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.
Highlights
Customer satisfaction is very important for logistics companies seeking competitive advantage, because theyHow to cite this paper: Meng, Q.L., Jiang, X. and Bian, L.L. (2015) A Decision-Making Method for Improving Logistics Services Quality by Integrating Fuzzy Kano Model with Importance-Performance Analysis
First we introduce the proposed fuzzy Kano model
In resources limited situation, seeking relationship between customer satisfaction and logistics service performance is meaningful for the development of logistics companies
Summary
Customer satisfaction is very important for logistics companies seeking competitive advantage, because theyHow to cite this paper: Meng, Q.L., Jiang, X. and Bian, L.L. (2015) A Decision-Making Method for Improving Logistics Services Quality by Integrating Fuzzy Kano Model with Importance-Performance Analysis. Customer satisfaction is very important for logistics companies seeking competitive advantage, because they. (2015) A Decision-Making Method for Improving Logistics Services Quality by Integrating Fuzzy Kano Model with Importance-Performance Analysis. In order to identify the priority of logistics services quality attributes, a decision-making method is constructed. Brandt [4] firstly developed a dummy regression model to identify the non-linear and asymmetric impacts of attribute performance on overall customer satisfaction. Yang [5] recommended that the results of classification should be divided into eight categories, so as to improve the accuracy of the Kano model These methods facilitate the analysis of customer requirements, it ignores the fact that quality attribute performance and importance can affect the results of classification.
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