Blockchain-enabled carbon emission trading data quality regulation: A tripartite evolutionary game analysis

Data quality issues are hampering the stability of the carbon trading market. To address these challenges, this paper proposes an innovative tripartite evolutionary game model integrating prospect theory for the government, enterprises and the public. The model delves into the application of blockchain technology in the carbon trading market and its impact on participants' strategic choices. Additionally, a penalty mechanism based on blockchain is introduced to curb source data quality issues, considering the influence of decision-maker psychology on strategy selection. Simulation analyses reveal various factors affecting the stability of each party's strategy options, including carbon price, blockchain construction cost, enterprise lying penalties, integrity gains and the public rewards. Our findings highlight that the government's initial willingness to apply blockchain, carbon pricing, penalty enforcement, and public participation significantly influence the strategic decisions of all parties involved. Ultimately, this study underscores the importance of promoting blockchain application in carbon trading, fostering public participation, enhancing the cost of enterprise deceit, and increasing the initial willingness of government to effectively achieve carbon emission reduction goals.