A soft computing method for selecting evaluation criteria of service quality

The problem of the selection/building of criteria is a most important issue for service providers and supervision departments, as it is important to consider whether the criteria can effectively evaluate/improve service quality for service industries and provide a basic level of service quality. Furthermore, the criteria often simultaneously have independent, dependent and interdependent characteristics, and they also often teem with indefinite, undefined, vague and fuzzy data. Thus, the building of criteria of service quality has become very complex and difficult in a real-life environment. Therefore, the analysis of the relationships among criteria is very difficult using the conventional methods, as we are unsure whether we can obtain unequivocal data or major samples to investigate service quality data. A new relationship analysis method combining the concepts of fuzzy sets and grey relation analysis is proposed to analyze the problems of relationships among criteria and to reduce the number of criteria by selecting representative criteria. Furthermore, this paper uses a numerical example of the selection of criteria for intercity bus industries in Taiwan to illustrate the proposed method. The results show that this method is an effective means for tackling criteria selection problems.