An application of fuzzy logic to assess service quality attributes in logistics industry
Differentiation, growing competitive advantage, and excellence has been proved to be the result of service quality. At the same time, measuring attributes of service quality and customer satisfaction is fuzzy and ambiguous, and methods available for their measurement are generally classical. This paper proposes a fuzzy method to identify the service quality attributes. This approach was developed using crisp assessment methods in a logistics company. Applying the proposed fuzzy approach, service quality attributes and indicators are identified and then organized into 8 categories, to see the uncertainty level of each. The proposed method was successfully conducted in a real logistics company. The results show the membership degree of each indicator, suggesting customer expectations regarding quality. Also, the membership degrees of the service quality attributes suggest the ability of each to describe service quality in logistics industry.