A Decision-Making Method for Improving Logistics Services Quality by Integrating Fuzzy Kano Model with Importance-Performance Analysis

Abstract

In resources limited circumstances, seeking relationship between customer satisfaction and logistics service performance is meaningful for the development of logistics companies. Therefore, it is crucial for logistics companies to understand that logistics service quality attributes can increase satisfaction and their improvement priorities can help make better decisions. Thus, the identification of logistics service quality attributes importance and their contributions on improving customer satisfaction have become more necessary to logistics companies success. Considering traditional Kano model classification is subjective, the contribution of this study is, therefore, to integrate fuzzy Kano model with importance-performance analysis to address the shortcomings with using these two methods separately. What’s more, constructing a decision-making method can help logistics companies determine the priority of logistics service quality attributes. Finally, an empirical study on customer satisfaction was undertaken. The feasibility and effectiveness of this method had been verified.