achieving customer value

8/2/2019 Achieving Customer Value

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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


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



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


5/21


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



6/21

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



8/21

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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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


H5: Trust in technology mediates the effect of oper-

ational competence on (a) perceived value from the


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.


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



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


11/21


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


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


12/21

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



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


13/21


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


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


14/21

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



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


15/21


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


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


16/21

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,




17/21


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.)

achieving customer value

Documents