Punishment or reward? Environmental information disclosure in Chinese listed companies based on evolutionary game systems

Rongjiang Cai, Xi Wang, Tao Zhang, Nana Liu, Qiaoran Jia

Research output: Contribution to journalArticlepeer-review

Abstract

In February 2022, the Chinese government implemented a mandatory environmental information disclosure policy for publicly traded corporations. To assess the factors influencing environmental information disclosure, we developed a tripartite evolutionary game system model based on strategic interactions between the government, enterprises and the public. Afterwards, we conducted a simulation to examine the systemic interaction equilibrium among the parties involved. Additionally, we assessed critical factor changes in decision-making for three stakeholders: initial strategy selection, related policy subsidies, regulatory penalties and public incentives. Incorporating Gaussian white noise into the evolutionary game model enhances the realism of simulations, allowing for a more accurate representation of how random disturbances affect decision-making among the government, the public and enterprises. The study reveals that the active participation of the public in information disclosure activities has a certain degree of substitution effect on the government's choice to regulate high-quality information disclosure by enterprises actively. The penalty mechanism is more effective than the subsidy mechanism. The public's decision-making process is susceptible to the direct economic benefits that enterprises can gain from disclosing low-quality environmental information.

Original languageEnglish
JournalSystems Research and Behavioral Science
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • Chinese listed companies
  • environmental information disclosure
  • evolutionary game systems
  • multiple agents

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