relationships between the factors

of the proposed model are included.

The Structural Equation modeling (SEM)

examines the relationships between one or more

independent or dependent variables, continue or

discrete (Ullman & Bentler, 2012) . There are a wide

range of indices in order to have an indication of

goodness of fit. These indices are (Svensson, 2004;

Byrne, 2001): Minimum Sample Discrepancy /

Degrees of Freedom (CMIN/DF), Relative Fit Index

(RFI), Comparative Fit Index (CFI), Normed Fit

Index (NFI), Root Mean Square Residual (RMR),

Root Mean Square Error of Approximation

(RMSEA). The results (Table 2) show that based on

these indices the overall goodness of fit of the

proposed model is very good.

The predictive power of the model can be

considered as very good, since all independent

factors can explain 52% of the variation of the

dependent factor (purchase intention - PI). They can

also explain 34% and 30% of the variations of

service quality and customer satisfaction

respectively.

Further, the results highlight the strong (.62)

direct relationship between customer satisfaction and

purchase intention, as well as the weak (.21) direct

relationship between overall service quality and

purchase intention. Most of the other factors of the

model (except service reliability and trust) are

related with purchase intention only indirectly

(through their relationship with overall service

quality and customer satisfaction). Therefore, one

could conclude that based on the direct relationship

between the factors of the model, only hypotheses

H2a, H5a, H7b, H8, H9 and H10 are accepted. The

other eleven hypotheses are rejected.

6 SUMMARY AND

CONCLUSIONS

Although all the factors included in the proposed

model have been studied by different researchers, it

is the first time that their combined effect on

Customers' Satisfaction and their Purchase Intention

is examined in one paper. Also, it is the first time

that their effect is examined in a country where

capital controls have been imposed. These are the

two main factors that distinguish this research from

other similar researches.

Investigation and Identiﬁcation of Quality Dimensions in e-Business

117

Figure 1: The SEM Model.

Table 2: Indices indicating goodness of fit in SEM.

CMIN/DF

RFI

CFI

NFI

RMR

RMSEA

< 5

> .900

< .100

.661

.911

1.000

.945

.000

The results of this study have several important

implications for managers as it investigates and

identifies the quality dimensions that are essential in

order to operate a quality e-shop and help to improve

its performance.

The findings of this research show that more than

60% of the participants increased their purchases

from e-shops after the imposition of capital controls

in 2015. It seems that customer satisfaction is the

main factor directly affecting purchase intention. It

is important, therefore, to understand the factors that

affect customer satisfaction. Based on the findings

of this survey, personalization, website usability and

overall service quality seem to be the main factors

affecting customer satisfaction. Thus, developers

should pay special attention to these factors. Of

course, this does not mean that the other factors

should be neglected, since they play an important

indirect role.

Concluding, Greek companies, which in most of

the times operate an e-shop in parallel with their

physical shop, must have a clear strategy in order to

offer high level of quality e-services. They must

achieve this in order to have and maintain a number

of dedicated customers. The continuous evaluation

of quality dimensions will help companies to focus

on their target which is to provide high quality of e-

services. This will allow companies to be

competitive in the electronic market.

This study has limitations that are noteworthy.

The size of the sample of this study is relatively

small (360 participants) and cannot be considered as

representative of the Greek population. Further, this

study did not incorporate the actual purchase

behavior in the proposed research model. However,

this limitation can be considered as relatively

unimportant since substantial empirical support

exists between intention and behavior.

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