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Improving dual importance analysis based on a Shapley value associated with a fuzzy measure when interactions of criteria are significant

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  • Jiunn-I Shieh
  • Hsin-Hung Wu

Abstract

Kano's model is very useful to classify customer needs into different categories by completely using self-stated evaluations. However, the derived evaluation approach uses a less direct way of uncovering the evaluations that are most reliable to reflect the respondents' view from the survey. In addition, interaction effects among items, particularly non-linear interactions, are often incurred in practice. This study proposes a framework of using the dual importance graph with self-stated performance and derived importance computed by a Shapley value associated with a fuzzy measure method to classify the service items into different types of Kano's category by considering both linear and nonlinear effects among items. A case of evaluating the service quality of a particular hospital is illustrated to show how this proposed framework works. The result shows that using the Shapley value-based dual importance graph is more practical to deal with interactions of items.

Suggested Citation

  • Jiunn-I Shieh & Hsin-Hung Wu, 2019. "Improving dual importance analysis based on a Shapley value associated with a fuzzy measure when interactions of criteria are significant," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 31(2), pages 168-183.
    • Handle: RePEc:ids:ijisen:v:31:y:2019:i:2:p:168-183
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    Cited by:

    1. Xiaoyan Wang & Anquan Wang, 2022. "A Two-Level Hierarchical Linear Model Analysis of the Effect of Teacher Factors, Student Factors, and Facility Conditions on Students’ Cognitive Scores in Rural China," Sustainability, MDPI, vol. 14(13), pages 1-17, June.

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