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.
|Journal||International Journal of Operations & Production Management|
|Publication status||Published - 1 Jan 2002|
Behara, R. S., Fisher, W. W., & Lemmink, J. G. A. M. (2002). Modeling and Evaluating Service Quality Measurement Using Neural Networks. International Journal of Operations & Production Management, 22(10), 1162-1185. https://doi.org/10.1108/01443570210446360