Several limitations are existed in this study; first, the SFR model developed is grounded on the one stage HoQ of the QFD methodology. In order to further convey the service failures through to firms’ available resources, the process can be continued to a third or fourth phase. Next, there is no systematic procedure for Neural Network constructing in order to build both of the performance function and the valuable gap function for SFs identification, thus the determination of the final network will be affected by analyzer’s subjective judgment (Tsaur et al., 2002). Therefore, on the basis of the VGA approach proposed in this study, further researchers can suggest a more efficient estimated method for algorithm operations. In addition, this study suggests that some critical factors, such as cost and risk, need to be included in the further SFR analysis to determine the best recovery strategy as well as to decrease the gap between theory and practice. Finally, in order to verify the validity of the SFR model, an empirical case is presented, but the results failed to be generalized to other service industries. This study therefore suggests that more empirical researches by using the SFR model as the basis for drawing up the service recovery strategies are needed.
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APPENDIX A
The classifications codes (Table A1) used in Carnevalli and Miguel’s (2008) study were adapted to record the QFD and DEMATEL articles.
Table A1
QFD / DEMATEL article classifications codes
T1: Kind of studyA Modeling
B Theoretical–conceptual C Literature review D Simulation E Survey F Case study G Action-research H Experimental T9: QFD/DEMATEL application
A1 QFD/DEMATEL use to develop strategy
A2 Application to help implant methods, norms, etc.
A3 Applications for product development A4 Applications to develop software A5 Applications to develop services A6 QFD/DEMATEL use to help planning A7 Other applications
APPENDIX B Research Questionnaire
Respondents rated the service performance on each scale item using a seven-point scale (1 = strongly disagree/unimportant, 7 = strongly agree/important). The items below are grouped by dimension for expositional convenience; they appeared in random order on the survey. The symbols preceding the items correspond to the variable names through the article.
Part I: Service quality – referring to SERVQUAL
Tangibles
T1 The service company has modern-looking equipment.
T2 The physical facilities are visually appealing.
T3 The number of service branches are various. (*) T4 Employees are neat-appearing.
T5 Materials associated with the service are visually appealing
Reliability
REL1 When the service company promises to do something by a certain time, it does so.
REL2 When a customer has a problem, the service company shows a sincere interest in solving it.
REL3 The service company performs the service right the first time.
REL4 Services are provided at the time the service company promises to do.
REL5 The records are error-free.
Responsiveness
RES1 Employees tell customers when services will be performed.
RES2 Employees give prompt service to customers.
RES3 Employees are willing to help customers.
RES4 Employees are never too busy to respond to customer’s requests.
Assurance
ASS1 The behaviour and knowledge of employees instill confidence in customers. (*) ASS2 Customers feel safe in their transactions.
ASS3 Employees are consistently courteous.
ASS4 Employees have support from top management to answer customer’s questions. (*)
Empathy
EMP1 The service company has the flexibility to give individual attention to the customer.
(*)
EMP2 Employees give personal attention to customers.
EMP3 The service company understands specifics needs of its customers.
EMP4 The service company has customer’s interest at heart.
EMP6 The tariff of mobile phone calling is reasonable. (*)
Convenience
EMP5 Operating hours are convenient to all customers.
EMP7 The choices of payment channel are various. (*)
EMP8 The types of tariff of mobile phone calling are diverse. (*)
EMP9 Processes of contract-related events are convenient to all customers. (*)
Calling
CAL1 The service company has the capability of maintaining the calling articulation. (*) CAL2 The service company can ensure to receive the message on the go. (*)
CAL3 The service company can ensure that the message always being with the stable signal. (*)
Part II: Web quality - referring to e-SERVQUAL
Efficiency
EFF1 This site makes it easy to find what I need.
EFF2 It makes it easy to get anywhere on the site.
EFF3 It enables me to complete a transaction quickly.
EFF4 Information at this site is well organized.
EFF5 It loads its pages fast.
EFF6 This site is simple to use.
EFF7 This site enables me to get on to it quickly.
EFF8 This site is well organized.
System Availability
SA1 This site is always available for business.
SA2 This site launches and runs right away.
SA3 This site does not crash.
SA4 Pages at this site do not freeze after I enter my order information.
Fulfillment
FUL1 It delivers orders accurately when promised.
FUL2 This site makes services promised within a suitable time frame. (*) FUL3 It sends out the services contracted. (*)
FUL4 It is truthful about its offerings.
FUL5 It makes accurate promises about delivery of services. (*)
Privacy
PRI1 It protects information about my Web-using behavior.
PRI2 It does not share my personal information with other sites.
PRI3 This site protects information about my finical related data.
Responsiveness
RESP1 It provides me various channels/suggestions for problems resolving. (*) RESP2 It provides me with well operational processes for service complaints. (*) RESP3 This site offers a meaningful service guarantee.
RESP4 It tells me what to do if my transaction is not processed.
RESP5 It takes care of problems promptly.
Compensation
COM1 This site compensates me for problems it creates.
COM2 It compensates me when service doesn’t arrive on time. (*)
COM3 It receives rejected services resulted from the online problems. (*)
Contact
CON1 This site provides a telephone number to reach the company/branch.
CON2 This site has customer service representatives\available online.
CON3 It offers the ability to speak to a live person if there is a problem.
Note: The symbol (*) means the item is modified or the item is new added.
Part III: Customer satisfaction
Single item is used for satisfaction; respondents rated the overall service using a scale of 1 (poor) to 7 (excellent).
OCS Overall, how likely are you to think about the services provided by the service company……
APPENDIX C
The procedure of implementing GA approach includes two phases with seven steps which are summarized in Figure C1.
Figure C1 The procedure of VG analysis
Selecting parameters and learning termination are two critical determinations of Back-Propagation Neural Network prediction capability. Thus the design of parameters and learning termination are discussed as follows.
1. Parameter selection: Five parameters necessary for Neural Network building include number of hidden layers, number of hidden neurons, activation function, learning rate, and momentum.
(1) Commonly, setting more hidden layers will increase the complexity of Neural Network operating. Kaastra and Boyd (1996) indicated that a neural network with one hidden layer can approximate any continuous function if the number of hidden
Phase 1:
To obtain the performance function
Training and testing the BPNN to obtain final function Listing all of the service attributes the
company provided
Assessing customers’ expected service, perceived service, and OCS
Importing input and output data for BPNN design
Phase 2:
Valuable gap analysis
Identifying the service failures
paired t-test method
Microscopic viewpoint Testing the significance of total service
quality gap of the service system
Macroscopic viewpoint Testing the significance of service quality gap for all service attributes
neurons is sufficient. This suggestion was followed and confirmed by recent studies.
Therefore, one hidden layer was adopted in this study.
(2) The number of hidden neuron will affect the learning ability of Neural Network.
However, there is no formal rule for selecting the optimum number of hidden neuron. This study, therefore, referring to previous studies (e.g., Khaw, Lim & Lim, 1995), integrated Try Error Method with Taguchi method to determine the optimum number of hidden neuron of Neural Network.
(3) As for the choice of the activation functions, two functions which have been widely used by previous studies are such as the sigmoid function, and
hyperbolic tangent function, . In this study, hyperbolic tangent function is chosen due to the better results of goodness of fit test.
(4) Most Neural Network software packages provided default values for both parameters of learning rate and momentum term. The common practice used in this study was to start training with a high learning rate, 0.7, and decrease the rate as training proceeds.
2. Learning termination: There are two rules for learning termination: (1) when mean
square error (MSE) between the expected value and network output value dropped
below the preset Threshold; and (2) when the preset Epoch of learning iterations had reached.Additionally, to examine the fitness of Neural Network, two common indicators were used in this study and illustrated as follows.
1. Mean square error (MSE)
1 (C-1)