首页> 外文期刊>Journal of Service Science and Management >A Decision-Making Method for Improving Logistics Services Quality by Integrating Fuzzy Kano Model with Importance-Performance Analysis
【24h】

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

机译:模糊卡诺模型与重要绩效分析相结合的提高物流服务质量的决策方法

获取原文
       

摘要

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.
机译:在资源有限的情况下,寻求客户满意度与物流服务绩效之间的关系对物流公司的发展具有重要意义。因此,对于物流公司而言,至关重要的是要了解物流服务质量属性可以提高满意度,而其改进重点可以帮助做出更好的决策。因此,确定物流服务质量属性的重要性及其对提高客户满意度的贡献对于物流公司的成功变得越来越必要。考虑到传统的Kano模型分类是主观的,因此,本研究的目的是将模糊Kano模型与重要性-绩效分析相结合,以分别使用这两种方法来解决缺点。此外,构建决策方法可以帮助物流公司确定物流服务质量属性的优先级。最后,对客户满意度进行了实证研究。已经验证了该方法的可行性和有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号