Embed Size (px)
Citation preview
Offline and online banking –where to draw the line whenbuilding trust in e-banking?
Kenneth B. YapUniversity of Western Australia, Perth, Australia, and
David H. Wong, Claire Loh and Randall BakCurtin University of Technology, Perth, Australia
Abstract
Purpose – The purpose of this paper is to examine the role of situation normality cues (onlineattributes of the e-banking web site) and structural assurance cues (size and reputation of the bank,and quality of traditional service at the branch) in a consumer’s evaluation of the trustworthiness ofe-banking and subsequent adoption behaviour.
Design/methodology/approach – Data were collected from a survey and a usable sample of 202was obtained. Hierarchical moderated regression analysis was used to test the model.
Findings – Traditional service quality builds customer trust in the e-banking service. The size andreputation of the bank were found to provide structural assurance to the customer but not in theabsence of traditional service quality. Web site features that give customers confidence are significantsituation normality cues.
Practical implications – Bank managers have to realise that good service at the branch is anecessary condition for the promotion of e-banking. They cannot rely on bank size and reputation to“sell” e-banking.
Originality/value – This is the first study that examines how traditional service quality and abank’s size and reputation influences trust in e-banking.
Keywords Trust, Customer services quality, Electronic commerce, Banking
Paper type Research paper
IntroductionOnline banking, also commonly known as internet banking or e-banking, hasexperienced phenomenal growth in recent years. In 2006, Pew Internet and AmericanLife Project reported that nearly half of internet users in the United States – 63 millionadults – bank online (Fox and Beier, 2006). Nonetheless, the authors note that thegrowth rate in e-banking has not kept pace with that of internet usage and attributethis gap to the lack of trust among bank customers, particularly among internet usersage 65 and older. News headlines about e-mail scams, identity theft, and “phishing”that undeservedly distort consumer perceptions may be one of several reasons whysuch a lack of trust persists (Gerrard et al., 2006).
The authors of this study propose that this lack of trust can be overcome with abetter understanding of factors that can boost customers’ trust for e-banking. It isimportant for bank managers to understand that trust has to be developed and theycan do so with a combination of traditional and online measures. This proposition isparticularly pertinent in the current context because e-banking features prominently in
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0265-2323.htm
Offline andonline banking
27
Received March 2009Revised October 2009
Accepted October 2009
International Journal of BankMarketing
Vol. 28 No. 1, 2010pp. 27-46
q Emerald Group Publishing Limited0265-2323
DOI 10.1108/02652321011013571
the corporate strategy of many retail banks. The long-term savings in operating costsmore than offsets the massive start-up cost (investment in technology combined withmarketing expenditure).
However, banks are increasingly faced with a perceived conundrum: customersmay appreciate the convenience of e-banking but as they migrate away fromtraditional banking, the extent of personal interaction with bank staff decreases asdoes the switching cost and ultimately long-term customer commitment (Sarel andMamorstein, 2003). Yet, such a conundrum exists only because bank managers viewtraditional and online banking as mutually exclusive or substitutable. This view is alsoevident in the conceptualisation of academic research in this area because manyresearchers who investigate trust in the e-banking context have limited the scope oftheir study to constructs that concern only virtual attributes or the internet.
The authors of the current study do not adopt such a perspective and concur withWong et al. (2008) who view traditional and online banking as complementary methodsof banking. Heeding their call for further research in this area, the authors of this studywill investigate the role of brick-and-mortar and virtual elements in developing trustfor e-banking. Three constructs are of particular interest: the attributes of the bankoffering e-banking services, the quality of traditional banking service, and the featuresof the e-banking web site. There are no studies to date accounting for both virtual andnon-virtual constructs in a model of e-banking adoption; thus, this study makes such acontribution by examining the interaction of both elements in predicting trust fore-banking.
Any valid explanation of how trust for e-banking is developed would be amiss toneglect these virtual and non-virtual constructs because the customer experience isintegrated and he/she may not view e-banking in isolation from the entirety of benefitsthat a bank’s service provides. Research findings by Patricio et al. (2003) suggest thatsatisfaction with the bank’s traditional service delivery may lend credence to new oralternative delivery channels. Findings from other studies prompt the authors of thisstudy to also consider the role of the bank’s size and reputation in developing customerconfidence in its e-banking service (Doney and Cannon, 1997; Jarvenpaa et al., 2000;Chen and Dhillon, 2003). Moreover, there is sufficient evidence for the authors of thisstudy to propose that a customer’s impression of an e-banking web site influenceshis/her trust towards it (Koufaris and Hampton-Sosa, 2004; Hampton-Sosa andKoufaris, 2005; Casalo et al., 2007; Vatanasombut et al., 2008). There is still a lack ofknowledge on how these constructs interact in the development of trust for e-banking.
It is important for bank managers to understand how trust for e-banking develops.Gan et al. (2006) predict that e-banking is necessary for banks to stay profitable in thefuture; however, the aforementioned “trust gap” is a barrier to growth in the adoptionof e-banking services. Vatanasombut et al. (2008) suggest that the formation of trust fore-banking will help convert non-adopters, particularly those for whom fears aboutusing the online service is a key inhibiting factor. Customer retention is also at stake:Morgan and Hunt’s (1994) trust-commitment theory purports that trust leads tocommitment in relationships. If trust for e-banking is developed over time, then thecustomer is more likely to adopt it as a complementary service delivery channel. Thisadoption, in turn, raises defection costs and the customer will become more committedto the bank (Mukherjee and Nath, 2003; Vatanasombut et al., 2008).
IJBM28,1
28
Literature review and theoretical frameworkTrust in e-bankingThe nature of online service delivery gives rise to a lack of trust in e-banking amongsome customers. In an online environment, there is no direct physical contact betweenbuyer and seller. This spatial distance means that consumers cannot use the physicalcues, such as observing the sales people or the physical office/store space, in order tojudge trustworthiness (Reichheld and Schefter, 2000). In the online environment,consumers and online retailers often face spatial and temporal separation; consequently,transactions carried out online often do not involve a simultaneous transaction of goods(or services) and money (Grabner-Kraeuter, 2002). Fears of hackers and privacy invasioncompound the uncertainty surrounding online services (Hoffman et al., 1999; Yoon, 2002).
Faced by scepticism and uncertainty, bank managers need to bridge the trust gap inorder to grow e-banking as a viable medium of service delivery. Trust plays a large rolein determining consumers’ initial and continued use of the e-banking service (Suh andHan, 2002; Rexha et al., 2003; Lichtenstein and Williamson, 2006). Research findingsshow that trust not only effects intent to use e-banking (Suh and Han, 2002; Liu and Wu,2007), but trust in e-banking has also been found to be an antecedent to commitment toe-banking (Kassim and Abdulla, 2006; Vatanasombut et al., 2008). This is a sample ofstudies that have conceptualised trust in their research to assist bank managers.
McKnight and Chervany (2002) propose a typology of trust in the e-commercecontext that includes the following: dispositional trust, institutional trust, andinterpersonal trust. The type most pertinent to this study is institutional trust, which isdefined as “an individual’s belief that favourable conditions are in place which areconducive to situational success” (McKnight and Chervany, 2002, p. 45). Institutionaltrust is, in turn, derived from two components – situational normality, and structuralassurance (McKnight et al., 1998; McKnight and Chervany, 2002; Balasubramanianet al., 2003). Institutional trust is formed when both of these components are present.
Situational normality refers to trustees’ beliefs that “everything seems in properorder” (Lewis and Weigert, 1985, p. 974), and is said to be formed by a perception thatthings in a situation are “normal, customary, fitting or in proper order” (McKnight andChervany, 2002, p. 48). Structural assurances refer to “trustees” beliefs that protectivestructures in place are conducive to situational success” (McKnight and Chervany,2002, p. 48). Authors of the present study propose that these are two cues by whichcustomers use to evaluate the trustworthiness of e-banking. Situational normality cuesare sought from the online attributes of the e-banking web site; while, structuralassurances cues are sought from traditional attributes of the bank offering e-banking.
Online attributes of the e-banking web siteBalasubramanian et al. (2003) propose that the virtual attributes of the e-banking website create the situational normality which one uses to create trust in the onlineenvironment. They add that attributes such as a well-designed customer interfaceprovide the cognitive cues for a sense of order. Past studies in this area have classifiedonline attributes into four factors: perceived security, perceived privacy, perceivedusefulness and perceived ease of use (Koufaris and Hampton-Sosa, 2004;Hampton-Sosa and Koufaris, 2005; Casalo et al., 2007; Vatanasombut et al., 2008). Inthe current study, the authors propose that these four factors influence trust fore-banking.
Offline andonline banking
29
In order for a customer to have trust in the online context, including e-banking, acustomer must be made to believe that the transactional medium is secure, and thatany information provided to those web sites are not being intercepted or given to athird party (Suh and Han, 2003). Studies have found that perceptions of privacy andsecurity can be influenced by the use of third party assurances, privacy policies andother security tools (Suh and Han, 2003), and it is these attributes which createconsumers’ perceptions of security and privacy. Such perceptions reinforce thecustomer’s views that actions being performed online are the norm and build trust forthe online environment (Jarvenpaa et al., 2000; Koufaris and Hampton-Sosa, 2004; Liuet al., 2005; Casalo et al., 2007; Chen and Barnes, 2007; Vatanasombut et al., 2008).
The “usability” – or the effort required to use a computer system as defined byCasalo et al. (2007) – of the e-banking web site can also influence a customer’sconfidence in it. It has been found that increased usability reduces the likelihood oferror, increases predictability of the web site’s behaviour, and creates a comfortableenvironment which would positively influence customer disposition towards the website. Other studies have also purported that the factors of usefulness and ease of use ofa web site function in the same way as a salesperson’s personal attributes in thecreation of trust traditional retailing (Koufaris and Hampton-Sosa, 2004;Hampton-Sosa and Koufaris, 2005).
Hence, the authors of this study put forward the following hypotheses:
H1a-d. Attributes of the e-banking web site – (a) perceived security, (b) perceivedprivacy, (c) perceived usefulness, and (d) perceived ease of use – have apositive effect on trust in e-banking.
Traditional attributes of the bankA significant proposition forwarded in this study is that trust in e-banking is derivedfrom structural assurances that a customer infers from the size and reputation of thebank concerned. The size of an organisation is often regarded as a proxy for securityand trustworthiness. Doney and Cannon (1997) and Jarvenpaa et al. (2000) purport thatif a firm is large, it must have performed well in order to have grown to such a size.They go further to suggest that customers making an initial decision to engage in anytransaction would expect that larger firms would have more impetus to deliver, havingmore to lose if they were to engage in untrustworthy behaviour. Chen and Dhillon(2003) argue that in the online environment where the physical cues which consumerscan draw trust from are absent, the size of a firm behind the web site is one of the fewways in which a customer can base their decision to trust the firm in an e-commercesetting. Moreover, a customer must be able to believe that the seller has the capacity todeliver the goods or services and firm size is one of the proxy indicators.
Several studies have established the relationship between firm size and trust for thefirm (Doney and Cannon, 1997; Jarvenpaa et al., 2000; Koufaris and Hampton-Sosa,2004); nonetheless, a literature review has not uncovered any study that has examinedthe relationship between the size of a bank and trust for its e-banking web site. Theliterature on size and trust lead the authors of this study to propose that:
H2a. The perceived size of a bank has a positive effect on trust in e-banking.
Apart from size, a bank’s reputation is indicative of its trustworthiness. The bank’sreputation is particularly relevant in the online context because unlike the
IJBM28,1
30
brick-and-mortar environment where physical cues such as the appearance of thebank’s branch can be called upon, structural assurance in e-banking is inferredprimarily from intangible cues (Reichheld and Schefter, 2000). Similar to the creation ofinterpersonal trust, a bank with a reputation of being trustworthy would have a greaterincentive to institute measures to avoid losing such a reputation (Casalo et al., 2007).This implies that a bank with a trustworthy reputation would want to ensure thatevery facet of its online offering is designed to create and maintain customers’ beliefs inthe structural assurance of e-banking.
Past research in the area of e-banking has found that perceived reputation is indeeda factor in the creation of trust in e-banking (Casalo et al., 2007; Mukherjee and Nath,2003); however, the relationship between perceived reputation and structuralassurance has not been empirically tested so far. Similar to the hypothesised effectof size, the authors of this study propose that:
H2b. The perceived reputation of a bank has a positive effect on trust in e-banking.
The perceived size and reputation of a bank may have an effect on trust in e-banking;however, the extent of its influence may vary with cues that emanate from encounterswith the bank of a more personal nature. The authors of this research study argue thateven though a large and reputable bank may be endowed with a greater propensity forits customers to trust its e-banking service, that level of trust is only has high as thequality of traditional service it provides.
Traditional service qualityThe concept of service quality revolves around a disconfirmation of expectations abouta service received. Parasuraman et al. (1988) provide a conceptualisation of service thatis useful for this research study. Their conceptualisation outlines five dimensions bywhich service quality can be evaluated: reliability, responsiveness, assurance,empathy, and tangibles. Service quality and SERVQUAL has been featuredextensively in the financial services marketing literature; hence, the author of thisstudy will omit any lengthy discussion of its historical and theoretical development.However, they do draw the reader’s attention to the relevance of service quality in themodel proposed in this study.
Recent research into the area of service quality for electronic commerce ande-banking has largely revolved around how electronic service quality can be measuredor managed (Alzola and Robaina, 2005; Parasuraman et al., 2005; Ibrahim et al., 2006;Fassnacht and Kose, 2007; Shamdasani et al., 2008). Electronic service quality may be auseful concept in e-banking research; however, electronic service quality cannot beassessed if a customer has not yet adopted any e-banking services. Authors of thepresent study argue that trust for e-banking precedes its adoption and service qualityhas a role in influencing trust. Unfortunately, the relationship between trust andtraditional and/or electronic service quality remains unexplored.
There is good reason to argue that traditional service quality has a role ininfluencing trust for e-banking. The quality of service delivered through traditionalchannels is what most bank customers are familiar with and accustomed to; hence,in-person service quality is effectively a de facto indication of the quality of otherservices, including e-banking. This notion is particularly credible when e-banking isless tangible than counter service at the bank. It could also be argued that service that
Offline andonline banking
31
exceeds customer expectations gives rise to a level of trust that can be harnessed tocross-sell other products (Fassnacht and Kose, 2007; Liu and Wu, 2007). Themultiplicity of plausible explanations warrants further investigation in this area.
The authors of this study pose to the reader a hypothetical scenario: a customer ismore likely to trust the e-banking web site if the bank offering it was large andreputable. A customer is also less likely to trust the e-banking web site of a small bankwith a lesser reputation. Ideally, the customer would have more confidence if the bankalready provides good counter service; however, what if the large bank provided poorcounter service? The authors reason that the large size and favourable reputation of thebank lend structural assurance to the e-banking service; however, poor counter servicewould negate the impact of the bank’s large size and reputation. Consequently, thisinconsistency raises doubts about e-banking. Naturally, a large and reputable bankthat provides good counter service can garner enough customer confidence for them totrust any of its alternative services. In this case, the structural assurance for e-bankingthat size and reputation provides is augmented by high service quality at the bank’sbranch. Findings by Fassnacht and Kose (2007) and Liu and Wu (2007) provide therationale for this claim. Hence:
H3a. Service quality positively moderates the relationship between perceived sizeof a bank and trust in e-banking
H3b. Service quality positively moderates the relationship between perceivedreputation of a bank and trust in e-banking
Willingness to adopt e-bankingTrust is essential in situations where risk, uncertainty and interdependence exist(Mayer et al., 1995), and the online environment certainly encapsulates those factors.Increased trust will mean that a person’s attitudes towards a particular behaviour (inthis case, using e-banking) are positive, which will likely increase a person’s intent toperform that behaviour. Jarvenpaa et al. (2000) demonstrated that trust leads topurchase intentions; while, Liu et al. (2005) found that to be also true in e-banking.Hence, the authors of this study purport that:
H4. Trust in e-banking has a positive effect on the willingness to adopt e-banking
The model tested in the study is thus summarised in Figure 1.
MethodologyTo test the conceptual model, a cross-sectional survey was administered using aninstrument containing 89 items. The 89 items used were adapted from establishedscales from past studies measuring respondents’ expectations, perceptions andattitudes regarding the service quality of their primary bank, perceptions of the sizeand reputation of their primary bank, perceptions of the bank’s e-banking web siteattributes, their trust in their primary bank’s e-banking web site, and their willingnessto it. Great care was taken when adapting the scales to ensure that the originalconcepts being measured by the scale had theoretical congruence and relevance to thisstudy. Each item is measured on a seven-point Likert scale with “0” denoting the lowend and “6” the high end. The questionnaire was then pre-tested on a conveniencesample of university staff. Refinements to the questionnaire were made based on
IJBM28,1
32
feedback from the pre-test. All items in the final instrument were then reviewed bymarketing academics for content validity.
MeasuresThe traditional service quality measures are based on the 22-item SERVQUAL scalepublished in the Parasuraman et al. (1985) study. The continued usefulness of this scaleas a measure of traditional service quality in the current e-banking context has beenconfirmed by Wong et al. (2008), where it was found that the importance ranking of thefive SERVQUAL dimensions have not changed dramatically over the years.Respondents were asked about their service expectations of banks in general beforethey were asked to record their perceptions of service quality of their primary bank.Nine of the items are negatively worded and responses were subsequentlyreverse-scored prior to data analysis.
The measures for perception of bank size and reputation are adapted from Doneyand Cannon’s (1997) seminal work in the area of trust in buyer-seller relationships.Their measurement scales have been used in different contexts to investigate trust (e.g.Jarvenpaa et al., 2000; Pavlou, 2003, Kim and Ahn, 2006). However, additional itemswere added to this scale, using the work of Jarvenpaa et al. (2000) and Pavlou (2003), forthe clarity and definition they gave to this dimension. Respondents were asked aboutperceptions of the size and reputation of their primary bank.
The set of questions about the online attributes of the e-banking web site wasderived from several sources. Items relating to perceived security were adapted fromthe entire Perception of Authentication of Data and Data Integrity scale published bySuh and Han (2003) with the exception of one item, which was replaced with an itemfrom Kim and Ahn’s (2006) scale relating to web site security. The item substitutionimproved the clarity of the scale during the pre-test. To measure perceived privacy, theauthors of this study used two items from Suh and Han’s (2003) Perception of PrivacyProtection scale which were most relevant to the present study. These items, whichmeasured confidentiality, were picked for its theoretical congruence to the study. Tomeasure perceived usefulness and perceived ease of use, items were drawn from workby Pavlou (2003), Kim and Ahn (2006), and Pavlou and Fygenson (2006). The items
Figure 1.Proposed model
Offline andonline banking
33
taken from each of these scales were chosen because it required the least altering ofwording, so as to maintain the integrity of the measure, as well as, the similarity ofcontexts in which these measures are used.
The set of questions used to measure trust in e-banking is a composite of itemsadapted from works of Doney and Cannon (1997), Jarvenpaa et al. (2000), and Suh andHan (2002). These items were chosen for its wording, which directly related to trust inthe service of e-banking, and a belief in the benefits and trustworthiness of e-banking.The final section of the survey measured the willingness to use e-banking by usingitems that measure attitudes and intentions towards using e-banking. Items in the scalewere sourced from scales published by Pavlou (2003), Kim and Ahn (2006), andVerhagen et al. (2006). Demographic data were also collected for the purpose ofclassification and determining the generalisability of the results.
Sample and data collectionA non-probability judgement convenience sample of university faculty andadministrative staff was selected. University staff is deemed to be educated andinformed about a range of issues, and so it was concluded that they would likely have ahigher chance of responding to the survey, with more accuracy and honesty in theirreplies. The survey was self-administered and data collection took place over twoweeks. A mix of paper and online questionnaires were distributed across ten facultiesin the university in two waves. The data collection process yielded a total of 218returned questionnaires, of which 202 passed manipulation checks and were usable.The response rate was 34.8 per cent.
ResultsFactor analysisThe data collected were subjected to exploratory factor analysis using principalcomponents extraction with varimax rotation. The items in each factor were thentested for scale reliability using standard Cronbach alpha indices. The results of theexploratory factor analysis on service quality items yielded five factors, identical to thedimensions found in Parasuraman et al.’s (1991) analysis. Each dimension is alsocharacterised by a high alpha score, the lowest of which is 0.625. A composite scorewas computed for each dimension by totalling scores for the items in a dimension anddividing it by the number of items. This procedure was carried out for bothexpectations and perceptions of service quality. Paired sample t-test showed thatperceived service quality fall significantly short of expectations. Subsequently,difference scores (perceptions from expectations of service quality) were calculated torepresent overall service quality scores.
Items measuring traditional attributes of the bank formed two factors as expected:perceived size (alpha ¼ 0.894) and perceived reputation (alpha ¼ 0.828). Fourdimensions were extracted for online attributes of the e-banking web site but theproposed classification of perceived security, perceived privacy, perceived usefulness,and perceived ease of use was not replicated. The four dimensions comprised of avariety items, all of which had factor loadings of 0.500 and higher. Each dimension, inturn, had a coefficient alpha of 0.857 or higher. Based on the nature of items, the fourdimensions were subsequently re-themed to represent Clarity, Control, Confidence, andConfidentiality. Trust for e-banking and willingness to use e-banking also proved to be
IJBM28,1
34
single-factor constructs with alphas of 0.964 and 0.957, respectively. For all of thedimensions discussed above, a composite score was also generated by using theaverage of summed item scores (Table I).
Regression analysisTo test H1, which is the relationship between attributes of the e-banking web site andtrust in e-banking, a simultaneous regression analysis was conducted. OnlyConfidence-related attributes of the e-banking web site had a significant influenceon trust for e-banking (Beta ¼ 0.381, t ¼ 3.524). The Confidence factor is comprised ofitems that give the customer a sense of confidence in dealing with the e-banking website. These items include “The transactions I send are transmitted to the real site whichI want to transmit to” and “All communications with my bank’s web site are restrictedto the web site and me”. The coefficients for other factors were not significant; thus, H1received only partial support.
To test the relationship between traditional bank attributes and trust in-banking(H2), as well as, the moderating effect of service quality (H3), hierarchical moderatedregression was conducted. This method was proposed by Baron and Kenny (1986) toexamine moderating effects. In conducting hierarchical moderated regression analysis,a series of regressions were performed. The first involved regressing the dependentvariable on the independent variable, then the dependent to the independent and themoderating variable, and finally the dependent to the independent, the moderator and across-product of the dependent and the moderator. The results of the analysis aredisplayed in Table II.
The analysis yielded results quite different to what was hypothesised. The model inwhich bank size is the only independent variable was tested and results show that thecoefficient for bank size was not significant. This model was then tested for explanatorypower against five models, each of which had bank size and a service quality dimensionas the independent variables. Result of these comparisons showed that the models withbank size and service quality had significantly improved R-squared values from themodel with bank size alone. For all five models, none the coefficients for bank size weresignificant and all of the coefficients for service quality were. The results of hierarchicalmoderated regression suggest that it is not bank size that has a positive influence ontrust in e-banking, but rather traditional service quality.
The five models with bank size and service quality as independent variables werere-tested for its explanatory power by including the cross-product of both variables toeach model. A significant increase in the R-squared value would indicate that amoderating effect exists. Results in Table II show that only the model containing thereliability dimension of service quality had the presence of a moderating effect. Thecoefficient of the cross-product (between bank size and reliability) is significant and is20.775, as listed in Table II. This result suggests that service reliability has a directeffect on trust in e-banking while bank size had a significant negative moderatingeffect.
The hierarchical moderated regression analysis was repeated for the effect of bankreputation on trust in e-banking and the results were mixed. Results summarised inTable III below indicate that bank reputation had a direct positive influence on trust ine-banking. When tested against Model 2 (bank reputation and service quality asindependent variables), only models with reliability, tangibles and assurance
Offline andonline banking
35
Fac
tor
Item
sL
oad
ing
Cro
nb
ach
’sa
Em
pat
hy
Th
efi
ve
serv
ice
qu
alit
yd
imen
sion
sin
this
stu
dy
are
iden
tica
lto
fact
orst
ruct
ure
inP
aras
ura
man
etal.’
s(1
991)
stu
dy
.No
item
sw
ere
dro
pp
edfr
omth
eS
ER
VQ
UA
Lb
atte
ry
0.75
6a;
0.87
3b
Rel
iab
ilit
y0.
847a
;0.
918b
Tan
gib
les
0.80
4a;
0.87
4b
Ass
ura
nce
0.82
1a;
0.84
5b
Res
pon
siv
enes
s0.
625a
;0.
827b
Per
ceiv
edsi
zeof
ban
k(M
ym
ain
ban
kis...)
Av
ery
larg
eco
mp
any
0.92
40.
894
On
eof
the
larg
est
inth
ein
du
stry
0.89
8Is
wel
lk
now
n0.
846
On
eof
the
smal
lest
pla
yer
sin
the
mar
ket
(rev
erse
-cod
ed)
0.82
8P
erce
ived
rep
uta
tion
ofb
ank
(My
mai
nb
ank...)
Has
are
pu
tati
onfo
rb
ein
gh
ones
t0.
860
0.82
8Is
kn
own
tob
eco
nce
rned
abou
tit
scu
stom
ers
0.83
3W
ill
do
its
job
rig
ht
even
ifn
otm
onit
ored
0.82
1H
asa
bad
rep
uta
tion
inth
em
ark
et(r
ever
se-c
oded
)0.
701
Isk
now
nto
be
dep
end
able
0.66
5
Cla
rity
Lea
rnin
gh
owto
use
e-b
ank
ing
from
my
mai
nb
ank
’sw
ebsi
tew
ould
be
easy
0.89
40.
954
Ifi
nd
my
mai
nb
ank
’sw
ebsi
teea
syto
use
0.87
9M
yin
tera
ctio
nw
ith
my
mai
nb
ank
’sw
ebsi
teis
clea
ran
du
nd
erst
and
able
0.87
6E
-ban
kin
gon
my
mai
nb
ank
’sw
ebsi
tew
ould
be
easy
0.85
9In
tera
ctin
gw
ith
my
mai
nb
ank
’sw
ebsi
ted
oes
not
req
uir
ea
lot
ofm
enta
lef
fort
0.83
2T
he
con
ten
tof
my
mai
nb
ank
’sw
ebsi
teis
use
ful
tom
e0.
793
My
mai
nb
ank
’sw
ebsi
teis
use
ful
inca
rry
ing
out
tran
sact
ion
s0.
568
Con
trol
(My
mai
nb
ank
’sw
ebsi
te...)
Asc
erta
ins
my
iden
tity
bef
ore
sen
din
gan
ym
essa
ges
tom
e0.
801
0.86
7A
scer
tain
sm
yid
enti
tyb
efor
ep
roce
ssin
gan
ytr
ansa
ctio
ns
rece
ived
from
me
0.77
6D
evot
esti
me
and
effo
rtto
pre
ven
tu
nau
thor
ized
acce
ssto
my
info
rmat
ion
0.66
8U
ses
secu
rity
con
trol
sfo
rth
eco
nfi
den
tial
ity
oftr
ansa
ctio
ns
0.65
8C
hec
ks
all
com
mu
nic
atio
ns
bet
wee
nth
esi
tean
dm
efo
rp
rote
ctio
nfr
omw
iret
app
ing
orea
ves
dro
pp
ing
0.65
2
(continued
)
Table I.Constructs and itemloading
IJBM28,1
36
Fac
tor
Item
sL
oad
ing
Cro
nb
ach
’sa
Imp
lem
ents
secu
rity
mea
sure
sto
pro
tect
its
onli
ne
cust
omer
’sin
form
atio
n0.
593
Con
fid
ence
Th
em
essa
ges
Ire
ceiv
ear
etr
ansm
itte
dfr
omth
ere
alsi
tefr
omw
hic
hI
wan
tto
rece
ive
from
0.82
30.
858
Th
etr
ansa
ctio
ns
Ise
nd
are
tran
smit
ted
toth
ere
alsi
tew
hic
hI
wan
tto
tran
smit
to0.
819
My
mai
nb
ank
’sw
ebsi
tew
ould
enh
ance
my
effe
ctiv
enes
sin
carr
yin
gou
ttr
ansa
ctio
ns
0.62
5A
llco
mm
un
icat
ion
sw
ith
my
mai
nb
ank
’sw
ebsi
tear
ere
stri
cted
toth
ew
ebsi
tean
dm
e0.
564
Con
fid
enti
alit
yM
ym
ain
ban
k’s
web
site
nev
erse
lls
my
per
son
alin
form
atio
nin
thei
rco
mp
ute
rd
atab
ases
toot
her
com
pan
ies
0.86
60.
857
My
mai
nb
ank
’sw
ebsi
tew
ill
not
use
my
per
son
alin
form
atio
nfo
ran
yp
urp
ose
un
less
Iau
thor
ize
itto
do
so0.
820
Iam
con
vin
ced
that
my
mai
nb
ank
’sw
ebsi
tere
spec
tsth
eco
nfi
den
tial
ity
ofth
etr
ansa
ctio
ns
rece
ived
by
me
0.53
1T
rust
ine-
ban
kin
gE
-ban
kin
gis
tru
stw
orth
y0.
927
0.96
4I
tru
stin
the
ben
efits
ofe-
ban
kin
g0.
923
Itr
ust
e-b
ank
ing
0.91
7W
illi
ng
nes
sto
use
e-b
ank
ing
Ith
ink
itis
ag
ood
idea
tou
see-
ban
kin
g0.
960
0.95
7I
inte
nd
tou
see-
ban
kin
gin
the
futu
re0.
958
Th
eth
oug
ht
ofe-
ban
kin
gis
app
eali
ng
tom
e0.
947
Iw
ill
reco
mm
end
toot
her
sth
atth
eyu
see-
ban
kin
g0.
892
Iex
pec
tm
yu
seof
e-b
ank
ing
toin
crea
sein
the
futu
re0.
878
Notes:
aE
xp
ecta
tion
sof
serv
ice
qu
alit
y;
bP
erce
pti
ons
ofse
rvic
eq
ual
ity
Table I.
Offline andonline banking
37
Pre
dic
tin
gT
rust
ine-
ban
kin
ga
Var
iab
les
ente
red
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Ban
ksi
ze0.
078
Em
pat
hy
0.16
4*
Banksize
£em
pathy
Ban
ksi
ze2
0.12
6R
elia
bil
ity
0.98
2*
Banksize
£Reliability
20.
775
*
Ban
ksi
ze0.
028
Tan
gib
les
0.17
3*
*
Banksize
£Tangibles
Ban
ksi
ze0.
078
Ass
ura
nce
0.24
2*
Banksize
£Assurance
Ban
ksi
ze0.
046
Res
pon
siv
enes
s0.
154
*
Banksize
£Responsiveness
DR
20.
003
0.02
6*
0.00
00.
002
0.06
10.
024
*0.
001
0.03
0*
0.00
10.
006
0.05
8*
0.00
70.
002
0.02
4*
0.00
3T
otal
R2
0.00
30.
029
0.02
90.
002
0.06
30.
086
0.00
10.
031
0.03
20.
006
0.06
50.
071
0.00
20.
025
0.02
8DF
0.53
05.
061
0.02
90.
321
12.3
874.
906
0.17
85.
902
0.17
61.
133
11.3
821.
286
0.32
34.
570
0.54
2d
.f.
188
187
186
191
190
189
193
192
191
183
182
181
190
189
188
Notes:
aS
tan
dar
diz
edre
gre
ssio
nco
effi
cien
tsar
esh
own
only
for
mod
els
wh
ere
the
chan
ge
inR
2is
sig
nifi
can
t;*p,
0.05
Table II.Results of moderatedhierarchical regressionanalyses for bank sizeand service qualitydimensions
IJBM28,1
38
Pre
dic
tin
gT
rust
ine-
ban
kin
ga
Var
iab
les
ente
red
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Mod
el1
Mod
el2
Mod
el3
Ban
kre
pu
tati
on0.
260
*
Em
pat
hy
Bankreputation
£Empathy
Ban
kre
pu
tati
on0.
157
Rel
iab
ilit
y0.
170
*
Bankreputation
£Reliability
Ban
kre
pu
tati
on0.
224
*
Tan
gib
les
0.14
7*
Bankreputation
£Tangibles
Ban
kre
pu
tati
on0.
135
Ass
ura
nce
0.18
5*
Bankreputation
£Assurance
Ban
kre
pu
tati
on0.
273
*
Res
pon
siv
enes
sBankreputation
£Responsiveness
DR
20.
068
*0.
003
0.01
80.
061
0.02
1*
0.00
90.
064
0.02
1*
0.00
00.
051
0.02
6*
0.00
00.
075
*0.
004
0.01
2T
otal
R2
0.06
80.
071
0.08
90.
061
0.08
10.
090
0.06
40.
084
0.08
50.
051
0.07
70.
077
0.07
50.
079
0.09
1DF
13.3
120.
562
3.54
112
.002
4.20
01.
725
12.6
894.
251
0.01
89.
632
4.92
30.
022
14.8
650.
752
2.47
7d
.f.
183
182
181
186
185
184
187
186
185
178
177
176
184
183
182
Notes:
aS
tan
dar
diz
edre
gre
ssio
nco
effi
cien
tsar
esh
own
only
for
mod
els
wh
ere
the
chan
ge
inR
2is
sig
nifi
can
t;*p,
0.05
Table III.Results of moderated
hierarchical regressionanalyses for bank
reputation and servicequality dimensions
Offline andonline banking
39
dimensions of service quality had a significantly higher R-squared value. Explanatorypower of these models did not improve with the inclusion of the cross-product. Thecoefficients for independent variables are also displayed in Table III. Results indicatethat the influence of traditional service quality and trust in e-banking vary with theservice quality dimension.
A regression analysis was conducted to test the relationship between trust ine-banking and willingness to adopt it (H4). The R-squared for the model is 0.385 andthe regression coefficient of 0.741 is significant. This result supports the hypothesisthat trust in e-banking has a positive influence on the willingness to adopt e-banking.
Discussion and implicationsThe results of this study suggest that traditional service quality plays a moreimportant role in influencing trust in e-banking than does the size of the bank. Thisfinding adds some depth to the e-banking literature because past studies examiningattitudes and behaviours towards online banking have confined their investigation toantecedents and cues emanating from the same medium of service delivery (Alzola andRobaina, 2005). The association between traditional service quality and attitudes andbehaviours towards traditional counter service banking has been well established(Zeithaml et al., 1996; Fassnacht and Kose, 2007; Yap and Sweeney, 2007); nonetheless,the customer experience goes beyond traditional counter service and now encompassesalternative media of service delivery. It is timely to consider the influence of traditionalservice quality on online service offerings and the findings from this study has takenthe important first step in this direction.
While the proposition of e-banking is to provide banking services at the convenienceof the customer’s desktop; e-banking is not independent of traditional service. Forcustomers who are new to e-banking, they often rely on bank counter staff to explainthe features of e-banking, help set up the e-banking account and password, resolveproblems with the e-banking web site, and provide clarification, follow-up, orsupplementary services to e-banking transactions. Such services provided at thecounter become more salient if a customer lacks the level of knowledge or trustrequired to adopt e-banking. The finding that traditional service quality has a directinfluence on trust in e-banking is consistent with such anecdotal examples. Moreover,this finding is parallel to the work of Semijin et al. (2005), which found that ine-commerce, offline fulfilment was just as important as online service quality.
The lack of a significant relationship between bank size and trust in e-banking is aresult that whilst not expected does not directly contradict the literature. Past findingsregarding size and trust have been with the view of size and its effect on the dimensionof interpersonal trust (Doney and Cannon, 1997), and not the institutional trust that isdefined in this study. The authors of this study aptly propose that the confidence thatcustomers derive from receiving good service at the bank’s branch will outweigh anypotential structural assurance that customers infer from dealing with a large bank.
Results also show that bank size only comes into play when customers assess thereliability of the service before trusting the e-banking web site. A negative moderatingeffect on the reliability-trust relationship implies that a larger bank has to work harderto provide a reliable service in order to build sufficient trust in e-banking. It alsoimplies that for smaller banks, service reliability takes on an even greater importancein building customer trust for its e-banking service. The authors of this study propose
IJBM28,1
40
that if service at the branch is poor, the size of bank cannot be relied upon to build trust.It is plausible that customers have even higher service reliability expectations of alarger bank and if it fails to deliver, customers will tend not to trust its e-bankingservice. This finding reiterates the notion that size does not matter.
Findings on the influence of a bank’s reputation are mixed and suggest that there issome hierarchy to which service quality dimensions have a greater influence on trust ine-banking. Wong et al. (2008) reported the expectations ranking of service qualitydimensions in the following order: Reliability (highest expectations), Assurance,Responsiveness, Tangibles, and Empathy (lowest expectations). The result of thisstudy point to the possibility that lower-order traditional service quality dimensions,such as empathy and responsiveness, are not applicable in building trust. In thesecircumstances, bank reputation has a direct influence on trust. Higher-order servicequality dimensions such as reliability and assurance then become more salient than thebank’s reputation in building trust. It is plausible that customers look for servicereliability and assurance cues in particular to provide the structural assurance requiredto trust e-banking. After all, the customer would like to know that the bank can at leastconsistently deliver on its promises and can do so dependably.
Reliability and assurance cues of service at the branch are most pertinent toe-banking because it is the necessary requirement of an effective e-banking service. Ascustomers migrate to e-banking, the bank can no longer provide the kind of empathetic,responsive, and tangible service that staff at a branch can provide. These cues thenbecome so important in forming structural assurance that the reputation of a bankbecomes no longer relevant. The extent to which a bank’s reputation providesstructural assurance only goes so far as certain expectations of service quality arefulfilled. This finding is consistent with the proposition that traditional service qualityis critical in building trust in e-banking, particularly in areas of service reliability andassurance.
The examination of the influence of e-banking web site attributes on trust revealedthat only the attributes that give customers a sense of confidence are salient. Thisfinding is consistent with the findings relating to service quality. Customers want to begiven a sense of security or reliability before trusting this technology, which is a notionsupported by Suh and Han (2003). Given that the items which coalesced into theConfidence dimension primarily relate to a consumer’s confidence in communicatingwith the web site, the results imply that banks should ensure that users are given clearindications of the actions of what the web site is doing at all times, with clearindications as to the timing and security of actions performed on the web site, so as toensure customer confidence with the e-banking web site.
Finally, the relationship between trust in e-banking and willingness to adopt it arenot surprising as it concurs with findings by Liu et al. (2005). Customers who arewilling to trust e-banking can then adopt it with less apprehension about reliability andsecurity concerns that may relate to the web site. Researchers and managers shouldview trust as a predisposition to behaviour or behavioural intentions towardse-banking and perhaps other technological service offerings.
Managerial implicationsIt is important for bank managers to understand that trust in e-banking is earned byproviding high traditional service quality at the retail branch level. They should not
Offline andonline banking
41
rely on the size and reputation of the bank to lend credence to e-banking becausecustomers are more likely to make inferences about e-banking from the level of servicethey currently receive at the branch, rather than factors that bank managers thinkmight give them the capacity or legitimacy to offer e-banking. Bank managers need torecognise that the customer experience with the bank’s service is integrated andseamless; moreover, good service at the branch may give rise to a halo effect.Customers probably reason that good service they receive at the counter is indicative ofgood service they are about to receive online (Patricio et al., 2003).
Bank managers have to pay more attention to how and when e-banking might bepromoted to the customer. Delightful service encounters at the branch representcross-selling opportunities for other products. A satisfied customer repays the serviceprovider by trusting it and giving it other opportunities to provide a service. Thisopportunity can be used to promote the attributes of the e-banking web site,particularly the web site features that give customers the perception of confidence. It isimportant for bank managers to realise that the promotion of e-banking does not residejust with the marketing department and their advertising campaigns. Rather, the entirebank branch and how well traditional service is delivered over the counter arepromotional tools in themselves, giving the customer confidence that they will receivethe same level of service online.
Managers of larger banks should not presume that the size and reputation of theirbank are de facto indicators of trustworthiness. The bank that excels in providing areliable service is the one that will be most successful in earning the trust of itscustomers to try e-banking. It appears that good counter service outweighs thepotential structural assurance that a large bank can provide. Larger banks have to earntheir keep and not rely on its size as a cue for structural assurance, particularly ifservice at the branch is poor. For managers of smaller banks, a focus on providing ahighly reliable counter service will pay dividends even in the online environment.
Advertising and personal promotion of e-banking should emphasise thetrustworthiness of the web site in its message. It should highlight the securityfeatures of the e-banking web site that will allow customers to use it with confidence.The promotional message should also assure customers that if they are happy with theservice at the branch, they can then expect the same level of high quality service frome-banking. Bank managers should also consider e-banking customer testimonials as apromotional tool. Customer testimonials that convey a message of trust for e-bankingwill be particularly effective in generating trial and adoption.
Limitations and directions for future researchThe results of this research should be taken in light of the limitations discussed below.First, there are a number of factors that are beyond the scope of this study – constructssuch as a consumer’s level of awareness of e-banking benefits, its cost, existingconsumer habits, and perceived risk of the internet in general – which may alsoinfluence the willingness to adopt e-banking. Specifically, trust in the internet has beenshown to reduce perceptions of risk in particular facets of the internet, such asperceptions of risk in e-commerce (Pavlou, 2003). There is still a lack of empiricalresearch in this area; thus, future studies should incorporate these variables to makethe model of e-banking adoption more comprehensive.
IJBM28,1
42
Secondly, the scope of this study is limited to Australia, where the internet is amature technology (Lichtenstein and Williamson, 2006), and as such, these results maynot be entirely generalisable to other contexts where technological maturity of theinternet has not been reached. Replications of this study in underdeveloped countriesor mature or elderly consumers are opportunities for further research. Studies indifferent countries with varying levels of technological development are recommended,as different expectations of service quality and requirements for trust may result.
Thirdly, the factor analysis for e-banking web site attributes failed to replicate thestructure in past studies from which items were sourced (Pavlou, 2003, Suh and Han,2003; Kim and Ahn, 2006; Pavlou and Fygenson, 2006). Research in this area willbenefit from a consolidation of scales measuring attributes of the web site. Finally, thisstudy conceptualised trust as institutional trust. Given the importance of traditionalservice quality as cues of structural assurance and situational normality, future studieswill benefit to consider interpersonal trust as a potential mediating moderating factor.
This study has highlighted the importance of traditional or offline factors ininfluencing attitudes and behaviours relating to online services. The examination oftraditional service quality in this study yielded significant results; however, furtherinvestigation may be required to fully identify the host of brick-and-mortar factors thatplay a role in the adoption of e-banking. This study, along with that of Patricio et al.(2003) and Flavian et al. (2006), are a good point of departure for further research in thisarea. The direct effect of traditional service quality on trust in e-banking has beenestablished, but the role of bank size and reputation as moderators need to beconfirmed by further research.
References
Alzola, L.M. and Robaina, V.P. (2005), “SERVQUAL: its applicability in electronic commerceB2C”, The Quality Management Journal, Vol. 12 No. 4, pp. 46-56.
Balasubramanian, S., Konana, P. and Menon, N.M. (2003), “Consumer satisfaction in virtualenvironments: a study of online investing”, Management Science, Vol. 49 No. 4, pp. 871-89.
Baron, R.M. and Kenny, D.A. (1986), “The moderator-mediator variable distinction in socialpsychology research: conceptual, strategic and statistical considerations”, Journal ofPersonality and Social Psychology, Vol. 51 No. 6, pp. 1173-82.
Casalo, L.V., Flavian, C. and Guinaliu, M. (2007), “The role of security, privacy, usability andreputation in the development of online banking”, Online Information Review, Vol. 31 No. 5,pp. 583-603.
Chen, S.C. and Dhillon, G.S. (2003), “Interpreting dimensions of consumer trust in e-commerce”,Information Technology and Management, Vol. 4 Nos 2-3, pp. 303-18.
Chen, Y.H. and Barnes, S. (2007), “Initial trust and online behaviour”, Industrial Management andData Systems, Vol. 107 No. 1, pp. 21-36.
Doney, P.M. and Cannon, J.P. (1997), “An examination of the nature of trust in buyer-sellerrelationships”, Journal of Marketing, Vol. 61 No. 2, pp. 35-51.
Fassnacht, M. and Kose, I. (2007), “Consequences of web-based service quality: uncovering amulti-faceted chain of effects”, Journal of Interactive Marketing, Vol. 21 No. 3, pp. 35-54.
Flavian, C., Guinaliu, M. and Torres, E. (2006), “How bricks-and-mortar attributes affect onlinebanking adoption”, International Journal of Bank Marketing, Vol. 24 No. 6, pp. 406-23.
Offline andonline banking
43
Fox, S. and Beier, J. (2006), “Online banking 2006: surfing to the bank”, Pew Internet & AmericanLife Project, available at: www.pewinternet.org/Reports/2006/Online-Banking-2006.aspx(accessed 17 March 2009).
Gan, C., Clemes, M., Limsombunchai, V. and Weng, A. (2006), “A logit analysis of electronicbanking in New Zealand”, International Journal of Bank Marketing, Vol. 24 No. 6,pp. 360-83.
Gerrard, P., Cunningham, J.B. and Devlin, J.F. (2006), “Why consumers are not using internetbanking: a qualitative study”, Journal of Services Marketing, Vol. 20 No. 3, pp. 160-8.
Grabner-Kraeuter, S. (2002), “The role of consumers’ trust in online-shopping”, Journal ofBusiness Ethics, Vol. 39 Nos 1-2, pp. 43-50.
Hampton-Sosa, W. and Koufaris, M. (2005), “The effect of web site perceptions on initial trust inthe owner company”, International Journal of Electronic Commerce, Vol. 10 No. 1, pp. 55-81.
Hoffman, D.L., Novak, T.P. and Peralta, M.A. (1999), “Information privacy in the marketspace:implications for the commercial uses of anonymity on the web”, Information Society,Vol. 15 No. 2, pp. 129-39.
Ibrahim, E.E., Joseph, M. and Ibeh, K.I.N. (2006), “Customers’ perception of electronic servicedelivery in the UK retail banking sector”, International Journal of Bank Marketing, Vol. 24No. 7, pp. 475-93.
Jarvenpaa, S.L., Tractinsky, N. and Vitale, M. (2000), “Consumer trust in an Internet store”,Information Technology and Management, Vol. 1 Nos 1-2, pp. 45-71.
Kassim, N.M. and Abdulla, A.K.M.A. (2006), “The influence of attraction on internet banking: anextension to the trust-relationship commitment model”, International Journal of BankMarketing, Vol. 24 No. 6, pp. 424-42.
Kim, M. and Ahn, J. (2006), “Comparison of trust sources of an online market-maker in thee-marketplace: buyer’s and seller’s perspectives”, The Journal of Computer InformationSystems, Vol. 47 No. 1, pp. 84-94.
Koufaris, M. and Hampton-Sosa, W. (2004), “The development of initial trust in an onlinecompany by new customers”, Information & Management, Vol. 41 No. 3, pp. 377-97.
Lewis, J.D. and Weigert, A.J. (1985), “Trust as a social reality”, Social Forces, Vol. 63 No. 4,pp. 967-85.
Lichtenstein, S. and Williamson, K. (2006), “Understanding consumer adoption of internetbanking: an interpretive study in the Australian banking context”, Journal of ElectronicCommerce Research, Vol. 7 No. 2, pp. 50-66.
Liu, C. and Wu, L.W. (2007), “Customer retention and cross-buying in the banking industry: anintegration of service attributes, satisfaction and trust”, Journal of Financial ServicesMarketing, Vol. 12 No. 2, pp. 132-45.
Liu, C., Marchewka, J.T., Lu, J. and Yu, C.S. (2005), “Beyond concern – a privacy-trust-behavioralintention model of electronic commerce”, Information & Management, Vol. 42 No. 2,pp. 289-304.
McKnight, H.D. and Chervany, N.L. (2002), “What trust means in e-commerce customerrelationships: an interdisciplinary conceptual typology”, International Journal ofElectronic Commerce, Vol. 6 No. 2, pp. 35-59.
McKnight, H.D., Cummings, L.L. and Chervany, N.L. (1998), “Initial trust formation in neworganizational relationships”, Academy of Management Review, Vol. 23 No. 3, pp. 473-90.
Mayer, R.C., Schoorman, F.D. and Davis, J.H. (1995), “An integrative model of organizationaltrust”, Academy of Management Review, Vol. 20 No. 3, pp. 709-34.
IJBM28,1
44
Morgan, R.M. and Hunt, S.D. (1994), “The commitment-trust theory of relationship marketing”,Journal of Marketing, Vol. 58 No. 3, pp. 20-38.
Mukherjee, A. and Nath, P. (2003), “A model of trust in online relationship banking”,International Journal of Bank Marketing, Vol. 21 No. 2, pp. 5-15.
Parasuraman, A., Berry, L.L. and Zeithaml, V.A. (1991), “Refinement and reassessment of theSERVQUAL scale”, Journal of Retailing, Vol. 67 No. 4, pp. 41-50.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), “A conceptual model of service qualityand its implications for future research”, Journal of Marketing, Vol. 49 No. 3, pp. 41-50.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: a multiple-item scale formeasuring consumer perceptions of service quality”, Journal of Retailing, Vol. 64 No. 1,pp. 12-40.
Parasuraman, A., Zeithaml, V.A. and Malhotra, A. (2005), “E-S-QUAL: a multiple-item scale forassessing electronic service quality”, Journal of Service Research, Vol. 7 No. 3, pp. 213-33.
Patricio, L., Fisk, R.P. and Cunha, J.F.e. (2003), “Improving satisfaction with bank serviceofferings: measuring the contribution of each delivery channel”, Managing Service Quality,Vol. 13 No. 6, pp. 471-82.
Pavlou, P.A. (2003), “Consumer acceptance of electronic commerce: integrating trust and riskwith the technology acceptance model”, International Journal of Electronic Commerce,Vol. 7 No. 3, pp. 101-34.
Pavlou, P.A. and Fygenson, M. (2006), “Understanding and prediction electronic commerceadoption: an extension of the theory of planned behaviour”, MIS Quarterly, Vol. 30 No. 1,pp. 115-43.
Reichheld, F.F. and Schefter, P. (2000), “E-loyalty: your secret weapon on the web”, HarvardBusiness Review, Vol. 78 No. 4, pp. 105-13.
Rexha, N., Kingshott, R.P.J. and Aw, A.S.S. (2003), “The impact of the relational plan on adoptionof electronic banking”, Journal of Services Marketing, Vol. 17 No. 1, pp. 53-65.
Sarel, D. and Mamorstein, H. (2003), “Marketing online banking services: the voice of thecustomer”, Journal of Financial Services Marketing, Vol. 8 No. 2, pp. 106-18.
Semeijn, J., van Riel, A.C.R., van Birgelen, M.J.H. and Streukens, S. (2005), “E-services and offlinefulfilment: how e-loyalty is created”, Managing Service Quality, Vol. 15 No. 5, pp. 182-94.
Shamdasani, P., Mukherjee, A. and Malhotra, N. (2008), “Antecedents and consequences ofservice quality in consumer evaluation of self-service internet technologies”, The ServiceIndustries Journal, Vol. 28 No. 1, pp. 117-38.
Suh, B. and Han, I. (2002), “Effect of trust on consumer acceptance of internet banking”,Electronic Commerce Research and Applications, Vol. 1 No. 3, pp. 247-63.
Suh, B. and Han, I. (2003), “The impact of customer trust and perception of security control on theacceptance of electronic commerce”, International Journal of Electronic Commerce, Vol. 7No. 3, pp. 135-61.
Vatanasombut, B., Igbaria, M., Stylianou, A.C. and Rodgers, W. (2008), “Information systemscontinuance intention of web-based applications customers: the case of online banking”,Information & Management, Vol. 45 No. 7, pp. 419-28.
Verhagen, T., Meents, S. and Tan, Y.H. (2006), “Perceived risk and trust associated withpurchasing at electronic marketplaces”, European Journal of Information Systems, Vol. 15No. 6, pp. 542-55.
Wong, D., Rexha, N. and Phau, I. (2008), “Re-examining traditional service quality in ane-banking era”, International Journal of Bank Marketing, Vol. 26 No. 7, pp. 526-45.
Offline andonline banking
45
Yap, K.B. and Sweeney, J.C. (2007), “Zone-of-tolerance moderates the service quality-outcomerelationship”, Journal of Services Marketing, Vol. 21 No. 2, pp. 137-48.
Yoon, S.J. (2002), “The antecedents and consequences of trust in online-purchase decisions”,Journal of Interactive Marketing, Vol. 16 No. 2, pp. 47-63.
Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996), “The behavioral consequences of servicequality”, Journal of Marketing, Vol. 60 No. 2, pp. 31-46.
About the authorsKenneth B. Yap is a Doctoral Candidate in Marketing at the University of Western Australia. Hisresearch interests are in macromarketing and services marketing, particularly banking. Kennethhas experience as a marketing consultant in New York, working with several of the Fortune 500companies. He has recently published in the Journal of Services Marketing. Kenneth B. Yap is thecorresponding author and can be contacted at: [email protected]
David H. Wong is a Lecturer in Marketing at Curtin University of Technology, Australia. Hisresearch revolves around topics in innovation and the diffusion of technology, service quality,and electronic modes of delivery in banking and higher education sectors. Dr Wong has beeninvited as a reviewer for many journals and conferences, and is keenly sought as a reviewer fortexts in marketing research. He has consulted in a large number of commercial market researchprojects for both the profit and not-for-profit sectors, and is an Associate of the AustralianMarketing Institute and a Fellow of The Academy of Marketing Science.
Claire Loh is a member of the academic staff at Curtin University of Technology, Australia.Her research interests are in the adoption and diffusion of technology in the banking and highereducation sectors, services marketing and tourism and hospitality marketing. Claire hasexperience in consultancy having worked on several projects for both profit and not-for-profitsectors.
Randall Bak is a Research Student at Curtin University of Technology, Australia. Hisongoing research interests revolve around the banking industry and how new forms ofbank-customer interactions impact on traditional relational constructs.
IJBM28,1
46
To purchase reprints of this article please e-mail: [email protected] visit our web site for further details: www.emeraldinsight.com/reprints
