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Research on the optimal incentive and constraint mechanisms for corporate carbon information disclosure considering different market contexts: A network-based evolutionary game analysis

Chaoping Zhu, Yixuan Su, Ruguo Fan, Ruiheng Xu and Bing Li

Energy Economics, 2025, vol. 142, issue C

Abstract: Corporate carbon information disclosure (CCID) is essential for facilitating a low-carbon transition in energy-intensive industries and achieving the “dual carbon” goals. However, many enterprises fail to fulfill their CCID obligations. This paper develops a complex network evolutionary game model for examining CCID in diverse market contexts and determining optimal incentive and constraint mechanisms. The findings reveal that: (1) The optimal single tax discount incentive or joint punishment constraint in a perfectly competitive market is lower than that in a monopolistically competitive market. (2) There is no notable discrepancy in the optimal single financial penalty constraints between the two market contexts. (3) The optimal combined incentive and constraint and the evolutionary time of CCID in a perfectly competitive market are less than those in a monopolistically competitive market. (4) Joint punishments reduce the optimal constraint for the complete diffusion of CCID compared to financial penalties, and combined mechanisms shorten the evolutionary time of CCID compared to the single mechanisms. This study not only identifies the optimal incentive and constraint mechanisms for CCID under single and combined scenarios, but also offers practical insights for the formulation of effective strategies to guide CCID in different market contexts.

Keywords: Carbon information disclosure; Incentive and constraint mechanism; Complex network evolutionary game; Energy-intensive industry (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:142:y:2025:i:c:s0140988325000301

DOI: 10.1016/j.eneco.2025.108207

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Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant

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