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Three-way conflict analysis based on interval-valued Pythagorean fuzzy sets and prospect theory

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Abstract

Conflict analysis gives guidelines for conflict resolution, which has been thoroughly studied and received widespread interest. Three-way conflict analysis research has achieved remarkable results and has been extended to Pythagorean fuzzy information systems because the three-way decision coincides with three attitudes of agents on issues, where the positive and negative degrees of agents are depicted by the membership and non-membership degrees. However, agent’s opinions on issues must not be expressed only by real numbers, and the form of ranges can be used. Interval-valued Pythagorean fuzzy sets allow the membership and non-membership degrees of a given set to have interval values, which can effectively handle this problem. This work analyzes a three-way conflict analysis based on interval-valued Pythagorean fuzzy information systems. First, we introduce the concept of interval-valued Pythagorean fuzzy information systems and illustrate how to divide positive, neutral, and negative alliances by the measurement function and thresholds. Then, we focus on a three-way conflict analysis based on prospect theory by considering the subjective risk attitude and preference of decision-makers. Finally, we further investigate three-way conflict analysis based on interval-valued Pythagorean fuzzy sets and prospect theory with group decision theory, where the outcome matrices are provided by multiple experts. Several examples of software development project team conflicts are employed to illustrate the process of conducting a three-way conflict analysis based on interval-valued Pythagorean fuzzy information systems and prospect theory. The comparative analysis is utilized to show the effectiveness and superiority of the proposed three-way conflict analysis approach compared with other models and methods.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We sincerely thank the anonymous reviewers and editor for their valuable advice to improve the quality of the article. We would like to thank the EssayStar Company (http://essaystar.com/) for their assistance in improving the English language of this article. This work is supported by the National Natural Science Foundation of China (Nos. 62206129, 62276136, 62106205, 72274098 and 61876079), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Nos. 22KJB520019 and 20KJA520006) and the Natural Science Foundation of Chongqing (No. cstc2021jcyj-msxmX0824).

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Authors and Affiliations

  1. School of Business, Nanjing Audit University, Nanjing, 211815, People’s Republic of China

    Tianxing Wang

  2. School of Artificial Intelligence, Southwest University, Chongqing, 400715, People’s Republic of China

    Libo Zhang

  3. School of Computer Science, Nanjing Audit University, Nanjing, 211815, People’s Republic of China

    Bing Huang

  4. Department of Control and Systems Engineering, School of Management and Engineering, Nanjing University, Nanjing, 210093, People’s Republic of China

    Xianzhong Zhou

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  1. Tianxing Wang
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Correspondence to Bing Huang.

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Wang, T., Zhang, L., Huang, B. et al. Three-way conflict analysis based on interval-valued Pythagorean fuzzy sets and prospect theory. Artif Intell Rev 56, 6061–6099 (2023). https://doi.org/10.1007/s10462-022-10327-w

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