The Behavioral TOPSIS Based on Prospect Theory and Regret Theory.
Published In: International Journal of Information Technology & Decision Making, 2023, v. 22, n. 5. P. 1591 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Liu, Xinwang; Yang, Yuyao; Jiang, Jing 3 of 3
Abstract
Technique for order preference by similarity to ideal solution (TOPSIS) is a famous technique for solving multicriteria decision-making problems. However, the classical TOPSIS is invalid to distinguish the alternatives when the distances to the PIS and NIS are the same, and the current researchers about TOPSIS seldom consider the psychological characteristics of loss aversion and regret aversion which affect the decision quality in real world. This paper proposes a behavioral TOPSIS with prospect theory and regret theory considering risk attitudes. First, the defect of classical TOPSIS is illustrated as motivation. Next, we introduce a behavioral TOPSIS with prospect theory and show how it overcomes the defect of classical TOPSIS. Then, regret theory is applied to extend behavioral TOPSIS to show the regret attitude. Finally, a numerical example is used to demonstrate the feasibility and comparative analysis is presented to show the novelty and validity of the proposed method. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Information Technology & Decision Making. 2023/09, Vol. 22, Issue 5, p1591
- Document Type:Article
- Subject Area:Business and Management
- Publication Date:2023
- ISSN:0219-6220
- DOI:10.1142/S0219622022500778
- Accession Number:170750507
- Copyright Statement:Copyright of International Journal of Information Technology & Decision Making is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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