Factor Influencing Customer Repurchase Intention

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Factor Influencing Customer Repurchase
Intention:
An Investigation of
Switching Barriers that Influence the Relationship
between Satisfaction and Repurchase Intention in the
Low Cost airlines Industry in Thailand
Parawee Kitchathorn
School of Business Administration (DBA), University of South Australia, Australia
Keyword(s): Repurchase Intention, Customers Satisfaction, Switching Barriers, Low cost airline
industry, Thailand
Abstract: This research aims to address the deficiencies in predicting Customer repurchase intention by investigating
factors influencing (determinants) of customer repurchase intention. With regards to determinants of customer
repurchase intention, many past studies have found a very strong relationship between customer satisfactions and
repurchase intention. Customer satisfaction is viewed as the most important factor leading to repurchase intent. It is
stated that the higher satisfaction, the more likely for customer to repurchase. However, there are other researchers
who have argued that Customer satisfaction should not be sufficiently used as determinant of Repurchase intention,
there should be other variables relevant to the relationship of these two constructs . It is in this context that
Switching barrier was proposed as moderating variable, which may have effects in between two constructs. Switching
barrier is defined as any factor that makes it difficult or costly for customers to change providers. Previous studies
investigating the influence of satisfaction on repurchase intentions have focused on linear, additive models, however,
this study represents as one of the few efforts at conceptualizing switching barriers, and one of the first attempt to
empirically testing their influencing on direct effect and indirect effect (both moderating effect and mediating effect) on
Satisfaction and Repurchase intentions relationship. Four types of switching barriers link to repurchase intention were
presented to be tested in the model based on theoretical foundation. The conceptual model was tested in the Low cost
airline industry in Thailand. This industry was chosen because of the characteristic of Low Fare service which possibly
has high temptation for customer to easily switch their purchase intention to others. Therefore, it is important for the
service provider to learn how to retain or to prevent their existing customers from switching their purchase to other service
providers in the high competition ground. Result from CFA and SEM confirming the hypotheses are reported.
1. Introduction
The concept of repurchase intention is adopted and modified from both social psychology and
marketing perspectives. In social psychology, the intention to continue/to stay in a relationship
is referred to as relationship maintenance by Social Exchange Theory (Thibaut and Kelley,
1959) and also by Investment Model of Commitment (Rusbult, 1980).
Customers’ repurchase intention or customer retention is referred to as a key to Defensive
Marketing strategies and business success in general (Cronin et al., 2000). As competition and
costs of attracting new customers increase, companies are focusing on defensive strategies
(Barlette, 2007). They focus on protecting the current customer or making them to repurchase
rather than primarily concentrate on the Offensive Marketing Strategies (Fornell, 1992) which
focus on acquiring new customers and increasing market share.
By following this key to a Defensive Strategy, it is important for academic researchers to
understand the significance of factor influence or determinants of repurchase intentions/
customer retention (Dow, 2006). This area of study was focused in this research, with the
objective to investigate customer satisfaction and the switching barriers as main, moderating
and mediating determinant/ variables which may have an effect on of customer repurchase
intention.
This research focuses on customer satisfaction as the main determinant (independent variable)
to repurchase intention (dependent variable) since many researchers have found a very strong
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relationship between customer satisfactions and repurchase intention. Some researchers
indicated that customer satisfaction is a stronger indicator and more indicative of actual
customer repurchase behavior and retention than other determinants which have already been
mentioned. It was stated that the higher their satisfaction, the more likely for customers to
repurchase (Sharma and Patterson, 2000).
It is in this concept that switching barriers was proposed as Moderator or Moderating variable,
which has effects in between two constructs (Heide and Weiss, 1995; Ranaweera and Prabhu,
2003). According to Aiken and West (1991), a moderator is a variable that affects the direction
and/or strength of relationship between an independent/predictor variable (Satisfaction) and a
dependent/criterion variable (Repurchase Intention).
As defined by Jones et al., (2000), switching barrier is any factor that makes it difficult or costly
for customers to change providers. Though several researchers have emphasized that th e role
of switching barriers is important, because they prevent customers from defecting to another
service providers (Maute and Forrester, 1993), still have not received much attention in
marketing literature (Vasudevan et al., 2006). As one of few efforts to address the deficiencies
in predicting repurchase intention, therefore, this research is set to investigate the
effect/influence of switching barriers on customer satisfaction and repurchase intention
relationship. The research questions and the hypotheses have predicted the main
effects (direct effects) of switching barriers on repurchase intentions and moderating
effects and mediating (indirect effects) on the relationship (See Figure-1).
Fig. 1 General Model
Independent &
Moderating & Mediating Variables
Main/Direct
Effect
Mediating
Indirect effect
Effect
4 Type of Switching
Barriers:
H2-H5(C)
H2-H5(A)
Moderating effect
H2-H5(B)
Overall
Satisfaction
Independent
Variable
H1
Repurchase
Intentions
Dependent
Variable
In this research, there are 4 types of switching barriers to be tested in the model based on prior
research studies and theoretical foundation: social exchange theory (Thibaut and Kelley 1959),
Investment model (Rusbult,1980), Disconfirmation Theories (Oliver 1997), and Bonding Theory
(Wilson, 1990). These four switching barriers are considered to be associated with airline
industry service (e.g. Bejou et Palmer, 1988; Lorenzoni and Lewis, 2004). They are:
Interpersonal Relation, Attractiveness of Alternative, Switching Cost, and Service Recovery
Evaluation).
The proposed model and hypotheses were tested in the Low Cost Airline (LCA) service
Industry in Thailand, with questionnaire survey administrated at the airport. This industry is
chosen for several reasons:

Firstly, according to Street (1994) the airline industry is a service industry which fulfills the
main criteria of heterogeneity, intangibility and perishability, thus there seems to be a
high degree of interaction between the service providers and the customers.

Secondly, the Low cost airline industry is recognized as a new emerging market in
Southeast Asia (Lawton and Solomko, 2005). In Thailand, private airlines were allowed to
traffic rights which had been held exclusively by Thai Airways International. This started a
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new era of air industry competition and led to the emerging of a number of new airline
operators, especially low cost airlines in to the Thai sky market (Hooper, 2005).

Thirdly, though there is evidence that shows the low cost airline market share was
drastically increased (Dobruszkes, 2006), it appears that the nature of Low Fare
characteristic service itself may be the temptation for the customers to easily switch their
purchase intention to other service providers (referred from the study of Lawton and
Solomko, 2005) “When being the lowest cost is not enough”.
2. Literature and Theoretical Background
2.1 Repurchase intention and Customer Retention
Repurchase intention refers to the likelihood of using a service provider again in the future
(Fornell, 1992). Jackson (1985) views “repurchase intent” as a “consumer behavioral intention”
that measures the tendency to continue, increase, or decrease the amount of service from a
current supplier.
The measures of repurchase intention are usually obtained from surveys of current customers
assessing their tendency to purchase the same brand, same product/service, from the same
company. Cronin et al., (2000) has treated “behavioral intentions” and “repurchase intention”
and as synonymous constructs. Ranaweera and Prabhu (2003) defined “future behavioral
intentions” as the future propensity of a customer to continue or to stay with their service
provider, while some researchers have used the term “customer retention” to describe the
construct with this definition (Zeithaml, 1981).
2.1.1 Importance of Repurchase intention and Customer retention
As stated by Jones and Sasser (1995), customer repeat purchase or retention is the most
vital goal for company success and probably the most important concept in marketing.
According to Rosenberg and Czepiel (1984), than the cost of generating a new customer is
believed to be approximately “six times”, the cost of keeping an existing customer. As a
result, firms are refocusing their efforts on keeping existing customers or making them
repurchase, rather than focusing entirely on gaining new customers (DeSouza, 1992).
2.1.2 Determinants/Antecedents of Repurchase intention
Existing research from Marketing and Tourism literature has yielded several key antecedents as
influencing a customer’s intent to revisit or repurchase (Petrick et al., 2006). Variables are for
example 1.) Consumer satisfaction, 2.) Past experience/ behavior, 3.) Brand loyalty, and 4.)
Quality and Service quality. All have been addressed in the literature.
Numbers
of researchers have stated that traditionally customer satisfaction is viewed as the
most important factor leading to repurchase intent (Sharma & Patterson,2000). Therefore, this
study primarily focuses on the consumer satisfaction as the antecedent of repurchase intention.
3. Customer Satisfaction
Customer Satisfaction is an overall evaluation of performance based on all prior experiences with
a firm (Anderson and Fornell, 1994). Bitner and Hubbert (1994) refer it to the consumer's overall
dis/satisfaction with the organization based on all encounters and experiences with that
particular organization.
3.1 Importance of Satisfaction
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A number of research studies have indicated the importance of customer satisfaction to
marketers that the satisfied consumers have positive impact or influence on repeat purchase
behavior and word-of-mouth (Zemke and Shaff, 1990). It is supported that satisfied
consumers are more likely to make repeat purchases and to buy more in future transactions,
than dissatisfied customers (e.g. Reichheld, 1996; Zemke and Shaff, 1990).
3.2 Measuring Satisfaction: (Dis) Satisfaction Theories/Disconfirmation Theories
With a closer examination of the customer satisfaction literature, the theoretical basis for
models of satisfaction/dissatisfaction arises from consumer psychology and especially from
the Theory of Disconfirmation (Oliver, 1980). Empirical studies reveal that this
Disconfirmation paradigm explains that customer satisfaction consists of many determinants/
antecedents. They are expectations, perceived performance and the resultant satisfaction/
dissatisfaction (Oliver, 1997). If performance exceeds expectations, the customer is highly
satisfied, or delighted (Schneider & Bowen, 1999).
3.3 Relationship between repurchase intention and customer satisfaction:
Customer satisfaction as antecedent/predictor of repurchases intention
In general, there are number of previous research studies which support a strong, positive
relationship between satisfaction and repurchase intentions. (e.g. Anderson and Fornell,
1994; Rust and Zahorik,1993). Sharma and Patterson (2000) also support that it is an
established fact that satisfaction has a significant impact on customer repurchase
intentions.(see Table-1).
Table-I:
4.
A Proportion of Prior Studies Support (Pro) and Argue (Con) on the Strong
Relationship between Customers Satisfaction and Repurchase Intention
Satisfaction should be solely used as
determinant /indicator for Actual customer Repurchase
Intention.
(Pro)
Satisfaction is the most important determinant of
Repurchase Intention
Satisfaction should NOT be solely used as
determinant/indicator for Actual Customer Repurchase
Intention
(Con)
“Customer satisfaction is not a surrogate for customer
retention”
Oliver (1980); Churchill and Suprenant (1982);
Bearden and Teel, 1983); LaBarbera and Mazursky
(1983) ; Oliver and Swan, (1989); Daly, (1989); Yi,
(1990); Cronin and Taylor (1992); Fornell, (1992);
Anderson and Sullivan, (1993); Rust and Zahorik,
(1993); Anderson and Fornell (1994); Sharma and
Patterson (2000).
Coyne (1989); Fornell, (1992); Anderson, and
Sullivan(1993); Reichheld (1993); Anderson and Fornell
(1994); Suh (1994); Jones and Sasser (1995); Gotlieb et
al.,(1994);
Hoffman,
(1995);
Keaveney,
(1995);
Reichheld (1996); Sandvik et al., (1997); Barksdale,
Johnson and Suh (1997); Jones, Mothersbaugh & Betty,
(2000); Ranaweera and Prabhu (2003).
Argument on using ‘Customer Satisfaction’ as predictor/ antecedent of
repurchase intention
While satisfaction (from early studies) may be one important driver of repurchase intention,
there are other studies providing arguments concerning this positive influence of
satisfaction on repurchase intentions in the service industry and product markets (Anderson
and Sullivan, 1993; Keaveney, 1995; Sandvik et al., 1997). Several recent studies have
presented their argument that though customer satisfaction is a necessity, it does not
seem to be a sufficient condition (Reichheld, 1996; Barksdale et al.,1997).(See Table-1).
5.
Switching Barriers
As defined by Jones et al, (2000) ‘switching barrier’ is any factor that makes it difficult or
costly for customers to change providers. It also represents the customers’ service evaluation
of the way companies handle complaints and service failure (Valenzuela et al., 2005).
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Previous studies have supported that switching barriers come in several shapes and forms
and are classified differently by many researchers. For example, Ping (1993) classified
switching barriers into: a.) switching cost, b.) alternative attractiveness, c.) investment,)
uniqueness of investment in the wholesaler. Jones et al., (2000) divide them into: a.)
interpersonal relationship b.) switching cost, and c.) attractiveness of alternatives.
5.1 Switching Barrier and Repurchase Intention
Aside from customer satisfaction, Fornell (1992) states that switching barriers are another
means to encourage customer repurchase intention. The link between switching barriers
and customer retention in the past has been recognized in the business-to-business
marketing literature (Jackson, 1985). Some recent research studies also support the view
with regard to the influence of switching barriers and repurchase intention that switching
barriers may have interactive effects on repurchase intention (Gremler & Brown, 1996; Bansal &
Taylor,1999).
5.2 Switching barriers associated with Customer Satisfaction and Repurchase
Intention
Based on the review of prior research and on theoretical foundations, this research
focuses on four main switching barriers, which are believed to be important variables in
retaining customers or customer repurchases intention. These four barriers are selected
because they are also considered to be associated with airline industry (e.g. Bejou et
Palmer, 1988; Lorenzoni and Lewis, 2004). And four types of Switching Barriers are
selected based on theoretical support are discussed as follows:
5.2.1) Interpersonal relationships
Interpersonal relationships refer to the strength of personal bonds that develop between
customers and their service (provider’s) employees (Berry and Parasuraman, 1991). For
example, Gremler (1995) used the term interpersonal bond to refer to the "degree to which
a customer perceives having a personal or sociable relationship with a service provider
employee(s)”.
5.2.2)
Attractiveness of Alternatives
In service marketing context, the “attractiveness of alternatives” refers to the level of
service expected in one's best available alternative to the present servic e provider
(Rusbult, 1980). “Alternative attractiveness” is also conceptualized as the client’s estimate
of the likely satisfaction available from an alternative relationship (Ping, 1993).
5.2.3) Switching Costs
Switching cost (Porter, 1988) is formally defined as the cost involved in changing from
one service provider to another. These costs can be real, perceived, monetary and/or
non monetary (Gremler, 1995). These are consistent with the findings in social
psychology and marketing management concept, which explain that many customers
may not switch service providers because the expense of doing so is too high.
5.5.4) Service recovery evaluation from customers’ complaint and service failure
Handling
Referring to Theory of Disconfirmation (Oliver, 1980) reviewed in the previous section,
Negative disconfirmation results when a product or service performance is less than the
customer's expectations, and it will create complaint and negative words of mouth (Zemke
and Shaff, 1990). On the other hand, Barlow and Moller (1996) view a “complaint” as “a
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gift” to the firm, because they give firms an opportunity to find out what customers
problems are, so companies can solve them.
6.
Research Questions and Hypothesis Formulation
For This research study, there are 13 hypotheses to be tested. The proposed
hypotheses are developed based on theoretical reviews and prior research reviews.
Research questions and Hypothesis Formulation: Referring to research objectives
which aim to investigate the effect/influence of switching barriers on the relation of
customer satisfaction and repurchase intention, the problem statement and research
questions are set in accordance with this objective, and they are discussed as follows.
 The intervention between customer satisfaction and repurchase
Intention
According to Heillers (1995) there is a need to define more accurately the intervening
component between satisfactions and repurchase intention. With regard to the relationship
between satisfaction and repurchase intention, some researchers have supported the
positive strong relationship between the two constructs (Cronin and Taylor, 1992), while
some others still question this relationship (Sandvik et al.,1997) (see: Table-I).
 Notion of Low Cost Airline in Asia and in Thailand
As for the notion of low cost airlines (LCA), it is found that even though studies related to
low cost airlines business do exist (Dobruskes, 2006), they are mostly conducted in the
West, with few perspectives for Asia (O’Connell, 2005) and very few in the Thai context
(Hooper, 2005). Thus, by combining two problems statements above, the research
questions are set: as follows .
Research Question (RQ1):
RQ1:
-
What is the effect/influence of (Low Cost airline) customer
satisfaction on the repurchase intention ?
Hypothesis formulation for Research Question 1 -
Satisfactions as driver of repurchase intention (direct effect of satisfaction on repurchase
Intention)
As discussed in the previous section, several research studies have supported the view that
satisfied consumers are more likely to make repeat purchases or to buy more in future
transactions than dissatisfied customers (Reichheld 1996; Zemke and Shaff 1989). Empirically,
considerable number of research studies support the strong linkage between satisfaction and
retention, or positive influence on purchase intention (e.g., Fornell, 1992; Taylor and Baker,
1994). Thus, in line with previous researches, the following hypothesis is offered.
H1:

The higher the level of satisfaction, the higher the level of
customer repurchase intention.
The role and influence of Switching barrier
Some researchers (Jones et al., 2000; Anderson and Fornell, 1994) have indicated that the role
of switching barriers has received relatively little attention in marketing. Anderson and Fornell
(1994) has stated that switching barrier is an important variable which may have
effect/influence on the satisfaction and the repurchase intention. Moreover, they have also
indicated a need to examine not only direct effect of the switching barriers but also their
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moderating effects and mediating effects (indirect effect) which may also play an important
role in the relationship between customer satisfactions and repurchase intention. Thus, the
research questions are set, as follows:
Research Question (RQ2 and RQ3):
RQ2: What is the direct effect of switching barriers on repurchase intention?
RQ3: What is the moderating effect and mediating effect (indirect effect) of
switching barriers on the relationship between Low Cost Airline
customer satisfaction and repurchase intention?
- Hypothesis formulation for Research Question: 2 and 3 Switching Barriers
The following discussion offers several switching barriers which are hypothesized
to have a direct effect (A) on repurchase intentions as well as a moderating
influence (B) and a mediating influence (C) on the satisfaction/ repurchase
intentions relationship. By testing them in different service settings of low cost
airline service, it is believed that the result will help reveal valuable information
which will provide more understanding about the relationship between satisfaction
and repurchase intentions,
(A)
“Switching barrier” as driver of customer repurchase intention/
direct effect (a) of switching barriers on repurchase intention:
“Switching barrier” is any factor that makes it difficult or costly for customers to
change providers (Jones et al., 2000). Keaveney (1995) has conducted a critical
incident study, which was one of the first to examine switching barriers as a
determinant of customer switching behavior.
(B)-(C) “Switching Barriers” as moderating (b) and mediator influencer
(c)/indirect effect on the satisfaction/ repurchase intentions relationship:
While the main effect of switching barriers on retention has been empirically
validated in a number of settings (Heide and Weiss, 1995) and employer -toemployee relationships (Weiss and Anderson, 1992), there are few studies which
have tested the moderating effects or indirect effect of switching barriers on the link
between satisfaction and retention (Ranaweera and Prabhu, 2003).

Four Switching Barriers are:
1.)
2.)
3.)
4.)
Interpersonal Relationships
Attractiveness of Alternative
Switching Costs, and
Service Recovery from Service failure and complaint
Switching Barrier: No. 1) Interpersonal relationships
(A) Direct Effect of “Interpersonal Relationships” on “Repurchase intention”
Interpersonal relationships refer to the strength of personal bonds that develop
between customers and their service employees (Berry, 1991; Turnbull and Wilson,
1989). From the study of Jone et.,al (2000) the results suggest that interactions
between customers and service employees can lead to personal relationships that
bind customers and service providers. Thus, it is hypothesized that:
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H2(a): The higher the level of interpersonal relationship, the higher
level of the repurchase intention
(B)-(C): Moderating effect and mediating effect of “Interpersonal relationship” on
“Satisfaction/ Repurchase Intention relationship” Jones et al. (2000) discovered that,
in situations of low customer satisfaction, strong interpersonal relationships positively
influence the extent to which customers intend to repurchase. Thus, it is
hypothesized that:
H2(b): For a given level of customer satisfaction, the higher level of
interpersonal relationship, the weaker the relationship between
satisfaction and repurchase intention
Anderson and Fornell (1994) have also indicated a need to examine not only the
direct effects of the switching barriers but also their moderating and indirect effects
(mediating effects) which may also play an important role in the relationship
between customer satisfaction and repurchase intention. Thus, it is hypothesized
that H2(c):
H2(c): Interpersonal relationship mediates relationship between
customer satisfaction and repurchase intention
Switching Barrier No: 2) Attractiveness of Alternatives
(A): Direct Effect of “Attractiveness of alternatives” on “Repurchase intention”.
Attractiveness of alternatives refers to customer perceptions regarding the extent to
which viable competing alternatives are available in the marketplace. When
consumers perceive few viable alternatives, the perceived benefits of defecting should
be relatively low, resulting in higher levels of retention. (Rusbult,1980). The study
conducted by Ping (1993), supports the view that when viable alternatives are lacking,
the probability of terminating an existing relationship decreases. Thus it is
hypothesized that:
H3(a): The lower the level of attractiveness of alternatives, the higher
level of repurchase intention
(B)-(C): Moderating effect and mediating effect of “attractiveness of alternative” on
“satisfaction/and repurchase relation”. Ping (1993) also provided empirical support
for the interaction between satisfaction and the attractiveness of alternatives when
predicting retention in a channels context. Thus, this research suggests that the
attractiveness of alternatives may moderate the influence of satisfaction on
retention. Consistent with marketing channels research but in a services
marketing context, Jones et al., (2000) suggests that if there are few attractive
service providers from which to choose (i.e., low attractiveness of alternatives),
the customer is less likely to change service providers despite low or moderate
levels of satisfaction with the current provider. Thus, it is hypothesized that:
H3(b): For a given level of customer satisfaction, the lower the level of
attractiveness of alternatives, the weaker the relationship
between satisfaction and repurchase intention
According to Ranaweera and Prabhu (2003) there are few studies which tested
indirect effects/(mediating effect) of switching barriers on the link between
satisfaction and retention. Thus, it is hypothesized H2(c) that:
H3(c): Alternative of attractiveness mediates relationship
between customer satisfaction and repurchase intention.
Switching Barrier: No 3.) Switching Costs
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(A): Direct Effect of “Switching costs” on “Repurchase intention” According to Jones
(1998), switching costs refers to the costs associated with changing service providers
and include the following specific types of costs: continuity costs, contractual costs,
learning cost, search costs, setup cost, and sunk costs. From the study of Patterson
and Smith (2001), the relational switching costs are found to be an antecedent to
commitment or “retention”. Therefore, it is hypothesized that:
H4(a): The higher the level of switching costs, the higher level of
repurchase intention.
(B)-(C): Moderating effect and mediating effect of “Switching Cost” on
“Satisfaction/Repurchase intention relation”. According to Steenkamp & Baumgartner
(1992), it might well be that a customer stays with a service supplier, not because they
are very satisfied with the service offering, but rather because the costs of switching are
too high. Thus, it is hypothesized that:
H4(b): For a given level of customer satisfaction, the higher the level of
perceived switching cost, the weaker the relationship between
customer satisfaction and repurchase intention
Prior researchers (Ranaweera and Prabhu ,2003;Heide and Weiss,1995) have stated
that switching barriers may have an indirect effect in between customer satisfaction
and repurchase intention. Thus, it is hypothesized H4(c) that:
H4(c): Switching costs mediate relationship between customer
satisfaction and repurchase intention
Switching Barrier No. 4.) Service recovery evaluation
(A): Direct Effect of “service recovery evaluation” on “repurchase intention”.
According previous researchers, service recovery is recognized as a significant
determinant of customer retention (Fornell and Wernerfelt, 1987; Tax and Brown,
1998). And according to the study of Vincent 2004, the study result reveal that a
customer who has experienced a prior failure with the service provider is more
likely to be impressed by superb recovery than a customer who has never
encountered a problem with a service provider. Thus to be in line with the
previous research, the following hypothesis is proposed.
H5(a): The higher the level of service recovery evaluation, the
higher level of customer repurchase intention
(B)-(C): Moderating effect and mediating effect of “Service recovery evaluation” on
“Satisfaction /Repurchase Intention Relation” Valenzuela et al., (2005) has
mentioned as quoted in the previous section, that the relationship between service
recovery evaluation and switching barriers is not known. This implies that
marketers do not know if switching barriers has a positive or negative effect on the
customers’ evaluation of the way that firms are handling complaints (Valenzuela et
al, 2005). Therefore, the moderating and mediating effect of switching barrier
(service recovery) should be tested. Thus, hypotheses (b) and (c) are proposed:
H5(b): For a given level of customer satisfaction, the higher the level
of service recovery, the weaker the relationship between
customer satisfaction and repurchase intention
H5(c): Service recovery mediates the relationship between
customer satisfaction and repurchase intention
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7.
Conceptual Model
The proposed model represents one of the attempts to better understand the
relationship between satisfactions and repurchase intention by investigating possible
moderating influence/effect of switching barriers. The proposed combination of the model
(see: Fig-2) represents an effort to better understand and to address the deficiencies in
predicting repurchase intentions (Dependent variable or Criterion variable) by using
satisfaction as antecedent (Independent variable).
This model shows hypothesis test links between satisfaction-customer repurchase
intention and also hypothesizes test of four kind of switching barriers as
moderating/mediator variables. They are interpersonal relationships, switching costs,
attractiveness of alternatives, and service recovery. The hypothesis will predict the main
effects or moderating effects (directly/indirectly effect) of these four barriers on
repurchase intentions. These four barriers are selected because they are considered to
associate with airline industry (e.g. Bejou et Palmer, 1988; Lorenzoni and Lewis, 2004). The
airline industry is the chosen industry to test the model because, according to Street
(1994) who supports that “an airline industry” is a service industry which fulfilling the
main criteria of heterogeneity, intangibility and perishability, thus there seems to be high
degree of interactions between the service provider and the customers. Thus, it may be
suite to test the proposed model.
8.
Methods
8.1
Quantitative study Method
Quantitative study method was adopted and quantitative data was collected for this research.
Due to the nature of the research questions proposed, the researcher is required to see or to
obtain a clear/degree of measurement or an indicative scale for each factor (variables),
including their relation and correlations between variables.
Fig.2
Conceptual Model of Satisfaction, four type Switching Barriers, and Repurchase Intention
4 types of Switching Barriers
Moderating Effect
(b)
Interpersonal
relationship
Mediating
Effect (c )
H2(c)
H2(a)
H2(b)
Direct effect (a)
Attractiveness of
Alternatives
H3(c )
H3(a)
H3(b)
Overall
Satisfaction
H1
Repurchase
Intentions
H4(b)
H4(c )
H4(a)
Switching Costs
H5(c)
)
H5(a)
H5(b)
Service recovery
Evaluation from failure
and complaint
Switching
Cost
8.2
Satisfactory/
/(Dis)confirmation
Paradigm
Social Exchange
Theory
Investment Model
Theoretical Foundations
Bonding Theory
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8.2 Data collection and Research Instrument/Tool
Moreover, the review of the methodology utilized in the prior research shows that “all” of
researchers in this area of study chose quantitative method to conduct their studies and
to test their hypotheses. Therefore, quantitative method was adopted for this research
study.
The model and hypotheses were tested in the low cost airline industry in Thailand. The
data was collected from airline passengers who are waiting for their flight at airports of
Thailand, with official permission from the Airport Authority of Thailand to access
customers at the Airport. The survey was administrated approximately 3 weeks from the
last week of January 2005 until the second week of February 2008.
8.3 Reliability and Validity Test
After the pre-test stage, the reliability & validity tests for the questionnaire were
conducted. According to Sproull (1995), Validity and reliability are usually estimated or
tested by using correlation coefficients. Therefore, in this process, the Cronbach
Alpha Coeffient was used as a tool assessing the reliability of scale (Santos,1999)
in order to test the reliability and validity of the questionnaire.
8.4 Pre-test
Data from 30 Thai questionnaires for the Pre-test were collected to test the reliability of
the questionnaire. The data were processed or entered into SPSS program version 16.0
and the data were analyzed to get the reliability coefficient of the questionnaires.
The result showed that each set of variables gave a Cronbach Alpha value range
between 0.729 - 0.884 which indicated good reliability for this set of questionnaires and
feasible to use as the research tool in main study.
After the pre-test stage, the questionnaire was revised and edited for “Thai wording" to
make it more comprehensible for the passengers. . Next stage, the Final questionnaire
was developed in order to use as the survey tool in the main study.
8.5
Determination of Scales and Format of Measurement in the Questionnaire
For the measurement scale of construct (used in questionnaire), two measurement
scales were proposed in this research. Due to the fact that all of data collected are
considered as Interval scale (Satisfaction, Repurchase Intention and switching
barriers), Two measurement scales were applied: (Bi-polar) Semantics Differential
scale and Likert scale with those interval variables. Moreover, as mentioned in the
prior studies of e.g. Jones et al., (2000), Colgate Lang (2001) and Ranaweera and
Prabhu (2003), the researchers have also supported the use of these two scales in
their studies.
From the previous research reviews, it is found that, in the study of Jones et al.,
(2000), seven-point semantic differential scale was used to measure the customer
satisfaction and repurchase intentions, while a seven-point likert scale was used as a
tool to measure “the effect of switching barriers”. In the study of Colgate and Lang
(2001) who had used 5 point likert scale in the study of “The effect of switching barriers
(4 types) on customer intention to stay with service provide”.
9. Data Collection and sample characteristic: Data Sampling and Target population
The total number of questionnaires sampled was allocated to each air line based on
Quota sampling. And the number of sample size for each airline would vary on
12
proportion or percentage of actual customers from 3 low cost airlines operators in
Thailand.
As for scope of target population in this research, this research focus on the passenger
who was Decision Maker for the airline ticket and also on Leisure traveler/passenger
rather than business passenger. Because several literature reviews or studies (Levitt,
1981; Whipple and Thach, 1988), had presented that a leisure product/service
performance may be the crucial determinant of future purchase intentions including
positive word of mouth.
Main Survey Administration: The field surveys were conducted with Low cost
passengers at the airports for approximately 2 weeks. 750 questionnaires were
distributed to three airline passengers based on quota sampling. Total number of
complete questionnaires collected was 600 and the survey was conducted within a
controlled period. This aimed to minimize interferences from high seasonal, sale
promotion and other social influences.
With this face to face interview method, the result yielded 83 % of passenger
participation, including incomplete questionnaires or missing data value. The percentage
for complete questionnaires was 80%. This method had also been effectively used in
both prior related studies and with the airline studies: Chang and Chen, (2007) and Bejou
and Palmer (1998).
10.
Results
10.1 Results from Confirming factor Analysis (CFA)
After employing item-total correlations and alpha coefficient were computed for each
variable and each aggregate level.
The confirmatory factor analysis demonstrated a reasonable fit of the data to the six-factor
measurement model on several criteria. The model has the Chi-square of 626.13 with 379
degree of freedom, GFI of .937, AGFI of .918 and RMSEA of .033.
The RMSEA less than .05 which indicates good fit.(RMSEA=0.0 indicates exact fit, from
.08 to .10 indicates mediocre fit, greater than .10 indicates poor fit (Zencaroline,2007).
The CMIN/DF of 1.65, indicating a good fit model of the data. CMIN/DF in the range of 2
to 1 or 3 to 1 indicate acceptable fit between the hypothetical model and the sample data.
Different researchers have recommended using ratio as low as 2 or as high as 5 to
indicate a reasonable fit (Marsh&Hocevar,1985). Chi-square/df ratio values lower than 2
are widely considered to represent a minimally plausible model (Byrne, 1991).
10.2 Hypothesis Testing and Result Analysis
The Hypotheses were tested with SEM resulted from AMOS version 7.0. The full model in
this study was a combination of six measurement and a structural model. However, the
most important part was its structural model. The structural model was constructed by the
thirteen hypotheses. (See Table-2)
10.2.1 Relation of Satisfaction (SAT) and Repurchase Intention (REP)
Hypothesis 1 (SAT REP) stated that the higher the level of satisfaction, the
higher level of customer repurchase intention. This hypothesis was shown as the path from
SAT to REP (Table-2). The standardized coefficient of this path was .834. The t-value was
11.403, which was significant at a = .001. The significant coefficient provided evidence of
support for Hypothesis 1.
13
10.2.2
Direct and Indirect Effect (Moderating and Meditating Effect) of 4 type
Switching
Barriers
on Satisfaction (SAT) and Repurchase Intention (REP)
Relationship
-Interpersonal Relationship (INR)
Hypothesis 2(a) explored the relationship between interpersonal relationship and
repurchase intention, the direct effect, was shown as the path from INR to () REP in
Table-XIII)
Hypothesis 2(a) was not supported since the t-test for the path coefficient was not
significant (t-value of 1.025) indicating that interpersonal relationship did not influence the
repurchase intention.
Hypothesis 2(b), exploring the moderating effect of INR on satisfaction and repurchase
intention relationships, H2(b) was hypothesized that for a given level of
customer satisfaction, the higher level of interpersonal relationship, the weaker the
relationship between satisfaction and repurchase intention. This relationship, indicated by
the path from (INR x SAT) to REP, shown was found to be not significant, with a t-value of
.770, so hypothesis 2(b) was not supported.
Hypothesis 2(c), exploring the mediating effect/indirect effect of INR on satisfaction and
repurchase intention relationship, H2(c) stated that interpersonal relationship mediates
relationship between customer satisfaction and repurchase intention. This hypothesis
was shown as the path from SAT  INR  REP. The standardized coefficient for this
path (indirect effect) was .019. The t-value of the path from SAT  INR was 9.236 and,
the t-value of the path from INRREP was 1.025 which was not significant at a = .05.
The insignificant coefficient provided evidence of no support for hypothesis 2(c).
Hypothesis 3(b) stated that for a given level of customer satisfaction, the lower the level
of attractiveness of alternatives, the weaker the relationship between satisfaction and
repurchase intention. This relationship, indicated by the path from (ATA x SAT) to REP
was found to be insignificant at an alpha level of a = .005, with a t -value of -.989, so
hypothesis 3(b) was not supported.
- Attractiveness of Alternative (ATA)
Hypothesis 3(a) hypothesized that the lower the level of attractiveness of alternative,
the higher level of repurchase intention (direct effect of ATA  REP). This relationship,
indicated by the path from ATA to REP, was found to be insignificant at an alpha level of a =
.05, with a t-value of .871, so hypothesis 3(a) was rejected.
Hypothesis 3(c) stated that the alternative of attractiveness mediates relationship
between customer satisfaction. This hypothesis was shown as the path from
SATATAREP. The standardized coefficient for this path (indirect effect) was .005.
The t-value of the path from SAT ATA was -3.432 and, the t-value of the path from
ATA  REP was .871 which was not significant at a = .05. The insignificant coefficient
provided evidence of no support for hypothesis 3(c).
- Switching Costs (SWC)
Hypothesis 4(a) explored the relationship between switching costs and repurchase
intention shown as the path from SWC to REP (direct effect of SWC REP),shown in Table2, Hypothesis 4(a) was supported since the t-test for the path coefficient was significant (t-value
of 2.442), indicating switching costs influenced the repurchase intention.
14
Table-2: Summary of Hypothesis Testing for SEM Full Model
Effect
H
Structural
Path Relationship
t
p
p < .05
Standardized
Regression
Coefficient
Direct
Direct
Effect
H1
SAT  REP
Direct
Effect
H2(a)
INR  REP
H3(a)
Moderating
Effect
.000
.834
1.025
.306
.040
-
Not Supported
ATA  REP
.871
.384
.030
-
Not Supported
H4(a)
SWC  REP
2.442
.015
.093
-
Supported
H5(a)
SVR  REP
-.149
.822
-.006
-
Not Supported
H2(b)
(INR X SAT)  REP
-.770
.441
-
-
Not Supported
H3(b)
(ATA X SAT)  REP
-.989
.323
-
-
Not Supported
H4(b)
(SWC X SAT)  REP
-.720
.472
-
-
Not Supported
H5(b)
(SVR X SAT)  REP
-1.302
.194
-
-
Not Supported
9.236
1.025
.000
.306
.479
.040.
-
-
-
0.019
-3.432
.871
.000
.384.
-.163
.030.
-
.000
.015
.280
.093
.005
-
Not Supported
Supported
SAT  INR
INR  REP
H2(c)
Mediating
Effect
SAT  INR  REP
SAT  ATA
ATA  REP
11.403
Indirect
-
H3(c)
SAT  ATA  REP
SAT  SWC
SWC REP
5.475
2.442
H4(c)
SAT  SWC  REP
SAT  SVR
SVR  REP
12.557
-.149
SAT  SVR  REP
-
H5(c)
-
-
(Hypothesis Test)
Structural
Equation Model
Supported
-
-
.026
.000
.882
.615
-.006
-
-
-
0.004
Not Supported
Not Support
Hypothesis 4(b) hypothesized that for a given level of customer satisfaction, the higher
the level of perceived switching cost, the weaker the relationship between customer
satisfaction and customer repurchase intention. This relationship indicated by the path from
(SWC x SAT) to REP was found to be not significant, with a t-value of -.720, so hypothesis 4(b)
was not supported.
15
Figure- 3:
Standardized parameters from Analysis of Structural Equation Model (SEM)
of the Full Revised Model
Hypothesis 4(c) stated that switching cost mediate relationship between customer
satisfaction and repurchase Intention This hypothesis was shown as the path from SAT
SWC REP. The standardized coefficient for this path (indirect effect) was .026. The tvalue of the path from SAT SWC was 5.475 and, the t-value of the path from SWC to REP
was 2.442 which was significant at a = .001. Thus, the significant coefficient provided
evidence of support for hypothesis 4(c).
-Service Recovery from Service Failure and Complaint (SVR)
Hypothesis 5(a) stated that the higher level of service recovery evaluation, the higher
level of customer repurchase intention (direct effect of SVR REP) was shown as the path
from SVR  REP . Hypothesis 5(a) was not supported since the t-test for the path coefficient was
significant (t-value of -.149) indicating service recovery evaluation did not influence the
repurchase intention.
Hypothesis 5(b) was hypothesized that for a given level of customer satisfaction, the
higher level of service recovery, the weaker the relationship between customer satisfaction and
customer repurchase intention .This relationship indicated by the path from (SVR x SAT) to
REP was found to be not significant, with a t-value of -1.302, indicating service recovery
evaluation did not influence the repurchase intention so hypothesis 5(b) was not supported.
Hypothesis 5(c) stated that service recovery evaluation mediates relationship
between customer satisfaction and repurchase intention. This hypothesis was shown as the
path from SAT SVR REP. The standardized coefficient for this path (indirect effect) was
.004. The t-value of the path from SAT  SVR was 12.557 and, the t-value of the path from
SVR to REP was -.149 which was insignificant at a = .05. The insignificant coefficient
provided evidence of no support for hypothesis 5(c).
16
11.
Discussion
The objective of this research is to investigate the effect/influence of switching barriers on
customer satisfaction and repurchase intention relationship. Many studies assume that
relationship between satisfaction is strong and certain, however results vary as to the strength
and magnitude of relationship in different industries. Previous studies had focused their
investigation mainly on direct effect or moderating effect of switching barriers.
This dissertation provides one of the first attempts to investigate conceptualizing
switching barriers, and empirically test on 3 types of their influence i.) direct effect ii.)
moderating effect and iii.) mediating effect on the satisfaction and repurchase intention
relationship.
The results from hypothesis testing, not surprisingly and consistently with Hypothesis-1,
Satisfaction was found to have a strong influences on repurchase intentions. Respondents who
report high levels of satisfaction with the airlines were likely to have high repurchase intentions.
“Satisfaction”, was found to have the main effect or direct effect on repurchase intention. And,
among 4 types of switching barriers (interpersonal relationships, the attractiveness of
alternatives, switching costs, and service recovery.), only “Switching Cost” was found to have
main effect/direct effect on repurchase intentions. Thus, Hypotheses (2a), (3a), and (5a), were
not supported. Only hypothesis 4(a) was supported (the higher level of switching costs, the
higher level of repurchase intentions).
As for moderating effect of 4 types of switching barriers on the relationship of satisfaction and
repurchase intention, these were inconsistency with hypothesis 2(b), 3(b), 4(b) and 5(b), none of
the four switching barriers performed their role as “moderator” on satisfaction and repurchase
intention relation.
For the mediating effect of 4 types of switching barriers on the relationship of satisfaction and
repurchase intention, only one out of four Hypotheses (2c, 3c, 4c, and 5c) was supported. Only
hypothesis 4(c) was supported, predicting that ‘switching costs’ mediate relationships between
satisfactions and repurchase intention. Switching costs, again, besides its direct effect on
satisfaction/repurchase intention relation, were found to have mediating influence on repurchase
intention. It appears that when switching costs is high, repurchase intentions remained relatively
high, despite the lower levels of satisfaction.
In conclusion, these results showed that from Low Fare samples, three out of the thirteen
hypotheses were supported, and ten hypotheses were rejected. Consistent with hypothesis,
Customer Satisfaction was found to have a strong influences on repurchase Intentions.
Respondents who report high levels of satisfaction with the airlines were likely to have high
repurchase intentions. The hypotheses testing on Switching Barriers indicated that when
customer were highly satisfied, only “Switching costs” was found to have a positively direct
influence and mediating effect on repurchase intention
12.
Implications
The theoretical implications from this study are numerous. This current study has addressed
critical issues that have received inadequate attention in literature such as; i) defining more
accurately the role of satisfaction on repurchase ii) defining the intervention between customer
satisfaction and repurchase intention, and iii) identifying the role of the switching barriers and
determining their influence both direct effect and indirect effect on repurchase intention. The
findings from this dissertation are also relevant to practitioners. It also helps extend the notion
of Low cost airline and identifying the customer behaviour or variable/antecedents leads to repeat
purchase in low cost industry
Therefore, for the practitioners, it is quite clear in this low fare service that overall satisfaction
and switching costs can be important factors in retaining customers. For developing customer
17
retention strategies, then, the effort should be put on most satisfying their customers and
creating a high level of switching costs in order to achieve the highest level of repurchase
intention and subsequent of retention.
13.
Limitations
There are some limitations in this research. Firstly, the body of knowledge related to low cost
airline itself may still be considered limited as Thais are not yet quite acquainted with the nature
of this business and the nature of business is not yet normalized to Thais (the low cost airline
business has started in Thailand in 2004). Customer perception and knowledge may still be
limited. Secondly, there are other factors which may influence customer retention apart from
factors suggested in this study, such as demographic characteristics of customer, service life
cycle, and usage pattern of airline service. Due to the fact that this research focuses on the Thai
context and will be tested in a field setting of national scope, for generalization, in order to apply it
to other cultures, the cross-cultural effects have to be taken into account as well.
14.
Future research Directions
The findings of this dissertation provide several research implications for future research
directions in a number of areas.
Firstly, a future study can be designed to investigate other multi-sample differences
such as; by gathering a larger sample and comparing high and low repurchase intent groups.
Secondly, future research can further examine the behavioral outcomes of
repurchase intention. This type of research can incorporate relationship stability, willingness
to accommodate willingness to recommend, and complaint behavior to enrich our
understanding of business-to-customer relationships and how these relationships impact
repurchase behavior.
Next, research should also test the model using consumers in other demographical
segmentation, such as customers living in smaller to mid-size cities. It seems possible for low
fare service that switching barriers might have a greater effect for consumers living in smaller
cities where the choice of service providers are much less than the choice in larger cities.
Furthermore, the study of switching barriers should be extended to other industries
such as hotels and fast food restaurants services, then appropriate theories developed
should also reconfirm these findings and enhance generalizability.
18
REFERENCES:
Anderson, E. W. & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction
for firms. Marketing Science, 12 (Spring), 125–143.
Anderson, E. W. & Fornell C. (1994). A customer satisfaction research prospectus. Services Quality:
New Directions in Theory and Practice, R.T. Rust and R. L. Oliver, eds. Thousand Oaks, CA: Sage
Publications, Inc., 241-268.
Bansal, H.S. and Taylor, S.F. (1999). “The service provider switching model (SPSM): a model of consumer
switching behavior in the service industry”. Journal of Service Research, 2(2), 200-18.
Barksdale, H. C., Jr., Johnson J. T. J, & Suh M. (1997). A relationship maintenance model: a comparison
between managed health care and traditional fee-for-service. Journal of Business Research, 40 (3), 237247.
Barlow, J., & Moller, C. (1996). A Complaint is a Gift, San Francisco, Berrett-Koehler Publishers.
Bartlett, M. (2007). Online banking evolving to create a hub for CU Members. Credit Union Journal,11(32),
14-14.
Bearden, W. O. & Jesse E. T. (1983). Selected determinants of consumer satisfaction and complaint reports.
Journal of Marketing Research, 20(Feb), 21-8.
Bejou, D. & Palmer, A. (1998) .Service failure and loyalty: an exploratory empirical study of airline
customers”, Journal of Service Marketing,12(1), 7-22
Bennis, W. G., Schien, E. H., Berlew, D. E., & Steele, F. I.(1964). Interpersonal dynamics. Homewood, IL:
Dorsey Press.
Berry, L. & Parasuraman, A. (1991). Marketing services: competing through quality, The Free Press, New
York, NY.
Bitner, M. J. & Hubbert A. R. (1994). Encounter satisfaction versus overall satisfaction versus quality:
the customer's voice in Service Quality.New Directions in Theory and Practice, Roland T. Rust and
Richard L. Oliver, eds., Thousand Oaks, CA: Sage Publications, Inc., 72-94.
Boshoff, C. (1997). An experimental study of service recovery options. International Journal of Service
Industry Management 1997,8(2).
Byrne, B. M. (1991). The maslach inventory: validating factorial structure and invariance across
intermediate, secondary, and university educators. Multivariate Behavioral Research, 26, 583-605.
Chang,Y. and Chen,. F.( 2007) . Relational benefits, switching barriers and loyalty: A study of Airline
customers in Taiwan. Journal of Air Transport Management, 13, 104–109.
Choi, T. Y., & Chu R. (2001). Determinants of hotel guests’ satisfaction and repeat patronage in the Hong
Kong hotel industry. Hospitality Management, 20, 277-97.
Churchill, G.A. & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction”,
Journal of Marketing Research, 19(Nov), 491-504.
Colgate, M., & Lang, B. (2001). Switching barriers in consumer markets: an investigation of the financial services
industry. The Journal of Consumer Marketing, 18(4/5),323-347.
Coyne, Kevin P. (1989). Achieving a Sustainable Service Advantage, Journal of Business Research, 3-10
19
Cronin, J. J., Brady M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value and customer
satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193218.
Cronin, J. J., Jr. & Taylor, A. T. (1992). Measuring service quality: a reexamination and extension. Journal
of Marketing, 56 (July), 55–68.
Daly, R. W.( 1989). The failed Health Care revolution. Harvard Business Review; Jul/Aug 89, 67 (4), 157.
Day, G. S. & Wesley, R. (1988). Assessing advantage: a framework for diagnosing competitive superiority”.
Journal of Marketing, 52, 1-20.
DeSouza, G. (1992). Designing a customer retention plan. Journal of Business Strategy, March/April, 24-28.
Dickson, P. R. & James L. G. (1987). Market segmentation, product differentiation and marketing strategy,"
Journal of Marketing, 43 (Fall), 8-19.
Dobruszkes, F. (2006). Analysis of European low cost airlines and their networks. Journal of transport
Geography, 14, 249-264.
Dow, R. (2006). Bank regulatory enforcement actions against institution affiliated parties defensive
strategies. Banking Law Journal, 123 (5), 426-439.
Dresner, M. (2005). Leisure versus business passengers: similarities, differences, and implications, Journal
of Air Transport Management, 12, 28-32.
Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal of
Marketing,56, 6–21.
Fornell, C., & Wernerfelt, B. (1988). A model for customer complaint management. Marketing Science, 7
(Summer), 271-286.
Fornell, C. & Wernerfelt, B. (1987). Defensive marketing strategy by customer complaint management: a
theoretical analysis”, Journal of Marketing Research 24, 337-46.
Gotlieb, Jeny B., Dhruv G.,& Stephen W. B. (1994). Consumer satisfaction and perceived quality:
complementary or divergent constructs?" Journal of Applied Psychology, 79 (Dec), 875-885.
Gremler, D. D. (1995). The impact of satisfaction, switching costs and interpersonal bonds on service
loyalty”, PhD dissertation, Arizona State University, Tempe, AZ.
Gremler, D. D. and Brown, S. W. (1996). Service loyalty: its nature, importance, and implications”, in
Edwardson, B., Brown, S.W. and Johnston, R. (Eds), Advancing Service Quality: A Global Perspective,
International Service Quality Association, 171-80.
Gronroos, C. (1990). Relationship approach to the marketing functions in service contexts, Journal of
Business Research, 29(1), 3-12.
Heide, J.B. & Weiss, A.M. (1995). Vendor consideration and switching behavior for buyers in high-technology
markets, Journal of Marketing, 59(3),30-43.
Hellier, P. K. (1995). Discovering the major factors influencing customer retention in service industries,"
Asia Journal of Quality Management, 4 (2), 62-65.
Hoffman, K. D., Scott W. K., & Holly M. R. (1995). Tracking Service Failures and Employee Recovery
Efforts, Journal of Services Marketing, 9 (2), 49-61..
Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology,63, 597–606.
20
Hooper P. (2005). The environment for Southeast Asia’s new and evolving Airlines. Journal of Air
Transport Management,11 335–347.InternationaCivil Aviation Organization, 252/1 ViphavadiRangsit Road, Bangkok 10900, Thailand.
Jackson, B. B. (1985). Winning and Keeping Industrial Customers, Lexington, MA: Lexington Books.
Johnson, M.D. and Fornell, C. (1991). A framework for comparing customer satisfaction across individuals and
product categories. Journal of Economic Psychology,12( 2), 267-86.
Jones, M A., Mothersbaugh, D. L., & Beatty D., S.E (2000). Switching Barriers and Repurchase Intention In
Services. Journal of Retailing,76(2), 259-274.
Jones, M. (1998). Satisfaction and repurchase intentions in the service industry: the moderating influence
of switching barriers, Ph.D. (Dissertation) University of Tuscaloosa, Alabama.
Jones, Thomas O. and Sasser W. E.,(1995). Why Satisfied Customers Defect, Harvard Business
Review, (Nov-Dec),88-99.
Keaveney, S.M. (1995), “Consumer switching behavior in service industries: an exploratory study ”, Journal
of Marketing,Vol. 59 No. 2, pp. 71-82.
LaBarbera, P. A., & Mazursky, D. (1983). A longitudinal assessment of consumer satisfaction/ dissatisfaction: the
dynamic aspect of the cognitive process”. Journal of Marketing Research, 24, 393-404.
Lawton T.C and Solomko S. (2005). When being the lowest cost is not enough: Building a successful lowfare airline business model in Asia. Journal of Air Transport Management,11, 355–362.
Lorenzoni, N. & Lewis, B. R. (2004). Service recovery in the airline industry: a cross-cultural comparison of
the attitudes and behaviors of British and Italian front- line personnel. Managing Service Quality, 14 (1),
11-25.
Maute, M. F., & Forrester, W. R., Jr. (1993). The structure and determinants of consumer complaint
intentions and behavior. Journal of Economics Psychology, 14,.219–247.
Morrell, P. (2005). Airlines within airlines: an analysis of US network airline responses to low cost carriers.
Journal of Air Transport Management ,11,303–312.
O’Connell, F. & Willaim, G. (2005). Passenger’s perception of low cost airlines and fill Service carriers: A
case study involving Ryanair, Aer Lingus, Air Asia and Malaysia Airline, Journal of Air Transport
Management, 11, 259-272.
Oliver, R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction
Decisions. Journal of Marketing Research, 17 (Nov), 460-469.
Oliver, R. L. & John E. S. (1989). Consumer perceptions of interpersonal equity and satisfaction in
transactions: a field survey approach. Journal of Marketing, 53 (April), 21–35.
Oliver, R. L (1997). Satisfaction: a behavioral perspective on the consumer. Boston: Irwin McGrawHill.
Petrick, J. F., Tonner, C. & Quinn, C. (2006). The Utilization of Critical Incident Technique to Examine Cruise
Passengers Repurchase Intentions. Journal of Travel Research,44; 273.
Ping, R. A., Jr, (1993). The Effects of Satisfaction and Structural Constraints on Retailer Exiting, Voice,
Loyalty, Opportunism, and Neglect. Journal of Retailing, 69 (3,Fall), 320– 352.
Porter, M. E. (1980). Competitive strategy:Techniques for Analyzing Industries and Competitiors. New York:
Macmillan.
21
Porter, M. E. (1988) Competitive strategy: Techniques for Analyzing Industries and Competitiors. The free
Press New York.
Ranaweera, C. & Prabhu, J. (2003). The influence of satisfaction, trust and switching barriers on customer
retention in a continuous purchasing setting, International Journal of Service Industry Management,
14(3/4), 374-395.
Reichheld, F. F. (1993). Loyalty-Based Management, Harvard Business Review, 71 (March-April), 64-73.
Reichheld, F. F. (1996). The loyalty effect. Boston: Harvard Business School Press.
Reichheld, F. F. (1996). Learning from customer defections, Harvard Business review,74 (2),56-69.
Rosenberg, L. J. & Czepiel J. A. (1984). A Marketing Approach for Customer Retention. Journal of
Consumer Marketing.
Rusbult, C. E. (1980). Commitment and satisfaction in romantic Associations: a test of the investment
model, Journal of Experimental Social Psychology, 16,172-186.
Rust, R.T. & Zahorik, A.J. (1993). Customer satisfaction, customer retention, and market shar. Journal of
Retailing, 69( 2) Summer, 193-215.
Sandvik, K., Gronhaug K., & Lindberg ,F. (1997). Routes to customer retention: the importance of
satisfaction, performance quality, brand reputation and customer Knowledge. American Marketing
Association, Winter, 211-217.
Santos, R. A. (1999). Extension Information Technology Texas Agricultural Extension service, Texas A & M
University College Station, Texas. USA.
Schneider, B. & Bowen, D. (1999). Understanding customer delights and outrage, Sloan Management
Review, Fall, 35-45.
Sharma, N. and Patterson, P.G. (2000). Switching costs, alternative attractiveness and experience as
moderators of relationship commitment in professional consumer services. International Journal of
Service Industry Management,11(5), 470-490.
Sproull, N. (1995). Handbook of Research Methods, 2 nd edn, The Scarecrow Press, London.
Steenkamp, Jan-Benedict E. M., & Baumgartner, H.(1992). The role of optimum stimulation level in
exploratory consumer behavior Journal of Consumer Research, Dec 19 (3), 434-448.
Street, M. (1994). Trainning people to deliver service excellence in British Airways. Managing Service
Quality, 4( 4), 13-6.
Surra, C., Longstreeth, M. (1990). Similarity of outcomes, interdependence and conflict in dating
relationships. Journal of Personality and Social Psychology, 59, 501-16.
Suh, M. (1994), An Examination of the Client-Professional Service Provider Relationship Maintenance from
the Clients' Perspective, unpublished dissertation, Georgia State University
Tam, J. L. (2000). The effects of service quality, perceived value and customer satisfaction on behavioral
Intentions. Journal of Hospitality and Leisure Marketing, 6 (4), 31-41.
Taylor, S. A. & Baker T. L.. (1994). An assessment of the relationship between service quality and
customer satisfaction in the formation of consumers’ purchase intentions. Journal of Retailing, 70 (2),
163–178.
Tax, S., Brown, S. & Chandrashekaran, M. (1998). Customer evaluations of service complaint experiences:
implications for relationship marketing. Journal of Marketing, 62, 60-76.
22
Thibaut, J. W. &. Kelley, H. H. (1959). The Social Psychology of Groups, New York: Wiley.
Turnbull, P.W. & Wilson, D.T. (1989). Developing and protecting profitable customer relationships ””,
Industrial Marketing Management, 18, 233-8.
Valenzuela, F., Pearson, D., Epworth R. (2005). Influence of switching barriers on service recovery
Evaluation. Journal of Services Research, Special Issue, (Dec, 2005), 240- 255.
Vasudevan H., Gaur S. S., & Kumar Shinde R. 2006). Relational switching costs, satisfaction and
commitment. A study in the Indian manufacturing context. Asia Pacific Journal of Marketing and
Logistic, 18( 4), 342-353.
Vincent P. M. (2004). An Examination of the moderators of the service recovery paradox. Ph.D dissertation
of Business Administration, Old Dominion University, May 2004.
Yi, Y. (1990). A critical review of consumer satisfaction, in Zeithaml, V.A. (Ed.), Review of Marketing,
American Marketing Association, Chicago, IL, 68-123.
Zikmund, W. (1997), Business Research Methods, 5th edn, The Dryden Press, U.S.A.
Zeithaml, V. A. (1981). How Consumer Evaluation Processes Differ Between Goods and Services, Marketing
of Services, J. H. Donnelly and W. R. George, eds. Chicago, IL: American Marketing Association, 186190.
Zencaroline (2007), The only Things Change unchanged is change. Los Angeles, United States. Available
at http://Zencaroline.blogspot.com/2007/04/global-model-fit.html (Cited on 20 October 2008)
Zemke R., & Schaff D. (1990). The Service Edge: 101 Companies that Profit from Customer Care, Plume
Books.
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