Quality evaluation of mediation of conflicts and disputes based on fuzzy comprehensive evaluation method: take H city as an example

Hailang Chen; Meigui Yin

doi:10.1117/12.2649454

27 September 2022 Quality evaluation of mediation of conflicts and disputes based on fuzzy comprehensive evaluation method: take H city as an example

Hailang Chen, Meigui Yin

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Proceedings Volume 12345, International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022); 123450U (2022) https://doi.org/10.1117/12.2649454
Event: 2022 International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022), 2022, Qingdao, China

Abstract

With the rapid development of network technology and social economy, the increasing number of non-litigious conflicts and disputes has stimulated the rapid development of online conflict and dispute mediation mechanisms in countries around the world. How to scientifically and efficiently improve the quality of conflict mediation and facilitate the parties to reach an agreement is crucial to effectively mediate conflicts and disputes, prevent them from escalating, and maintain social harmony and stability. In this paper, a fuzzy comprehensive evaluation method is used to evaluate the quality of conflict mediation based on the "online multi-conflict integration platform" in city H. The application of this evaluation method shows that it can better evaluate the quality of conflict mediation. The application practice shows that the evaluation can reflect the conflict mediation situation more objectively and multi-dimensionally, and provide data support for further improving social governance and implementing personalized conflict mediation guidance.

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Hailang Chen and Meigui Yin "Quality evaluation of mediation of conflicts and disputes based on fuzzy comprehensive evaluation method: take H city as an example", Proc. SPIE 12345, International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2022), 123450U (27 September 2022); https://doi.org/10.1117/12.2649454

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Fuzzy logic

Quality systems

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