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2
ow consumers feel about themselvesparticularly in relation to
technologymay have an important influence on their adoption and use of
technology. Although research on electronic channels has shown that Web site
and consumer characteristics are important predictors of consumer trust,
researchers have not considered the role played by consumerscommitment to
their identity as technology users. This paper explores whether consumer iden-
tity commitment and calculative commitment to electronic channels impact
consumer use of electronic channels and perceived value from the service firm.
More specifically, it examines whether these effects are mediated by trust in tech-
nology and trust in the firm. Using survey data from 834 consumers engaged in
both offline and online banking, plus transaction frequency data supplied by a
host firm, the study finds that identity commitment plays an important role in
building consumer trust in technology and that calculative commitment increas-
es transaction frequency directly, unmediated by trust in technology.Theoreticaland managerial implications of these findings are explored.
DEVON S. JOHNSON
2007 Wiley Periodicals, Inc. and Direct Marketing Educational Foundation, Inc.
JOURNAL OF INTERACTIVE MARKETING VOLUME 21 / NUMBER 4 / AUTUMN 2007
Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/dir.20091
ACHIEVING CUSTOMER VALUE
FROM ELECTRONIC CHANNELS
THROUGH IDENTITY COMMITMENT,
CALCULATIVE COMMITMENT, AND
TRUST IN TECHNOLOGY
H
DEVON S. JOHNSONis an Assistant Professor of Marketing,
College of Business Administration,
Northeastern University;
e-mail: [email protected]
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ACHIEVING CUSTOMER VALUE FROM ELECTRONIC CHANNELS 3
Journal of Interactive Marketing DOI: 10.1002/dir
Electronic channels improve consumers ability to
access products and services and give them control
over their relationships with companies and their rep-
resentatives. Some consumers have warmed to the
benefits of electronic channels, especially in the area
of PC banking. For instance, eMarketer, a marketing
research firm that tracks online growth trends,reports that within the United States almost 73 mil-
lion adult consumers engaged in online banking in
2006, and forecasts annual growth rates of between
6.5% and 9.5% through 2010 (eMarketer, 2007). Yet
evidence indicates that distrust of online banking is
not reducing and remains of concern to customers.
American Banker reports that the number of cus-
tomers concerned about online fraud grew by 10% in
2005 (Wolfe, 2005). A 2005 study by ForeSee, an
online marketing research firm, reports that 68% of
customers who say they are not interested on online
banking cite privacy concerns as their main reason(Kersner, 2005). Consumer discomfort with electronic
channel use is both concerning and surprising in light
of the positive benefits of electronic channel adoption.
These benefits include the cost reductions that banks
enjoy by shifting services online, the extra value that
consumers receive from online customization, and the
increase in consumer loyalty that comes from struc-
tural lock-in and stickiness of customized online
interfaces. For example, Citibank.com reports that
their online consumers use a greater number of the
banks products and are 40% more profitable for
the bank than their offline counterparts (Schneider,
2004). Academic researchers have also found that per-
sonal computer (PC) banking consumers are on aver-
age more profitable and maintain higher balances than
their offline counterpart (Hitt & Frei, 2002). These
compelling benefits of the Internet have driven adop-
tion of electronic channels to the point where many
consumers who have not adopted the Internet are fac-
ing exclusion and marginalization. For example, U.S.
seniors are being encouraged to use Web sites to deter-
mine the most suitable health care plan for obtaining
Medicare benefits (ODonnell, 2006). The reluctance ofmany consumers to adopt electronic channels in the
face of marginalization implies that more research is
needed to more comprehensively understand how trust
can be engendered in electronic channels.
Prior research in this area has made significant pro-
gress toward understanding how trust is developed.
These articles have investigated the effectiveness of a
variety of approaches to building trust in Web sites
and online vendors. Table 1 summarizes some of the
important conceptual models proposed by researchers
across the marketing and information systems litera-
ture. Previously examined antecedents of trust in
electronic channels generally comprise four categories
of factors. One set of factors centers on branding,including the effects of incumbent brand reputation
or transferable brand equity (McKnight, Choudhury,
& Kacmar, 2002) and brand strength of the firm
(Bart, Shankar, Sultan, & Urban, 2005; Pavlou, 2003;
Yousafzai, Pallister, & Foxall, 2005). A second set of
factors includes privacy and security issues, such as
institution-based assurances, independent expert
advisors, trust seals, legal and regulatory mecha-
nisms, privacy policy, and situational normality
(Balasubramanian, Konana, & Menon, 2003; Gefen,
Karahanna, & Straub, 2003; Hoffman, Novak, &
Peralta, 1999; Pavlou & Gefen, 2004; Urban, Sultan, &Qualls, 2000; Yousafzai, Pallister, & Foxall, 2005).
The third set examines the role of consumer personal
dispositions or propensity to trust (McKnight,
Choudhury, & Kacmar, 2002; Pavlou & Gefen, 2004).
Finally, the fourth set looks at the role of a Web sites
performance aspects, such as navigation, order fulfill-
ment, and Web site quality (Bart, Shankar, Sultan, &
Urban, 2005; McKnight, Choudhury, & Kacmar,
2002). In summary, this research stream regards
trust in electronic channels as a function of charac-
teristics of both the Web site and the customer.
However, despite the attention given to the role of
consumer characteristics in electronic channel use,
the role of consumer identity motivation as it relates
to trust has not been addressed. Identity theory sug-
gests that individuals establish relationships in order
to reflect a desired identity (Stryker, 1980; Stryker &
Serpe, 1994), and Arnett, German, and Hunt (2003)
have argued that this theory has the potential to
explain the role of noneconomic benefits in relational
exchange. Recent empirical studies indicate that the
social norms embraced by consumers significantlyinfluence their online purchase decisions. For
instance, Hansen (2005) found that online grocery
purchasers rely on social norms and argued that this
may be because online shoppers are less able to
observe other shoppers in the act of purchasing.
Previous research has also examined the effects of the
more general construct of intrinsic motivations
(described as feelings of accomplishment, prestige,
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4 JOURNAL OF INTERACTIVE MARKETING
personal growth, and pleasure) on consumer trial of
self service technology (Meuter, Bitner, Ostrom, &
Brown, 2005). If consumers think of themselves as
avid technology users (or as technology-averse indi-
viduals), to what extent will this perception influence
their trust in technology and their use of electronic
channels?
Regardless of how committed a consumer is to a
technology-oriented identity, how compelling consumers
Journal of Interactive Marketing DOI: 10.1002/dir
ANTECEDENTS OF TRUST IN ELECTRONIC
STUDY CHANNELS FOCAL TRUST CONSTRUCT CONSEQUENCES
Hoffman,Novak,& Peralta (1999) Lack of control over Web merchants Trust in Web vendors
access to personal information
Urban, S ultan, & Qualls (2000) Virtual-advisor technology, p rovide unbiased Three stage process: Customer loyalty
information,include competit ive products, trust in the Internet and
keep your promise, ensure consumer privacy, specific Web site,trust in
transferring recognized brand equity information displayed,
and trust in delivery and
fulfillment
McKnight & Chervany (2002) Disposition to trust, institution-based trust Trusting beliefs (specific Trusting intentions,
others) trusting behaviors
McKnight, Choudhury, & Deputation,site quality, structural assurances Trusting intentions:willingness Intention to: follow
Kacmar (2002) of the Web, perceived risk to depend on Web vendor vendor advice, share
trusting beliefs in Web vendor personal information,
purchase
Balasubramanian, Konana, & Operational competence, environmental security Trustworthiness of online Satisfaction
Menon (2003) broker
Pavlou (2003) Reputation, past satisfaction, frequency Trust in Web retailer Intentions to transact,
reduces perceived risk,
usefulness,ease of use
Suh & Han (2003) Perceived control, authentication, Trust in e-commerce Attitude towards
non-repudiation, privacy protection, using, behavioral
data integrity intention to use,
actual use
Bart, Shankar, Sultan, & Urban (2005) Privacy, security, brand strength, advice, Trust in a Web site Behavioral intent
absence of errors, community features,
order fulfillment
Yousafzai, Pallister,& Foxall (2005) Institution-based trust:security policies, privacy Trust in e-banking: ability belief, Trusting intentions
policies, legal & regulatory compliance, trust integrity belief,and benevolent
third party verification,guarantees situational belief
normality; testimonials Web site design & quality,
brand identification
Schlosser,White,& L loyd (2006) Web site investment,privacy,and security Ability, integrity,and benevolence Online purchase
intentions
Wang, Beatty, & Foxx (2004) Privacy, disclosures,security disclosures,return Cue-based trust (trust based on Book-marking,
policy,seal of approval cues from initial Web site willingness to
encounter) provide personal
information
TABLE 1 Selected Studies on Trust in a Web Site
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find the firms value proposition is an important
determinant of a consumers use of an electronic chan-
nel. This paper examines the role of consumers calcu-
lative commitment to PC bankingcommitment to
the service arising from how compelling consumers
find the firms value propositionin determining con-
sumer trust and use of PC banking.
This paper also contributes to an evolving under-
standing of the dimensions that comprise trust in
electronic channels. Researchers have conceptualized
trust in the Web as beliefs and intentions or willing-
ness to rely on a Web vendor (McKnight & Chervany,
2002; McKnight, Choudhury, & Kacmar, 2002). These
beliefs and intentions have been further refined as
consumers beliefs in the vendors ability, integrity,
and benevolence (Yousafzai, Pallister, & Foxall, 2005;
Schlosser, White, & Lloyd, 2006). However, these
dimensions of trust focus on the characteristics of theWeb vendor and do not incorporate consumer percep-
tions and attitudes toward the technology used by the
vendor. Although studies have examined trust in a
Web site, the degree to which this trust represents the
technology or the firm sponsoring the Web site is
unclear. This paper addresses this gap by examining
the roles of trust in technology and trust in the firm
as separate mediators of the effects of identity com-
mitment and calculative commitment on electronic
channel use and customer value. Trust in technology
is conceptualized as reliance due to performance and
ability beliefs as distinct from benevolent beliefs. In
examining the role of different levels of trust, the pre-
sent paper addresses the relative importance of micro
trust or trust in agents of the firm (technology and
frontline employees) versus macro trust or trust inthe firm as a holistic economic agent.
Finally, although many researchers have examined
how trust can influence customer attitudes and behav-
ioral intentions, very few studies have measured
trusts influence on actual channel usage behavior
(a notable exception is Suh & Han, 2003). This article
empirically examines the role of trust in technology in
influencing the number of transactions actually per-
formed by customers in a financial services setting.
The paper begins by briefly explaining the conceptualframework guiding this study and by discussing the
conceptual foundations of its key constructs. It then
presents hypothesized relationships, followed by
methodology, study findings, and implications.
CONCEPTUAL FRAMEWORK
The conceptual framework presented in Figure 1
proposes that consumers have two fundamental
ACHIEVING CUSTOMER VALUE FROM ELECTRONIC CHANNELS 5
Journal of Interactive Marketing DOI: 10.1002/dir
Identitycommitment totechnology
Calculativecommitment totechnology
Trust in PCbankingtechnology
PC bankingtransactionfrequency
Control variable:Transaction variety
Internetenvironmentalsecurity Perceived
value fromthe firm
1
2
3
5
1
3
4
5
4
Trust inthe firm
Operationalbenevolence
Operationalcompetence
2
FIGURE 1Conceptual Model of the Mediating Role of Trust in Technology
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6 JOURNAL OF INTERACTIVE MARKETING
motivations to engage electronic channels. First, they
have a commitment to their personal identity as tech-
nology users, and second, they have a calculative com-
mitment to the channels value proposition. The
framework further holds that the impact of these
motivations on consumer behavior are mediated by
consumer trust in a firms channel technology.
The main purpose of this paper is to test whether
identity commitment and calculative commitment to
technology influence consumer use of electronic chan-
nels and to determine whether trust in technology
mediates these effects. However, in order to test a com-
prehensive model and to better understand the rela-
tive influence of these constructs of interest, the study
examines the role of three additional factors that
have been recognized by prior research as important
determinants of consumer trust, namely environmen-
tal security, operational competence, and operationalbenevolence. Operational competence is concerned
with how visible management policies and practices
convey to customers that the firm is able to deliver on
its promises, whereas operational benevolence
reflects a tendency to give priority to customers inter-
est (Siredshmukh, Singh, & Sabol, 2002). Operational
competence examines observed activities of the firms
offline retail services and is intended to complement
the online focus of calculative commitment to PC
banking technology. Trust in the firm is also examined
as a mediating variable to further clarify the relation-
ship between micro trust and macro trust and their
relationships with antecedents and consequences.
Figure 1 presents perceived customer value from the
firm as a dependent variable, recognizing that con-
sumers ultimately desire a valuable service experi-
ence regardless of the channel they use. Customer
value is consumers overall assessment of the utility
of a service based on their perceptions of what is given
and received (Zeithaml, 1988). Research has recog-
nized that much of the value consumers derive from a
service firm results from the interactivity betweenconsumers and its touch points, which facilitates a
more customized service outcome. According to the
emerging service-dominant logic, which regards spe-
cialized skill(s) and knowledge as the fundamental
unit of exchange rather than tangible goods, customer
value is created in-use as customers use the facilities
of the service firm and tangible products are mere
conduits for the delivery of services (Norman &
Ramirez, 1993; Vargo & Lusch, 2004). This logic
implies a need to better understand what factors
motivate consumers to use electronic channels and
the paths via which their perceptions determine the
value they ultimately perceive from a firm.
Managers at the host financial institution involved in
this research and a perusal of consumer transaction
data provided by the firm indicate that consumers
perform four functions: check balances, transfer
funds, pay bills, and make purchases (loans and
investment products). Frequency of transactions is a
sum of the occasions consumers perform the afore-
mentioned four types of transactions over a three
month period immediately following the study. Next,
the paper develops the concepts of calculative com-
mitment to PC banking and identity commitment to
technology, followed by a discussion of the mediatingroles of trust in technology and trust in the firm.
Identity Commitment to Technology
Identity theorists (Stryker, 1980; Stryker & Serpe,
1994) regard the self as a multifaceted construct
comprising multiple role identities from which indi-
viduals derive self-esteem. Individuals become com-
mitted to an identitya shared social perception of
what it means to be a particular kind of selfand
engage in social behaviors to reflect their identity,
including establishing ties to individuals and organi-
zations (Burke & Reitzes, 1991). According to identity
theory (Stryker, 1980), individuals develop commit-
ment to their identities from these social ties. For
instance, college students who share a common cause
and membership in advocacy groups develop personal
relationships with one another that produce identity
commitment to the cause. The social and emotional
well-being of individuals would be adversely impacted
by discontinuing the network of social relationships
surrounding an identity cause. The greater these ties,
the greater their commitment to their identity.
This paper extends this notion of identity commit-
ment to explain consumer use of electronic channels.
Identity commitment to technology refers to the value
that consumers place on being perceived by others as a
technologically competent individual (Stryker & Serpe,
1994). For example, consumers with a reputation for
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being knowledgeable about computers may feel that
they are expected to use computer technology in their
normal course of living. Refusal or avoidance of elec-
tronic channels would be contradictory to their iden-
tity and could therefore result in an embarrassing
challenge to an important aspect of their self-identity
in the eyes of family and peers. Hence, social rela-tionships exert pressure on consumers to conform to
role identities.
Motivational pressures to use electronic channels are
likely to contribute to consumer trust in technology
because even technologically savvy consumers must
first overcome some initial fears or concerns about the
technology before adopting it. Consequently, social
pressure to use electronic channels may make these
consumers less inclined to be critical and more willing
to work cooperatively to solve problems encountered
using these channels. Identity commitment shouldmotivate consumers to overcome reticence, clarify
vulnerabilities, and substantiate the capabilities of
electronic channels.
Calculative Commitment to PCBanking Technology
A partners desire to maintain a relationship or rela-
tionship commitment is an essential indicator of the
quality or health of a relationship (Dwyer, Schurr, &
Oh, 1987; Moorman, Zaltman, & Deshpande, 1992;
Morgan & Hunt, 1994). This desire reflects a part-
ners expectation that a relationship will continue to
yield benefits in the future. Calculative commitment
is a rational economic notion of commitment arising
from how compelling consumers find a firms value
proposition. The benefits of the PC banking value
proposition include explicit efficiency as well as
implicit potential inefficiency of available alterna-
tives if the service is foregone (Anderson & Weitz,
1992; Gundlach, Achrol, & Metzer, 1995; Gustafasson,
Johnson, & Roos, 2005). Consumers calculative com-mitment to PC banking arises from conveniences,
such as 24-hour access, no geographic limitations,
speed of service, and transaction automation. These
benefits constitute the primary attraction to the chan-
nel, and a compelling realization of these benefits
verifies the efficacy of the technology and creates the
perception that the technology is trustworthy.
The Influence of Additional Factors
Environmental security: The use of the Internet
as a superhighway for electronic channels presentssecurity risks for the consumer. Perceived environ-mental security is consumers level of concern thattheir privacy may be violated on the Internet, espe-cially regarding the integrity of exchange transactions.This concern stems from a belief that institutions andindividuals external to an Internet-based transactioncan compromise the transactions integrity and out-come. Firms can improve perceived environmentalsecurity by keeping consumers informed about theeffectiveness of detection and security violation proce-dures, reminding them of the presence of externalregulatory oversight and reassuring them aboutavenues for resolution should a privacy violationarise. A secure Internet environment creates the per-ception that privacy violations are preventable
(Balasubramanian, Konana, & Menon, 2003; Pavlou& Gefen, 2004). This perception improves the efficacyof the Internet as a conduit for personal transactionsand provides a catalyst for consumers to develop trustin Internet-based channels (McKnight, Cummings, &Chervany, 1998).
Operational competence: The operational com-
petence of management polices and practices refers topolicies that customers believe enhance the compe-tent execution of a companys visible behaviors(Sirdeshmukh, Singh, & Sabol, 2002). Operationalcompetence has been shown to lead to trust in a com-
panys policies and in its front-line employees(Sirdeshmukh, Singh, & Sabol, 2002). Competent ser-vice delivery, such as responsiveness and promptrecovery, conveys to customers that the firm has thenecessary skills and abilities to perform effectively(Smith & Barclay, 1997). Consistent with prior re-search, operational competence should directly increasetrust in the firm.
It is anticipated that offline operational competence will
also directly increase consumer trust in PC banking
technology. According to impression management theo-
ry, consumers make assumptions about back-stageservice quality from observing front-stage service qual-
ity. Consequently, firms actively manage front-stage
impressions to create positive impressions of back-stage
competency and efficiency (Grayson, 1998). Similarly,
customers may formulate their impression of the back-
stage performance of firm technology from observ-
ing competent front-stage retail banking. Because
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technology often provides the infrastructure for oper-
ational efficiency, consumers may assume a common
technology infrastructure for offline and online opera-
tions, leading to higher level of trust in PC bank-
ing technology when offline competency is observed.
Operational benevolence: It also is anticipatedthat consumers perception of a firms operational
benevolence will contribute to their trust in the firms
electronic channel. Operational benevolence refers to
behaviors that reflect an underlying motivation
to place consumers interest ahead of self-interest
(cf. Sirdeshmukh, Singh, & Sabol, 2002, p. 18).
Because consumers are often not fully informed about
all security controls implemented by firms, they are
left to draw broad conclusions about a vendors deter-
mination to protect their privacy based on policies
and practices they observe with other channels, such
as retail outlets and services providers (Suh & Han,2003). For example, a retail banking policy may
give customers a 24-hour grace period to revise trans-
actions and associated charges. Policies whereby
companies sacrifice income opportunities or incur
additional costs in order to satisfy customers will con-
vey honest motives to consumers and may also indicate
that the firm intends to honor its promises regarding
the use and abuse of personal information. Consistent
with prior research findings (Sirdeshmukh, Singh, &
Sabol, 2002), it is also anticipated that operational
benevolence will increase trust in the firm.
The Mediating Roles of Trust inPC Banking Technology andTrust in the Firm
The notion that consumers can place trust in technol-
ogy is not new. Engineering psychologists argue that
because technologies, such as decision support sys-
tems, are so complex that users never completely
understand these systems (Muir, 1987) and therefore
have no option but to rely on some degree of trust.Other studies have demonstrated that a supervisors
decision to manually control a technology system that
can be set to operate automatically is directly related
to their level of trust in the technology and that a
deterioration of trust is dependent on how transient
or systematic the fault is perceived to be (Lee, 1994;
Lee & Moray, 1992; Muir, 1994; Zuboff, 1988).
Although some researchers (e.g., Mayer, Davis, &
Schoorman, 1995) have noted that trust between
human beings is comprised of three subdimensions
(ability, benevolence, and integrity), engineering psy-
chologists have embraced a conceptualization of trust
that is more oriented toward the first of these dimen-
sions. For instance, Muir (1987) applies Barbers(1983) and Rempel, Holmes, and Zannas (1985)
experience-based notion of trust to human-machine
relationships. As he argues (p. 533), users evaluate
the predictability and dependability of decision sup-
port systems based on their usage experience (p. 533).
He also points out that Barbers (1983) notion of trust
as an expectation of technically competent role per-
formance is at the heart of trust in machines (p. 529).
This view of trust in technology has also received sup-
port in the marketing literature. Schlosser, White,
and Lloyd (2006) demonstrate empirically that con-sumers ability beliefs about a firm are more essential
than benevolent and integrity beliefs in determining
online purchase intentions. These authors justify this
finding by arguing that online customers tend to be
objective and performance orientated when searching
for information relevant to their decision and will
therefore be more attuned to ability and performance
beliefs. Researchers of human computer interaction
have agued that when computers mediate interac-
tion among individuals or when computers use
expanded sensory channels, like voice or gesturing, to
communicate with users, humanlike perceptions,
such as gender stereotyping, may be attributed to
computers (Nass, Moon, & Green, 1997; Reeves &
Nass, 2000). Thus, although it is recognized that
under specific conditions it may be possible for con-
sumers to attribute non-performance-based evalua-
tions of trust in technology, the present study focuses
on consumer use of a basic typing computer interface
to carry out banking functions. Hence, the study exa-
mines consumers ability and performance beliefs about
PC banking as the basis of trust in technology. Trust
in technology is customers expectations of technicallycompetent, reliable, and dependable performance.
A key principle of relationship marketing is that trust
mediates the influence of company actions on consumer
behaviors (Morgan & Hunt, 1994). To say that trust
mediates the effects of these variables on consumer
decisions and behaviors is to argue that trust plays an
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important middleman function in market exchange.
It suggests that managerial action does not necessarily
have a direct effect on consumers, and instead has an
effect only to the extent that it increases consumer trust.
The mediating role of trust has been demonstrated in a
number of studies. For example, Bart, Shankar, Sultan,
and Urban (2005) find that the mediating role of trustin a Web site on behavioral intention is stronger than
the direct effect of any antecedent variable on behav-
ioral intention. As another example, Schlosser, White,
and Lloyd (2006) find that the effect of perceived
investment in a Web site on purchase intentions is
totally mediated by consumer trusting beliefs.
However, it remains an open question whether trust will
also mediate the influence of more social-psychological
variables, such as identity commitment and calcula-
tive commitment. Consumers with strong commit-
ment to a technology user identity may be inclined touse electronic channels regardless of their level of
trust in the technology, leading to identity commit-
ment having a main effect on frequency of interac-
tions. The potential of identity reinforcing actions to
improve self-esteem (Gecas & Schwable, 1983) make
them a powerful motivator. Given a substantive value
proposition, calculative commitment may also directly
determine frequency of transactions. Research on the
technology acceptance models suggest that individu-
als are inclined to use technology if they consider it
useful or if it improves their performance, regardless
of their attitude toward the technology (Davis, 1989).
Also, as earlier noted, some individuals are being
forced to use the Internet regardless of their attitudes
toward such technology. Even though trust increases
perceived usefulness (Pavlou, 2003), consumers may
be forced by circumstance or externalities to use PC
banking technology beyond their comfort level. This is
indicated by the fact that although consumer use of
PC banking has grown, their privacy concerns have
not diminished (Wolfe, 2005). Trust may therefore
not mediate the effect of calculative commitment on
consumer PC banking use. However, because consid-erable previous research has demonstrated the
centrality of trust as a mediator in market exchange,
it is both theoretically and managerially useful to
examine its potential to mediate the influence of the
variables introduced in this study. The study therefore
tests whether identity commitment and calculative
commitment influence consumer behavior directly and
indirectly because they influence trust, which in turn
influences consumer behavior.
It is proposed that trust in PC banking technology
mediates the effects of calculative commitment, iden-
tity commitment, environmental security, operational
benevolence, and operational competence on perceivedvalue from the firm by performing a middleman
function in the interactive process of producing cus-
tomer value. According to Sawhney (2006, p. 370), the
value of a solution can be decomposed into three ele-
ments: the value of individual products and services
that make up the solution; the value of marketing and
operational integration in creating the offering; and the
value of customizing for context and customer specific
needs. Even though firms are in control of the first
two, achieving a customer-centric value laden solution
requires that customers engage the technology pur-
posefully to determine its functionality and reliability.Some degree of risk-taking behavior is necessary for
consumers to learn to use electronic channels effective-
ly. But such risk-taking behavior will only materialize
by enhancing consumer confidence in the capability of
the channel.
In the absence of trust in technology, the benefits of
calculative commitment and identity commitment
may be stymied by high perceived risk and stress
associate with the use of electronic channels. In the
specific case of identity commitment, it is argued that
when consumers discover PC banking technology to
be untrustworthy, their identity may be threatened as
they may loose reputation among associates. Because
consumers regard their technology user identity as
important, their perception of value will be severely
diminished and may even discontinue use to the chan-
nel. Thus trust in technology is essential if the benefits
of identity commitment are to be realized.
Finally, a hierarchical perspective on trust is taken by
examining whether the impact of trust in PC banking
technology on perceived value from the firm is mediat-ed by trust in the firm. Even though a consumer may
trust a firms PC banking technology, trust in the firm
remains necessary for generating commitment, loyalty,
and reducing consumers attention to competing offers
(Crosby, Evans, & Cowles, 1990; Morgan & Hunt,
1994). Thus consumers who trust the firm are better
able to recognize value in the firms service offering.
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10 JOURNAL OF INTERACTIVE MARKETING
In light of prior discussions, the following are
anticipated:
H1: Trust in technology mediates the effect of iden-
tify commitment to technology on (a) perceived
value from the firm and (b) PC banking transaction
frequency.
H2: Trust in technology mediates the effect of calcu-
lative commitment to PC banking on (a) perceived
value from the firm and (b) PC banking transaction
frequency.
H3: Trust in technology mediates the effect of envi-
ronmental security on (a) perceived value from the
firm and (b) PC banking transaction frequency.
H4
: Trust in technology mediates the effect of oper-
ational benevolence on (a) perceived value from the
firm and (b) PC banking transaction frequency.
H5: Trust in technology mediates the effect of oper-
ational competence on (a) perceived value from the
firm and (b) PC banking transaction frequency.
H6: Trust in the firm mediates the effect of (a) oper-
ational benevolence (b) operational competence and
(c) trust in PC banking technology on perceived
value from the firm.
Control Variable
Because transaction frequency should increase as cus-
tomers adopt new types of transactions, transaction
variety is included as a control variable in predict-
ing transaction frequency. Transaction variety is a
measure of the how many of the four types of transac-
tions (checking balances, transferring funds, bill pay-
ment, and online purchases) customers have adopted.
RESEARCH DESIGN
Data Collection
The study employed a multimethod approach to data
collection, combining survey data with transaction
data supplied by the host company. Data were collect-
ed from members of a regional teachers credit union
located in the northwestern United States. In addi-
tion to the traditional credit union savings and loan
products, this credit union, like most others operating
in the United States, offers a comprehensive portfolio
of financial products from associated companies for
cross-selling and up-selling to members. A survey of
the total population of 2,745 members who used PCbanking was conducted via mail. The questionnaire
was accompanied by a cover letter explaining the pur-
pose of the study and inviting members to participate.
Respondents were given the option of responding by
completing the mailed survey and returning it via a
self-addressed postage-paid envelope or responding to
the same questionnaire posted on a Web site. A single
mailing was carried out followed up by telephone calls
to encourage completion of the survey. The survey
yielded 834 responses, representing a 30% response
rate. Twenty-two percent (22%) responded via the
Web site and 78% responded via mail. Sample char-acteristics are reported in Table 2. The average
household income of the sample is approximately
$50,000, and the sample is 59% female. The predomi-
nance of women in the teaching profession accounts
for a lower-than-average percentage of males.
Journal of Interactive Marketing DOI: 10.1002/dir
SEX AGE LEVEL OF EDUCATION INCOME
Male 41 1824 25.3 High school 4.9 Less than $30,000 10.2
Female 59 2534 16.2 Some college 26.2 $30,000$50,000 27.4
3544 14.4 College degree 36.5 $51,000$75,000 28.8
4554 21.3 Graduate degree 29.9 $76,000$100,000 21.9
55 22.8 Professional qualifications 2.5 $101,000$150,000 1.3
TABLE 2 Demographic Profile of Respondents
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Measurement Development
Measurement scales applied in the study are dis-
played in the Appendix. Scale items were adopted
from the literature whenever possible and in some
instances minor changes were made to accommodate
the context. All latent constructs were measuredusing seven-point scales with 1: strongly disagree,
and 7: strongly agree, except perceived value, which
was measured using a 10-point semantic differential
scale. Descriptive statistics and intercorrelations are
presented in Table 3, and scale reliabilities are pre-
sented in Table 4. Measures of trust in PC banking
technology were developed from a review of studies
that measured reliability and dependability or cogni-
tive aspects of trust (Johnson & Grayson, 2005;
Johnson-George & Swap, 1982; McAllister, 1995).
Three items were developed that embody themes of
perceived reliability and dependability of the PCbanking technology in executing transactions. The
scale has a Cronbach Alpha value of .78, indicating
satisfactory reliability.
Regarding antecedents of trust in PC banking tech-
nology, calculative commitment was measured using
a new scale, which taps consumer motivation to use
PC banking technology arising from benefits of time
efficiency and convenience. The scale achieved
acceptable reliability with a Cronbach alpha of .86.
Operational competence and operational benevolence
were measured using 3-item scales developed by
Sirdeshmukh, Singh, and Sabol (2002). Identity com-
mitment was measured using a formative scale adopted
from Stryker and Serpe (1994). The scale comprises
four measures. One item asks respondents to rate the
extent to which family and close friends think the
respondent is good at using computer technology. A
second item asks the same question in relation tocoworkers. The remaining two items ask respondents
to rate how important it is to them that family and
close friends, and coworkers view them as competent
at using computer technology. An identity commit-
ment score was created for each respondent by multi-
plying each of the prior measures by the respective
latter measure and summing these two scores. This
approach to measuring identity commitment assumes
that the greater the importance placed on an identity
and the more an individual is perceived to be associ-
ated with an identity, the more committed the indi-
vidual is to the identity (Stryker & Serpe, 1994, p. 27). A new 4-item scale was developed to measure envi-
ronmental security. The scale taps concerns about
unsolicited contact, ability to protect personal infor-
mation, and the likelihood of user privacy being com-
promised. The scale has a satisfactory Cronbachs
alpha of .81. Overall Cronbachs alpha reliability of
latent constructs are all above the recommended .70
threshold, with the lowest being .75.
Trust in the firm was measured using a 5-item scale
comprising three items measuring honesty and two
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TABLE 3 Means, Standard Deviations, and Correlation Matrices
VARIABLES MEAN STANDARD DEVIATION RANGE 1 2 3 4 5 6 7 8 9 10
1. Perceived value from firm 8.1 1.07 110 1
2. PC transactions freq. 20.1 21.4 1157 .05 1
3. Trust in the firm 5.2 1.2 17 .64 0.06 1
4. Trust in PC technology 5.5 1.04 17 .45 .10 .60 1
5. Identity commitment 49.0 24 298 .08 .04 .10 .23 1
6. Calculative commitment 5.4 1.26 17 .28 .21 .38 .61 .23 1
7. Operational benevolence 5.5 1.2 17 .48 .06 .73 .52 .04 .33 1
8. Operational competence 5.4 1.03 17 .33 .03 .50 .44 .00 .26 .66 1
9. Transaction variety 2.2 .61 17 .05 .33 .07 .12 .01 .18 .07 .02 1
10. Environmental security 3.11 1.85 17 .05 .02 .07 .15 .04 .00 .03 .07 .10 1
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12 JOURNAL OF INTERACTIVE MARKETING
items measuring benevolence, developed from a review
of the empirical trust literature (e.g., Ganesan, 1994).
The five items collectively have a Cronbachs alpha of
.87. To reduce the possibility of common method bias
affecting the study results, frequency of PC banking
transactions was measured objectively using transaction
data provided by the host firm. It is the sum of trans-
actions performed by a customer in the quarter
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CONSTRUCT INDICATORS STANDARDIZED LOADING (L)a RELIABILITY VARIANCE EXTRACTED
Identity commitment
Idf1 .99
Calculative commitment .86 .72
Tskft1 .72
Tskfit2 .86
Tskft3 .93
Tskft4 .87
Operational benevolence .88 .78
OBP1 .90
OBP2 .92
OBP3 .82
Operational competence .80 .65
OC1 .68OC2 .87
OC3 .85
Trust in PC technology .78 .66
TTH1 .79
TTH2 .74
TTH3 .91
Environmental security .81 .55
Env1 .80
Env2 .90
Env3 .66
Env4 .56
Trust in the firm .87 .70
Trus1 .82Trus2 .87
Trus3 .87
Trus4 .77
Trus5 .73
Perceived value .86 .76
Pval1 .86
Pval2 .90
Pval3 .85
PC Transaction frequency
PTR .92
Transaction variety
THG .93
a All loadings are significant atp .01. Descriptive fit statistics:2 (308) 1540 (p .01); RMSEA .069; CFI .96,IFI .96
TABLE 4 Properties of the Measurement Model
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immediately following the customer survey. Trans-
action variety is the number of types of transactions
(check balance, funds transfer, bill payment, and pur-
chase) performed by a customer in the quarter follow-
ing the survey. Finally, perceived value was measured
using a 3-item semantic differential scale adopted from
Sirdeshmukh, Singh, and Sabol (2002).
Measurement Evaluation
Confirmatory factor analysis procedures (CFA) were
used to evaluate the measurement model. Both the
measurement and structural models were estimated
using maximum likelihood procedures in LISREL 8.54
(Joreskog & Sorbum, 1993). Results are displayed in
Table 4. All items load significantly (p .001) on their
intended factor, supporting the discriminant validity
of the study constructs. Error terms for the indicator
of single-item constructs (transaction frequency,transaction variety, and identity commitment) were
set at (1)2 (Crosby, Evans, & Cowles, 1990). Discri-
minant validity was further tested using procedures
recommended by Fornell and Larcker (1981), which
compare the variance extracted by each construct
with the squared correlation between the construct
and each of the other constructs in the model. All con-
structs passed the test, providing further support of
discriminant validity. The variance extracted by each
of the ten latent constructs exceeds the .50 threshold,ranging from .55 to .78.
The chi-square for the measurement model is 1540
(p.001, df 308), and the models fit statistics suggest
a satisfactory fit of the model to the data (CFI 0.96,
IFI 0.96, RMSEA 0.069). In summary, the mea-
surement analyses indicate that the scales are inter-
nally consistent, able to discriminate among con-
structs, and are adequate indicators of the theoretical
constructs.
RESULTS
Parameter estimates for the proposed structural
relationships simultaneously estimated with the
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PATHS HYPOTHESIZED TRUST MEDIATED MODEL RIVAL MODEL
Identity commitment trust in PC technology (11) .11*** -Calculative commitment trust in PC technology (12) .46*** -
Environmental security trust in PC technology (13) .13*** .13***
Operational benevolence trust in PC technology (14) .26*** .42***
Operational competence trust in PC technology (15) .13*** .15***
Operational benevolence trust (24) .59*** .50***
Operational competence trust (25) .04 .02
Trust in technology trust (21) .31*** .29***
Trust in technology transaction frequency (31) .08** .05
Trust in technology perceived value (41) .10** .10**
Trust perceived value (42) .58*** .58***
Covariate: transaction variety transaction frequency (35) .33*** .33***
R2 transaction frequency .12 .11
R2 perceived value .41 .41
2 (d.f.) 1643(326)p .01 1867328p .01
2 difference test: 2 difference of 224 at 3 d.f.sig.p .01
RMSEA .070 .075
CFI .96 .96
IFI .96 .96
***p .01,**p .05
TABLE 5 Results: Structural Model
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14 JOURNAL OF INTERACTIVE MARKETING
measurement model are presented in Table 5. The chi-
square for the proposed model is 1643 with 326 degrees
of freedom (p .01). An IFI of .96 and CFI of .96 and a
RMSEA of .070 indicate acceptable fit of the proposed
conceptual model to the data. R2 for transaction fre-
quency and perceived value are .12 and .41, respectively.
The combined survey and transaction data supports
the role of consumer identity commitment and trust
in technology. Regarding the main effects, consumer
identity commitment (11 .11,p .001), calculative
commitment to PC banking (12 .46,p .001), envi-
ronmental security (13 .13, p .001) operational
benevolence (14 .26, p .001), and operational
competence (15 .13,p .001) all have a significant
positive effect on trust in PC banking technology.
Operational benevolence significantly contributes to
trust in the firm (24 .59,p .001), but the effect of
operational competence on trust in the firm is insignif-icant. Regarding the consequences of trust in PC bank-
ing technology, trust in technology positively and sig-
nificantly affects trust in the firm (21 .31p .01),
perceived value (41 .10 p .05) and transaction
frequency (31 .08p .05). Finally, transaction vari-
ety positively affects transaction frequency (35 .33
p .001). To demonstrate the added contribution of
identity commitment and calculative commitment, a
rival model was estimated without the paths from
identity commitment and calculative commitment totrust in PC banking technology. The results are pre-
sented in Table 5. The rival model exhibits inferior
model fit compared with the hypothesized model,
indicated by a significant deterioration in chi-square
fit (2 difference of 224; (d.f.3) significant atp .001)
and a deterioration of the RMSEA by .005.
Results of mediation tests following steps recom-
mended by Baron and Kenny (1986) are presented in
Tables 6 and 7. Trust in technology fully mediates the
effect of identity commitment to technology and envi-
ronmental security on perceived value as these vari-
ables are significantly related to trust in technology
but not perceived value and trust in technology is sig-
nificantly related to perceived value. Trust in PC
Journal of Interactive Marketing DOI: 10.1002/dir
STEP 4:
INDEPENDENT
STEP 1: STEP 2: STEP 3: DEPENDENT (IN THE
INDEPENDENT MEDIATING INDEPENDENT PRESENCE OF TRUST
DEPENDENT VARIABLE: MEDIATING DEPENDENT DEPENDENT IN TECHNOLOGY) CONCLUSION
Perceived value
Identity commitment .11*** .03 .03 Full mediation
Calculative Commitment .45*** .12*** .05 Full mediation
Operational benevolence .29*** .48*** .43*** Partial mediation
Operational competence .13*** .17*** .15*** Partial mediation
Environmental security .13*** .01 .05 Full mediation
Trust in PC technology .45*** .15***
Transaction frequency
Identity commitment .11*** .05 .05 Fail
Calculative Commitment .45*** .22*** .22*** Fail
Operational benevolence .29*** .05 .05 Fail
Operational competence .13*** .05 .05 Fail
Environmental security .13*** .02 .02 Fail
Trust in PC technology .13*** .00 .01 Fail
**p .05,***p .01,
TABLE 6 Test of Mediating Effects of Trust in PC Banking Technology
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banking technology also fully mediates the effect of
calculative commitment on perceived value, indicated
by the effect of calculative commitment on perceived
value becoming insignificant in the presence of trust
in technology. Trust in technology partially mediates
the effects of operational benevolence and operational
competence on perceived value from the firm, indicat-
ed by the coefficients decreasing from .48 to .43 and
from .17 to .15, respectively, in the presence of trust in
technology. Hence, hypotheses 1a to 5a are supported
by the data.
The mediation tests for trust in PC banking technolo-
gy on transaction frequency reveal a different picture.
The results presented in Table 6 indicate that
although trust in technology has a significant effect
on transaction frequency ( .13,p .001), when a
direct path from calculative commitment to transac-
tion frequency is estimated ( .22, p .001), the
path from trust in technology to transaction frequen-
cy becomes insignificant. This implies that trust in
PC banking does not mediate the effects of antecedent
variables on transaction frequency. Consequently,hypotheses 1b to 5b are unsupported. These results
indicate that calculative commitment to PC banking
is the principal driver of transaction frequency,
unmediated by trust in technology.
Results of the mediating effect of trust in the firm on
perceived value from the firm are displayed in Table 7.
Trust in the firm fully mediates the effect of trust in
technology on perceived value, indicated by the effect of
trust in technology on perceived value becoming
insignificant in the presence of trust in the firm (step 4).
Trust in the firm does not mediate the effect of opera-
tional competence, indicated by operational competence
not having a significant effect on trust in the firm.
However, trust in the firm partially mediates the effect
of operational benevolence on perceived value from the
firm. Hence the data support hypotheses 6a and 6c.
In light of the finding that calculative commitment is
unmediated by trust in PC banking technology, arevised structural model with a direct path from con-
sumer-technology fit to transaction frequency was
estimated. The results displayed in Figure 2 indicate
that calculative commitment has a significant effect
on transaction frequency (31 .18,p .001) and that
the path from trust in technology to transaction fre-
quency has become insignificant. Although the
revised model has the same RMSEA as the original
model (.070), the reduction in the chi-square of 9 points
at 1 degree of freedom for the revised model compared
with the proposed model is significant at p .001.
This finding indicates that the revised model is supe-
rior to the proposed model.
Finally, given that the sample is disproportionately
female (59% females and 41% males), multigroup
SEM analysis was applied to the total sample to
determine whether the results of the revised model
are consistent across gender. The results reveal that
ACHIEVING CUSTOMER VALUE FROM ELECTRONIC CHANNELS 15
Journal of Interactive Marketing DOI: 10.1002/dir
STEP 4:
INDEPENDENT STEP 1: STEP 2: STEP 3: DEPENDENT
INDEPENDENT MEDIATING INDEPENDENT (IN THE PRESENCE
DEPENDENT VARIABLE: MEDIATING DEPENDENT DEPENDENT OF TRUST IN TECHNOLOGY) CONCLUSION
Perceived value
Operational competence .04 .15*** .19*** Fail
Operational benevolence .59*** .44*** .21*** Partial mediation
Trust in PC technology .32*** .15*** .03 Full mediation
Trust in the firm .54*** .35***
TABLE 7 Test of Mediating Effects of Trust in the Firm
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16 JOURNAL OF INTERACTIVE MARKETING
all of the relationships supported by the general sam-
ple also hold for the male and female subsamples,
indicating that study results are not gender-specific.
DISCUSSION
This study investigated the role of consumer technolo-
gy identity commitment as a driver of consumer trust
in electronic channels and the mediating role of trust
in technology relative to trust in the firm. Combined
survey and transaction data from online banking cus-
tomers were used to test the proposed model and
hypotheses. The findings of this study make several
contributions to the extant literature.
First, the study findings extend the relevance of iden-
tity theory as a theoretical foundation for consumer
relationships in the electronic channel environment.
The finding that consumer commitment to their
technology-user identity significantly influences trust
in technology supports the perspective that the use of
electronic channels has socially constructed meaning
(Speier & Venkatesh, 2002). Consumers who regard
their social image as technology users to be important
tend to have higher level of trust in PC banking tech-
nology. This finding suggests that strategies that
enhance the social signaling benefits of prospective
users can potentially increase consumer trial and
loyalty to electronic channels.
Second, the mediating role of trust in technology
demonstrated by this study supports the relevance of
a performance/ability-based notion of trust in a SST
context. This finding corroborates research findings
by Schlosser, White, and Lloyd (2006), suggesting
that ability beliefs are especially relevant to efforts to
increase online purchase intentions.
Third, the results provide insights on the boundary
conditions under which trust is likely to influence
consumer decision making. Contrary to prior rela-
tionship marketing research and theory, the results
show that trust (in technology) does not mediate the
effect of antecedents on transaction frequency, where-
as it does mediate the effect of antecedents on cus-
tomer value from the firm. There are at least two
plausible explanations for why trust in technology
does not mediate the influence of antecedents on tran-
saction frequency. One explanation may be that trust
Journal of Interactive Marketing DOI: 10.1002/dir
Identitycommitment totechnology
Calculative
commitment totechnology
Trust in PCbankingtechnology
PC bankingtransactionfrequency
Internetenvironmentalsecurity
1
2
3
5
1
3
Control variable:Transactionvariety 5
4
Trust inthe firm
Operationalbenevolence
Operationalcompetence
2
Perceivedvalue fromthe firm
4
Y11.11***
Y12.46***
Y13.13***
Y14.26***
Y24.59***
Y25.04 N.S.
21.31***
31.05, N. S.
41.10**
42.58***
35.31***
R2.14
R2.41
X21634, d.f.325, p .01; RMSEA .070; CFI & IFI .96;
Compared with hypothesized model: X2 difference of 9 at 1 d.f. sig. at p .01*** p .01, **p .05; N. S. not significant
Y32.18***
Y15.13***
FIGURE 2Results of the Revised Model
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is not an essential factor influencing electronic channel
use once consumers have adopted the channel. A
study by Bart, Shankar, Sultan, and Urban (2005)
supports this explanation. Their study found that the
mediating effect of trust on behavioral intent is
stronger for online computer purchases and weaker
for ongoing use of financial service Web sites. Theyargue that that trust has less of a mediating role in fre-
quent interaction situations than in high-involvement
infrequent interaction situations that involve elaborate
decision making for which trust can be invoked. A sec-
ond plausible explanation is the aforementioned view
that some consumers may be forced by externalities to
use electronic channels regardless of how trustworthy
they consider the channel.
Fourth, the study demonstrates that incumbent per-
ceptions of operational competence and operationalbenevolence of a firms bricks-and-mortar operations
hold strong implications for consumer trust in elec-
tronic channels. Service researchers have long argued
that information technology is a central enabler of
service quality by facilitating internal, external, and
interactive marketing (Parasuraman, 2000). As tech-
nology assumes greater significance in boundary
spanning, further research is required to fully under-
stand the relationship between service quality and
perceptions of firm technology.
Finally, the studys pattern of results suggests thatconsumer trust in a firm may operate hierarchically.
For instance, the study found that operational compe-
tence did not directly increase trust in the firm;
instead its effect on trust in the firm is totally medi-
ated by trust in technology. The study also found that
trust in the firm mediates the effect of trust in tech-
nology on perceived value from the firm. This finding
suggests that trust in the firm is essential in order for
consumers to associate the benefits of each channel
with the overall value they receive from the firm.
Efforts to improve corporate brand image by improv-
ing electronic channels may be unsuccessful unless
they are accompanied by improvements in trust in
technology and trust in the firm. Front-line employ-
ees and electronic channels may be regarded as micro
targets of trust that contribute to macro trust in the
firm. Evaluations of micro trust may be related to
operational experiences and observations, whereas eva-
luations of macro trust may be more closely related to
top management, corporate mission and identity, and
brand image.
Managerial Implications
The studys finding that calculative commitmentdirectly increases frequency of electronic channel trans-
actions, unmediated by trust, raises the possibility
that some consumers may view electronic channels as
generic and undifferentiated. Once these consumers
adopt an electronic channel, usage may become a
mindless behavioral activity without regard for the
broader perceptions of the brand. Managers should be
wary of possible brand dilution among consumers
who migrate exclusively to electronic channels.
Online consumers may need to be targeted more fre-
quently with brand image reinforcing advertise-
ments. Study findings also suggest that managersneed to focus simultaneously on building trust in elec-
tronic channels and building trust in the firm.
Channel-level trust-building efforts, such as online
privacy policy, should be linked to the firms brand
values and corporate identity. Moreover, managers
should consider brand differentiation of electronic
channels to more fully leverage their potential.
The finding that consumer identity commitment
increases consumer trust in technology presents an
interesting alternative to existing approaches to
marketing electronic channels. Unlike calculativecommitment or operational competence, identity com-
mitment is not directly under the control of the firm.
Thus, to use identity commitment strategically, firms
must help consumers to realize their desired identity.
This identity can be accomplished through identity
reinforcing initiatives such as designating customers to
different usage levels (e.g., silver, gold, or platinum)
to make them more self-aware of their progress as
technology users. Firms can also help customers to
signal their status as technology users to peers by giv-
ing them useful specialty advertising items to pass on
to their peers. Because identity reinforcement has the
potential to improve self-esteem (Gecas & Schwable,
1983), this strategy has the possibility to improve cus-
tomer satisfaction and service recovery evaluations as
well (Zemke & Bell, 2000).
Finally, study results indicate that although per-
ceived environmental security, identity commitment,
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18 JOURNAL OF INTERACTIVE MARKETING
and operational competence are important and
comparable in their effects on building trust in PC
banking technology, calculative commitment and per-
ceived operational benevolence are the most essential
priorities firms need to address in their trust build-
ing efforts. At the very minimum, managers need to
provide a compelling value proposition and assureconsumers that their transactions are protected.
Limitations and Directionsfor Future Research
Caution should be observed in generalizing the find-
ings of this study because of the context of data col-
lection. Data were collected from members of a credit
union who engage in online banking. Arguably, cre-
dit union members are likely to have a more coopera-
tive disposition than customers of a retail bank. Also,
because study data were collected from members of ateacher credit union, the sample contains a dispro-
portionate number of females. However, as previously
noted, multigroup structural equation analysis indi-
cates that all structural model relationships hold for
separate male and female subsamples. Hence, the dis-
proportionate number of females in the sample
appears not to have a material effect on study find-
ings. Another limitation of this study is that the range
of responses may be limited because data collection
was restricted to customers who used both online
and offline services and does not include exclusively
offline customers. Thus, conclusions drawn from thisstudy relate only to users of electronic channels and
not the general universe of consumers. Frequency of
transactions is a sum of the occasions consumers per-
form four types of transactionscheck balances,
transfer funds, pay bills, and make purchases (loans
and investment products)over a 3-month period
immediately following the study. Even though trans-
action variety is included as a covariate in the model,
a possible limitation of the study is that this measure
may contain a high incidence of repeated automated
transactions. Finally, it may be argued that the per-
ceived value of electronic channels is a more appro-
priate dependent variable than perceived value from
the firm. Overall value from the firm was selected
because the respondents are offline users who now
use PC banking in complement with offline activities
and may therefore not be able to reliably isolate only
the perceive value associated with PC banking.
Regarding avenues for further research, study data
were collected in the context of PC banking. However,
it is possible that consumer attitudes differ across
various electronic channels. For instance, the antec-
edents of consumer trust in ATMs or in-store kiosks
may differ from that of a Web site. In-store kiosks and
ATMs may be viewed as more similar to retail storesand therefore more dependent on trust in the brand.
Also, the question remains: How does the role of cal-
culative commitment vary across these contexts?
Further research is required on these issues. This
paper echoes the call by Sirdeshmukh, Singh, and
Sabol (2002) for further research on customer value
especially within the context of electronic channels,
which involves self-initiated customer learning. As
electronic channels continue to assume a greater role
in the boundary spanning function of the firm, strate-
gies focused on improving consumer calculative com-
mitment and identity commitment present additionalavenues for achieving enduring customer loyalty.
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Calculative commitment to PC banking technology (new) (1. strongly disagree7. strongly agree)
1. Good time management dictates that I do PC Branch banking.
2. My banking activities would require considerably more time and effort, if I were to stop using PC Branch.3. For the sake of being able to function more efficiently, I feel motivated to do PC Branch banking.
4. When I consider the convenience of PC Branch, it makes sense for me to do it.
Identity commitment to technology (Stryker & Serpe, 1994)
Formative measure created by addition of measures (1*2) (3*4) below
1. How important is it to you that your co-workers view you as being competent at using computerized technology?
(1. not at all important7. very important)
2. How good at computerized technology do your co-workers think you are? (1. poor7. excellent)
3. How important is it to you that your family and close friends view you as being competent at using computerized
technology?
4. How good at computerized technology do your family and close friends think you are? (1. poor7. excellent)
Operational benevolence (Sirdeshmukh, Singh, & Sabol, 2002) (1. strongly disagree7. strongly agree)1. The Credit Union has policies that indicate respect for the customer.
2. The Credit Union has policies that favor the customers best interest.
3. The Credit Union acts as if the customer is always right.
Firm operational competence (Sirdeshmukh, Singh, & Sabol, 2002) (1. strongly disagree7. strongly agree)
1. XYZs branches are organized so as to make it easy for me to execute my transactions.
2. XYZs branches are generally not congested.
3. XYZs branches keep tellers moving so you dont have to wait.
Internet environmental security (new) (1. strongly disagree7. strongly agree)
1. I worry about unsolicited contact on the Internet from people/firms I dont even know. (reverse)
2. I am very concerned that people/firms are able to get my email. (reverse)
3. The Internet is out of control in terms of our ability to protect personal information. (reverse)4. With the best of care, my privacy on the Internet can still be compromised. (reverse)
Trust in PC banking technology (new) (1. strongly disagree7. strongly agree)
1. I can rely on PC Branch technology to execute my transactions reliably.
2. Given the state of existing PC banking technology, I believe that technology related errors are quite rare.
3. In my opinion, PC Branch technology is very reliable.
Trust in the Firm (new) (1. strongly disagree7. strongly agree)
1. If XYZ firm provides an explanation for a problem, I can be certain they are telling the truth.
2. XYZ firm has been honest in dealing with customers.
3. I can count on XYZ firm to be sincere in our transactions.
4. In the future, I can count on XYZ to consider how its decisions will affect me.
5. I can rely on XYZ firm to provide advice that is not detrimental to my long-term interest.Perceived value from the firm (Sirdeshmukh, Singh, & Sabol, 2002)
1. For the charges you pay for using this credit union, would you say that XYZ firm is:
1. a very poor deal . . . 10. a very good deal.
2. For the time you spend in order to use the service of XYZ firm, would you say it is: 1. highly unreasonable . . .
10: highly reasonable.
3. How would you rate your overall experience with XYZ firm:
1. not at all worthwhile . . . 10. extremely good value.
APPENDIX 1 MEASURES
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Transaction frequency:A count of the number of transactions performed by customers in the three months prior to the
survey (provided by host firm).
Transaction variety
Consumers engaging in 1 to 4 categories of transactions:
1. Check balances
2. Transfer funds
3. Pay bills
4. Make purchases (e.g., apply for loans, purchase investment products etc.)