The Relationship Bonding Strategy and Customer Relationship Download

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2008 現代經營管理研討會
Relationship marketing, service quality, and
customer actual behaviors
Relationship marketing, service quality, and customer actual
behaviors
HUI-JU CHEN
Lecturer of Department of Business Administration, De Lin Institute of Technology.
Abstract
Purpose - This study aims to examine how relationship marketing and service quality influence banking
customers’ actual behaviors through development of an empirical model to explore the links among service
attributes (financial bond, social bond, structural bond, functional service quality, and technical service quality),
customer satisfaction, customer trust, customer loyalty, and customer actual behaviors (relationship length, depth,
and breadth) with the financial services.
Methodology/Approach – A theoretical framework is proposed to suggest the links between the eleven
constructs. Data from 1211 customers of a Taiwanese bank is examined through structural equation modeling
(SEM).
Findings - Results indicate that service attributes influence customer satisfaction, except for social bond and
technical service quality. This study also demonstrates customer satisfaction and customer trust influence
customer loyalty, and customer loyalty has a positive impact on relationship length, depth, and breadth.
Practical implications – Financial services providers’ marketing budget allocations can be planned according to
the results of this study. Managers should keep in mind that customer discriminates different service attributes
when they consider their relationship length, depth, and breadth with the financial services provider.
Originality/Value – This paper contributes to the understanding of the antecedents and consequences of
customer loyalty, which is relevant within financial services context, also to the discovery of the relative
importance of service attributes in enhancing customer actual behaviors.
Keywords Relationship marketing, Service quality, Customer loyalty, Relationship length, Relationship depth,
Relationship breadth
Paper type: Research paper
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1. Introduction
Owing to the deregulation in the financial services industry, institutions from one sector
have attempted to generate business at the expense of other sectors (e.g. banks have explored
opportunities in brokerage houses and insurance companies). In the process of trying to gain
business at the expense of other sectors, managers should realize that loyal customers are by
far the best prospects for upgrading or new products/services (Kamakura et al., 1991). As a
consequence, managers should take the view of “customer lifetime value” when they are
trying to enhance firm profits. Customer lifetime value is defined as the net present value of
all earnings from an individual customer (Blattberg et al., 2001; Reinartz and Kumar, 2003;
Rust et al., 2000; Venkatesan and Kumar, 2004). To fully recognize customer profitability,
companies must consider all customer actual behaviors, including buying more (Bell et al.,
2005; Chiu et al., 2005; De Wulf et al., 2001; Doney and Cannon, 1997; Garbarino and
Johnson, 1999; Gruen et al., 2000; Hennig-Thurau et al., 2002; Lemon et al., 2002;
Macintosh and Lockshin, 1997; Rauyruen and Miller, 2007; Rust et al., 2000), using more
(e.g., Bolton et al., 2000; Evanschitzky et al., 2006), paying more (Zeithaml et al., 1996), and
buying across categories (e.g., Crosby et al., 1990; Johnson and Grayson, 2005; Verhoef,
2003; Verhoef et al., 2001). Bolton et al. (2004) proposed three types of customer behaviors,
which are related to customer lifetime value through the revenues they generate for the firm,
that is, relationship length, depth, and breadth. Relationship length refers to the probability a
customer will continue the relationship with the firm, relationship depth refers to the
deepening of the customer’s relationship with the firm through increased usage or upgrading,
and relationship breadth is reflected in cross-buying; that is, the number of different products
or services purchased from a company over time (Blattberg et al., 2001). In order to have an
advanced and full-scale understanding of the consequences of customer loyalty, with this
study, we adopt Bolton et al.’s (2004) perspective to investigate three types of customer
actual behavior for financial services.
Relationship marketing has been shown to generate stronger customer relationships that
enhance customer loyalty and firm profits (Abdul-Muhmin, 2005; Beatty et al., 1996; Bolton
et al., 2004; Chiu et al., 2005; Crosby et al., 1990; Liang and Wang, 2006; Morgan and Hunt,
1994; Palmatier et al., 2006). This holds especially true for those industries which already
depend heavily on their customer relationship management, as is the case with the financial
sector (Chiu et al., 2005; Crosby et al., 1990; Liang and Wang, 2006). Aside from identifying
relationship marketing instruments as the key drivers of customer loyalty, the study by Crosby
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actual behaviors
and Stephen (1987) of the life insurance industry found that product performance also plays
an important role in influencing customer decision making. Some scholars, thus, suggested
and empirically supported service quality as the mainstay around which financial services
industry and business performance revolves. (Bell et al., 2005; Crosby et al., 1990; Johnson
and Grayson, 2005; Liang and Wang, 2006; Roos et al., 2006). Although prior studies
pertaining to the effectiveness of relationship marketing and service quality have contributed
to understanding financial services consumers’ perception and behavioral intention, studies
examining the joint effects is lacking. Therefore, it is important to understand the relative
influence of each factor, which can be judged and appropriately implemented by financial
services providers.
With this article, we propose and test an integrative theoretical model that identify the
relative importance of each service attribute on customer loyalty, and to examine the impact
of customer loyalty on three levels of customer actual behavior, which includes relationship
length, relationship depth, and relationship breadth. To achieve these, we first review previous
research dealing with the exogenous and endogenous variables of the proposed model, then
present the research methodology including the instruments used for hypothesis testing.
Finally, the empirical results are examined, and key managerial and research implications are
provided.
2. Conceptual Framework and Hypotheses
Drawing on previous literature, we propose the extended and advanced customer loyalty
model (see Fig. 1). It is predicted that relationship bonds (financial, social, and structural) and
service quality (functional and technical) will impact customer loyalty indirectly through
customer satisfaction and trust. Moreover, an exploratory component of this study is to
discover if customer loyalty play an important role on influencing the three dimensions of
customer actual behavior. In sum, we argue that if customers perceive high quality of service
attributes, they are more likely to feel satisfied with and trustworthy in the financial services
provider, which in turn contributes to customer loyalty and leads to excellent business
performance.
--------Take in Figure (1)---------
2.1 Relationship Marketing
The importance of relationship marketing has received considerable research attention,
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particularly in service contexts (Macintosh and Lockshin, 1997). Relationship marketing,
defined as marketing activities that attract, maintain, and enhance customer relationships
(Berry, 1995; Berry and Parasuraman, 1991; Gronroos, 1994), has changed the focus of
marketing orientation from attracting short-term, discrete transactional customers to building
long-lasting, intimate customer relationships. To foster customer loyalty, three relationship
bonds have been identified and well recognized: financial, social, and structural bond (e. g.,
Armstrong and Kolter, 2000; Berry and Parasuraman, 1991; Chiu et al., 2005; Hsieh et al.,
2005; Lin et al., 2003; Peltier and Westfall, 2000; Williams et al., 1998).
Financial Bond
Berry (1995) defined financial bond as stimulating customer’s consumption motivation
and acquiring customer loyalty by using pricing incentives, such as price discounts and gifts.
In previous studies, researchers have argued that one motivation for customers to engage in
relational exchanges is to save money (e.g., Gwinner et al., 1998; Peltier and Westfall, 2000;
Peterson, 1995). Financial services providers often reward loyal customers with special price
offers in response to the fierce price competition. This kind of relationship bond is similar to
functional bond identified by Smith (1998), and thus is the multiplicity of economic,
performance, or instrumental ties or linkages that serve to promote continuity in a
relationship. The effectiveness of such tactics is based on increased customer satisfaction
resulting from receiving a value without a corresponding cost or payment (Anderson et al.,
1994). Financial bond may have positive consequences for sellers, including leading buyers to
perceive a purchase as having an improved acquisition utility (Ailawadi et al., 2001;Chandon
et al., 2000; Chiu et al., 2005), spreading positive information, and maintaining exchange
relationships (Campbell, 1999).
Social Bond
Social bond is personal ties or linkages forged during interpersonal interactions (Berry,
1995; Wilson, 1995) and identifications (Smith, 1998; Turner, 1970). Proponents of this
strategy include mutual interaction, communication, support, empathy, openness, and
closeness. From the viewpoint of the customer, such tactics dispose customers to selfdisclosure, listening, and caring, which in turn improve the mutual understanding between the
customer and the service provide (Chiu et al., 2005), provide psychological benefits (Beatty et
al., 1996; Gwinner et al., 1998), and promote relationship quality further (Crosby et al.,
1990). The function of social bond also positively influence customers’ emotions toward or
feelings associated with the service experience and contribute to the formation of an affective
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component of attitude (Chiu, 2002; Edwards, 1990).
Structural Bond
Structural bond offers customers value-added benefits that are difficult or expensive for
business to provide and that are not readily available elsewhere (Berry, 1995; Chiu et al.,
2005). This kind of bond means providing a structural solving program for customers, such as
integrated services through their business partners that are not available from other sources,
thus raising the customer’s cost of switching to a competitor and successfully retaining the
customer. Service providers can utilize an integrated customer database to emphasize
structural bonds with their customers (Dibb and Meadows, 2001). They can also provide
knowledge and information about the industry and customized products to customers (Hsieh
et al., 2005). Some may even consider forming alliances with other service providers to
provide customers with greater choices (Ranganathan and Ganapathy, 2002). By providing
this level of relationship bond, service providers can consolidate their relationship with
customers, improve customer efficiency and productivity, and generate sustainable
competitive advantages (Berry and Parasuraman, 1991; Peltier and Westfall, 2000).
2.2 Service Quality
The foundation of service quality theory lies in the product quality and customer
satisfaction literature (Brady and Cronin, 2001). In Gronroos’s (1982; 1984) seminal
conceptualization of service quality, which suggested two service quality dimensions:
functional and technical. Functional service quality relates to the process by which the core
service is delivered. Technical service quality reflects the outcome of the service act or what
the customer receives in the service encounter. Based on Gronroos’s framework, Rust and
Oliver (1994) and Brady and Cronin (2001) developed more integrated service quality models.
As to the empirical results, McDougall and Levesque (1994) and Bell et al. (2005) also found
support for functional and technical service quality in the financial services context. Therefore,
this study postulates that functional service quality and technical service quality are able to
affect consumer’s attitude and behavior.
Functional Service Quality
Financial services are designed to help customers achieve profits while avoiding risk,
and its products are highly complex and information asymmetric, making them difficult for
customers to fully understand (Crosby et al., 1990).
Therefore, financial services are
comprised of more credence property than other services. Alford and Sherrell (1996) argued
that credence property services are frequently judged by service delivery. Sweeny et al. (1999)
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defined service promptness and help willingness as the process quality. Furthermore,
Sirdeshmukh et al. (2002) articulated the impact of how service providers resolve problems
that arise during service delivery and recognize it as a critical point that provide insights into
service provider character. Adopting a broader view, Farmer (1987) and Lam et al. (2004)
incorporated timeliness, reliability, ease of trading, process flow, process flexibility, and
promptness as key components of functional service quality. Czepiel et al., (1985) suggested
that the attitude, behavior, and expertise of service employees define the quality of the
delivered service and ultimately affect what clients evaluate as a satisfactory encounter.
Similarly, many researchers also hold the same opinion toward functional service quality
(Bitner, 1990; Bitner et al., 1990; Brady and Cronin, 2001; Gronroos, 1990). The significance
of this dimension is captured in Surprenant and Solomon’s (1987) work, which suggested that
service quality is more the result of processes than outcomes.
Technical Service Quality
There is a consensus in the literature that the technical quality of a service encounter
significantly affects customer perceptions of service quality. Czepiel et al. (1985) refer to the
technical outcome as the actual service and posited that it is a determinant in assessing the
quality of a service encounter. Rust and Oliver (1994) considered the service outcome as the
service product and suggested that it is the relevant feature customers evaluate after service
delivery. Bell et al. (2005) and Hsieh and Hiang (2004) also found the significant impact of
technical service quality on customer perception and behavioral intention. Further, Brady and
Cronin (2001) indicated that the customer may have a positive perception of other service
quality dimension, but the negative valence of the outcome can ultimately lead to an
unfavorable service experience. For example, consider a customer who approaches a bank to
inquire about a mortgage loan. Service performance may be irrelevant if the loan is not
approved. Therefore, Service outcome is critical for judging the service quality, and is an
important determinant to form an opinion about the results of service delivery (Rust and
Oliver, 1994).
2.3 Customer Satisfaction
Customer satisfaction is perceived as a relative judgment that considers the qualities
versus the costs and efforts obtained through a purchase (Ostrom and Iacobucci, 1995).
Satisfaction with the relationship is considered an important outcome of buyer-seller
interaction (Roos et al., 2006; Smith and Barclay, 1997). The literature contains two general
conceptualizations of customer satisfaction: transaction-specific satisfaction and cumulative
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satisfaction (Bolton and Drew, 1991; Cronin and Taylor, 1994; Shankar et al., 2003). While
transaction-specific satisfaction may provide specific diagnostic information regarding a
specific product or service encounter, cumulative satisfaction resulting from a series of
transactions or service encounters is a more fundamental indicator of a firm’s past, current,
and future performance (Anderson et al., 1997; Lam et al., 2004; Oliver, 1997). Therefore,
this study focuses on cumulative satisfaction and defines satisfaction as the emotional state
developed from a relationship that resulted from customer interactions with an online service
provider over time.
Theoretically, service attributes can be considered as a cognition-based construct, while
customer satisfaction is mainly an affective and evaluative response (Oliver, 1993). Social
science literature indicates that cognitive thought processes trigger affective responses
(Weiner, 1986), suggesting that customer assessments of service attributes affect their
satisfaction attitude. That is, the degree to which service provider could meet the requirements
of customers influenced the strength of the customer’s positive attitude toward the services
providers (Baker et al., 1999; Turnbull and Moustakatos, 1996). In accordance, Bolton et al.
(2004) suggested that relationship marketing instruments and service quality programs
enhance customer satisfaction. Thus, we propose that
H1a: Financial bond positively influences customer satisfaction.
H1b: Social bond positively influences customer satisfaction.
H1c: Structural bond positively influences customer satisfaction.
H1d: Functional service quality positively influences customer satisfaction.
H1e: Technical service quality positively influences customer satisfaction.
2.4 Customer Trust
Trust is likely to be salient in the financial services context because customer-firm
relationships are characterized by credence qualities that reduce the ability of customer to
make objective assessments of service quality (Alford and Sherrell, 1996; Johnson and
Grayson, 2005). The development of trust is thought to be an important result of investing in
dyadic buyer-seller relationships (Gundlach et al., 1995). Crosby et al. (1990) indicated that
trust is a conviction when the customer develop a tacit understanding with a sellers, and a
seller can be relied upon to behave in such a manner that the long-term interest of the
customer will be served. According to Morgan and Hunt (1994), trust plays a major role in the
success of developing customer relationships. Drawing on previous literature (Gounaris, 2005;
Sirdeshmukh et al., 2002), we define trust as a consumer’s confidence in the financial service
provider’s reliability, benevolence, and integrity.
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In previous studies, satisfaction precedes trust is well established in the marketing
literature (e.g. Garbarino and Johnson, 1999; Geyskens et al., 1998). The rational is that
satisfaction with past outcomes leads to a perception of equity in exchange process, which
enhances confidence that a partner will continue to meet his/her obligations in the future
(Ganesan, 1994). That is, the experience of satisfaction or dissatisfaction potentially
contributes to perceptions of trust (Johnson and Grayson, 2005). Thus,
H2: Customer satisfaction positively influences customer trust.
2.5 Customer Loyalty
In Oliver’s (1999) study, loyalty is defined as a deeply held commitment to repatronize a
preferred product/service consistently in the future. According to Zeithaml et al. (1996),
Ganesh et al. (2000), and Soderlund (2006), when customers praise the company, express
preference for the company over others, or show their intent to stay with the company, they
are loyal customer and they forge bonds with the company. A literature search found three
main streams of loyalty research: behavioral loyalty, attitudinal loyalty, and composite loyalty.
However, many researchers (e.g., Dick and Basu, 1994; Jacoby, 1971; Jacoby and Chestnut,
1978) supported the utilization of a composite measure of loyalty having behavioral and
attitudinal aspects, which provides a full explanation of the concept of customer loyalty.
Based on the existing literature, we define customer loyalty as a consumer’s psychological
attachment toward the online service provider, accompanied by this consumer’s willingness to
make an effort in maintaining the customer-firm relationship.
The antecedents of customer loyalty would appear to be the affective component
including variables such as satisfaction and trust (Macintosh and Lockshin, 1997). In theory,
Aaker (1991) speculated about the contribution of satisfaction to customer loyalty. In
empirical research, the literature also shows the link between satisfaction and customer
loyalty (Anderson and Sullivan, 1993; Geyskens and Steenkamp, 2000; Fullerton, 2003;
Rauyruen and Miller, 2007; Yu and Dean, 2001). As to the impact of customer trust on
customer loyalty, several research studies have demonstrated a direct link between these two
dimensions (Chaudhuri and Holbrook, 2001; Delgado-Ballester and Munuera-Aleman, 2001;
Johnson and Grayson, 2005; Liang and Wang, 2006; Rauyruen and Miller, 2007;
Sirdeshmukh et al., 2002). Therefore, we suggest
H 3a: Customer satisfaction positively influences customer loyalty.
H 3b: Customer trust positively influences customer loyalty.
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2.6 Customer Actual Behavior
Having discussed the antecedents of customer loyalty, we now focus on its behavioral
consequences. According to Ganesh et al. (2000), Srinivasan et al. (2002), and Zeithaml et al.,
(1996) customer loyalty impacts behavioral outcomes and, ultimately, the profitability of a
company. To fully recognize firm profits, companies must consider all customer relationship
performance, including the length, depth, and breadth (Blattberg et al., 2001; Bolton et al.,
2004; Reinartz et al., 2005; Reinartz and Kumar, 2003;Verhoef, 2003; Verhoef et al., 2001).
Length of a relationship refers to the probability a customer will continue the relationship
with the firm and continue to purchase current products/services, which is often defined as
customer retention (Fullerton, 2003). Depth of a relationship refers to the deepening of the
customer’s relationship with the firm through increased usage or upgrading. Breadth of a
relationship is reflected in cross-buying; that is, the number of different products or services
purchased from a company over time. Therefore, this study proposes that the integrated model
of customer loyalty should collect the effects of relationship length, depth, and breadth in
order to provide a full measurement of customer actual behavior.
Many academics and practitioners consider customer loyalty to have a powerful impact
on firm’s financial performance. For example, some authors (Lam et al., 2004; Reichheld and
Teal, 1996; Rust et al., 2000) believed that loyal customers offer a steady stream of revenue
for a company by remaining with the brand and rejecting the overtures of competitors.
Customers who are loyal to a relationship might have a greater propensity to act because of
their need to remain consistent with their commitment (Moorman et al., 1993). For the first
type of customer relationship performance, many researchers proposed that customer loyalty
is an important precursor to customer retention (Beatty et al., 1988; Dwyer et al., 1987;
Fullerton, 2003; Gounaris, 2005; Macintosh and Lockshin, 1997; Verhoef, 2003). Regarding
relationship depth and breadth, researchers suggested that loyal customers are more likely to
seek greater relationship expansion and enhancement (Bendapudi and Berry, 1997). As to the
empirical results, Evanschitzky et al. (2006) confirmed that loyal customers have higher
service usage levels. Research by Reichheld and Sasser (1990) and Srinivasan et al. (2002)
also revealed that loyal customers have higher relationship depth with their preferred service
providers. Using longitudinal data, Verhoef (2003) confirmed that committed customer have
more willingness to cross-buy new products or services. Thus, this study proposes
H5a: Customer loyalty positively influences the relationship length.
H5b: Customer loyalty positively influences the relationship depth.
H5c: Customer loyalty positively influences the relationship breadth.
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3. Methodology and Data
3.1 Procedure and Sample
The financial services industry was chosen for this study. In particular, we focus on
wealth management advisory services, which are designed to build and maintain personalized
relationships with the clients. Thus, we collaborated with a Taiwanese bank to implement a
two-year project, which aims to enhance customer relationship by promoting service quality,
launching relationship marketing programs, and conducting professional marketing research
about customer attitude and behavior. This study is a byproduct of this project.
The sample company, which was founded in 1969 and has since grown to be among the
three largest banks in Taiwan, has established 124 branches in Taiwan and 3 branches
overseas. The lines of its business include corporate banking, consumer banking, wealth
management, credit card, treasury services, trust services, and government banking.
With the help of the company’s wealth management department, a questionnaire was
sent via e-mail to 3000 randomly selected customers. Clients from the wealth management
department were sampled due to the higher frequency of contact they had with advisers and
the increased likelihood of them being able to recall and comment on the service quality and
relationship bonds they receive. The scope of the study and the assurance of anonymity were
explained in the first page of the questionnaire. Meanwhile, the purposes of the research were
not disclosed. A total of 1465 surveys were eventually returned, yielding a response rate of 49
percent. Due to the “Listwise” deletion of cases with missing values on variables, a total of
1211 valid questionnaires were eventually obtained.
3.2 Measurement
Based on previous studies, we developed nine items to measure the respondents’
relational bonds with financial service providers (Berry, 1995; Williams et al., 1998; Lin et al.,
2003; Chiu et al., 2005) and six items to measure service quality (Bell et al., 2005; Brady and
Cronin, 2001; Johnson and Grayson, 2005). Regarding the dependent variables, six items to
measure customer satisfaction and trust (Hsieh and Hiang, 2004; Morgan and Hunt, 1994) and
four items were adapted from Zeithaml et al. (1996) to measure the customer loyalty. Finally,
based on the practices of financial services, we use three single-item indicators to measure
customer actual behavior (“How long have you been the customer of this bank?” “In average,
how many times this bank touches with you during one month?” “How many financial
services have you bought from this bank?”).
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Variables relevant to this study are described in the Table 1. A seven-point Likert-type
response format ranging from “1” (strongly disagree) to “7” (strongly agree) was used. The
survey was originally prepared in English and then translated into Chinese. Thirty bank
customers were asked to adapt previously established scale items to reflect the context of
financial services. Prior to implementing the survey, managers of the wealth management
department were consulted with the final questionnaire to uncover potential problems with
statements, instructions, and format. Finally, some minor modifications were made to
established measures to suit the study context and capture the nature of financial services.
-------Take in Table (1)-----
3.3 Analysis and Results
Preliminary analysis
We conducted a confirmatory factor analysis (CFA) to test the adequacy of the measurement
model and used LISREL 8.30 to analyze the covariance matrix. Separate CFAs were used for
exogenous variables (relationship bonds and service quality) and endogenous variables
(customer satisfaction, customer trust, and customer loyalty), and an overall CFA for all
scales. The fit statistics corresponded reasonably well with those found in the literature (see
Table 2) (Bagozzi and Yi, 1988; Hair et al., 1998; Hu and Bentler, 1999). These results
showed that the data had reasonable model fit, thus enabling the evaluation of the structural
model to proceed.
-------Take in Table (2)----We then examined the proposed model in two stages. First, the reliability and validity of
the constructs for the total measurement model were assessed. Second, the overall fit of the
structural model and the structural parameters were examined to determine if the data
supported the proposed model and hypotheses.
Reliability and Validity
To examine the reliability of the scales of relationship bonds, service quality, customer
satisfaction, customer trust, and customer loyalty, we calculated the Cronbach’s alphas for the
scales. All the alphas exceeded the suggested value of 0.70 (see Table 1); therefore, a high
internal consistency was suggested among the items and with their related constructs
(Nunnally, 1978). To test the construct validity of each scale, Churchill (1979) suggested
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examining convergent and discriminant validity. Convergent validity was supported as a
result of all item loadings exceeding the suggested level of 0.70 and being highly and
statistically significant (Hatcher, 1994; Segars, 1997). Moreover, Hair et al. (1998) posited
that average variances extracted (AVE) values exceeding 0.50 are also a proof of convergent
validity (see Table 1). As for discriminant validity, it was assessed using the procedure
recommended by Anderson (1987) and Bagozzi and Phillips (1982). This entailed analyzing
all possible pairs of constructs in a series of two-factor CFA models. Each model was run
twice: one while constraining the phi coefficient to unity and the other within free parameters.
A chi-square difference test was then performed on the nested models to assess whether or not
the chi-square values were significantly lower for the unconstrained models (Anderson and
Gerbing, 1988). The critical value (chi-square difference) exceeded 3.84 in all cases.
Consequently, it can be concluded that all constructs possessed satisfactory reliabilities and
validities.
Structural Model and Hypotheses Testing
Table 3 lists the assessment of overall model fit and the tests of the research hypotheses.
The overall chi-square = 1626.84 is significant (p<0.001). However, because of the large
sample size, this may not be a useful diagnostic for evaluating model fit. All the other fit
indices suggest that the model closely fits the data. In testing the hypotheses, all relationships
are significant, except for the links between two service attributes (social bond and technical
service quality) and customer satisfaction, thus, providing initial support for the conceptual
model and the related hypotheses.
In testing the effect of service attributes on customer satisfaction, financial bond (0.33),
structural bond (0.22), and functional service quality (0.20) were found to be statistically
significant while social bond (0.01) and technical service quality (0.08) were insignificant.
This finding is agreement with the results of Crosby et al. (1990), Hsieh and Hiang (2004),
and Liang and Wang (2006), which concluded that not all service attributes contribute to
customer satisfaction for financial services transaction. As to the effects of customer
satisfaction on customer trust and customer loyalty, the significantly positive result (0.89;
0.55) is in line with our proposition. Regarding the effects of customer trust on customer
loyalty, as our inference, trust has positive influence on customer loyalty (0.46). This finding
corresponds to prior study (Johnson and Grayson, 2005), which identified trust as the most
formidable driver to customer loyalty for people engaging in financial services.
Ultimately, hypotheses testing the linkage between customer loyalty and the three actual
behaviors were all proven to be significant in our model (length, 0.09; depth, 0.19; breadth,
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0.20). This finding is in line with previous studies (Eastlick et al., 2006; Evanschitzky et al.,
2006; Verhoef, 2003) which proposed that a customer’s attachment with the service provider
will influence their intention to buy more, use more, and buy across categories. This study,
therefore, demonstrates there are three types of outcomes for customer loyalty.
-------Take in Table (3)-----
4. Conclusions
4.1 Discussions
More than ever before, managers in the financial services industry must understand their
customers so that they can better meet their best customers’ needs and prevent them from
switching to other companies. This study has been one of the most integrative researches that
stressed the impact of various service attributes on customer loyalty for financial services
context. Although there are many ways for banks to engage in customer loyalty, results show
that relationship marketing and service quality can drive customer loyalty, through the
intervening effects of customer satisfaction and trust. In addition, customer loyalty is also
demonstrated to enhance customer relationship length, depth, and breadth, which is crucial to
improving firm profits.
An important theoretical contribution of this study stems from discovering the relative
importance of service attributes in enhancing customer loyalty. By integrating relationship
marketing and service quality, this study enables us to establish financial bond, followed by
structural bond and functional service quality, as the important factors of customer loyalty.
Moreover, customer loyalty is also proved to firmly build and enhance customer relationship
depth and breadth in addition to relationship length. Surprisingly, this aspect has not received
attention in previous customer loyalty study.
Although Chiu et al. (2005) and Lin et al. (2003) identified all the relationship bonds are
evaluated by customers from financial services institutions; our results only support the
effectiveness of financial and structural bonds. The insignificance impact for social bond may
due to customers define financial services as comprising of more utilitarian benefits in terms
of the transactions frequently involving large amount money. Social bond contains more
hedonic benefits, however, less utilitarian benefits than financial and structural bonds, thus,
hardly arouses customer satisfaction. This argument is based on Chandon et al.’s (2000)
proposition, which developed a benefit congruency framework that predicts the utilitarian
benefits are given more weight when consumers make a utilitarian purchase decision and that
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hedonic benefits are given more weight when consumers make a hedonic purchase decision.
In Johnson and Grayson’s work (2005), they also suggested that customer satisfaction in the
financial service industry is primarily based on core aspects of service delivery, which this
study argues is more relevant with the importance of financial and structural bonds.
The results also show that technical service quality did not significantly contribute to
customer satisfaction. While the finding may be true and may need further validation, a
possible explanation may due to the phenomenon revealed by Mittal et al. (1999). They
pointed out that many firms are offering consumption systems instead of offering products of
services alone. Consumption systems are offerings characterized by a significant product and
service subsystem, which specifically argued that both the product and service subsystem
influence customer satisfaction. For example, when considering the investment results,
mutual fund investors may accord some weight to the financial advisers’ suggestion while
also attribute product performance to the mutual fund company. In Taiwan, banks are the
major channels to distribute investment products manufactured by mutual fund and insurance
companies. Thus, when customers judge the technical service quality, they may rationally
attribute the results to the producers, but not accuse bank’s financial advisers for wrong or
good advisement. This inference is in line with Johnson and Grayson’s results (2005), which
found service delivery is able to impact financial service relationships, however, product
performance has only modest influence.
Regarding the hypothesized link between customer satisfaction, customer trust, and
customer loyalty, all the paths were significant. Therefore, we could infer that the higher the
customer satisfaction and trust, the higher their commitment toward this specific financial
service provider. As to the consequences of customer loyalty, the results showed that three
dimensions of customer actual behaviors will be influenced, that is, customer retention, usage
frequency, and cross-buying. Particularly about the relations between customer loyalty and
cross-buying, from the highly path coefficient, we could reason that loyal customers’
committed feeling will spillover to cross-buying behavior. This argument is also supported by
brand extension studies. Researchers demonstrated that when customers feel commitment
towards a parent brand, they would be convinced of the willingness of the original company
to provide a good offer, even in a new field; thus, loyal customers are more likely to purchase
new goods and services (Kirmani et al., 1999; Volckner and Sattler, 2006). Blattberg et al.
(2001) argued that cross-buying contributes to firm financial performance while few studies
consider this field. This point may be especially acute for financial services providers, with
most firms trying to meet customer needs via one-stop shopping and have begun to build,
maintain, and develop customer relationships through relationship marketing instruments and
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actual behaviors
service quality programs.
Overall, this study finds support for most of the hypothesized relationships in the
proposed model, and the results highlight the key antecedents and consequences of customer
loyalty in the financial services context. Therefore, we suggest that as financial service
providers pursue long-term relationships with customers to maximize firm profits, they should
be particularly concerned with how customers discriminate between different service
attributes when considering customer loyalty and customer actual behaviors.
4.2 Managerial Implications
Managers in the financial services industry are faced with one major challenge, and that
is how to transfer customers from switchers to stayers and to encourage stayers to buy more,
use more, and buy across categories. The results of our study provide some strategic
implications for financial services companies seeking to build their customer relationships
firmly.
First, financial service provider’s marketing budget allocations can be planned according
to the results of this study. Managers of banks should perceive that with the era of intense
competition, a bunch of bankers are capable of offering a wider range of services at the same
price, thus, the customer almost demands a better price from the bankers if it is to maintain
their loyalty. Increasing deposit interest rate or saving transaction cost for customers is able to
influence their decision making since they would haggle over every ounce on the price.
Particularly for the experienced customers who have much experience with other banks and
are acquainted with offers and prices from other banks, they are able to make fine judgment
about the preferential treatment provided by the bankers which would then to influence their
actual behavior.
Second, managers should also consider providing value-added activities in order to
differentiate their offerings with others, such as providing online transaction system (e-bank),
establishing fast and well-structured hyperlinks with the websites of strategic partners,
alliance with other industries to acquire integrated product/services to its customers, which
may lead to customer positive attitude and behavioral intention. Furthermore, through one-onone online communication to immediately address questions and offer personalized
information, these are effective devices to express a banker’s concern with customer, which in
turn will consolidate customer relationships. This notion is especially true in the case of
financial services, since customization is increasingly important in this industry.
Third, since financial services are defined as professional services rather than as
convenient services, which are advisory in nature and involve considerable interaction
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between representatives of transacting parties. Therefore, characteristic of this industry is the
tendency for the financial advisers to be predominantly responsible for functional service
quality. Due to the critical importance of the financial advisers, long-term relationships are
often forged with financial service organizations on the basis of the adviser’s expertise.
Accordingly, bankers should invest in professional education which would help financial
advisers developing their diagnostic ability, knowledge, and discretion. During the service
delivery process, customers might perceive banker’s personnel possessing the skills, abilities,
and knowledge required for effective task performance.
Fourth, managers should realize that loyal customers are by far the best prospects for
upgrading or new products/services. As a consequence, it is considerably more profitable to
keep and satisfy existing customers than to renew a strongly churning customer base. Such
strategy may be quite useful for bankers, with most firms trying to meet customer needs via
one-stop shopping and have begun to explore customer lifetime value through developing
customer relationship depth and breadth. This study therefore suggests that financial advisors
shall not only be equipped with adequate knowledge on the basic product line, but also need
to develop themselves as being asset/liability portfolio consultant in the long run and it
becomes clear that solutions to customer problems must transcend traditional service
boundaries. Therefore, as customer relationship endures, expertise should reflect
demonstrated competency in the broader aspects of the customer purchase/usage system,
particularly when customers make multiple purchases in a service category and expects the
salesperson to understand the interrelationship among those purchases to better satisfy
customer needs. Customers can then use a single channel to shop for numerous different
financial services they require, and achieve improved access to integrated financial planning
from financial advisers. Through such a change, practitioners can create customer lifetime
value more effectively and economically.
4.3 Study Limitations and Future research
This study has some limitations that must be considered. First, the questionnaire may
have created a common method variance that could inflate the construct relationships. This
could be particularly threatening if the respondents were aware of the conceptual framework
of interest. However, the respondents were not told of the specific study aims, and all of the
construct items were separated and mixed such that respondents could not detect which items
were affecting which factors (Lages and Lages, 2004). Additionally, the proof of convergent
and discriminant validity and the test for separate and overall CFA suggest that common
method variance is unlikely.
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actual behaviors
Second, our model does not take into account the customer’s individual-level variables
outside the control of the financial services provider, such as variety-seeking behavior and
involvement in the financial services category, which may also impact customer loyalty (Floh
and Treiblmaier, 2006). Based on our findings, more comprehensive models of customer
loyalty can be developed and tested.
Third, owing to the increasing economic role of the Internet, it is important to compare
customer responses to service attributes in brick-and-mortar outlets with those in online
settings (Harris et al., 2005). Since the exchange is via the Internet, the requirements of online
customers regarding service attributes may differ from those of offline customers.
Consequently, it is necessary to ask whether this model would still hold in the context of the
Internet.
Despite these limitations, we believe that this study provides some important insights
into the theory and practice of customer loyalty for financial services industry. The
development and sustainability of customer loyalty is increasingly difficult to achieve and is
still surrounded with ambiguity regarding its underlying determinants, so we believe that our
research makes a significant contribution. There is strong support for the view that customers
evaluate relationship marketing and service quality, and an understanding of these elements is
therefore a first step toward effective service management for the financial services industry
in the long term.
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Relationship marketing, service quality, and customer
actual behaviors
Table 1: Construct, item, reliability, and validity
Construct and item
Standardized
item-loading
Financial Bond
1. This bank offers free gifts for regular transactions.
2. This bank offers additional rebate if I trade beyond a certain
amount.
Social Bond
1. This bank keeps in touch with me.
2. This bank makes me feel that I am a unique customer.
3. This bank collects my opinions about services.
4. This bank sends me greeting cards on special days.
Structural Bond
1. This bank offers a variety of ways to get information more
efficiently.
2. This bank provides me with customized products/services that I
need.
3. This bank provides products or services from other sources to
resolve my problems.
Functional Service Quality
1. Trading financial services with this bank is easy.
2. Trading financials services with this bank is reliable.
3. Trading financial services with this bank is timely.
Technical Service Quality
1. This bank has assisted me to achieve my financial goals.
2. This bank has performed well in providing the best return on
my investments.
3. This bank has performed well in investing my money in
appropriate investment options.
Customer Satisfaction
1. I am satisfied with the products provided by this bank.
2. I am satisfied with the services provided by this bank.
3. When I consider my experience at this bank, I am satisfied.
4. Overall, this bank is a good company.
Customer Trust
1.This bank can be counted on to do what is right.
2. This bank can be trusted.
Customer Loyalty
1. I am willing to continue using this bank’s services.
2. I consider this bank my first choice to buy financial services.
3. I would highly recommend this bank to my friends and family.
4. I would not take some of my business to another banks as long
as I live or work in this neighborhood.
191
Cronbach’s
alpha
AVE
0.83
0.70
0.94
0.81
0.95
0.86
0.93
0.81
0.92
0.79
0.93
0.75
0.94
0.89
0.90
0.68
0.85
0.83
0.84
0.93
0.91
0.91
0.92
0.94
0.93
0.91
0.92
0.87
0.92
0.90
0.85
0.82
0.90
0.89
0.86
0.93
0.95
0.79
0.75
0.88
0.86
2008 現代經營管理研討會
Table 2: Results of measurement models
χ 2 / df
GFI
AGFI
RMSEA
SRMR
CFI
NNFI
CFA-Exogenous
5.13
0.97
0.95
0.049
0.020
0.99
0.98
CFA-Endogenous
6.77
0.98
0.96
0.058
0.016
0.99
0.99
CFA-Overall
3.97
0.96
0.94
0.042
0.022
0.98
0.98
Suggested values
<3
> 0.90
>0.80
<0.06
<0.08
>0.95
>0.90
Measurement
model
Note: (1) “CFA-Exogenous” means CFA tests of the constructs of functional service quality,
technical service quality, financial bond, social bond, and structural bond.
Note: (2) “CFA-Endogenous” means CFA tests of the constructs of customer satisfaction,
customer trust, and customer loyalty.
192
Relationship marketing, service quality, and customer
actual behaviors
Table 2: Results of the proposed model
Hypothesized path
Hypothesis
Expected
Sign
Estimated
coefficient
T-value
Result
Financial Bond
Customer Satisfaction
H 1a
+
0.33
6.64***
Supported
Social Bond
Customer Satisfaction
H 1b
+
0.01
0.18
Rejected
Structural Bond
Customer Satisfaction
H 1c
+
0.22
5.59***
Supported
Functional Service Quality
Customer Satisfaction
H 1d
+
0.20
5.03***
Supported
Technical Service Quality
Customer Satisfaction
H 1e
+
0.08
1.51
Rejected
Customer Satisfaction
Customer Trust
H2
+
0.89
41.06***
Supported
Customer Satisfaction
Customer Loyalty
H 3a
+
0.55
16.09***
Supported
Customer Trust
Customer Loyalty
H 3b
+
0.46
14.21***
Supported
Customer Loyalty 
Relationship Length
H 4a
+
0.09
3.74***
Supported
Customer Loyalty 
Relationship Depth
H 4b
+
0.19
7.63***
Supported
Customer Loyalty 
Relationship Breadth
H 4c
+
0.20
8.13***
Supported
Note: (1) * means p<0.05; ** means p<0.01; *** means p<0.001.
(2) χ 2 / df =4.93; GFI=0.94, AGFI=0.92; RMSEA=0.048, SRMR=0.041; CFI=0.97, NNFI=0.97.
193
2008 現代經營管理研討會
Figure 1: Proposed model
Financial
Relationshi
Bond
p Length
H1a
Social
Bond
Structural
H1b
H1c
Bond
H4a
Customer
H3a
Customer
H4b
H5a Loyalty
Satisfaction
H1d
Relations
hip Depth
H4c
Functiona
H2
H3b
l Service
Quality
H1e
c
Customer
Technical
Relationship
Trust
Breadth
Service
Quality
194