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Exploration of lead factors affectingservice recoveryWen-Bao Lin aa Graduate Institute of Technology Management , NationalKaohsiung Normal University , Kaohsiung City, Taiwan, Republic ofChinaPublished online: 28 Oct 2009.
To cite this article: Wen-Bao Lin (2009) Exploration of lead factors affecting service recovery, TheService Industries Journal, 29:11, 1529-1546, DOI: 10.1080/02642060902793342
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Exploration of lead factors affecting service recovery
Wen-Bao Lin�
Graduate Institute of Technology Management, National Kaohsiung Normal University, KaohsiungCity, Taiwan, Republic of China
(Received 20 June 2007; final version received 21 September 2007)
This research attempts to explore the influence of empowerment on service recoveryfrom the viewpoint of managers and also to probe into the possible differences in theadoption of service recovery strategies in different corporate cultures. Linearmultivariate data analysis and nonlinear fuzzy neural network are combined toanalyze data and verify the proposed hypotheses. Through the investigation intoChinese and Western food chain stores, it is shown that the more empoweredemployees will adopt more active failure recovery strategies; and tougher corporatecultures tend to have passive service recovery strategies, whereas minor corporatecultures tend to have active service recovery strategies. Customer relationshipinvolvement reveals positive influences on the adoption of recovery strategies. Thecharacteristic of this research is that, on the one hand, through the empiricalconclusion of the nonlinear fuzzy neural network model, we not only measure therelationship among the variables more precisely, but also have less restrictiveconditions. Also, according to organizational management factors, this researchproposes and examines the influencing factors affecting service recovery strategies. Itexplores the responses to service recovery from the viewpoint of internal preventionin the organization, which is different from past research that focussed mostly uponconsumers’ views.
Keywords: empowerment; service recovery; corporate culture
Introduction
In a time with a high degree of industry work division and micro-profit, aggressively
developing new customers is one of the ways for firms to expand new markets. In addition,
in order to maintain old customers’ loyalty, reducing the probability of service failure is
the feasible direction. However, when there is any service failure, the kinds of service
recovery tend to affect customers’ after-sale satisfaction and loyalty (Cranage & Sujan,
2004; Spreng, Harrell, & Mackoy, 1995). Cranage and Mattila (2005) indicated that
when there was service failure and the front-line service personnel did not effectively
deal with or compensate for the loss due to the failure, the customers’ dissatisfaction
would be increased. Besides, nowadays when the output value of the service industry is
increasing and becoming more important, the issues of service quality will reflect
before and in the service. The success or failure of service providers in the service
process has become more and more important in a time when consumer consciousness
has greatly increased. In other words, firms have relatively valued the recovery and
response of ‘service failure’.
ISSN 0264-2069 print/ISSN 1743-9507 online
# 2009 Taylor & Francis
DOI: 10.1080/02642060902793342
http://www.informaworld.com
�Email: [email protected]
The Service Industries Journal
Vol. 29, No. 11, November 2009, 1529–1546
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Generally, the past studies related to ‘service failure’ showed the following directions:
(1) Emphasizing the selection and application of recovery strategies after service
failure. For example, the empirical study of Weun, Beatty and Jones (2004) indi-
cated that the degrees of service failure significantly influenced customers’ satis-
faction, trust and commitment. Bitner, Booms and Tetreault (1990), Kelley,
Hoffman and Davis (1993) and Spreng et al. (1995) argued that the most com-
monly used service recovery measures included apology, assistance and compen-
sation. The study of Tax, Brown and Chandrashekaran (1998) suggested
evaluating whether service recovery allowed customers to have fair cognition
toward the service recovery from three constructs: outcome fairness, procedural
fairness and interactional fairness. Mattila (2001) investigated different effects
of service failure recovery in different service industries, such as the effective
service recovery in a hair salon: apology and intangible compensation had a posi-
tive influence on customers’ recovery satisfaction and loyalty.
(2) Exploring the types of service failure and compensation and the reasons of for-
mation. For example, service failure could be divided into process and outcome
failure. The former referred to the service errors during the process of service
delivery, whereas the latter meant that the customers were not satisfied after
receiving the service. The reason might be in that, on the one hand, they did not
have the service they deserved and, on the other hand, the companies did not
carry out the commitment of service guarantee conditions (Hoffman, Kelley, &
Rotalsky, 1995; Smith, Bolton, & Wanger, 1999).
(3) Many Previous studies probed into the relationship between service recovery and
cognitive fairness. For instance, the study of Tax et al. (1998) found that there was
a positive correlation among distributive justice, procedural justice, interactive
justice and service compensation satisfaction. Mattila and Patterson (2004) have
also compared the influence of cultural factors on the difference of fairness and
satisfaction cognition of the consumers in East Asian countries and America
during the process of service recovery. The empirical result indicated that compen-
sation resulted in the fairness cognition of American consumers.
(4) After combining the past related studies, we found that most of them recognized
that the level of service failure would positively and significantly affect the oper-
ation of future service recovery strategies from the process or after-service views
(Forbes & Kelley, 2005; Swanson & Kelley, 2001). This research focused on three
constructs. We first explored the influence of empowerment on the methods of
service recovery from the employees’ view; second, we probed into the possible
differences of service recovery measures of the managers with different cultural
backgrounds from the standpoint of corporate culture; third, this research
studied the influence of the interaction with customers on service recovery
measures from the view of relationship marketing.
Literature review
Empowerment included power authorization and the function of making employees
become capable (Barner, 1994). Although the scholars’ definitions of empowerment
were not necessarily the same, we could generalize them into two views: the first was
the internal viewpoint formed in an individual’s mental aspect. For instance, Conger
(1989) suggested that empowerment was the act of strengthening an individual’s con-
sciousness of self-efficacy. In other words, it allowed the employees to be capable
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instead of simply participating in the process of authorization; the second viewpoint was to
stimulate training. On one hand, it empowered the ability from external to internal aspects
and on the other hand, it increased individual’s internal motivation. In other words,
through external incentives and information, it enhanced employees’ capacities and
increased their willingness to contribute to the organization. However, empowerment
should also comply with other managerial mechanisms to fulfill the effect. For
example, Bowen and Lawler (1995) suggested that empowerment could increase the
employees’ participation and sharing of power and information with employees. With a
proper return system, it stimulated hard-working employees and further increased their
willingness to serve the customers and provided service quality, which could effectively
retain the customers. Bowen and Lawler (1992) proposed four different ranks of empow-
erment. The highest rank of empowerment allowed the most basic employees to have a
high degree of involvement and undertake corporate performance. The empirical study
of Carson, Carson, and William (1998) revealed that there was a positive correlation
between the employees’ work attitude and empowerment. When service employees had
service failure and they had the power and knowledge to compensate the unsatisfied
customers, they would satisfy and retain the customers (Bowen & Lawler, 1992, 1995).
Specifically speaking, the empowered employees must recognize their capacities for fin-
ishing the job. Besides, the employees must believe that it was meaningful to fulfill the
goal. In addition, the empowered employees must have the autonomy to decide how to
accomplish the work. Finally, the employees must recognize that the act was influential
or they could have alternative acts to finish the job (Spreitzer, 1995). Miller, Craighead
and Karwan (2000) indicated that there was a positive correlation between the empower-
ment degrees for basic employees and service failure recovery. In other words, when
executives empowered the first-line employees, they would reduce the dealing time of
service failure which would indirectly influence the effect of service failure recovery.
H1: More empowered employees tend to have more active failure recovery strategies.
The past studies probing into the influence of cultural value differences on service
failure recovery strategies mostly focused on the exploration of the consumers’ different
cultural backgrounds. For example, Wong (2004) investigated the consumers in America,
Singapore and Australia and the influences of different cultural values on service recovery
measures in different service failure situations. The empirical finding showed that for the
consumers in Singapore, apology could increase their satisfaction. The specific measures
such as compensation could strengthen the evaluation effect of service contact for the con-
sumers in these three countries. Mattila and Patterson (2004) compared the consumers
with eastern and western cultural values and empirically demonstrated that the consumers
with different cultures had different cognition toward the attributes of service failure. Kim,
Kim, Im and Shin (2003) also demonstrated that the reason why consumers had a negative
attitude toward service might be related to culture. This research tried to explore the oper-
ation affecting service failure recovery strategies from the views of the managers with
different cultural backgrounds. As to the types of corporate culture, there were several
different classification criteria in the past and many scholars had also studied the corre-
lation between corporate culture and performance or customer satisfaction. Most of
them agreed that there was a significant relationship between them Conrad, Brown and
Harmon, 1997 and Wilfred, Dobni, and Harel, 1998. Although different criteria and
results were considered for cultural classification, there were major and minor cultures
according to the corporate requirements on the employees’ consistent behavior, attitude,
values, target achievement and immediateness (Robbins, 1994). When the past studies
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investigated the leadership style of the firms in Taiwan, they have suggested that most of
the corporate leaders were powerful and had boss-centered leadership (Bond & Hwang,
1986; Cheng, 2005). In other words, single-whip leadership was generally seen in
Chinese firms. Since the patriarchal idea of traditional family was still the leaders’
behavior style, authority and doctrinal behavior existed in the interaction consciously or
unconsciously. Powerful behavior treated the accomplishment of group performance as
the goal and created shared values, and so strategic vision was the necessary element that
usually could be managed through rituals, paragons and rules. Besides, in major culture, a
few people controlled decision-making rights, resource share and reward power. The
standardization and consistency of shared behavior were the requirements of this culture.
On the contrary, in minor cultural environments, employees could have more decision-
making and measurement rights for self-efficacy. Therefore, managers of major cultures
were more likely to interfere with the timing of the basic employees’ service recovery
strategies resulting even in an air of laziness and irresponsibility. Thus, when employees
encountered service failure and were required to react immediately, they would deal with
it passively. Hence, we have established the following hypotheses:
H2: Types of corporate culture are related to the adoption of service recovery strategies.
H2-1: Major corporate culture tends to have passive service recovery strategies.
H2-2: Minor corporate culture tends to have active service recovery strategies.
Czepiel, Solomon, Surprenant, and Gutman (1985) and Bitner et al. (1990) indicated
that service contact was the interaction between customers and the service delivery
system, which includes the targets such as service personnel, substantial facilities and
other tangible factors. It was not simply the contact with the service providers; it included
the overall interactive feeling and evaluation perceived by customers during the process of
service contact. In addition, Meuter, Ostrom, Roundtree, and Bitner (2000) studied the
situations of service interaction between service firms and customers by self-service
technologies. However, for the service industry companies having more frequent
contact with the customers, how to maintain long-term and positive interaction with
customers would be more important than the operation of intermediary tool of service
contact. Besides, providing complete service to customers and interacting with them
closely were not only the important issues, but also the critical factors avoiding the loss
of customers (Eriksson & Vaghult, 2000).
Crosby, Evans and Cowles (1990) and Lagace, Dahlstrom, and Gassenhheimer
(1991) suggested that the degree of interaction relationship establishment between the
employees in the firms and customers would affect the quality of the two parties’
relationship and corporate operational performance. According to Barnes’ (1997) sug-
gestion, there was positive correlation between the degree of intimacy in the relationship
and two-way communication frequency among the employees, and the former was also
closely connected with trust, sympathy and interactive relationship of the relationship
targets perceived. These elements were generally connected with the core products
and services of high-risk involvement. Thus, in the situations without frequent personnel
contact, a high degree of involvement or high emotional factors, the establishment
of intimate customer relationship would be considerably challenging. The necessary
condition of intimacy was two-way instead of ‘one-way’ communication. Therefore,
we could infer that when the degrees of corporate managerial involvement on service
personnel were higher, the willingness to increase the intimacy with the customers
would be enhanced due to the consideration of job stress or performance or the drive
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of corporate major culture. The depth of ‘interactive contact’ between the customers
and firms was the strategic index to evaluate the intensity of customer relationship
involvement (Wyner, 1998).
The positive relationship between firms and customers could strengthen the customers’
loyalty and repurchase behavior. Besides, when the rivals intended to win over the
customers, they must spend time constructing trust and commitment for the consumers
(Priluck, 2003). Sin, Tse, Yau, Lee, and Chow (2002) also argued that relationship
marketing had a positive influence on corporate sales growth and customer retention. In
a time of micro-profit, strengthening the relationship with the customers should not
only be revealed in the normal service stage without failure, but also at the stage of
service failure, the firms should further enhance the relationship with the customers
since the cost of developing new consumers is higher than that of retaining old ones.
The idea of ‘intimacy’ was significant for marketing personnel. When managers had a
higher degree of involvement, strengthening customer relationship tended to become one
of the principles followed by the employees in the service industry due to the consideration
of accomplishment of customer satisfaction or fulfilling the managers’ directions. In addition,
in terms of relationship marketing, when firms had a closer relationship with the customers,
they tended to manage more active recovery strategies in the situations with service failure
(Lin, 2006). Based on the above discussion, we could establish the following hypothesis.
H3: Customer relationship involvement reveals a positive influence on the adoption ofrecovery strategies.
Research method
Research structure
Through the above exploration and inference, we can establish the research framework, as
shown in Figure 1.
Questionnaire design
The design of the questionnaire content in this research was based on the findings of
related studies with the research purpose and framework modified. Through the partici-
pation of the managerial cadre in one Chinese and one Western food chain store in the
pretest, the researcher modified the unclear meaning or terms in the questionnaire and
further verified the content validity to finish the draft.
According to the research framework, the questionnaire content was divided into
five sections. The first four sections were, respectively, four constructs in this research
and the fifth section contained the basic information of the firms.
Figure 1. Research framework.
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Definition and assessment of variables
The definitions of the major variables in this research were given below and each was
measured by a 7-point Likert scale.
Types of corporate culture
According to Robbins’ (1994, 2002) view, we basically measured if the firms required
the employees’ attitude and behavior with regard to group performance orientation,
innovation activeness, human orientation and organizational stability.
Service recovery strategies
According to the views of Carson et al. (1998) and Kelley et al. (1993), service recovery
strategy meant the recovery measures undertaken when there was service failure during
the process of serving the customers, such as activeness, apology, active measures of
rapid response, explanation for the failure to the consumers, compensation and providing
free service, and passive measures such as products, returns, discounts and coupons.
Empowerment
According to Spreitzer’s (1995) operational definition of the empowerment cognition
model, this research allocated empowerment into four constructs: (1) meaning: it
meant the value of job targets or goals and it was used to evaluate the standard and
ideas of an individual; (2) competence: it could also be called self-efficacy and it
meant that an individual believed that he was capable of executing the skills needed
in the activity; (3) self-determination: it meant the employees’ autonomy rights to
develop and maintain job behavior and process; (4) impact: it meant an individual’s
influence at work on managerial or operational results.
Customer relationship involvement
According to the views of Bitner et al. (1990), Crosby et al. (1990) and Wyner (1998), it
meant the degree of maintenance of the customer relationship during the interaction
between firms and customers.
Sampling method and sample analysis
The population of this research was composed of Chinese and Western food chain stores
having frequent contact with their customers. The researcher adopted convenience sampling
and selected two chain stores each in the cities of Taipei, Taichung and Kaohsiung. There
were 12 stores in total and the researcher distributed 20 questionnaires to each store (240
copies in total). By adopting various helpful methods for soliciting valid questionnaires,
such as giving away a gift or asking for the help from acquaintances, we collected 107
valid returns at last, and the return rate was about 44.58%. The respondents of the question-
naire were mostly the basic managerial cadre. Table 1 showed the characteristics of the valid
samples. The establishment years of the firms were mostly within 5 years.
In addition, in order to ensure that the questionnaires of return samples could represent the
population of the whole sample, this research tested the representation of data between the
population and samples by two methods. The corporate basic characteristics were first used
to see if there was any significant difference between the returned samples and unreturned
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samples, as shown in Table 2. Subsequently, the researcher examined whether there was
any significant difference between the return samples in the previous and latter periods by
the same corporate basic characteristics, as shown in Table 3. The result showed that in
terms of employees’ service years, capital and years of establishment, with a 5% significance
level, two clusters did not show significant difference. Thus, the return questionnaires in this
research revealed a certain degree of representation for the entire population.
Data analysis method
Factor analysis
In order to reduce the constructs, this research performed factor analysis on empowerment,
customer relationship involvement, corporate culture types and service recovery strat-
egies, which were all based on principal component factory analysis. The researcher
further rotated the analytical results by varimax to extract principal construct factors.
The extracted eigenvalue was more than 1, factor loading was more than 0.5 and the differ-
ence between the factors was more than 0.3 (Hair, Anderson, Tatham, & Black, 1998).
Reliability and validity analysis
According to the view of Nunnally (1978), reliability over 0.7 meant relatively high
reliability; Cuieford (1965) also indicated that Cronbach’s a more than 0.7 implied high
Table 1. Basic characteristics of valid samples.
Characteristics CategoriesNumber of returned
questionnaires Percentage
Industries Chinese food chain store 43 40.18Western food chain store 64 59.82
Years of establishment Less than (including) 5years
75 70.09
Over 5 years 32 29.91Employees’ service
yearsLess than (including) 5
years69 64.48
Over 5 years 38 35.52
Table 2. Test of homogeneity of corporate basic characteristics (returned and unreturned samples).
Test of homogeneity Test methods Test value Significance
Years of establishment Chi-square likelihood test Likelihood ratio p = 0.45Employees’ service years t-Test of independent samples t = 0.37 p = 0.69Capital t-Test of independent samples t = 0.45 p = 0.51
Table 3. Test of homogeneity of corporate basic characteristics (returned samples in the previousperiod and unreturned samples in the later period).
Test of homogeneity Test methods Test value Significance
Years of establishment Chi-square likelihood test Likelihood ratio p = 0.55Employees’ service years t-Test of independent samples t = 0.42 p = 0.68Capital t-Test of independent samples t = 0.56 p = 0.49
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reliability. When it was less than 0.35, it should be rejected. There was a certain degree of
reliability since it was at least 0.7 in each construct in this research. With regard to
validity, it was expected that test content validity could be observed from related
literatures cited and factor loading. With regard to construct validity, we followed
Kerlinger’s (1986) item-total correlation method. In other words, we assumed that when
the total was valid, item and total coefficients were the measurement indexes of construct
validity. Item-total coefficients of the factors of each construct in this research were more
than 0.5, indicating a certain degree of construct validity (Table 4).
Fuzzy neural network model
Framework of fuzzy neural network. This research tried to fuzzy the figures collected by
the technique of fuzzy neural networks and transformed them into fuzzy quantities through
membership and fuzzy subsets. Thus, we could transform the internal relationship (pre-
cision mathematical model) between the original input and output figures and input and
output of the system into a kind of corresponding fuzzy relationship expressed by a con-
ditional clause: if (fuzzy subset of input language variate) and then (fuzzy subset of output
language variate) which fulfilled the fuzzy model of the system. In addition, language
variate could be divided into different levels: such as low, medium and high variates
and an even more specific one to reach the precise effect. In the fuzzy system, ‘Fuzzily’-.
‘Fuzzy inference’ -. ‘Fuzzy judgment’ formed the most basic framework of the fuzzy
system. After showing the fuzzy system by a connected network structure, we could
have a kind of fuzzy neural network. The fuzzy neural network was completely equal
to a fuzzy system in terms of the ends of input and output. The internal weighting or
node parameter could be modified through learning. In addition, certain learning algor-
ithms could automatically result in the proper shape of the membership functions and
fuzzy rules. After modifying these membership functions and fuzzy rules, we could
derive the nonlinear model of this system.
We used two input and one output fuzzy neural network frameworks as examples for
description. Other multiple input and output forms could be expanded by this model. The
framework is shown in Figure 2.
(1) Layer 1: Input layer.
Input units: Ið1Þ1 ¼ X1; i ¼ 1; 2
Output units: Oð1Þij ¼ I
ð1Þi ; i ¼ 1; 2; j ¼ 1; 2;D; n
(2) Layer 2: Fuzziness interface (linguistic term layer). At this layer, we would
infer the membership of the related membership functions and the first layer by
Gaussian function.
Input units: Ið2Þij ¼
�ðOð1Þij � aijÞ
2
b2ij
; i ¼ 1; 2; j ¼ 1; 2;L; n
Output units: Oð2Þij ¼ mAij
¼ expðIð2Þij Þ; i ¼ 1; 2; j ¼ 1; 2;D; n
where aij and bij, respectively, are the center and the width parameters of the Gaussian
function.
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Table 4. Factor analysis and validity and reliability analysis of each construct in this research.
Constructs Factors and variables Factor loading EigenvalueItem-to-totalcoefficient
Accumulatedexplanatoryvariance (%)
Cronbach’s avalue
Empowerment 0.786Ability 1. I am confident of my ability of work 0.859 2.134 0.806 17.78
4. I can guarantee that I am capable ofpracticing the skills needed for work
0.836 0.812
6. I am considerably confident of how tomanage my job
0.807 0.806
Autonomy andinfluence
7. I can decide how to manage my job 0.856 4.109 0.809 52.02
9. I can have independence and freedomto consider how to execute my job
0.842 0.795
10. As for me, I have a high degree of jobautonomy
0.795 0.812
11. I have highly free measurement right inmy job
0.783 0.797
12. I have many chances to workindependently
0.795 0.782
14. My decision is considerably influentialon other coworkers
0.786 0.802
Meaning 2. My work is meaningful to me 0.762 1.723 0.812 66.385. My work is very important to me 0.643 0.7048. The activities in my work aresignificant for me personally
0.705 0.816
Types of corporate culture 0.808Group and result
orientation1. The firm values the accomplishment of
group performance0.712 3.415 0.812 22.76
2. The firm does not allow members tohave risky behavior
0.684 0.794
(Continued)
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Table 4. Continued.
Constructs Factors and variables Factor loading EigenvalueItem-to-totalcoefficient
Accumulatedexplanatoryvariance (%)
Cronbach’s avalue
4. The firm emphasizes the importance oftarget management of each unit
0.796 0.712
6. The firm values the members’participation
0.758 0.787
9. The firm values group spirit 0.724 0.84110. The firm does not encourage individual
heroism0.701 0.697
Innovation andactiveness
11. The firm has the system encouraginginnovation proposals
0.771 2.998 0.752 42.75
13. The firm regularly examines theemployees’ performance
0.795 0.769
14. The firm emphasizes an open andlearning environment
0.811 0.812
15. The firm values the practice ofemployees’ performance reward andpunishment
0.635 0.731
16. The firm values the employees’opinions with regard to the job system
0.681 0.712
Human orientationand organizationalstability
18. The firm values the employees’morality mechanism
0.657 2.374 0.681 58.57
19. The firm values the regulation ofemployees’ work manners
0.742 0.712
20. The employees’ promotion follows theregular system
0.759 0.703
22. The firm does not change employees’duties frequently
0.684 0.689
Service recovery 0.847Active strategies 1. Apologizing to the customers 0.846 2.374 0.812 33.91
5. Clearly explaining the causes of theincidents and solutions
0.792 0.806
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6. Actively discovering the errors anddealing with them
0.812 0.814
Passive strategies 7. Changing the products at the sameprices
0.752 2.835 0.805 74.41
9. Inviting the executives to solveproblems
0.814 0.807
11. Avoiding the same mistakes the nexttime
0.787 0.794
12. Providing discounts as compensation 0.809 0.787
Customer relationshipinvolvement
1. I often actively keep in touch with thecustomers
0.812 4.486 0.805 64.08 0.798
2. I will actively greet my customers 0.794 0.8023. I often inform the regulations of the
firm to the customers0.805 0.797
4. I will actively ask customers to leavetheir contact information
0.798 0.811
5. Customers often ask for my service orconsulting
0.771 0.775
6. Customers also inquire about mysituations of work
0.674 0.698
7. My customers often ask me questionsrelated to products or services
0.726 0.705
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(3) Layer 3: Fuzzy inference (rule layer). At this layer, we inferred the propriety
degree of each rule in the rule database.
Input units: Ið3Þðj�lÞnþl ¼ O
ð2Þij O
ð2Þ2l ; j ¼ 1; 2;D; n; l ¼ 1; 2;D; n
Output units: Oð3Þi ¼ mi ¼ I
ð3Þi ; i ¼ 1; 2;D;m ð¼n2Þ
(4) Layer 4: Defuzzifier interface and output (output layer).
Input units: Ið4Þ ¼Xm
p¼1
Oð3Þp Wp
Output units: Oð4Þ ¼ m� ¼Ið4Þ
Pmp¼1 O
ð3Þp
According to the above framework, we find the typical rules below.
The typical rule is written as follows based on the above structure: if X1 ismA11 then W1 = K1
K1 ¼ constant (zero-order Sugeno fuzzy model)
or
K1 ¼ p� X1 þ q� X2 þ r (first-order Sugeno fuzzy model; p; q; r are all constants)
With regards to learning algorithm of the membership function, this study used the
steepest descent method of the backpropagation model, and the learning algorithm of
Rule Base (K) was based on least squares estimation.
Figure 2. Framework of fuzzy neural network.
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Research steps:
(1) After re-organizing the figures in the return questionnaires, we obtained 107 pieces
of figures.
(2) We defined the assumed input and output variables and decided the number of the
membership functions corresponding to each variable.
(3) Having fuzzy neural model training and each training of 107 pieces of data was
considered to be one epoch. During the time, we renewed the parameters to
obtain optimized membership function shape and rule database.
After the training, with the fuzzy neural model, we could test the influence of input
variables on output variables. Since we focussed on the influence of certain input variables
on output variables, except for the said input variable, other input variables were
fixed (referring to the average of 107 pieces of data to minimize the influence of these
variables).
Reasons to operate the fuzzy neural network model. The reason that this research applied a
nonlinear fuzzy neural network model was mainly to first reduce the variables for the input
of initial value of the neural network. By using the nonlinear method, we could more pre-
cisely probe into the interaction among the variables. White (1989) also emphasized that a
neural network was capable of identifying the patterns and relationships of data, which
could be applied to the scope of multivariate data analysis. Besides, the main reason
this research applied the fuzzy neural network model was that it was the most commonly
used, and the most completely developed model. It was suitable for not only prediction and
classification, but also uncertain behavioral systems. The method featured the following
advantages: (1) it could completely approach any nonlinear functions. The samples of
this research were a kind of high degree of nonlinear function; (2) all of the quantitative
or qualitative messages were averagely saved in the neutron of the network. Thus, they had
strong error-correction capacity and firmness; (3) it adopted a collateral and distributing
method to have rapid and increased calculation, which would be suitable for a nonlinear
system of more complicated behavioral science in business management; (4) we only
needed the data of input and output layers and the input system to obtain the relationship
among the variables and (5) in terms of learning epoch times, application of the relation-
ship among variables not studied in advance and the examples of sampling methods had a
broader scope than the traditional statistical method.
Empirical results
We first focus on H1 and explore if there is significant correlation between empowerment
and service recovery strategies. In terms of the empirical results of the fuzzy neural
network model, each input variable has two membership functions: low and high. The
rule database is partially based on zero-order Sugeno fuzzy model. After 103 learning
epochs, the average testing error is 0.1856 and the test result is shown in Figure 3. In the
figure, filled circle is the test figure of the input variable and diamond symbol is the
output figure inferred by the fuzzy neural network model. According to Figure 3a, we
find that the distribution points of ‘empowerment’ and ‘active service recovery strategies’
are more consistent and very close, and hence a significant correlation exists between the
two. Thus, H1 is supported.
In order to confirm H2 and explore the correlation between different corporate culture
types and service recovery strategies, after about 116 learning epochs, the average testing
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Figure 3. Each input variable and membership function of ‘empowerment’ and ‘service recoverystrategies’. Relationship degree of (a) ‘empowerment’ and ‘active service recovery strategies’ and(b) ‘empowerment’ and ‘passive service recovery strategies’.
Figure 4. Each input variable and membership function of ‘corporate culture types’ and ‘servicerecovery strategies’.
Figure 5. Each input variable and membership function of ‘different corporate culture types’ and‘service recovery strategies’. Relationship degree between (a) ‘major corporate culture’ and‘passive service recovery strategies’ and (b) ‘minor corporate culture’ and ‘active service recoverystrategies’.
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error is 0.2076 and the test result is shown in Figure 4. According to the results in the
figure, we find that there is significant correlation between ‘corporate culture’ and
‘service recovery strategies’. Thus, H2 is supported.
When we further confirm H2-1 and H2-2, through about 126 and 143 learning epochs,
respectively, the average testing errors are 0.1986 and 0.1479. In Figure 5a and b, we can,
respectively, find the reverse distribution of the inferred and test distribution points. Thus,
H2-1 and H2-2 are supported.
Finally, in order to confirm H3, we explore the influence of ‘customer relationship
involvement’ on ‘recovery strategies’. After about 117 learning epochs, the average
testing error is 0.1354, and the test result is shown in Figure 6. From the figure, we find
that ‘customer relationship involvement’ has a positive influence on ‘service recovery
strategies’. Thus, H3 is supported.
Conclusions and discussions
Through the fuzzy neural network model, the hypotheses proposed in this research are sup-
ported and several meanings of management can be inferred: (1) the empowered employ-
ees will have active strategies when facing service failures and the underlying
significance is that employees are completely satisfied with achievement and a respon-
sible work motive. Their confidence is strengthened and they further identify with the
firm to increase their loyalty to the firm; besides, this research agreed on the views of
Bowen and Lawler (1992): since the employees are empowered, they identify themselves
more with the work and they repond more immediately to dissatisfied customers.
(2) With regard to the fact that the major corporate culture tends to have passive
service recovery strategies, this research indicates that the following have underlying
significance: first of all, managers having a major corporate culture tend to grasp the
decision-making rights and the basic employees have a lower degree of autonomy
since they have limited space to fulfill it. Thus, instead of undertaking the risks that do
not meet their positions, they transfer the risk responsibility to other executives. In
addition, the support for H2 also responds to the conclusion of H1. In other words,
employees with a higher degree of empowerment tend to be smoothly involved in the
organizational culture. In other words, they will value individual difference and the
internal harmony and cooperation of the group. On the contrary, the major culture
Figure 6. Each input variable and membership function of ‘customer relationship involvement’ on‘service recovery strategies’.
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values the accomplishment of shared goals and missions instead of the employees’ satis-
faction with psychological feeling and needs. (3) In terms of the empirical cases, when the
employees adopt active or passive recovery strategies, most of them comply with the regu-
lation or requirement of the policies. However, some firms still provide partial authority to
their managers according to the level of seriousness of the service failure and the employ-
ees’ quality. The service industry, which needs to immediately respond to customers
should particularly value the timing and scope of authority. (4) The conclusion of the posi-
tive correlation between customer relationship involvement and service recovery strat-
egies can reflect the importance of relationship marketing, which also reveals that in the
industry environment with micro-profit and severe competition, it is urgent and necessary
to establish long-term and friendly interactions with customers.
In addition, the characteristics of this research are as follows: (1) through the empirical
conclusion of the nonlinear fuzzy neural network model, we can more precisely measure
the relationships among the variables and there is less restriction on the conditions. It can
be applied to the social science fields such as business management. (2) Based on the
internal management factors, this research proposes the operation of service recovery
strategies. In other words, it probes into the response of service recovery from the stand-
point of internal prevention in the organization, which is different from most of the past
studies focussing on the exploration of consumers’ views.
The directions for follow-up studies are proposed as follows: (1) they can analyze the
lead factors of different service failure stages to construct a complete model affecting
service failure recovery; (2) they can further compare the differences and similarities of
the results of different methods to verify the hypotheses, such as comparing the differences
and similarities of the confirmation of the relationships among the variables with respect to
the structural equation model and the nonlinear fuzzy neural network and the reasons.
The restrictions of this research are as follows: (1) although there are many food chain
stores in Taiwan, the organizational scales and leadership are considerably different (some
of the Chinese food stores are family businesses passed from generation to generation).
Thus, different styles of leadership can influence the adoption of recovery strategies.
Therefore, by comparing the differences of different organizational scales, leadership
and organizational climate, we might infer different meanings. (2) This research collected
totally 107 samples through sampling. However, there are many questionnaire variables
that might lead to a lower return rate. When we apply the fuzzy neural network method
and intend to reduce the error rate, the return samples required for one of the factors
should be at least 100 copies. Although this research generally meets this requirement,
we should still enhance the operation of learning epoch times to solve the problem of a
possible higher error rate. Future researchers can try to operate different algorithms and
enhance the will to fill out the questionnaires in order to increase the number of valid
return questionnaires. Thus, the precision degree of the results will be more significant.
(3) This research explores the lead factors affecting recovery strategies by cross-sectional
aspect. We suggest that future researchers can explore the issue by the longitudinal aspect
and their conclusions might be more likely to reflect the policies that should be adopted by
the firms when facing service failure.
References
Barner, R. (1994). Enablement: The key to empowerment. Training and Development Journal,48(6), 33–36.
Barnes, J.G. (1997, June). Exploring the importance of closeness in customer relationships,American Marketing Association Conference (pp. 227–238), Dublin.
1544 W.-B. Lin
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nloa
ded
by [
Nor
th D
akot
a St
ate
Uni
vers
ity]
at 1
2:12
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Nov
embe
r 20
14
Bitner, M.J., Booms, B.H., & Tetreault, M.S. (1990). The service encounter: Diagnosing favorableand unfavorable incident. Journal of Marketing, 54(1), 71–84.
Bond, M.H., & Hwang, K.K. (1986). The social psychology of Chinese people. In M.H. Bond (Ed.),The psychology of the Chinese people (pp. 312–366). Hong Kong: Oxford University Press.
Bowen, D.E., & Lawler, E.E., III. (1992). The empowerment of service workers: What, why, howand when. Slogan Management Review, 33(3), 31–39.
Bowen, D.E., & Lawler, E.E., III. (1995). Empowering service employees. Sloan ManagementReview, 36(4), 73–84.
Carson, P.P., Carson, K.D., & William, R.C. (1998). Does empowerment translate into action? Anexamination of service recovery initiatives. Journal of Quality Management, 3(1), 133–148.
Cheng, B.S. (2005). Leadership in Chinese organizations: Theory and reality (1st ed.). Taipei:Crown Bookstore Press.
Conger, J.A. (1989). Leadership: The art of empowerment others. The Academy of ManagementExecutives, 11(1), 17–24.
Conrad, C.A., Brown, G.A., & Harmon, H.A. (1997). Customer satisfaction and corporate culture: Aprofile deviation analysis of a relationship marketing outcome. Psychology and Marketing,14(7), 663–674.
Cranage, D.A., & Mattila, A.S. (2005). Service recovery and pre-emptive strategies for servicefailure: Both lead to customer satisfaction and loyalty, but for different reasons. Journal ofHospitality and Leisure Marketing, 13(3), 161–181.
Cranage, D.A., & Sujan, H. (2004). Customer choice: A preemptive strategy to buffer the effects ofservice failure and improve customer loyalty. Journal of Hospitality and TourismManagement, 28(1), 3–20.
Crosby, L.A., Evans, K.R., & Cowles, D. (1990). Relationship quality in service selling: An inter-personal influence perspective. Journal of Marketing, 54(3), 68–81.
Cuieford, J.P. (1965). Fundamental statistics in psychology and education (4th ed.). New York:McGraw Hill.
Czepiel, J.A., Solomon, M.R., Surprenant, C., & Gutman, E.G. (1985). A role theory perspective ondyadic interactions: The service encounter. Journal of Marketing, 49(1), 99–112.
Eriksson, K., & Vaghult, A.L. (2000). Customer retention purchasing behavior andrelationship substance in professional services. Industrial Marketing Management, 29(4),363–372.
Forbes, L.P., & Kelley, S.W. (2005). Typologies of e-commerce retail failures and recovery strat-egies. The Journal of Services Marketing, 19(5), 280–292.
Hair, J.F., Anderson, R.E., Tatham, R.L., & Black, W.C. (1998). Multivariate data analysis.New York: Macmillan.
Hoffman, K.D., Kelley, S.W., & Rotalsky, H.M. (1995). Tracking service failure and employeerecovery efforts. Journal of Service Marketing, 9(2), 49–61.
Kelley, S.W., Hoffman, K.D., & Davis, M.A. (1993). A typology retail failures and recoveries.Journal of Retailing, 69(4), 429–454.
Kerlinger, F.N. (1986). Foundations of behavioral research (3rd ed.). New York: Holt, Rinehart andWinston.
Kim, C., Kim, S., Im, S., & Shin, C. (2003). The effect of attitude and perception on consumer com-plaint intentions. Journal of Consumer Marketing, 20(4), 352–371.
Lagace, R.R., Dahlstrom, R., & Gassenhheimer, J.B. (1991). The relevance of ethical salespersonbehavior on relationship quality: The pharmaceutical industry. Journal of Personal SellingSales Management, 11(4), 39–47.
Lin, W.B. (2006). Correlation between personality characteristics situations of services failure, cus-tomer relation strength, and remedial recovery strategy. Services Marketing Quarterly, 28(1),55–88.
Mattila, A.S. (2001). The effectiveness of service recovery in a multi-industry setting. The Journal ofService Marketing, 15(7), 583–596.
Mattila, A.S., & Patterson, P.G. (2004). The impact of culture on consumers’ perceptions of servicerecovery efforts. Journal of Retailing, 80(3), 196–206.
Meuter, M.L., Ostrom, A.L., Roundtree, R.I., & Bitner, M.J. (2000). Self-service technologies:Understanding customer satisfaction with technology-based service encounters. Journal ofMarketing, 64(3), 50–65.
The Service Industries Journal 1545
Dow
nloa
ded
by [
Nor
th D
akot
a St
ate
Uni
vers
ity]
at 1
2:12
07
Nov
embe
r 20
14
Miller, J.L., Craighead, C.W., & Karwan, K.R. (2000). Service recovery: A framework and empiricalinvestigation. Journal of Operations Management, 18(4), 387–400.
Nunnally, R. (1978). Psychometric theory. New York: McGraw Hill.Priluck, R. (2003). Relationship marketing can mitigate product and service failures. Journal of
Services Marketing, 17(1), 37–48.Robbins, S.P. (1994). Management (4th ed.). New Jersey: Prentice Hall Inc.Robbins, S.P. (2002). Management (7th ed.). New Jersey: Prentice-Hall Inc.Sin, L.Y.M., Tse, A.C.B., Yau, O.H.M., Lee, J.S.Y., & Chow, R. (2002). The effect of relationship
marketing orientation on business performance in a service-oriented economy. Journal ofServices Marketing, 16(7), 658–670.
Smith, A.K., Bolton, R.N., & Wanger, J. (1999). A model of customer satisfaction with serviceencounters involving failure and recovery. Journal of Marketing Research, 36(3), 356–372.
Spreitzer, G.M. (1995). Psychological empowerment in the workplace: Dimension, measurementand validation. Academy of Management Journal, 38(5), 1442–1435.
Spreng, R.A., Harrell, G.D., & Mackoy, R.D. (1995). Service recovery: Impact on satisfaction andintentions. Journal of Services Marketing, 9(1), 15–23.
Swanson, S.R., & Kelley, S.W. (2001). Attributions and outcomes of the service recovery process.Journal of Marketing Theory & Practice, 9(4), 50–65.
Tax, S.S., Brown, W.B., & Chandrashekaran, O. (1998). Recovering and learning from servicefailure. Sloan Management Review, 39(1), 75–88.
Weun, S., Beatty, S.E., & Jones, M. (2004). The impact of service failure severity on servicerecovery evaluations and post-recovery relationships. The Journal of Services Marketing,18(2), 133–146.
White, H. (1989). Some asymptotic results for learning in single hidden layer feed forward networkmodels. Journal of the American Statistical Association, 84(408), 1003–1013.
Wilfred, J.Z., Dobni, D., & Harel, G.H. (1998). Promoting employee service behavior: The role ofperceptions of human resource management practices and service culture. Revue Canadiennedes Sciences del’ Administration, 15(2), 165–179.
Wong, N.Y. (2004). The role of culture in the perception of service recovery. Journal of BusinessResearch, 57(9), 957–963.
Wyner, G.A. (1998). The many faces of customer value. Marketing Research, 10(1), 34–36.
1546 W.-B. Lin
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