A Fuzzy Collaborative Approach for Evaluating the Suitability of a Smart Health Practice

Tin-Chih Toly Chen, Yu-Cheng Wang, Yu-Cheng Lin, Hsin-Chieh Wu and Hai-Fen Lin
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Tin-Chih Toly Chen: Department of Industrial Engineering and Management, National Chiao Tung University, 1001, University Road, Hsinchu 30010, Taiwan
Yu-Cheng Wang: Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung 41349, Taiwan
Yu-Cheng Lin: Department of Computer-Aided Industrial Design, Overseas Chinese University, Taichung 40721, Taiwan
Hsin-Chieh Wu: Department of Industrial Engineering and Management, Chaoyang University of Technology, Taichung 41349, Taiwan
Hai-Fen Lin: Electronic Systems Research Division, National Chung-Shan Institute of Science & Technology, Taoyuan 32557, Taiwan

Mathematics, 2019, vol. 7, issue 12, 1-20

Abstract: A fuzzy collaborative approach is proposed in this study to assess the suitability of a smart health practice, which is a challenging task, as the participating decision makers may not reach a consensus. In the fuzzy collaborative approach, each decision maker first applies the alpha-cut operations method to derive the fuzzy weights of the criteria. Then, fuzzy intersection is applied to aggregate the fuzzy weights derived by all decision makers to measure the prior consensus among them. The fuzzy intersection results are then presented to the decision makers so that they can subjectively modify the pairwise comparison results to bring them closer to the fuzzy intersection results. Thereafter, the consensus among decision makers is again measured. The collaboration process will stop when no more modifications are made by any decision maker. Finally, the fuzzy weighted mean-centroid defuzzification method is applied to assess the suitability of a smart health practice. The fuzzy collaborative approach and some existing methods have been applied to assess the suitabilities of eleven smart health practices for a comparison. Among the compared practices, only the fuzzy collaborative approach could guarantee the existence of a full consensus among decision makers after the collaboration process, i.e., that the assessment results were acceptable to all decision makers.

Keywords: smart health; fuzzy collaborative intelligence; fuzzy analytic hierarchy process; suitability (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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