Modeling and Evaluating Service Quality Measurement Using Neural Networks

R.S. Behara*, W.W. Fisher, J.G.A.M. Lemmink

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Effective measurement and analysis of service quality are an essential first step in its improvement. This paper discusses the development of neural network models for this purpose. A valid neural network model for service quality is initialy developed. Customer data from a SERVQUAL survey at an auto-dealership network in The Netherlands provide the basis for model development. Different definitions of service quality measurement are modelled using the neural network approach. The perception-minus-expectation model of service quality was found not to be as accurate as the perception-only model in predicting service quality. While this is consistent with the literature, this study also shows that the more intuitively appealing but mathematicaly less convenient expectation-minus-perception model out performs all the other service quality measurement models. The study also provides an analytical basis for the importance of expectation in the measurement of service quality. However; the study demonstrates the need for further study before neural network models may be effectively used for sensitivity analyses involving specific dimensions of service quality.
Original languageEnglish
Pages (from-to)1162-1185
JournalInternational Journal of Operations & Production Management
Volume22
Issue number10
DOIs
Publication statusPublished - 1 Jan 2002

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