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Issue title: Special Section: Fuzzy Decision Making and Applications in Knowledge Management
Guest editors: Justin Zhang
Article type: Research Article
Authors: Cheng, Tian-E.a; b | Wang, Junc | Zhang, Du-Juanc | Cao, Ming-Minga; *
Affiliations: [a] College of Urban and Environmental Sciences, Northwest University, Xi’an, Shaanxi, China | [b] School of Foreign Languages, Northwest University, Xi’an, Shaanxi, China | [c] College of Geography Science, Shanxi Normal University, Linfen, Shanxi, China
Correspondence: [*] Corresponding author. Ming-Ming Cao, College of Urban and Environmental Sciences, Northwest University, Xi’an, Shaanxi, 710127, China. Tel./Fax: +86 0451 86609816; E-mail: cmmcte201711@163.com.
Abstract: Recently, the TODIM (an acronym in Portuguese for Interactive Multi-criteria Decision Making) approach, which can characterize the decision makers’ psychological behaviors under risk, has been introduced to handle multiple attribute decision making (MADM) problems. Moreover, 2-tuple linguistic term set is an effective tool for depicting uncertainty of the MADM problems. In this paper, we will extend the TODIM method to the MADM with the 2-tuple linguistic information. Firstly, the definition and distance of 2-tuple linguistic information are briefly introduced, and the steps of the classical TODIM method for MADM problems are presented. Then, on the basis of the classical TODIM method, the extended TODIM method is proposed to deal with MADM problems in which the attribute values are in the 2-tuple linguistic information, and its significant characteristic is that it can fully consider the decision makers’ bounded rationality which is a real action in decision making. Finally, a numerical example for evaluating the service quality of boutique tourist scenic spot is proposed to verify the developed approach and its practicality and effectiveness.
Keywords: Multiple attribute decision making, 2-tuple linguistic variables, TODIM method, prospect theory, service quality
DOI: 10.3233/JIFS-179271
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2075-2083, 2019
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