Preference prediction analysis based on graph model for environmental governance conflict

Jinshuai Zhao; Baohua Yang; Jinshuai Zhao; Baohua Yang

doi:10.3934/mbe.2022287

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 6: 6141-6156. doi: 10.3934/mbe.2022287

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Preference prediction analysis based on graph model for environmental governance conflict

Jinshuai Zhao ¹,
Baohua Yang ^{2
,
,}

1.
School of Computer Science and Technology, Jiangsu Normal University, No.101 Shanghai Road, Tongshan District, Xuzhou 221116, China
2.
Business School, Jiangsu Normal University, No.101 Shanghai Road, Tongshan District, Xuzhou 221116, China

Academic Editor: Jeffrey Yi-Lin Forrest

Received: 30 January 2022 Revised: 02 April 2022 Accepted: 06 April 2022 Published: 14 April 2022

A mathematical model for decision maker's preference prediction in environmental governance conflict is established based on the graph model for conflict resolution. The rapid economic development in many countries, over the past decades, has caused serious environmental pollution. Sewage companies are the main source of contamination since they are always wavering on the issue of environmental governance because of their profit-seeking nature. Environmental management departments cannot grasp the offending company preferences accurately. The problem of how to obtain decision maker's preference in environmental governance conflict is studied in this paper. The mathematical model established in this paper can obtain a preference set of one decision maker on the promise that the ideal conflict outcome and preference of the other decision makers are known. Then, preference value distribution information entropy is introduced to mine the preference information contained in the preference set, which means that it is possible to get the preference information of conflict opponent at their own ideal conflict outcome. All of these preference sets provide the possibility to choose the appropriate coping strategies and lead the conflict to the direction that some decision makers want. Finally, the effectiveness and superiority of the preference prediction analysis method is verified through a case study of "Chromium Pollution in Qujing County" which took place in China. The preference prediction analysis method in this paper can provide decision making support for the decision makers in environmental governance from strategic level.
- environmental governance,
- preference prediction,
- environmental protection,
- decision making,
- graph model,
- conflict analysis,
- environmental pollution
Citation: Jinshuai Zhao, Baohua Yang. Preference prediction analysis based on graph model for environmental governance conflict[J]. Mathematical Biosciences and Engineering, 2022, 19(6): 6141-6156. doi: 10.3934/mbe.2022287

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Abstract

A mathematical model for decision maker's preference prediction in environmental governance conflict is established based on the graph model for conflict resolution. The rapid economic development in many countries, over the past decades, has caused serious environmental pollution. Sewage companies are the main source of contamination since they are always wavering on the issue of environmental governance because of their profit-seeking nature. Environmental management departments cannot grasp the offending company preferences accurately. The problem of how to obtain decision maker's preference in environmental governance conflict is studied in this paper. The mathematical model established in this paper can obtain a preference set of one decision maker on the promise that the ideal conflict outcome and preference of the other decision makers are known. Then, preference value distribution information entropy is introduced to mine the preference information contained in the preference set, which means that it is possible to get the preference information of conflict opponent at their own ideal conflict outcome. All of these preference sets provide the possibility to choose the appropriate coping strategies and lead the conflict to the direction that some decision makers want. Finally, the effectiveness and superiority of the preference prediction analysis method is verified through a case study of "Chromium Pollution in Qujing County" which took place in China. The preference prediction analysis method in this paper can provide decision making support for the decision makers in environmental governance from strategic level.

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