Fuzzy application in service quality analysis: An empirical study

Service activities have become the fundamental and dominant factors of the economic system over the past three decades and the significance and influence of service quality have been recognized through the great effect on customer satisfaction and customer loyalty. It should be noted that the assessment results obtained from multiple attributes decision-making problems of diverse intensity, such as service quality evaluation, may be misleading if the fuzziness of subjective human judgment is not taken into account. This paper develops an analysis architecture, which consists of fuzzy measurement of P–I gap, modified P–I analysis for attributes and ranking order determination for subjects, to deal with service quality measurement more effectively. The fuzzy measurement of P–I gap takes advantage of including the vagueness of evaluators’ judgment. By using the results of modified P–I analysis, effective ways for improving service quality perceptions can be focused on the attributes of high importance yet poor quality; meanwhile, resources or efforts attached to the attributes of low importance and good quality can be shifted to those of high importance yet poor quality. According to the ranking order of subjects, managers could devote more efforts to assist the subjects with inferior rankings to improve the service activities. The proposed analysis architecture can be used to investigate service quality effectively and track the trends periodically. An empirical study is conducted by using the proposed approach.