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TOPCO崇越論文大賞
論文題目：
Does Relationship Matter? Service
Failure, Attribution and Recovery
報名編號： ___M0078___
1
Does Relationship Matter? Service Failure, Attribution and
Recovery
Abstract
Because service failure is inevitable, a better understanding of how relationship
level influences consumer’s response to service failure and recovery is an important
topic for academics and practitioners. This study investigate the relationships among
consumer relationship level, failure attributions (i.e., stability and controllability),
service failure severity, perceived equity, and compensation and customer’s future
behavior in the context of restaurant and online shopping. The study empirically tested
the different consequence of compensation by manipulating the consumer relationship
level. Consumer relationship level motivates consumers to follow different attribution
process to judge severity of service failure and determines consumers’ perceived
equity. Moreover, consumers’ perspective of equity can influence consumers' future
relationship continuity. Findings from two studies (restaurants and online shopping
scenarios) using scenarios from difference industries indicate that when additional
compensation is offered after a service failure, perceived equity was found to increase
regardless of the consumer’s relationship level. Also, customers with low relationship
level are more sensitive to compensation. Furthermore, enhanced equity perception
automatically means that corresponding future relationship continuity is also
enhanced. The results further demonstrate that controllability attributions influence
service failure severity, and service failure severity negatively influence the perceived
equity of the exchange, which mediates the effectiveness of compensation as a
recovery effort. Managerial implications for restaurants and online shopping websites
are then discussed and provided.
Key words: Service failure, Relationship Level, Equity theory, Behavioral intentions.
1. Introduction
In the era of fierce business competition and declining economic and business
conditions, for entrepreneurs, to keep stable revenue and maintain consumer
relationships is important. Unfortunately, since services are intangible, perishable,
heterogeneous, consumed and produced at the same time, zero defect is impossible
(Goodwin and Ross, 1992; Hess, Ganesan and Klein, 2003). Service failure not only
causes loss but also, more seriously, ruins the relationships between consumers and
service providers and has enormous implications on the service providers. In addition,
a few researchers in services marketing suggested that the quality of a
consumer-organization relationship affects consumers’ responses to service failures
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(Kwon and Jang, 2012). Therefore, it is a very important issue for enterprise to
recovery consumer loss and to mend the consumer-organizations relationships in
service failure. It is critical to develop future relationships because only satisfied past
can generate present relationship and then generate future relationship.
Although service providers cannot avoid all service failures, they can learn how to
respond to service failures. This response, known as service recovery, is defined as the
process by which service providers attempt to correct a service failure (Hoffman and
Kelley, 2000). Service recovery creates an exchange in which consumers perceive a
loss due to the service failure and service organizations compensate for the loss with
recovery efforts (Smith, Bolton and Wagner, 1999; Grewal, Roggeveen and Tsiros,
2008). Service providers usually take service recovery actions, such as substantial
pecuniary compensation, discounts or apology, to heal the rift in the broken
relationships which caused by service failure.
The effect of service recovery is influenced by consumers' perceived failure severity,
compensations and perceived equity (Kelley, Hoffman and Davis, 1993). Service
recovery could make up the consumers' perceived loss due to service failure
(Andreassen, 2000), and in consequence consumers perceive equity from the service
recovery (Kwon and Jang, 2012). When consumers perceiving the equity from the
recovery which service providers proposed, the perception will turn the negative
emotions into positive emotions and improve consumer satisfaction (Andreassen, 2000).
Perceived fairness and positive attitude will strengthen consumer satisfaction and
loyalty, further enhance and continue the relationship between consumer and
organizations (Andreassen and Lervik, 1999). In particular, prior literatures rarely
discuss the associations among relationship level, failure severity, perceived equity and
compensation.
With respect to severity, consumers evaluate the fairness of compensation which
offered by failed firm based on their perceived failure severity. If we can understand
causes underpinned severity, we can design appropriate compensation level for
consumers in economic way. Failure severity is affected by attribution. Facing a failure,
consumers attribute service failures to different causes (Folkes, 1984; Hess et al., 2003;
Weiner, 2000). When a failure is attribute to more unstable and more uncontrollable by
a service provider, a consumer would think the failure is less severity.
Besides, prior studies suggest that consumers’ relationship level could influence
consumers’ failure attribution, severity perception and attitude. When a consumer has
high relationship with a service provider, he or she might attribute a service failure into
instability or uncontrollability and vice versa (Vázquez-Casielles, Á lvarez and Martín,
2007). Despite the importance of consumer-organizations relationship, little effort has
been made to investigate the role of consumers' relationship level in service recovery
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process. To clear up the role of the consumer-organization relationship in the service
recovery process, the underlying process of how consumers with relationship level
respond to recovery in different needs to be investigated in this study. Besides
relationship level could affect failure attribution, here, it is also suggested that
relationship level might moderate the effect of compensation on consumers’ perceived
equity after receiving service recovery. For the purpose of clarifying the association
among proposed variables, a conceptual framework is proposed and verify in the study.
Managerial implications will be provided accordingly.
Previous studies have identified several antecedents of consumer recovery
expectations such as attribution of failure (Hess et al., 2003), severity of failure and
service guarantee (Hess et al., 2003), and consumer-perceived quality and consumer
organizational commitment (Kelley and Davis, 1994). Until recently, previous research
on service failure and recovery has focused on how consumers respond to the
failure/recovery efforts (Andreassen, 2000). This study is focused on identifying
different relationship level between the firm and the consumer, and identifying various
factors that affect consumer respond to service recovery. Thus, the objectives of this
study are (1) to bridge the gap in the literature by examining the role of relationship
levels in service recovery process, (2) to investigate the antecedents of consumers’
behavioral intentions after service recovery, and (3) to verify whether perceived equity
plays a mediating role between consumers’ attribution in service failure and future
relationship continuity.
2. Literature Review and Hypotheses
2.1 Service Failure and Recovery
Due to the unique nature of intangibility, inseparability, and variability of service,
service failures are inevitable (Christopher, Kirk and Janis, 2004; Goodwin and Ross,
1992). Nevertheless, no one in the service industry can completely avoid service failure.
Even world-class companies giants such as Apple, GE, Toyota, Nestle, Johnson and
Johnson and Starbucks that follow a service dominant logic perspective can stumble
(Lusch and Vargo, 2006). It is difficult to avoid Service failure in real business
situations. Therefore, service failure and recovery have become important issues for
academics and practitioners.
Service failure is a concrete representation of the gap between customer’s
expectations and their actual experience (Ha and Jang, 2009; Oliver and Swan, 1989). In
a broad sense, service failure is any real or perceived service-related mishap or problem
that occurs during a consumer’s experience with the firm (Maxham III, 2001). Service
failures tend to triggered the negative emotions and behavioral intentions (Gre goire,
Tripp and Legoux, 2009) of consumers. Therefore, service failures could increase
operating costs, as employees’ time and customer remuneration are often required to
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offset negative consequences (Brady, Cronin, Fox and Roehm, 2008). The most serious
problems with service failure are that it may ruin the relationship between the customer
and the organization, and therefore lead negative word of mouth and negative future
behaviors (Ha and Jang, 2009). However, many researchers in the field of services
marketing suggested that the relationship between customer and organizations will
affect customers’ responses to service failures (Berry, 1995; Kelley and Davis, 1994). It
is important to understand how and to what extent relationship strength or quality
affects a customer’s response to a service failure and offset, because strong-relationship
customers are one of the key assets of a firm (Heskett, Sasser and Schlesinger, 1997).
Service recovery is employed to mitigate and repair the damage to a customer that
results from the providers’ failure to deliver a service as designed (Hoffman and Kelley,
2000). Therefore, service recovery is considered as methods include any action that
assists customers who encountered service failure to return to a state of satisfaction
(Andreassen, 2000). Understanding service recovery is relevant for customer retention,
which will affect companies’ profitability (McCollough, Berry, and Yadav 2000). In the
services marketing literature, service failure and recovery encounters are regarded as
critical moments of truth in the relationship between service provider and customers
(Smith and Bolton, 1998). Since that service failures are inevitable (Smith et al.,1999),
it is important to find how to control the frequency of service failure occurrence and
take appropriate service recovery to establish or maintain sustainable relationships with
customers (Wang, Wu, Lin and Wang, 2011). Not only correct service failure, the goal
of service recovery is also to develop long-term relationships with customer (Ha and
Jang, 2009).
2.2 Equity Theory
In the context of services and service recovery, an implicit promise of fairness is
salient because it is often difficult for consumers to evaluate the service before, and
sometimes after, the transaction is made (Maxham and Netemeyer, 2002). As Seiders
and Berry (1998, p. 8) mentioned, service consumers are vulnerable; they know it and
are unlikely to quickly forget or forgive treatment perceived as unfair. Fairness
perceptions are the core of the evaluation of recovery efforts following service failure
(Kwon and Jang, 2012). The perception of fairness is one kind of psychological
terminology that determines consumers’ perception concerning loss and gain in an
exchange relationship with companies.
Several scholars have adopted equity theory to illustrate consumer responses to
service failures and recovery efforts (Ha and Jang, 2009). These studies generally
believe that there are more and more consumers rating failing companies through the
perceived equity of service recovery. Thus, equity theory seems proper to play as a
theoretical rationale for the formation of some key psychological (i.e., failure attribution
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and perceived severity) and behavioral (i.e., future consumer-organization relationship)
outcomes in a service recovery background.
Prior researches in context of service failure and recovery suggest that scholars
should investigate not only the equity theory, but also failure attribution, failure severity,
compensation, because they are closely linked with each other. When a service failure
occurs, consumer tend to engage in causal attributions (Weiner, 2000), and farther
determine the severity of service failure. Perception of the failure severity will affect
consumer perceived equity and consumer expectations for compensation. Finally,
consumer perceived equity will influence consumer-organization relationships
continuity. Based on the framework, we explore the key variables in the following. This
study applies equity theory to predict how consumers’ service recovery expectations
influenced by (1) consumers’ causal attributions regarding the failure, (2) service failure
severity, (3) compensation, and (4) consumers’ intention of relationship continuity.
2.3 Consumer-Organization Relationship
Researchers believe that the relationship between customers and service providers is
an important factor affecting customers' respond to service failure and recovery (Ha and
Jang, 2009). High quality of relationship represents the customers are satisfied with
previous transactions experiences, and expect to the future interaction with the service
providers (Wong and Sohal, 2002). Researchers used numerous new terms to explain
the customer-organizations relationship, such as customer relationships, relationship
strength, tie strength, and relationships level. However, the core concepts of these terms
are essentially derived from relationship quality. Relationship quality gradually
developed into an important issue (Crosby, Evans and Cowles, 1990) of Relationship
Marketing (RM) (Gümmesson, 2002) and gained in importance as a measure of
successful commercial relationship. Relationship quality consist of trust and
commitment (De Wulf et al., 2001; Zhang, Fang, Wei, Ramsey, McCole and Chen,
2011). They are the indicators of relationship quality.
The relationships between customer and organizations reflect the cumulative
perception proposed by equity theory, (Kwon and Jang, 2012). Customers' relationship
level (RL) represents the degree of customers' interaction with the companies, and it
affect customers' attitude toward service failures and recovery efforts. A customer’s
relationship level was established based on positive accumulative transactions
experience. These satisfied interactive experiences generate high levels of cumulative
satisfaction (Smith and Bolton, 1998), and these satisfied customers have higher
intention to maintain long-term relationships with the companies. Bendapudi and Berry
(1997) also assert that previous satisfied interaction between customers and service
providers is a key determinant of customers’ receptivity to relationship maintenance.
Depending on different levels of consumer’s relationship with a service organization,
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customers may attribute a service failure to different attribution types and perceive
different level of failure severity. In addition, customers’ perception of recovery efforts,
compensation, and recovery results, equity, might be different as well, according to
different relationship level.
Previous literature have confirmed that stable and continued customer-organizations
relationships could bring numerous benefits for the enterprise, such as increasing
profitability, enhancing customer loyalty, spreading positive word of mouth, and
improving repatronage. Also, positive customer-organization relationship has been
found to either buffer or enlarge the negative impact of the service failure on a
customer’s future behavioral intentions (Kwon and Jang, 2012). The classical literature
on the maintenance of long-term relationships emphasizes trust and commitment
(Morgan and Hunt, 1994). Trust is defined as customers’ confidence that a firm is
dependable and can be relied on, and it reflects customers' evaluation of past transaction
experience (Crosby et al., 1990). Commitment means that the customers take on a
long-term orientation, based on the desire to maintain the relationship over time (De
Wulf et al., 2001; Morgan and Hunt, 1994).
2.4 Research Framework and Hypotheses
2.4.1 Relationship Level and Causal Attributions
Previous research has shown that customers’ relationship level is an important factor
to affect customers' respond to service failure and recovery (Ha and Jang, 2009). Past
encounters with the organization and quality of prior service performance influence
customers’ causal attributions (Heider, 1958). Thus, customers attribute service failure
to different causes by the consistency of past exchange experiences. Weiner (1980)
suggested that people form attributions by considering three dimensions: stability,
controllability, and responsibility (Wirtz and Mattila, 2004). However, Folkes (1984)
measured the attributions of responsibility and controllability separately and found that
the correlation coefficients of the two variables are up to 0.94. Unsurprising, Weiner
(2000), Tsiros, Mittal and Ross (2004) found the same result, they regard that
responsibility and controllability attributions seem to have a high degree of correlation
and proposed to combine these two conceptions. Therefore, this study examines the
effect of consumers’ relationship level on stability attribution and controllability
attribution. Compare with customers who have low level relationship with the
organizations, customers who have higher expectations of relationship continuity are
more likely to attributed failures to an unstable cause (Vázquez-Casielles, Á lvarez and
Martín, 2007). Heider (1958) and Weiner (2000) agree with the logic.
As to controllability, whether a failure is attributed to controllable or uncontrollable is
influence by relationship level as well. The higher the perception of service quality from
the past, the more likely consumers will attribute to the service organization high levels
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of competence and effort to avoid service failures (Narayandas, 1998). Also,
relationship could be a greater influence on attributions of controllability when the
causes of failures are more ambiguous (Hess et al., 2003). Based on the preceding
discussion, the following hypothesis is posited:
Hypothesis 1: Relationship level is negatively related to stability attributions about
the causes of the failure.
Hypothesis 2: Relationship level is negatively related to controllability attributions
about the causes of the failure.
2.4.2 Causal Attribution and Failure Severity
Customers' failure attribution will affect their behavioral intentions and attitude
toward the company (Folkes, 1984). Bitner (1990) examines the impact of control and
stability attributions on satisfaction and finds that when customers perceive that the firm
has control over the cause, they are more dissatisfied than when they believe the firm
has no control; when customers perceive the cause of the failure is stable, they also are
more dissatisfied than when they believe the failure is rare. Attribution of failure
influences overall customers' evaluation of the magnitude of the service failure and
recovery efforts (Tsiros, Mittal and Ross 2004). The hypothesized relationships between
failure attribution and failure severity are posited as accordingly:
Hypothesis 3: Stability attributions are positively related to severity of service
failure.
Hypothesis 4: Controllability attributions are positively related to severity of service
failure.
2.4.3 Failure Severity, Compensation and Perceived Equity
Swan (1989) verified that companies' recovery efforts can make up for the failure by
increasing the customer's perceptions of customer's outcomes. The failure severity
directly affects customers' outcomes, an element critical for customers evaluating a
transaction. The loss from severe service failure is greater than the loss resulted in a
minor failure, so more substantial recovery is required to restore customers’ perceived
equity. When a company provides the same level of compensation, customers facing
severe failure will have lower perceived equity (Goodwin and Ross, 1992). On the other
hand, equity influences how consumers respond to service recoveries (e.g., DeRuyter
and Wetzels, 2000), such that the effectiveness of recovery efforts may be a function of
equity in the exchange (Oliver and Swan, 1989). Consumers often expect to be
compensated for the harm done to preserve the equity of their relationship with the
company. Although compensation is one type of service recovery, past studies have
confirmed that effective compensation is one of most influential factor to make up for
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the loss of perceived equity and the most common method (Walster, Berscheid and
Walster, 1973). Consequently, we hypothesize:
Hypothesis 5: Failure severity is negatively related to customers’ perceived equity.
Hypothesis 6: Compensation is positively related to customers’ perceived equity.
2.4.4 Relationship Level and Severity
Previous accumulated exchange experience shape customers' expectations toward
service. Yi and La (2004) found that customers’ attitudes toward disconfirmation, such
as service failures, differ depending on their relationships with service providers. When
customers with high relationship level receive the new information which is inconsistent
with their existing beliefs, they will be inclined to ignore it and consider it as a
temporary problem. Customers’ previous expectations remain relatively consistent in
the future. On the contrast, low relationship level customer have low confidence to a
service provider because of lacking past experience which lead to unrealistic and
inaccurate expectations. Therefore, these customers have highly sensitivity for equal
service failure severity. Thus, the low relationship level customer tends to regard service
failure as an important indicator and adjust their previous expectations toward service
provider. Based on the preceding discussion, the following hypotheses are proposed:
Hypothesis 7: Relationship level is negatively related to severity of service failure.
2.4.5 The Moderating Effects of Relationship Level
Basing on a consumer’s relationship level, consumer will show different attitude
toward service failure (Kwong and Jang, 2012). Thus, the results of compensation differ.
After service failure occurs, a customer evaluates whether compensation is enough
restore loss according to relationship level between him/her and his/her service provider.
Customers with high RL are who have had cumulated enough satisfied service
experience that cannot be easily destroyed by accidental factors such as a service failure
and therefore have bigger tolerance zone. These customers believe service provider will
treat them well and thus are not easy to find that they are treated unfairly. Therefore,
Hypothesis 8 is proposed:
Hypothesis 8: Relationship level moderates the relationship between compensation
and perceived equity. Compared to consumer with higher relationship level with
service provider, consumer with lower relationship level are more sensitive to
compensation, that is, compensation has higher effects on perceived equity.
2.4.6 Perceived Equity and Relationship Continuity
Equity theory stresses the view of cumulative perspective to measure fairness
perception of service recovery (Olsen and Johnson, 2003). Equity concerns overall
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value for customers over an entire history of relationship, regardless of duration of a
relationship, which leads to customer satisfaction and customer loyalty (Leone, Rao,
Keller, Luo, McAlister and Srivastava, 2006; Raimondo, Miceli and Costabile, 2008).
From the perspective of equity theory, customers’ intention to relationship continuity
with service providers depend upon whether they perceive themselves as treated fairly;
that is, whether they feel justice was executed (McColl-Kennedy and Sparks, 2003).
Perception of relative fairness is a common predictor of the customer satisfaction and
loyalty (Andreassen and Lervik, 1999) and then influence trust and commitment (Berry,
1991) to build successful relationship. Based on the above discussion, the following
hypothesis is proposed:
Hypothesis 9: Perceived equity is positively related to relationship continuity.
The conceptual model is demonstrated in Fig. 1.
3. Methodology
Figure 1 The Proposed Conceptual Framework
3.1 Research Design and Data Collection
Scenario-based survey in the study where respondents were asked to rate their
attributions, perceived failure severity, perceived equity and future relationship
continuity with the organization in a set scenario. Based on previous studies (Ha and
Jang, 2009), this study developed hypothetical restaurant and online shopping websites
service failure scenarios in this study. It is not only for more in-depth verifying past
researches but also testing our hypothesis in the thesis whether it can be supported in
different industries or not. In the each of the two studies, data was collected from panels
provided by a professional research company in the Taiwan and participants were
randomly assigned to 1 of 4 experimental conditions in the 2×2 between subjects design.
The scenario for each condition described a service encounter during which a service
Dependent variables
Independent variables
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failure and recovery occur. The two manipulated variables were (1) relationship level
(high vs. low), (2) compensation (compensation vs. no compensation).
According to previous studies, restaurant is one of the places where people most
frequently encountered service failures. Any people could have experiences of
encountering service failure in a restaurant. 311 responses were collected and 301 of
them were valid questionnaires, producing a 96.7% effective response rate. Of the 301
respondents, 62 answered questions regarding HRL and additional compensation was
offered, 59 regarding HRL and no additional compensation were offered, 85 answered
questions regarding LRL and additional compensation was offered, and 95 answered
questions regarding LRL and no additional compensation was offered. Among the
respondents, 43.5% were female and 56.5% were male. 92.4% of the respondents had
restaurants’ service failure experiences. Over half of the respondents' ages between 20
to 24 years old (52.9%). More than half of the respondents have a university degree. In
addition, 49.5% of the respondents were students.
In Study 2, 379 responses were collected and 355 of them were valid questionnaires,
producing a 93.6% effective response rate. Of the 355 respondents, 107 answered
questions regarding HRL and additional compensation was offered, 98 regarding HRL
and no additional compensation were offered, 59 answered questions regarding LRL
and additional compensation was offered, and 91 answered questions regarding LRL
and no additional compensation was offered. Among the respondents, 70.1% were
female and 29.9% were male. 71.8% of the respondents had service failure experiences.
Over half of the respondents’ ages between 20 to 24 years old (69.9%), and 15.5% of
the respondents were 24 to 29 years olds. More than half of the respondents have a
university degree (62.5) and 25.6% of the respondents have a master degree. Besides,
most of the respondents were students (74.4%). Based on the results, 37.5% of the
sample shops online once a month, 30.4% quarterly, 16.2% once a week, and 15.9%
semi-annually. Also, we asked respondents’ average expenditure of online shopping,
43.9% of the sample spends average NT.501~1000 every time, and 29.6% spends
average NT.301~500. In additional, we investigated these respondents’ most often
purchased items in online shopping websites.
3.2 Questionnaire Design
The survey questionnaire consisted of six sections: (1) service failure scenario, (2)
failure attribution, (3) failure severity, (4) perceived equity, (5) future relationship
continuity and (6) demographic information. The section began with participant were
asked to read about a service failure and imagined they were in the situation. To help
respondents’ access scenarios, we provided rich details of a failure episode to enable
participants visualize themselves in the situation.
In study 1, the scenario stated that the service context was a meal in a hypothetical,
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moderately priced restaurant in which the participant was dining with a group of friends.
In study 2, the scenario stated that the service context was a pair of moderately priced
shoes, online shopping website which was holding a special sales event for its
anniversary. The restaurant and online shopping websites setting were based on the
different relationship level of the respondents, whose expectations should be well
established. Then, the respondents were asked to fill out the questionnaire. Finally,
respondents were asked to fill out basic personal information. And questionnaire design
and measurement items used in the study are demonstrated in Table 1.
Table 1 Questionnaire design
Constructs No. of Items Sources
Stability 2 Grewal et al. (2008); Wirtz and Mattila (2004)
Controllability 4 Grewal et al., (2008); Mattila and Cranage,
(2005); Wirtz and Mattila, (2004)
Severity 2 Sabharwal and Soch, (2011)
Perceived Equity 2 (Cumulative measures)
2 (Transaction-specific measures)
Kwon and Jang, (2012); Olsen and Johnson,
(2003)
Relationship
Continuity
3 (Trust)
3 (Commitment)
Garbarino and Johnson, (1999); Randalla,
Gravierb and Prybutok, (2011)
3.3 Pre-test
For assess whether the manipulations success, a pre-test invited 30 respondents and
2 experts to conduct pre-test. Each respondent first filled out the questionnaire, and then
the respondents discussed with the researchers issues including how well each scale
captured the construct that it was intended to measure, whether the wording of each
item was clear and understandable. Using there feedback the instrument was revised
further to ensure that the questionnaire was comprehensive, understandable and valid
from these experts’ perspective. As to perceived equity, we wanted to measure it
respectively from cumulative perspective and transaction-specific perspective. But,
according to respondents’ opinions, the two perspectives were too similar to be
confused. The measures were modified. After scenarios and the instrument were
modified, formal test was conducted. The items entering the survey are listed in Table 1.
4. Finding and Discussion
In this section, we present the analysis results of data collected from two studies
analysis, including manipulation check, main effects of variables, and interaction effects
of relationship level. To our surprise, we got the similar results from the two studies in
the thesis. Therefore, we described the findings of two studies in combination.
Additionally, we clearly and deeply discuss the results of data analysis.
4.1 Main Effects of Relationship Level and Compensation
ANOVA was conducted to examine (1) main effects of relationship level on service
attribution and failure severity, and (2) main effects of compensation on failure severity.
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The overall ANOVA results in both studies were presented in Table 2 and Table 3. We
run an ANOVA with the stability as the dependent variable, and one with controllability
as the other dependent variable. Stability attribution composes of two items and
controllability composes of four items. We find a significant effect of relationship level
on both dependent variables. The higher the relationship level, the lower the level of
stability attribution (Study1: MSTB-HRL = 3.0909 vs. MSTB-LRL = 3.3667, F (1, 300) =
8.951, p < .01 Study 2: MSTB-HRL = 3.1756 vs. MSTB-LRL = 3.7833, F (1, 354) = 56.924, p
< .001) and the lower the level of controllability attribution (Study1: MCON-HRL = 4.2376
vs. MCON-LRL = 4.3833, F (1, 300) = 4.481, p < .05; Study 2: MCON-HRL = 4.2293 vs.
MCON-LRL = 4.3933, F (1, 354) = 7.828, p < .01). Therefore, H1 and H2 are supported.
As shown in Table 2, with respect to the main effect of relationship level on failure
severity, the result indicates that consumers’ relationship level can’t influence their
perception of failure severity significantly. Thus, H7 was not supported in both studies.
In Table 3, the main effect of compensation on failure severity was also examined.
Besides, the ANOVA results also reveal that the main effects of compensation on equity
perception is significant (Study1: MCOM-HRL = 3.9355 vs. MNCOM-HRL = 3.4703;
MCOM-LRL = 3.9382 vs. MNCOM-LRL = 3.1526, F (1, 300) = 61.126, p < .001; Study 2:
MCOM-HRL = 3.6238 vs. MNCOM-HRL = 2.9515; MCOM-LRL = 3.6398 vs. MNCOM-LRL =
2.4560, F (1, 354) = 153.292, p < .001). Consumer will have higher equity perception
when consumers are compensated for the service failure than that when they are not,
supporting H6.
4.2 Interaction Effects of Relationship Level
In order to examine the interaction effect of relationship level on the relationship
between compensation and perceived equity, ANOVA was used. As presented in Table 3,
there is a significant interaction effect of compensation and relationship level on
perceived equity (Study 1: F = 4.013, p < .046; Study 2: F = 11.641, p < .001). Thus, H8
was supported. For further analyzing the role of relationship level, we plotted two linear
regression lines of the high relationship level (HRL) and low relationship level groups
(LRL) in Fig.2 and Fig. 3.
Fig. 2 and Fig. 3 demonstrate for both HRL and LRL groups that perceived equity are
higher when a company provides compensation. The results provide important evidence
that offering compensation is effective in improving perceived equity regardless of a
consumers’ relationship level. In addition, Fig. 2and Fig. 3 also shows that no matter
that compensation is provided or not, HRL group perceives higher equity than LRL
group does. Establishing and improving high relationship levels with customers is quite
important for service providers. Therefore, besides providing compensation after service
failure, retaining high relationship level is also an effective important way to enhance
consumers’ perceived equity.
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Moreover, it is found that when there is no additional compensation following a
service failure, the difference of perceived equity levels between the HRL group and
LRL group was bigger than that when compensation is provided. As additional
compensation was offered, the gap between HRL group and LRL group dramatically
diminished. The slope of the LRL regression line was steeper than that of the HRL line,
indicating that perceived equity increased more rapidly in the LRL group as
compensation was offered. When a consumer has a LRL with the service provider,
offering compensation (vs. offering nothing) significantly enhance perceived equity.
LRL group are more sensitive to compensation offering. LRL customers are much
sensitive to compensation.
Table 2 ANOVA results of H1, H2 and H7 in Study 1 and Study2
Study 1
Sources SS df MS F p
DV: Stability
RL 5.502 1 5.502 8.951 .003**
Error 183.800 299 .615
Total 189.302 300
DV: Controllability
RL 1.537 1 1.537 4.481 .035*
Error 102.531 299 .343
Total 104.068 300
DV: Failure severity
RL .032 1 .032 .040 .842
Error 236.385 299 .791
Total 236.417 300
Study 2
Sources SS df MS F p
DV: Stability
RL 31.991 1 31.991 56.924 .000***
Error 198.386 353 .562
Total 230.377 354
DV: Controllability
RL 2.332 1 2.332 7.828 .005**
Error 105.143 353 .298
Total 107.474 354
DV: Failure severity
RL .628 1 .628 1.057 .305
Error 209.630 353 .594
Total 210.258 354
Note: IV= Independent variable, DV= Dependent variable. ***: p < 0.001.
4.3 Severity, Perceived Equity and Future Behavioral Intention
To test (1) main effects of service attribution on failure severity, (2) main effects of
failure severity, and (3) main effects of perceived equity on future behavioral intention,
regression analysis was adopted. As presented in Table 4, the results show that
controllability attribution significantly and positively influences failure severity at
p< .001. Specifically, consumer thinks a failure is more severe, (Study 1: β = .619, t =
7.778, p < .001; Study 2: β = .623, t = 9.085, p < .001) when the failure is ascribed to
14
controllable cause, which supports H4. Table 4 also revealed that failure severity
significantly influences equity perception at p < .05. When a customer thinks a service
failure is less sever to him/her, his or her perception equity after failure recovery will be
higher (Study 1: β = -.099, t = -2.007, p < .05; Study 2: β = -.359, t = -6.524, p < .001).
H5 is therefore supported. In addition, equity perception significantly influences
consumers’ willingness for future relationship continuity with a service provider at
p<.001. Specifically, trust and commitment were significantly higher (Study 1: β = .193,
t = 5.529 vs. β = .725, t = 11.891, p < .001; Study 2: β = .182, t = 6.306 vs. β = .666, t =
14.887, p < .001) when compensation was perceived as enough to restore the equity of
the relationship than when it was not, supporting H9. The higher equity perceived a
customer, the stronger future relationship the customer wants to maintain.
Figure 2 Moderating effects of relationship
level on the relationship between
compensation and perceived equity in
study 1
Figure 3 Moderating effects of relationship
level on the relationship between
compensation and perceived equity in
study 2
Table 3 ANOVA results of H6 and H8 in Study 1 and Study 2
Study 1
Sources SS df MS F p
DV: Perceived equity
RL (Relationship level) 1.792 1 1.792 3.876 .050*
C (Compensation) 28.253 1 28.253 61.126 .000***
C*RL 1.855 1 1.855 4.013 .046*
Error 137.278 297 .462
Total 173.984 300
Study 2
Sources SS df MS F p
DV: Perceived equity
RL 4.841 1 4.841 10.230 .002***
C 72.546 1 72.546 153.292 .000***
C*RL 5.509 1 5.509 11.641 .001***
Error 166.112 351 .473
Total 251.950 354
Note: IV= Independent variable, DV= Dependent variable. ***: p < 0.001.
3.1526
3.9382
3.4703
3.9355
2.5
3
3.5
4
4.5
No
Compensation
Compensation
Per
ceiv
ed E
qu
ity
LRL
HRL
2.456
3.6398
2.9515
3.6238
2
2.5
3
3.5
4
No
Compensation
Compensation
Per
ceiv
ed E
qu
ity
LRL
HRL
15
Table 4 Regression results of Hypotheses 3 and 4 in Study 1 and Study 2
Hypotheses IV → DV Study 1 Study 2
β S.E. t-value β S.E. t-value
H3 Stability → failure
severity .017 .059 .280
*** .039 .047 .834
***
H4 controllability →
failure severity .619 .080 7.778
*** .623 .069 9.085
***
Study 1: R2 = .169, adj. R
2 = .164, F = 30.368
***; Study 2: R
2 = .209, adj. R
2 = .205, F = 46.554
***
H5 failure severity →
Perceived equity -.099 .049 -2.007
* -.359 .055 -6.524
***
Study 1: R2 = .013, adj. R
2 = .010, F = 4.029
*; Study 2: R
2 = .108, adj. R
2 = .105, F = 42.567
***
H9 Perceived equity →
Relationship
continuity (Trust)
.193 .035 5.529***
.182 .029 6.306***
Study 1: R2 = .093, adj. R
2 = .090, F = 30.575
***; Study 2: R
2 = .108, adj. R
2 = .105, F = 42.567
***
H9 Perceived equity →
Relationship
continuity
(Commitment)
.725 .061 11.891***
.666 .045 14.887***
Study 1: R2 = .321, adj. R
2 = 319, F = 141.394
***; Study 2: R
2 = .386, adj. R
2 = .384, F = 221.623
***
Note: IV= Independent variable, DV= Dependent variable. ***: p < 0.001.
5. Discussion and Conclusions
The study sheds some light into the role of the relationships among relationship level,
service failure attributions, failure severity, consumers’ perceived equity, compensation,
and relationship continuity under service recovery. In this study, ANOVA and regression
analysis were chosen to exam the proposed conceptual model and hypotheses. The
scenario design and manipulation were success. Respondents could accurately
distinguish their relationship level with their service provider in different scenarios. It
lends sufficient support to deeming the results and acceptable representation of the
hypothesized constructed. As predicted, we got the same results from both studies of
restaurant scenario and online shopping websites scenario. In other words, it means that
the proposed conceptual model and the hypotheses in this study can be widely and
stably applied to different industries. Seven out of nine hypotheses of the proposed
model were acceptable at statistical significance levels (p < .05) (see Tab. 5).
Table 5 Summary of Hypothesis Test Results
Hypothesis Relationship Conclusion
Study 1 Study 2
H1 RL → Stab Supported Supported
H2 RL → Ctrl Supported Supported
H3 Stab → Sever Not Supported Not Supported
H4 Control → Sever Supported Supported
H5 Sever → PE Supported Supported
H6 Comp → PE Supported Supported
H7 RL → Sever Not Supported Not Supported
H8 RL → Comp * PE Supported Supported
H9 PE → RC Supported Supported
16
Service encounters involve human endeavors and therefore service failures often
occur. With the widespread use of service recovery as a retention strategy (Ha and Jang,
2009), how effective compensation turns complaining customers into satisfied and loyal
customers has received increased attention from practitioners and researchers. This
study contributes to literature by providing a framework wherein not only compensation
and perceived equity influence consumer-organization future relationship/future
relationship continuity (i.e., repurchase intention and word of mouth), but also
consumers’ relationship level play an important role. This study has first deeply
investigated the role of consumers’ relationship level in service failure and recovery
situation. Consumers’ perceived equity on service recovery is not only depending upon
compensations but also upon the perceived severity of the service failure and failure
attribution.
As to relationship level, a large part of previous service failure related literatures
focused on the impact of cumulative satisfaction on customer future behavioral
intentions. Fewer studies pay attention to the consumer-organization interaction history
in service recovery contexts. This study first tries to measure cumulative satisfaction by
consumers’ relationship level. Furthermore, we explored the associations among
customers’ relationship level with a service provider, service failure attribution, failure
severity, perceived equity and future relationship continuity.
To verify the proposed hypotheses, experimental design was employed. To create
generalization of the proposed model, two studies were conducted in restaurant and
online shopping context. Basing on past literatures, scenarios in two studies and
measurements were designed. The questionnaire composed 5 constructs, 2-item
measure for stability attribution, 4-item for controllability, 2-item for consumers’
perceived severity, 4-item for perceived equity and 6-item for consumer-organization
relationship continuity (3-item for trust and 3-item for commitment). Totally we
collected 656 samples to exam the hypotheses. The results of manipulation were success
and most of respondents regard that designed scenario could happen in the in real life.
Results in both studies in this thesis indicated that customers’ relationship level could
affect his/her determination of service failure and recovery encounters. Besides, he/she
evaluates future relationship with service providers based on cumulative experience.
That is what prior studies never done. It further helps service providers to know the
impact of consumers’ relationship level on consumers’ reactions of service failure with
the recovery process.
This study makes both academic and practical contributions. By providing a
theoretical framework, the study adds to our understanding of how relationship level
affects consumers’ attribution behavior about service failures and perceived equity.
According to the result of ANOVA and regression analysis, it is found significant main
effects of relationship level and compensation and two-way interaction effect of above
17
two variables in restaurant context (Study 1). The results also indicate that relationship
level influence failure attribution and then failure severity, perceived equity and
consumer-organization future relationship. Besides, relationship level affects the effects
of compensation on perceived equity. To further generalize the result we ran another
study in an online shopping context and the result support finding in Study 1. In both
studies, seven of nine proposed hypotheses were supported (H3 and H7 were not
supported). That means our hypothetical model can be applied to different contexts.
The results inferred that relationship level can affect consumers’ attributed behavior
and mitigate consumers’ negative reactions to service failure. Consumers with HRL
showed higher perceived equity in both study. Also, when there is no compensation
provided after a service failure, HRL consumer perceived equity is higher than that of
LRL consumers. It proved that maintain closed contact and relationship with consumers
could bring more good than disadvantages. Service providers should dedicate to
develop and maintain relationship with their consumers for broadens their consumer’
service failure tolerance and enhance the mitigated effects of service failures. However,
we cannot expect that HRL consumers’ future behavioral intention will raise rapidly
because frequent compensations mean frequent failure occurrences. HRL consumers
expect for high service quality, therefore too much failure will make them feel betrayed.
Service providers should know tolerance is not unlimited and they should endeavor to
improve service quality. Also, they should not view service failures as a good chance to
turn a LRL consumer into a HRL one. Actively upgrading service quality to raise their
consumers' relationship level with them is the only key to success. However, we cannot
deny RL plays an important role in service failure and recovery process. Thus, we
recommend service providers to train their employees to respect service recovery and
the importance of consumer-organization relationship maintain.
Also there is an interaction effect of relationship levels and compensation on
perceived equity. For LRL consumers, compensation offering increase consumers
perceived equity. Compensation contributes higher increasing in perceived equity
compared to HRL consumers. Therefore, offering compensation is more effective to for
LRL consumers to improve their perceived equity of a service recovery.
This thesis differ from past researches uses equity theory instead of justice theory to
evaluate the fairness of recovery efforts from a cumulative perspective. Equity theory
not only considers the fairness of the recovery effort provided, but also considers the
entire history of shared interactions between company and customer. And the results of
main effects of consumers’ perceived equity on their future behavior. Analysis results
point out the possibility that the customer-organization relationship level varies
depending compensation. Additional compensations offered for service failure make up
damaged consumers’ perception of equity, which is consistent to prior studies (Kwon
and Jang, 2012).
18
Tangible compensation is efficient in raising perceived equity of service recovery
process especially for the consumers with LRL because the existence of the interaction
effects of relationship level and compensation. Managers should learn how to make
good use of compensation tools (i.e., monetary recovery, discounts) to catch these LRL
customers and then turn the LRL consumers to HRL one. Moreover, prior literature
indicated that managers should remember that tangible compensation is more efficient
than oral apology.
In addition, making good use of technological tools to assistant enterprises’ customer
relationship management is very important, such as customer relationship management
(CRM) system which could be used to distinguish consumers’ relationship level
efficiently. Then, service provider can train their employee to adopt different service
recovery strategy to raise consumers’ perceived equity by well using CRM.
Beyond the theoretical implications and managerial implications, there are certain
limitations to the thesis that point directions for future research. First, our research is
limited to scenario-based studies which may evoke more cognitively based reposes than
the emotional reactions a person experiences when in an actual service experience.
Therefore, to examine the validity of the findings future research should examine
customers’ actual behaviors given an identical relationship level and compensation
manipulation. Second, we only examined the distributive dimension of equity in the
study, because the lack of both transaction-specific and cumulative measures of equity
perception regarding procedure and interactional dimensions. It is suggested that future
research to develop constructs for both transaction-specific and cumulative perceived
equity regarding the procedural and interactional dimensions. Finally, we focus on the
presence or absence of compensation and operationalize its presence in each study.
Further research should explicitly examine the role of levels of compensation (e.g., 10,
20, 50 and 100 percent) and types of compensation (e.g., monetary, no- monetary).
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