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Expert Systems with Applications
Volume 32, Issue 2, February 2007, Pages 364-375
 
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doi:10.1016/j.eswa.2005.11.033    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2006 Elsevier Ltd All rights reserved.

An empirical of service quality model from the viewpoint of management

Wen-Bao LinCorresponding Author Contact Information, a, E-mail The Corresponding Author

aDepartment of Business Administration, National Formosa University, ADD:64, Wen-Hua Rd., Huwei, Yulin, Taiwan

Available online 6 January 2006.

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Abstract

This study discusses the major factors for the establishment of service quality models from the viewpoint of management, including the influence that different service encounters and company cultures have on service quality, and the influence of service quality on the attitude of consumers toward their perceived value in the future. Three hundred and fifty two IT companies with enterprises as their customers and 244 comprehensive travel agencies listed with the Tourism Bureau of Taiwan, Ministry of Transport and Communications, are selected as the research population of the study, and questionnaires are distributed to the managers of marketing-related departments of both industries for the survey. The fuzzy neural network model is used to verify assumptions that are derived from theories. The empirical research result indicates that the interpersonal service encounter has a higher performance than the technology-based service encounter in functional quality. The higher the difference in culture is, the higher the technical quality will be in performance than functional quality, while the lower the difference in culture is, the higher the functional quality will be in performance than technical quality. Improvement in service quality has a positive effect on the attitude of consumers toward the perceived value in the future.

Keywords: Service encounter; Technical quality; Functional quality; Perceived value

Article Outline

1. Introduction
2. Literature review
3. Research methods
3.1. Research framework
3.2. Questionnaire design
3.3. Operational definition of research variables
3.4. Sampling methods and sample character analysis
3.5. Reliability and validity analysis
3.6. Fuzzy neural network framework
4. Conclusions and discussions
References











 
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