Dynamic bargaining game DEA carbon emissions abatement allocation and the Nash equilibrium

被引:7
作者
Chu, Junfei [1 ]
Hou, Tianteng [1 ]
Li, Feng [2 ]
Yuan, Zhe [3 ]
机构
[1] Cent South Univ, Sch Business, Changsha 410083, Peoples R China
[2] Southwestern Univ Finance & Econ, Fac Business Adm, Sch Business Adm, Chengdu 611130, Sichuan, Peoples R China
[3] Leonard Vinci Pole Univ, Res Ctr, F-92916 Paris, France
基金
中国国家自然科学基金;
关键词
Carbon emissions abatement allocation; Dynamic bargaining game; Data envelopment analysis; Nash equilibrium; NONPARAMETRIC PRODUCTION ANALYSIS; DATA ENVELOPMENT ANALYSIS; UNDESIRABLE OUTPUTS; WEAK DISPOSABILITY; CO2; EMISSIONS; PERMITS; CHINA; EFFICIENCY; ALLOWANCE; SCHEMES;
D O I
10.1016/j.eneco.2024.107622
中图分类号
F [经济];
学科分类号
02 ;
摘要
Allocating carbon emissions abatement (CEA) is crucial for reducing carbon footprint of organizations (or decision-making units, DMUs) and mitigating global warming. However, discrepancies often arise among DMUs regarding CEA allocation. This study introduces a dynamic bargaining game approach to address the issue under the nonparametric production frontier analysis framework. Our approach employs an iterative process, allowing each DMU to propose its individual preferred CEA allocation proposal in each iteration. Subsequently, dynamic negotiations among the DMUs occur, leading to the eventual consensus on the CEA allocation result. Our theoretical analysis demonstrates that, at the end of the dynamic bargaining game, all DMUs will converge on the same CEA allocation result, termed as the consensus CEA allocation result. This agreement is reached despite each DMU customizing its individual CEA allocation proposal to suit its own interests. Moreover, we prove that this consensus CEA allocation result represents a Nash equilibrium solution, thereby ensuring its stability and acceptance among all DMUs. Finally, we provide a simple numerical example and a case study of CEA allocation across 27 European Union countries to illustrate the usefulness of our approach and compare it with prior CEA allocation approaches.
引用
收藏
页数:14
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