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THE PSYCHOLOGY BEHIND COMMITMENT AND LOYALTY
AN EMPIRICAL STUDY IN A BANK SETTING
Josée Bloemer*, Gaby Odekerken- Schröder**, Hilda Martens***
* PhD, Full Professor of Marketing and Market Research, University of Nijmegen, P.O. Box 9108, 6500 HK
Nijmegen, the Netherlands, tel: +31 24 3613018, fax: +31 24 3611933, e-mail: j.bloemer@nsm.kun.nl
** PhD, Associate Professor of Marketing, Maastricht University, P.O. Box 616, 6200 MD Maastricht, the
Netherlands, tel: +31 43 3883618, fax: +31 43 3884918, e-mail: g.schroder@mw.unimaas.nl
*** PhD, Assistant Professor in Human Resource Management, Limburg University Centre, University Campus,
Building D, 3590 Diepenbeek, Belgium, tel: +32 11 26 8662, fax: + 32 11 26 8700, e-mail
hilda.martens@luc.ac.be
2
THE PSYCHOLOGY BEHIND COMMITMENT AND LOYALTY
AN EMPIRICAL STUDY IN A BANK SETTING
ABSTRACT
Despite the extant literature on customer loyalty, it is recognized that the psychological
processes behind commitment and customer loyalty are still ill understood. Therefore, the
primary objective of this study is to assess the impact of three psychological antecedents
(position involvement, volitional choice and informational complexity) on affective,
calculative and normative commitment to a bank. In turn, we assess the impact of an
individual difference variable (consumer relationship proneness) on these three psychological
antecedents. And finally, this research project addresses the consequences of affective,
calculative and normative commitment on loyalty in terms of word of mouth, purchase
intention, price insensitivity and complaining. An empirical research among 439 bank
customers was conducted to test our conceptual model. Structural Equation Modeling (SEM)
results reveal the pivotal role of affective commitment as an antecedent of customer loyalty.
In turn, affective commitment can best be explained by position involvement. Moreover,
relationship proneness seems to be most strongly related to position involvement. Managerial
implications, limitations and directions for future research are provided.
3
INTRODUCTION
Despite the extant literature on customer loyalty, it is recognized that the psychological
processes behind customer loyalty and commitment are still ill understood (Pritchard et al.
1999). The objective of our study is threefold. First, we assess the three psychological
antecedents of commitment to a bank. Second, we study an individual difference variable
underlying these antecedents of commitment. Finally, we investigate the influence of
affective, calculative and normative commitment on customer loyalty in a bank setting.
In the literature on organizational psychology, Allen and Meyer (1990) distinguish
between affective, continuance (calculative) and normative commitment. The differences
between these three types of commitment reflect the psychological state that binds the
individual to the organization. Affective commitment refers to the emotional attachment to an
organization, while continuance commitment refers to the costs that individuals associate with
leaving the organization and the normative component refers to individuals’ feelings of
obligation to remain with the organization. They argue, that a more comprehensive
understanding of the link between commitment and loyalty will be achieved when all three
types of commitment are considered simultaneously.
Pritchard et al. (1999) argue that an analysis of commitment ‘should move beyond a
general expression of attachment and incorporate an understanding of the psychology inherent
in binding a person to that disposition’ (p. 334). They distinguish information processes,
identification processes and volition processes as antecedents of commitment. As we want to
grasp the psychology behind commitment, we will assess these three antecedent processes
simultaneously in a single study.
Finally, our aim is to move beyond an assessment of the antecedent processes and
investigate their origin in terms of a recently introduced individual difference variable
4
“consumer relationship proneness”. Consumer relationship proneness refers to the idea that
some customers are intrinsically inclined to engage in relationships (De Wulf et al. 2001). It
has been shown that consumer relationship proneness has a positive impact on commitment
and loyalty (De Wulf et al. 2001). We consider relationship proneness as an individual
difference variable that activates the psychological processes underlying commitment.
The studies mentioned before focus on a single aspect: either types of commitment, or
the psychological processes behind commitment or consumer relationship proneness. Despite
their tremendous contribution to the field, we aim at providing a complete picture by
investigating these aspects simultaneously. Therefore in this study we investigate the
relationships between consumer relationship proneness; the three antecedents of commitment;
the three types of commitment and customer loyalty in terms of word-of-mouth, purchase
intentions, price insensitivity and complaining in a bank setting.
We continue with a description of the theoretical background of our conceptual model.
Next, we formulate hypotheses about the interrelationships between the concepts. Then, we
describe the research design and the results of the empirical research conducted. Finally, we
come up with conclusions, managerial implications, limitations and recommendations for
future research.
THEORETICAL BACKGROUND
Figure 1 shows the conceptual model underlying this study. In this section, we will first
elaborate upon the three types of commitment, followed by their antecedent constructs and
consumer relationship proneness. Finally, we address the four types of customer loyalty.
5
Insert Figure 1 about here
Commitment
Commitment is generally referred to as an enduring desire to maintain a relationship (Morgan
and Hunt 1994). The concept of commitment is similar to the concept of a long-term
orientation that comprises the desire and utility of a buyer to have a long-term relationship
with a seller (Gruen 1995). In line with Day (1969), Dick and Basu (1994) stated that the
stronger commitment, the more likely the buyer is to overcome potential obstacles in the
buyer-seller relationship, resulting in customer loyalty. Similarly, Beatty, Homer, and Kahle
(1988) state that commitment and loyalty are related, yet by definition distinct constructs,
with commitment leading to loyalty.
In this research we distinguish three different types of commitment: affective
commitment, calculative commitment and normative commitment. Affective commitment can
be defined as “a party’s desire to continue a relationship because of the enjoyment of the
relationship for its own sake, apart from the instrumental worth and because they experience
a sense of loyalty and belongingness” (Allen and Meyer, 1990; Geyskens et al. 1996).
Calculative or continuance commitment can be defined as “the degree to which channel
members experience the need to maintain a relationship, given the significant perceived
termination of switching costs associated with leaving”. It is the cold calculation of costs and
benefits, including investments and available alternatives to replace or make-up for foregone
investments (Allen and Meyer, 1990; Geyskens et al. 1996). And normative commitment is
reflected in “the (moral) obligation to stay in a relationship” (Allen and Meyer, 1990). In line
with Allen and Meyer (1990), Geyskens (1998, p. 50) states that ‘the use of global
commitment measures – which measure intention to continue a relationship without
6
consideration of the underlying motivation – could confound or mask different, and possibly
even opposite effects’.
Psychological antecedents of commitment
Since commitment is a desirable outcome it is valuable to gain insights into its antecedent
processes. Position involvement, volitional choice and informational complexity represent the
three psychological formative processes distinguished by Pritchard et al. (1999): identification
processes, volitional processes and informational processes.
In our context, the identification process refers to the question whether customers
identify themselves with the values and images embodied by a particular bank. It is expected
that the more strongly customers identify themselves with the bank, the stronger their
commitment towards the bank. The volitional process refers to customers’ perceptions that
their preferences are free and not dictated by any constraints. When customers sense that their
choice for the bank is unhindered, the resulting commitment is likely to be stronger and more
deeply held (Pritchard et al. 1999). Finally, the informational process distinguished by
Pritchard et al. (1999) deals with cognitive structures and how customers manage information
about their preferred bank. It is assumed, that the need to maintain a consistent informational
structure, about for instance reasons for revisiting the bank, has a positive impact on
commitment.
Position involvement
Position involvement is considered to be an important construct representing the identification
process. Position involvement is defined as “a situation in which important values or self-
images are identified with a particular bank choice” (cfr. Freedman, 1964). Customers’
position involvement is determined by the extent to which the customer’s public association
7
with the service in question is in line with certain values and self-images of that customer.
Some researchers even indicate that the highest form of commitment is driven by the need for
social representation and self-identity (Buchanan 1985).
Volitional choice
According to Pritchard et al. (1999) volitional choice, being a construct representing the
volitional process, can be defined as “a process that involves both a freedom from constraints
and a freedom to choose”. In our setting, freedom from refers to the notion that a bank choice
is elicited freely and not constrained by external considerations that might limit a customer’s
sense of personal responsibility in that decision. The freedom to component of volitional
choice refers to the potential for a choice to reflect meaningful action or effort (Bagozzi,
1993). Research suggests that when people sense they are acting freely in choosing an object,
they attribute meaning toward that object (Bem, 1967). For instance, when customers choose
‘First American Bank’ or another bank from a wide range of banks, they usually infer greater
meaning in that selection (e.g. “It’s my favorite or the best alternative”).
Informational complexity
Informational complexity is deemed to be an important construct representing the
informational process. Informational complexity can be defined as “the extent to which
information processing is required to form cognitive structures”. Pritchard et al. (1999) claim
that when complex informational schema underlie customers’ commitment, changing their
mind becomes more difficult as accommodating disparate cognitions require even greater
change (Millar and Tessar, 1986). Moreover, deviation from an attitude that is supported by a
complex cognitive structure involves higher psychological costs than deviation from an
attitude that is supported by a simple cognitive structure (Salancik, 1977).
8
Consumer Relationship Proneness
Knowing which psychological processes underlie commitment is step one. But for banks it is
interesting to know which customers are most inclined to reveal these desirable antecedent
processes. Therefore, we investigate the individual difference variable of consumer
relationship proneness. In this study, in line with De Wulf et al. (2001), we define consumer
relationship proneness as “a consumer’s relatively stable and conscious tendency to engage in
relationships with retailers of a particular product category.” In the current context,
consumer relationship proneness refers to the stable tendency of a customer to engage in
relationships with banks and can therefore be considered as an individual difference variable.
In addition, we emphasize a conscious tendency to engage in relationships as opposed to a
tendency to engage in relationships based on inertia or convenience (e.g., Dick and Basu
1994). Moreover, the concept of proneness is focused on the tendency to engage in
relationships as opposed to the tendency to maintain or enhance relationships. The latter
would not be generic as it would be contingent upon a particular bank, leading to a close
resemblance to the construct of commitment. Finally, since several authors stress that a
buyer’s proneness to engage in relationships might vary across groups of sellers (Barnes
1997; Bendapudi and Berry 1997; Christy, Oliver, and Penn 1996) (e.g., banks versus
supermarkets), we postulate that consumer relationship proneness differs across service
retailers of different product categories (e.g. hotels, banks, supermarkets etc.).
Bagozzi (1975, p. 33) already stated that “retailers, for example, know that they will not
obtain repeat purchases if the consumer is taken advantage of and deceived”. While many
relationship marketing studies dealt with relationships based on dependence and locking in
buyers (constraint-based relationships), consumer relationship proneness focuses on positive
motivations of customers driven by a stable and conscious tendency to engage in relationships
with sellers (dedication-based relationships) (Barnes 1995/1997; Davis 1995; Ganesan 1994;
9
Oliver and Swan 1989; Palmer 1995; Smith and Barclay 1997). Christy, Oliver, and Penn
(1996) used the term “psychologically predisposed” in order to express the idea that some
buyers are intrinsically inclined to become loyal to a retailer.
Customer Loyalty
In line with Jacoby and Chestnut (1978) we define customer loyalty as the “biased (i.e. non
random) behavioral response, expressed over time, by some decision making unit, with
respect to one bank out of a set of banks, which is a function of psychological (decision
making and evaluative) processes resulting from commitment”.
The conceptualization and measurement of loyalty has often remained limited,
ignoring the full range of conceivable loyalty (re)-actions that may follow the evaluation of a
service (Zeithaml et al. 1996). Cronin and Taylor (1992) for instance focused solely on
repurchase intentions, while Bolding et al. (1993) measure repurchase intentions and
willingness to recommend. As Zeithaml et al. (1996) argue, dimensions of loyalty, such as,
willingness to pay more, and loyalty under increased pricing have often been left out in
previous research. Similarly, customer evaluations following a negative service experience
have received only limited attention in scales designed to measure customer loyalty intentions
and behavior (Singh 1991). With regard to behavioral intentions in a service setting Zeithaml
et al. (1996) proposed a comprehensive, multi-dimensional framework of customer behavior
intentions in services. This framework was conceptually comprised of the following four main
dimensions: (1) word-of-mouth communications, (2) purchase intentions, (3) price sensitivity,
and (4) complaint behavior. In this paper, we therefore also distinguish these four biased
behavioral responses.
10
THE INTERRELATIONSHIPS BETWEEN THE CONCEPTS
By definition, relationship proneness refers to a conscious tendency to engage in relationships
with banks (De Wulf et al. 2001). This tendency to engage in relationships is supposed to
have a direct positive influence on the antecedents of commitment in terms of position
involvement, volitional choice and informational complexity. Relationship proneness will
have a positive impact on position involvement as relationship prone customers will be more
eager to identify themselves with a particular bank choice that reflects their important values
or self-images, than customers who are not relationship prone (Freedman 1964). Moreover,
we expect relationship proneness to have a positive influence on volitional choice since
especially relationship prone customers will value dedication-based relationships as opposed
to constraint-based relationships. These relationship prone customers will appreciate a
voluntary choice, in term of a freedom from constraints and a freedom to choose, for a
particular bank more than customers who are not relationship prone (Bem 1967). Finally,
relationship proneness will have a positive impact on informational complexity because it can
be expected that customers who are relationship prone will have more complex cognitive
structures to make a conscious choice for a particular bank than customers who are not
relationship prone (Festinger 1957). By definition relationship proneness is a conscious
tendency to engage in relationships, which implies that relationship prone customers actively
process information concerning particular bank relationships. Therefore, we formulate the
following hypothesis:
H1 There is a positive relationship between relationship proneness and (a) position
involvement, (b) volitional choice and (c) informational complexity
11
Crosby and Taylor (1983) suggested that the congruence between a customer’s
personal values and self-images (position involvement) and the values and norms embodied
by a product or service, strengthens commitment. This implies that a customer who considers
a particular bank to represent important personal values will show a stronger commitment
towards this bank. Cialdini et al. (1978) argued that once volitional processes were engaged,
customers develop a sense of commitment in which they were prepared to continue with an
initial decision, even though certain sales incentives were withdrawn. In line with Festinger
(1957) we argue that much of a customer’s commitment is driven by the psychological cost
(informational complexity) involved in the cognitive reordering and rethinking of what was
known about the bank. Pritchard et al. (1999) found empirical support for the positive
relationships between position involvement, volitional choice, informational complexity and
commitment as a one-dimensional construct. To the best of our knowledge, no other study
investigated the impact of the three psychological antecedents of commitment on the three
distinct types of commitment as such. Therefore, in line with these preliminary findings, we
extend the positive relationship between the antecedents and commitment as a one-
dimensional construct to the three distinct types of commitment and hypothesize:
H2 There is a positive relationship between position involvement and (a) affective
commitment, (b) calculative commitment and (c) normative commitment
H3 There is a positive relationship between volitional choice and (a) affective
commitment, (b) calculative commitment and (c) normative commitment
H4 There is a positive relationship between informational complexity and (a) affective
commitment, (b) calculative commitment and (c) normative commitment
A desire to continue a relationship and a willingness to make efforts to maintain it,
imply higher chances of customer loyalty. Therefore, we assume there exists a positive
12
relationship between commitment and customer loyalty. Several authors support the notion
that commitment motivates buyers to act (Gruen 1995; Hennig-Thurau and Klee 1997;
Mathieu and Zajac 1990). Liljander and Strandvik (1993) concluded that commitment and
behavioral intentions are related concepts. Morgan and Hunt (1994) found significant
relationships between the level of a buyer’s commitment and his acquiescence, propensity to
leave, and cooperation, all of which can be regarded as behavioral intentions. Several
organizational commitment studies focused on the intent to leave and turnover as primary
behavioral intentions (Rylander, Strutton, and Pelton 1997). Moorman, Zaltman, and
Desphandé (1992) suggested that buyers who are committed to a relationship might have a
greater propensity to act because of their need to remain consistent with their commitment.
Finally, Dick and Basu (1994) stated that the stronger commitment, the more likely the buyer
is to overcome potential obstacles in the buyer-seller relationship, resulting in repeat
patronage.
The nature of affective, calculative and normative commitment is different, in terms of
the focus on the genuine want to stay, the need to stay out of economic and/or psychological
investments and the need to stay out of moral obligations. We argue, that the genuine want to
stay (affective commitment) and the need to stay out of moral obligations (normative
commitment) indeed have a positive impact on customer loyalty, whereas the need to stay out
of economic and/or psychological investments (calculative commitment) is negatively related
to customer loyalty. Affective and normative commitment can be considered to be driven by
mere personal considerations such as personal attachment or personal norms, while
calculative commitment is rather based on a rational trade-off of costs and benefits comparing
the focal bank with potential alternatives and the sunk costs made to establish the relationship
(Meyer and Allen 1984). A customer who is mainly calculatively committed is rather
sensitive for any change in the cost/benefit ratio in the marketplace. And therefore, customers
13
who show a high level of calculative commitment will be unwilling to voice positive word-of-
mouth and complaints, will be unwilling to increase their purchase intentions and will be
rather price sensitive, because there is no true intrinsic motivation to be loyal to the bank. The
reason here might be that customers who’s commitment is based on calculation do not want to
invest in the relationship with their bank either by talking positively about the bank or by
increasing their purchase intentions. These customers are even more price sensitive and
unwilling to complain. It might be expected that they might stay with the bank mainly
because of high perceived switching costs or other (perceived) constraints.
Therefore, we formulate the following hypotheses:
H5 There is a positive relationship between affective commitment and (a) word-of-mouth
(b) purchase intention, (c) price insensitivity and (d) complaining
H6 There is a negative relationship between calculative commitment and (a) word-of-
mouth (b) purchase intention, (c) price insensitivity and (d) complaining
H7 There is a positive relationship between normative commitment and (a) word-of-
mouth (b) purchase intention, (c) price insensitivity and (d) complaining
RESEARCH DESIGN
Data were collected from a sample of customers of three bank offices belonging to one
Belgian bank, in three mid-sized towns in the Flemish part of Belgium. In April 2001
customers were randomly asked to fill out the questionnaire. Four hundred and thirty nine
correctly filled out questionnaires were collected. The sample was found to be representative
for the customers of the focal bank in terms of gender, age, education and occupation.
14
The design of the questionnaire was based on multiple-item measurement scales that have
been validated and found to be reliable in previous research. All constructs were measured on
seven-point Likert scales ranging from completely disagree to completely agree. The
measurement items of the different constructs (consumer relationship proneness, volitional
choice, position involvement, informational complexity, affective-, calculative- and normative
commitment, word-of-mouth, price insensitivity, purchase behavior, and complaint behavior)
and their origin are shown in Table 1.
RESULTS
In order to test our conceptual model, structural equation modeling (SEM) with observed
variables was conducted using maximum likelihood estimation in LISREL 8.3. A variance-
covariance matrix was calculated using LISREL’s companion program PRELIS and was used
as input for the path analyses. We subsequently analyzed the overall model, the measurement
model and the structural model.
Overall Model Evaluation
In the overall model, the chi-square value is significant (1878.54 with 673 degrees of
freedom), a finding not unusual with large sample sizes (Doney and Cannon 1997). The ratio
of chi-square to degrees of freedom is 2.79, which can be considered as adequate. The values
of GFI (0.81) and AGFI (0.78) are somewhat lower than those of CFI (0.88), IFI (0.88) and
NNFI (0.87). This result is mainly due to the former measures being more easily affected by
sample size and model complexity. In general, the indicated fits are adequate, including
RMSEA, which is 0.066, and SRMR, being 0.010. Given the objectives of our study, the
15
adequacy of these indices, given the fact that the model was developed on theoretical bases,
and given the relative complexity of the model, no model re-specifications were made.
Measurement Model Evaluation
We assessed the quality of the measurement model (see Table 1) on unidimensionality,
convergent validity, reliability, and discriminant validity. Evidence for the unidimensionality
of each construct was based upon a principal components analysis revealing that the
appropriate items loaded at least 0.60 (except for one item of informational complexity) on
their respective hypothesized component, with a loading no larger than 0.30 on other
components. Convergent validity was supported by a good overall model fit, all loadings
being significant (p < 0.01), and most R
2
exceeding 0.50 (Hildebrandt 1987). Reliability was
indicated by composite reliability measures all exceeding 0.70 except for informational
complexity and complaint behavior. Discriminant validity was tested in a series of nested
confirmatory factor model comparisons in which correlations between latent constructs were
constrained to 1, and indeed chi-square differences were significant for all model comparisons
(p < 0.01). In addition, the average percentage of variance extracted for nearly all constructs
was greater than 0.50, except for informational complexity and complaint behavior. In sum,
the measurement model (Table 1) is clean, with evidence for unidimensionality, convergent
validity, reliability, and discriminant validity.
Insert Table 1 about here
Structural Model Evaluation
Table 2 and Figure 2 contain the detailed results related to the structural model. Almost all
proposed relationships between the concepts could be supported. However, we were not able
16
to find a significant positive relationship between normative commitment and purchase
intentions and normative commitment and complaining. Neither could we show a positive
relationship between volitional choice on the one hand and calculative and normative
commitment on the other hand.
Insert Table 2 about here
Insert Figure 2 about here
The results clearly show that affective commitment is the most important determinant
of loyalty in terms of increased positive word of mouth, increased purchase intention,
increased price insensitivity and increased complaining. Calculative commitment on the other
hand seems to have the hypothesized negative impact on loyalty. The influence of normative
commitment on loyalty is limited in the sense that it only has a small positive relationship
with positive word of mouth and price insensitivity.
Affective commitment is clearly positively influenced by position involvement and in
a lesser extent by informational complexity and volitional choice. Calculative commitment is
positively influenced by position involvement and informational complexity and negatively
influenced by volitional choice. And normative commitment is also positively influenced by
position involvement and informational complexity and negatively influenced by volitional
choice. Relationship proneness as an individual difference variable positively impacts the
psychological antecedents underlying commitment: position involvement, volitional choice
and informational complexity.
Moreover, the results did not show a significant relationships between normative
commitment and purchase intentions nor complaining. We might argue here that when a
customer’s commitment is based on a moral obligation to stay in the relationship, this
17
customer will not necessarily increase its intention to visit the bank more frequently.
Furthermore, this customer will not complain about problems with the bank, as this would
imply cognitive dissonance.
The unexpected negative relationship between volitional choice and calculative
commitment might be explained by the fact that calculative commitment is more a constraint
in terms of loyal behavior whereas volitional choice asks for freedom of choice and
dedication. Volitional choice therefore limits calculative commitment. The same applies for
the negative relationship between volitional choice and normative commitment. Volitional
choice is in contradiction with the (moral) obligation to stay in a relationship.
Finally, our results clearly indicate that affective commitment plays a pivotal role in
explaining customer loyalty, whereas the impact of normative commitment is positive but
rather limited and the impact of calculative commitment seems to be negative. These results
support the findings of Geyskens (1998) stating that the use of a global commitment construct
would have masked the effect of different types of commitment, stressing the importance of
our distinction between affective, calculative and normative commitment. In addition, we
explained more than 70% of the variance in affective commitment, which seems to be the
result of the strong impact of position involvement even to the neglect of important
antecedents such as for example satisfaction, trust and value (Sirdeshmukh et al. 2002). This
means that position involvement is a type of involvement that should be taken into
consideration in future research. Moreover, the refinement of the commitment construct as
well as the refinement of the antecedents seems to be promising as our empirical results
showed clear differences in terms of the directions and magnitudes of the relationships
between the constructs.
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MANAGERIAL IMPLICATIONS
The results of this study clearly show that affective commitment is the most important
determinant of word of mouth, purchase intentions, price insensitivity and complaining
behavior. Affective commitment deals with having a sense of belongingness to the bank,
being happy of being a customer of the bank, feeling emotionally attached to the bank and
feeling part of the family of the bank. Moreover, it deals with having a comfortable and
reliable relationship with the bank. Improving these aspects of affective commitment exceeds
a positive influence on loyalty. A bank therefore, should make sure that a customer is treated
as a true individual in which the bank is really interested and cares for. This can be achieved
by, among others, actually personalizing the communication efforts of the bank. And by
showing attachment and by being of personal meaning to each and every individual customer.
In line with our study, especially the effect of position involvement in stimulating affective
commitment might not be overlooked. Position involvement can be created by making sure
that the image of the bank comes close to the lifestyle of the customer and that the bank
reflects the personality of the customers in terms of their values and norms. Careful analyses
of which norms and values customers in the target market expect to be reflected in their bank
is important here and based upon this the concise selection of a well defined segment.
Moreover, our study indicates that the bank should target those customers who are
intrinsically inclined to engage in relationship with banks. It is important to realize that not
every customer is willing to engage in long-term relationships and therefore the bank should
not waste resources on targeting these unwilling customers. Relationship prone customers
tend to reveal high position involvement which impacts affective commitment and finally
loyalty.
19
Finally, our study shows the possible danger of the role of calculative commitment as this has
a negative impact on loyalty. Moreover, calculative commitment seems to function as an exit
barrier as long as the benefits of the current bank exceed the costs of switching. Apparently,
customers who feel constrained in their relationship do not experience the required dedication
to be loyal to the bank. This implies that the bank should avoid calculative commitment by
not stressing the cost benefit relationship of the offered services but rather emphasizing the
personal attachment and the comfort of having an ongoing relationship with the bank.
LIMITATIONS AND DIRECTIONS FOR FUTURE RESEARCH
Our research should be seen as a preliminary attempt to address an issue that has important
implications for marketing theory and practice. Any preliminary attempt will involve a
number of limitations. However, acknowledgement of these limitations also suggests new
directions for future studies.
A first potential shortcoming in the study is common method bias. As we used one
single questionnaire to measure all constructs included, the relationships between these
constructs may be somewhat inflated. No database information could be used as input for
measuring actual behavior. This study could be improved with access to more substantial data
on customer purchase histories that are not subject to potential recall loss. It would then be
possible to look at longer strings of purchases and to perhaps incorporate contextual
information. With respect to the measurement items, we have to conclude that the scales used
to measure informational complexity and complaining could be improved. In a follow-up
study we have to develop a more appropriate scale. Moreover, it must be recognized that our
sample of Belgian bank customers cannot necessarily be generalized. This limits the findings
as relevant only to these types of customers and service providers. Future studies need to
20
assess the generalizability of our findings to other contexts. Furthermore, future research
should concentrate on issues that could help management identifying, attracting and retaining
the relationship prone customers as they will have strong position involvement, reveal a high
affective commitment and will most probably be loyal to the bank.
In conclusion, it is hoped that these research results will serve as a stimulus for
additional empirical research involving ongoing relationships in a services setting.
21
TABLE 1
Measurement Model
Composite reliability
Variance explained
Loading
R
2
Consumer
relationship
1. Generally, I am someone who likes to be a regular
customer of a bank
0.87 0.69 0.63 0.39
Proneness
(De Wulf et al. 2001)
2. Generally, I am someone who wants to be a steady
customer of the bank
0.92 0.85
3. Generally, I am someone who is willing to ‘go the
extra mile’ to purchase at the same bank
0.91 0.82
Position involvement
(Pritchard et al. 1999)
1. I prefer to bank with Bank X because their image
comes closest to reflecting my lifestyle
0.85 0.65 0.77 0.60
2. When I bank with Bank X it reflects the kind of
person I am
0.88 0.77
3. I prefer to bank with Bank X because their service
makes me feel important
0.79 0.62
Volitional choice
(Pritchard et al. 1999)
1. My decision to bank with Bank X was freely chosen
from several alternatives
0.79 0.55 0.76 0.58
2. I did not control the decision on whether to bank with
Bank X (reversed)
0.65 0.42
3. I am fully responsible for the decision to bank with
Bank X
0.78 0.60
Informational
complexity
1. I don’t really know that much about Bank X
(reversed)
0.63 0.48 0.50 0.25
(Pritchard et al. 1999) 2. I consider myself to be an educated consumer
regarding Bank X
0.84 0.70
3. I am knowledgeable about Bank X*
22
Affective
commitment
1. I do feel a strong sense of belonging to Bank X 0.90 0.64 0.77 0.59
(based upon: Allen
and Meyer 1990)
2. I stay with Bank X because I am very happy to be
their customer
0.84 0.70
3. I stay with Bank X because of the comfortable
relationship I have with Bank X
0.83 0.69
4. Bank X has a great deal of personal meaning for me*
5. I do feel like “part of the family” at Bank X 0.78 0.61
6. I do feel “emotionally attached” to Bank X 0.77 0.59
Calculative
commitment
1. It would be too costly for me to leave Bank X,
therefore I stay
0.88 0.71 0.81 0.65
(based upon: Allen
and Meyer 1990)
2. One of the major reasons I continue to bank with
Bank X is that leaving would require considerable
personal sacrifice
0.93 0.87
3. I stay with Bank X because the costs of changing
exceed the benefits
0.78 0.61
4. If I had not already put so much of myself in Bank X
I might consider going elsewhere*
Normative
commitment
1. I do feel an obligation to remain with Bank X 0.84 0.52 0.66 0.43
(based upon: Allen
and Meyer 1990)
2. Even if it were to my advantage, I do feel it would be
wrong to leave Bank X now
0.66 0.43
3. I would feel guilty if I left Bank X now 0.71 0.50
4. Bank X deserves my loyalty*
5. I would not leave Bank X now, because I have a
sense of obligation to it
0.84 0.71
6. I owe a great deal to Bank X 0.71 0.50
Word-of-mouth
(based upon: Zeithaml
1. I say positive things about Bank X to other people 0.90 0.74 0.82 0.67
et al. 1996) 2. I recommend Bank X to someone who seeks advice 0.92 0.84
23
3. I encourage friends to go to Bank X 0.79 0.63
Purchase intentions 1. I consider Bank X as my first choice* 0.74 0.60
(based upon: Zeithaml 2. I go more often to Bank X in the next few weeks 0.91 0.82
et al. 1996) 3. I go less often to Bank X in the next few weeks
(reversed)
0.61 0.38
Price-insensitivity
(based upon: Zeithaml
1. When the services I usually buy at Bank X are
charged less at another Bank I go to that bank (reversed)
0.76 0.62 0.81 0.66
et al. 1996) 2. I am willing to go to another bank that offers more
attractive prices (reversed)
0.76 0.57
3. I am willing to pay a higher price than other banks
charge for the benefits I currently receive from Bank X*
Complaint behavior
(based upon: Zeithaml
1. I switch to a competitor if I experience a problem
with Bank X*
0.63 0.47
et al. 1996) 2. I complain to other consumers if I experience a
problem with Bank X (reversed)
0.75 0.56
3. I complain to an external agency if I experience a
problem with Bank X (reversed)
0.61 0.37
4. I complain to Bank X’SB: employees if I experience a
problem with Bank X*
* not included in structural model
24
TABLE 2
Structural Model
Parameter Hypo-
Thesis
ML
estimate
Relationship proneness Æ position involvement
Relationship proneness Æ volitional choice
Relationship proneness Æ informational complexity
Position involvement Æ affective commitment
Position involvement Æ calculative commitment
Position involvement Æ normative commitment
Volitional choice Æ affective commitment
Volitional choice Æ calculative commitment
Volitional choice Æ normative commitment
Informational complexity Æ affective commitment
Informational complexity Æ calculative commitment
Informational complexity Æ normative commitment
Affective commitment Æ word-of-mouth
Affective commitment Æ purchase intentions
Affective commitment Æ price insensitivity
Affective commitment Æ complaining
Calculative commitment Æ word-of-mouth
Calculative commitment Æ purchase intentions
Calculative commitment Æ price insensitivity
Calculative commitment Æ complaining
Normative commitment Æ word-of-mouth
Normative commitment Æ purchase intentions
Normative commitment Æ price insensitivity
Normative commitment Æ complaining
1a (+)
1b (+)
1c (+)
2a (+)
2b (+)
2c (+)
3a (+)
3b (+)
3c (+)
4a (+)
4b (+)
4c (+)
5a (+)
5b (+)
5c (+)
5d (+)
6a (+)
6b (+)
6c (+)
6d (+)
7a (+)
7b (+)
7c (+)
7d (+)
0.56**
0.37**
0.21**
0.79**
0.14**
0.40**
0.12**
-0.20**
-0.22**
0.11**
0.12*
0.26**
0.62**
0.56**
0.38**
0.21**
-0.11**
-0.18**
-0.10*
-0.33**
0.10*
0.07
0.11*
-0.05
Squared multiple correlations for structural equations Estimate
Position involvement 0.31
Volitional choice 0.14
Informational complexity 0.04
Affective commitment 0.71
Calculative commitment 0.06
Normative commitment 0.25
Word-of-mouth 0.43
Purchase intention 0.36
Price insensitivity 0.19
Complaining 0.14
25
FIGURE 1
Conceptual Model
relationship
proneness
information
complexity
volitional
choice
position
involvement
normative
commitment
calculative
commitment
affective
commitment
complaining
price
insensitivity
purchase
intention
word
of
mouth
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-
-
-
-
+
+
+
+
26
FIGURE 2
Structural Model
relationship
proneness
information
complexity
volitional
choice
position
involvement
normative
commitment
calculative
commitment
affective
commitment
complaining
price
insensitivity
purchase
intention
word
of
mouth
0.56
0.37
0.21
0.79
0.14
0.40
0.12
-0.20
-0.22
0.11
0.12
0.26
0.62
0.56
0.38
0.21
-0.11
-0.18
-0.10
-0.33
0.10
n.s
0.11
n.s
27
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