Service quality dimensions in technology-based banking: impact on customer satisfaction and loyalty – Document – Gale Academic OneFile
With the emerging a new phenomenon of Internet, the banks have gone through the traditional process and have reached the stage of modern banking in their career. Following this transition, the banks became familiar with numerous banking technologies. However, the main concern in the use of these technologies was the quality assessment and their impact on customers’ satisfaction and loyalty. Therefore, the objective of the present study is to provide a model which is able to assess the quality of any kind of banking technologies (whether the technologies that are already in use or those that will be used in the future). Firstly, exploratory factor analysis (EFA) method was used to identify the service quality dimensions within technology-based banking. Then, the effect of each variable on customers’ satisfaction and loyalty was investigated using structural equations modeling employing LISREL software. Following exploratory factor analysis, 8 dimensions of easiness, assurance, security, customization, comprehensiveness, convenience, support services and the employee knowledge were identified as the service quality dimensions within technology-based banking. Finally, the effect of each of the eight dimensions on the customers’ satisfaction and loyalty was investigated using structural equations modeling.
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INTRODUCTION
Increases in labor costs and advances in technology encourage
service firms to explore technology -based service options, which enable
customers to produce services independent of service employees [38].
Parasuraman [42] suggested, technology can dramatically change these three
relationships: company-customer, employee-customer, and company-employee
[37]. Banking has always been a highly information intensive activity that
relies heavily on information technology (IT) to acquire, process and deliver
the appropriate information to all relevant users and differentiate their
products and services [26]. In fact, rise of information technologies and the
internet in particular, have changed the consumption process of retail
banking as human-human interactions in service delivery is becoming
increasingly redundant. So traditional banking or branch banking is
increasingly being replaced by the technology-based banking [23]. Some of the
most popular form of technology-based banking are Internet banking (IB), ATMs
and telephone banking (TB).
With an increase in using technology- based banking technologies
and a change in the pattern of behavior in banks customers to apply these
tools more, the need for measuring the customers certainty and trust in using
these services has increased. Regarding that the presented Iranian bank
services are almost the same and similar for the customers in all of the
banks, the bank managers must make themselves distinct in the method of
customers serving from other competitors in order to be able to continue
their competition to gain customers satisfaction and loyalty. Based on the
performed researches and the presented theories, satisfaction and loyalty are
regarded to be among the most important factors in the evaluation of a
company or an organization’s performance. These two factors also have a
direct and positive influence on the amount of trust and certainty of the
customers in the company [9]. Therefore, it is necessary and essential to
recognize those factors of technology-based banking influencing the amount of
customer satisfaction and loyalty. The most influential factor on
customers’ satisfaction and loyalty in service marketing is the quality
of presented services. The more is the understood quality by the customer,
the more satisfied the customer would be. Therefore, managers of the service
businesses (such as banks) must recognize the dimensions demonstrating the
quality of the presented services in order to evaluate the amount of this
quality by measuring these factors.
Most of the performed studies on the quality of services in modern
banking have only sufficed to a determined dimension of the banking; for
instance, have paid attention to the service qualities of internet banking,
telephone banking, or ATM based banking evaluation. The concluded results
have been limited to that specific area of modern banking [1,15]. Performing
a research studying the quality of services dimension in the technology-
based banking (regardless of the technology type) and measuring its effects
on the customers’ satisfaction and loyalty is completely necessary. The
results of such a research can be generalized to different applied
technologies in presenting banking services. These results can even be
applied for the yet unborn serving technologies in the future. Therefore, the
purpose of this research is to recognize the quality dimensions of the
banking services, and to evaluate its effects on customers’ satisfaction
and loyalty. We are to present a model which is measurable for each type of
the technology- based services.
Literature review:
Service quality:
Service quality has been identified a s a critical success factor
for organizations to build their competitive advantage and increase their
competitiveness [46]. Service quality is dfined as the gap between
customers’ expectation of service and their perception of the service
experience [34]. Parasuraman et al. [42] developed a multiple-item scale,
SERVQUAL, for measuring service quality and argued that service quality, as
perceived by customers, originated from a comparison of customers’
expectations and their perceptions of the performance delivered by the firm
[30]. The five dimensions of SERVQUAL are:
(1) tangibles, which pertain to the physical facilities,
equipment, personnel and communication materials
(2) reliability, which refers to the ability to perform the
promised services dependably and accurately
(3) responsiveness, which refers to the willingness of service
providers to help customers and provide prompt service
(4) assurance, which relates to the knowledge and courtesy of
employees and their ability to convey trust and confidence; and
(5) empathy, which refers to the provision of caring and
individualized attention to customers [46].
According to previous studies on retail banking industry, it is
confirmed the link between service quality, productivity, reduced costs and
profitability [41]. Herington and Weaven [29] find that IT-based services
indirectly impact upon a customer’s perceived service quality and
satisfaction, and also they find support for service and product quality
impacting upon the reputation ofinancial institutions. Recent research also
shows that service quality delivery has a significant positive impact on
customers’ attitudes and behavioral intentions and on a company’s
financial outcome [51].
Service quality in technology-enabled services:
The rise of internet-based services has changed the way that firms
and consumers interact. E-service is conceptualized as an interactive
information service providing a mechanism firms to differentiate their
service offering and build competitive advantage [29]. In case of
technology-enabled services, research has identified new dimensions of
service quality (different from the traditional service quality dimensions),
such as automated search, communication among customers, information
acquisition, content, mass customization, and ease of use [23]. Bressolles
and Durrieu [6] identified: Quality and quantity of information, ease of use,
website design and aesthetic elements, reliability and respect of the
commitments, security and privacy, offer interactivity as the crucial
dimensions of e-service quality in the case of internet-enabled businesses.
E-service quality can also be considered from the perspective of process,
outcome and recovery quality [13]. Table I shows the e-service quality
measurement in prior studies.
The other important research areas related to technology-enabled
services are, Self-service technology (SST) and call centers (customer
service). With technological interfaces, SSTs enable customers to produce a
service independent of direct service employee involvement. Additionally,
integrated with internet, other SST options will provide a wide variety of
self-service possibilities. Examples of SSTs include interactive kiosks,
automated teller machines (ATMs), self-service banking by internet or the
telephone, electronic funds transfer by web and so on [12]. Consumer
perceptions of service quality vary depending on the type of SST used [15].
Dimensions of service quality for call centers, are adaptiveness, assurance,
offering of explanations, empathy, authority, educating customers,
personalization [8,45,22] and also customer feedback, customer focus and time
taken to respond are the other dimensions of call centers’ service
quality [18,19,22,23] In case of electronic banking, Rod et al. [46]
considered banking service quality with respect to technology use, such as
ATMs, telephone, and the internet and identified six dimensions. They were
convenience/accuracy; feedback/complaint management; efficiency; queue
management; accessibility; and customization. Lee and Lin [36] offered
another model with five dimensions of service quality: Website design,
Reliability, Responsiveness, Trust and Personalization. For Online banking
Bauer et al. (2006) found out the following dimensions of service quality:
(1) security/trustworthiness
(2) basic services (core services category)
(3) cross-buying services
(4) added value (additional services category)
(5) transaction support and
(6) responsiveness (problem-solving services category).
Besides these other dimensions identified for technology banking
are: reliability, responsiveness, web usability, security, trust, information
quality, access, service recovery flexibility and customization/
personalization [40,55,22,23].
Customer satisfaction and loyalty:
Service firms focus on achieving customer satisfaction and loyalty
by delivering superior value, an underlying source of competitive advantage
[2]. Customer satisfaction is often seen as the long-term success factor to
an organization’s competitiveness [55]. Satisfaction refers to a global
outcome assessment of the extent to which customers are pleased and have
positive emotional evaluations of suppliers [21]. The general consensus is
that higher customer satisfaction leads to higher levels of repurchase
intent, customer advocacy, and customer retention [53]. Customer satisfaction
is also considered from a cumulative satisfaction perspective and is defined
as customer’s overall experience to date with a product or service
provider. Most of the customer satisfaction studies are now using this
cumulative satisfaction concept [23]. Another important customer metric is
customer loyalty. Creating and maintaining customer loyalty has become a
strategic imperative for service firms in recent years [53] because high
loyalty coincides with consumers’ positive behavioral intentions, such
as spreading positive word-of-mouth, increased repurchasing intentions, and a
willingness to pay price premiums [43].
Impact of service quality on customer satisfaction and loyalty:
Satisfaction and quality are two concepts that are the core of
marketing theory and practice. The key to sustainable competitive advantage
lies in delivering high quality service that will result in satisfied
customers [32]. E-service quality is related to user satisfaction and
information systems (IS) success in the IS field, and is also related to
customer satisfaction, retention and loyalty in the marketed [58,14,16,47].
Prior studies generally support a positive relationship between e-service
quality and customer outcomes, such as channel satisfaction, user loyalty and
positive word-of-mouth [38]. Table II summarizes priofindings regarding the
relationship between the e-service quality dimensions and customer
relationship outcomes. According to Kim and Kim [33], e-service quality and
satisfaction are sigficant predictors for loyalty. In case of automated
banking service quality dimensions have been found to affect customer
satisfaction and loyalty [23]. In light of all these considerations the
following hypothesis is proposed:
H1: Generic service quality dimensions of technology-based banking
have direct positive effect on customer satisfaction.
H2: Generic service quality dimensions of technology-based banking
have direct positive effect on customer loyalty.
Besides that customer satisfaction also affects customer loyalty.
There is strong evidence of an overall positive main effect of the
relationship between customer satisfaction, as an antecedent, on loyalty
intentions and customer behaviors [53]. Research in different industries have
investigated the relationship between customer satisfaction and customer
loyalty–durable products, non-durable products, and services [20]; multiple
industries [21] B2B [53]; online gamers [48]; high-contact service industries
[57]; mobile communications [35]; e-retailers [43]; automobile [7] IT [50];
Coffee shops [49]; restaurants [25]; health care [11]; Banking [22,23,33]. In
light of all these considerations the following hypothesis is proposed:
H3: Customer satisfaction has a direct positive effect on customer
loyalty.
Methodology:
Measurement instrument:
The survey instrument was developed based on literature review
[22,23,33,32,12,15,45]. The variables included in the study have been adapted
from the existing literature. As we are not considering a specific technology
like internet, ATM or telephone, but treating the technology in generic terms
the items used were adopted from different studies. The measurement
instrument consists of three sections:
(1) 27 items related to Service quality items (including
technology-enabled service quality, customer service, problem solving
capabilities)
(2) 4 items related to customer satisfaction and
(3) 3 items related to customer loyalty.
Sampling and data collection:
We collected data from the all students of Islamic Azad University
(Ahwaz Branch) in IRAN. This student sample was chosen because they are heavy
users of technology banking. Students are the most innovative users of
technology [24]. 700 questionnaires were distributed online and 560 of which
were usable; therefore, the rate of return of questionnaires is calculated
08. The descriptive statistics of the respondents’ demographic
characteristics were analyzed and presented in Table III. Table IV shows the
frequency of use of types of technology-based banking.
Data analysis and results:
Exploratory factor analysis:
In the first stage an exploratory factor analysis was performed on
sample using the 27-variables related to the service quality of technology
banking. The criteria used for factor extraction is two fold, i.e. the eigen
value should be greater than one but more importantly the factor structure
should be meaningful, useful and conceptually sound [44].
Prior to the extraction of the factors, several tests should be
used to assess the suitability of the respondent data for factor analysis.
These tests include Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy,
and Bartlett’s Test of Sphericity. The KMO index, in particular, is
recommended when the cases to variable ratio are less than 1:5. The KMO index
ranges from 0 to 1, with 0.50 considered suitable for factor analysis. The
Bartlett’s Test of Sphericity should be significant (p<.05) for
factor analysis to be suitable [52]. The value of KMO and Bartlett’s
Test is separately calculated, which is shown in Table V.
Results of the factor analysis are shown in Table VI and fig1.
On examining the content of the items making up each of the
dimensions (factors) we label the factors as shown in Table VII and provide
concise definitions for the dimensions:
1) Easiness: this means that users can easily learn how to work
with the technology and use it.
2) Assurance: this means that technology works true.
3) Security: safety in using technology, proper handling of
information and quality information.
4) Customization: to make (something/services) according to a
customer’s individual requirements and needs.
5) Comprehensiveness: this means that the technology must be
capable of providing a wide range of customer needs.
6) Convenience: convenience of using technology over the employees
as well as speed and time of using technology.
7) Support services: the service provided to customers during
problem situations and through call centers.
8) Employee knowledge: the amount of employees’ information
and knowledge to solve customer problems.
Confirmatory factor analysis:
After identifying eight clear factors through exploratory factor
analysis, the next stage is to confirm the factor structure on sample.
Structural equation modeling (SEM) using Lisrel 8.80 was used to perform the
confirmatory factor analysis. Confirmatory factor analysis revealed that the
measurement items loaded in accordance with the pattern revealed in the
exploratory factor analysis.
Fitness of research model:
Fitness is the suitability and adequacy of data for the
investigated model, which means if fit indices indicate the fitness of the
model; the data had been suitable and adequate for analysis and conclusion of
relationships in the model. In other words, fitness of the model determines
the degree which supports the sample variance-covariance data of the
structural equation model [3]. Therefore, we examined fit indices. The
calculated values of these indices are given in Table VIII and indicate a
relatively good fitness of the model.
The method to analyze data and results:
In this study, the obtained information was analyzed using the
inferential statistical method, and the statistical technique of structural
equation modeling (analysis of the confirmed path) and confirmatory factor
analysis was used through LISREL 8.80 software. After Confirmatory Factor
Analysis and ensuring about significance of the coefficients between latent
variables (factor loads) and the measured variables (items of the
questionarie) as well as the confidence in the model fitness, research
hypotheses will be tested. That is, the significance of latent variable path
coefficients of will be examined using T-Student test. Since the confidence
level of 0.95 or the error level of 0.42 is considered in this research, the
positive path coefficients are characterized by the above significant 1.96
value of the statistic t and their associated research hypothesis will be
confirmed. The results from the confirmation or rejection of the hypotheses
are presented in Table X. Additionally, from Table IX, correlation between
constructs ranged from 0.05 to 0.69, with the correlations of no pair of
measures exceeding the criterion (0.9 and above) [28]. Empirical support thus
exists for the discriminant validity of the measures.
Discussion and managerial implications:
The present study intended to provide a model which is able to
assess service quality dimensions related to any kind of banking technologies
(i.e. irrespective of the technology being used by the banks for service
delivery). The model obtained in the present study was used to identify the
service quality dimensions regardless the applied banking technology,
therefore it is considered as a general model which is applicable to any kind
of banking technology. The dimensions identified in this study are: easiness,
assurance, security, customization, comprehensiveness, convenience, support
services and the employee knowledge. These dimensions will act as guidelines
for the managers of banking services as it will help them to understand the
particular dimensions that customers consider while evaluating the service
delivery process of banks using technology. The various dimensions of service
quality identified in this study should be viewed as levers of improving
bank’s perceived service quality in the minds of its customers. However,
the degree of emphasis placed on these dimensions depends on the objectives
of the banks. In a performed research by Ganguli et al. on the obtained
dimensions, they have found the four dimensions of security, convenience,
easiness, and customer services. Al-Hawari et al. have also referred to the
three dimensions of reality, concreteness, and responsiveness as the service
quality dimensions. Dean has also referred to supporting services,
convenience and certainty factors. According to the performed study, almost
the majority of the researchers have generally measured the easiness,
certainty, convenience, supporting services, and the employees’
knowledge factors as the dimensions of service quality. Thus, our research
has also introduced three variables of safety (safety and certainty were
considered as one variable in previous researches), customization, and
comprehensiveness as effective variables on service quality. The effect of
these eight dimensions is evaluated on the customers’ satisfaction and
loyalty in the remaining parts of this research. The results show that the
two variables of customization and comprehensiveness have not effected the
customers’ loyalty. The hypothesis of customization effect on customer
satisfaction was also rejected. Based on the obtained model, the bank
managers and the researchers can determine the applied technology in banking
to measure the quality, considering these eight dimensions. The bank managers
must keep in mind that ignoring the dimensions of service qualities and their
effect on customers’ satisfaction can cause bank customers’ lack of
satisfaction. Considering that we have recognized the service qualities
dimensions in the technology-based banking in this research regardless of the
applied technology by the bank, this model is therefore applicable to
different banking technologies.
ARTICLE INFO
Article history:
Received 12 August 2013
Received in revised form 24 October 2013
Accepted 5 October 2013
Available online 14 November 2013
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[60] Zeithaml, V.A., A. Parasuraman, & A. Malhotra, 2002.
Service quality delivery through web sites: a critical review of extant
knowledge. Journal of the Academy of Marketing Science, 30(4): 362-76.
(1) Amin Mojoodi (Ph.D. Student), (2) Nadereh Sadat Najafizadeh
(Ph.D.), (3) Paria Ghasemi
(1) Department of Business Management, Ahwaz Branch, Islamic Azad
University, Ahwaz, Iran
(2) Department of Business Management, Arak Branch, Islamic Azad
University, Arak, Iran
(3) Department of Business Management, Persian Gulf International
Educational Branch, Islamic Azad University, Khoramshahr, Iran
Corresponding Author: Amin Mojoodi (Ph.D. Student), Department of
Business Management, Ahwaz Branch, Islamic Azad University, Ahwaz, Iran
Table I: E-service quality measurement in prior studies
Authors Dimensions of e-service quality
Jun et al. [31] Reliable/prompt responses,
attentiveness, and ease of use
Parasuraman et al. [42] Privacy/security; information
content and availability ;
website design; ease of use;
and reliability/fulfillment
Yang and Fang [56] Ease of use; usefulness
Dabholkar [17] Speed of delivery; ease of
use; reliability; enjoyment;
and control
Gounaris et al. [22] Customer service; privacy/
security; website design; and
fulfillment/reliability
Zeithaml et al. [60] Information availability and
content, ease of use, privacy/
Security, graphic style and
fulfillment/reliability.
Lee and Lin [36] Web site design, reliability,
responsiveness, trust, and
personalization
Barnes and Vidgen [4] Tangibles, reliability,
responsiveness, assurance,
empathy
Wolfinbarger and Gilly [54] Fulfillment/reliability,
website design, privacy/
security, customer service
Yoo and Donthu [56] Ease of use, aesthetic design,
processing speed, security of
personal arfilnancial
information
Bauer et al. [5] Responsiveness, reliability,
process, functionality/
design, enjoyment
Carlson and O'Cass [10] Graphic quality, Clarity of
layout, Attractiveness of
selection,information quality,
Ease-of-use, Technical
quality, Reliability,
Functional benefit, Emotional
benefit
Table II: Prior studies about relationship between the e-service
quality dimensions and customer relationship outcomes
Articles Independent Dependent Result
variable (s) variable (s)
Rod et al. [46] Overall internet Satisfaction +
banking service
quality
Gounaris et al. [27] e-service quality Satisfaction +
and Loyalty
Lee and Lin [36] e-service quality Satisfaction +
Carlson and O'Cass [10] e-service quality Satisfaction +
and Loyalty
Yen and Lu [58] e-service quality Satisfaction +
and Loyalty
Sabiote et al. [47] e-service quality Satisfaction +
Kim and Kim [33] e-service quality Satisfaction +
and Loyalty
Table III: Demographic characteristics of respondents
%
Gender
Male 59.9
Female 40.1
Age
20 years and less 3.9
21-27 years 36
28-34 years 27.6
35-41 years 17.5
42-48 years 11
49 years and more 4
Education
Associates Degree 26
Bachelor's degree 51
Postgraduate education 23
Monthly income
Less than $400 42.8
Between $401-700 19.8
Between $701-1000 31.4
Greater than $1000 6
Period for which respondents are customers of their bank
Less than 6 months 11.9
Between 6-12 months 23.7
More than 1-up to 3 years 28.7
More than 3 years 35.7
Note : Adapted from SPSS
Table IV: Frequency of use of types of technology-based banking
More than 20 10-20 times 5-10 times
times per month (%) per month (%) per month (%)
ATM 12.8 35.7 24.8
IB 11 20.6 25.7
TB 13.2 21.5 28.3
Others 19 37.5 26.3
(mainly
credit card,
POS
Rarely (less Never (%)
than 5 per
month) (%)
ATM 19 7.7
IB 24 18.7
TB 18.6 18.4
Others 13.7 3.5
(mainly
credit card,
POS
Note: Adapted from SPSS
Table V: Kaiser-Meyer-Olkin Measure of Sampling
Adequacy and Bartlett's Test of Sphericity (SPSS Output)
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure .799
of Sampling Adequacy.
Bartlett's Test Approx. Chi-Square 1.103E3
of Sphericity df 451
Sig. .000
Table VI: Rotated Component Matrix for technology-based service quality
Rotated Component Matrix (a)
Component
1 2 3 4 5
q1 .163 .835 -.073 .082 .058
q2 -.015 .796 .281 .205 .218
q3 -.017 .609 .520 .043 .222
q4 .067 .365 .556 -.037 -.007
q5 .003 .007 .776 .078 .127
q6 .126 .075 .649 .121 -.027
q7 -.068 .162 .189 -.041 -.061
q8 .001 .128 .112 -.108 .367
q9 .139 .099 .044 -.012 .783
q10 .064 .222 .102 .071 .757
q11 .000 .374 -.173 .091 .073
q12 .139 -.057 .121 .066 .068
q13 .125 -.095 .133 -.014 .276
q14 .261 -.042 .009 .759 .083
q15 .197 -.054 -.143 .534 .091
q16 .001 .133 .172 .650 .085
q17 -.008 .172 .026 .597 -.074
q18 -.006 .006 .025 .772 .003
q19 .638 .290 -.107 -.188 -.314
q20 .691 .134 .113 -.205 -.016
q21 .674 .266 -.036 -.083 .064
q22 .709 -.045 .238 .126 -.003
q23 .629 -.130 -.023 .203 .198
q24 .723 -.034 -.051 .040 .004
q25 .352 .156 .016 .116 .031
q26 .613 .061 -.019 -.047 .248
q27 .165 .174 .083 .176 .133
Component
6 7 8 9
q1 .184 -.034 .053 -.017
q2 .051 -.028 .185 .088
q3 .070 .087 .130 -.102
q4 .111 -.056 .008 .508
q5 .001 .021 .141 .151
q6 .319 .184 -.126 -.258
q7 .814 .008 .124 .104
q8 .565 .117 .112 .079
q9 .091 -.024 .221 .047
q10 .022 .243 -.144 .034
q11 .355 .657 .014 .117
q12 .132 .710 .053 .155
q13 -.137 .544 .394 -.027
q14 .115 .251 .010 -.013
q15 .435 .066 -.428 -.167
q16 .057 -.024 -.024 .267
q17 -.034 .063 .313 -.112
q18 -.114 .018 .044 -.077
q19 -.155 .409 -.052 -.034
q20 -.224 .340 -.071 -.020
q21 .019 .242 .063 .129
q22 -.039 .181 .025 -.073
q23 -.042 -.076 .048 .237
q24 .067 -.056 .202 .148
q25 .151 .012 .644 .197
q26 .269 -.200 .211 -.068
q27 .190 .228 .616 -.179
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 13 iterations.
Table VII: Rotated factor matrix and dimensions
for technology-based service quality
Factors Measurement Factor Cronbach's
items loadings Alpha
Easiness Q1 0.835 0.7
Q2 0.796
Q3 0.609
Assurance Q4 0.556 0.77
Q5 0.776
Q6 0.649
Security Q7 0.814 0.81
Q8 0.565
Customization Q9 0.783 0.79
Q10 0.757
Comprehensiveness Q11 0.657 0.83
Q12 0.710
Q13 0.544
Convenience Q14 0.759 0.75
Q15 0.534
Q16 0.650
Q17 0.597
Q18 0.772
Support services Q19 0.638 0.77
Q20 0.691
Q21 0.674
Q22 0.709
Q23 0.629
Q24 0.723
Q26 0.613
Employee knowledge Q25 0.644 0.81
Q27 0.616
customer satisfaction Q28 0.718 0.83
Q29 0.736
Q30 0.71
Q31 0.74
customer loyalty Q32 0.73 0.84
Q33 0.78
Q34 0.76
Table VIII: Fit indicators
Index Value
[chi square] 1086.28
RMSEA 0.046
NFI 0.88
NNFI 0.86
CFI 0.86
GFI 0.88
AGFI 0.85
P<0.05 d.f=451
Table IX: Discriminant validity assessment
Construct eas assu secu custom compre
eas 1.00
assu 0.47 1.00
secu 0.52 0.53 1.00
custom 0.47 0.54 0.46 1.00
compre 0.53 0.61 0.42 0.43 1.00
conv 0.56 0.58 0.61 0.68 0.66
support 0.65 0.59 0.55 0.56 0.42
knowl 0.68 0.64 0.57 0.59 0.61
satisfa 0.68 0.64 0.69 0.63 0.52
Loyal 0.58 0.63 0.51 0.48 0.49
Construct conv support knowl satisfa Loyal
eas
assu
secu
custom
compre
conv 1.00
support 0.47 1.00
knowl 0.52 0.53 1.00
satisfa 0.57 0.68 0.60 1.00
Loyal 0.44 0.53 0.57 0.69 1.00
Table X: Results of research hypotheses
Hypothesis Hypothesized paths Estimated
path
coefficients
H 1. Service CS--easiness 0.68
quality/customer CS--assurance 0.58
satisfaction CS--security 0.57
CS--customization 0.46
CS--comprehensiveness 0.59
CS--convenience 0.48
CS--support services 0.53
CS--employee knowledge 0.49
H 2. Service CL--easiness 0.54
quality/customer CL--assurance 0.49
satisfaction CL--security 0.65
CL--customization 0.46
CL--comprehensiveness 0.35
CL--convenience 0.65
CL--support services 0.59
CL--employee knowledge 0.45
H 3. customer CS-CL 0.75
satisfaction/
customer loyalty
Hypothesis Statistic t Results
H 1. Service 5.12 Accepted
quality/customer 6.45 Accepted
satisfaction 4.11 Accepted
1.93 Rejected
3.49 Accepted
4.61 Accepted
3.71 Accepted
2.62 Accepted
H 2. Service 5.02 Accepted
quality/customer 5.36 Accepted
satisfaction 3.68 Accepted
1.68 Rejected
1.81 Rejected
3.48 Accepted
2.52 Accepted
2.43 Accepted
H 3. customer 6.28 Accepted
satisfaction/
customer loyalty
