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The governance of manufacturers’ greenwashing behaviors: A tripartite evolutionary game analysis of electric vehicles

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  • Liu, Changyu
  • Song, Yadong
  • Wang, Wei
  • Shi, Xunpeng

Abstract

Greenwashing seriously undermines the efforts toward a low carbon economy, and distorts quality information for green products including electric vehicles (EVs). However, it remains unclear how greenwashing behaviors (GWBs) can effectively be governed. Considering the formation mechanism of GWBs and collusion in EV certification processes, we constructed a tripartite evolutionary game model based on strategic interactions among manufacturers, certification authorities, and governments. Subsequently, we investigated the evolutionarily stable strategies (ESSs) and corresponding conditions of each game player and then conducted a simulation to explore the participants’ system equilibrium interactions. We also evaluated vital factor changes in three stakeholders’ decision-making, including initial strategy selection, the related cost, penalty, and reward. The results demonstrate that 1) the initial strategy selection is critical to the evolution of equilibrium strategies; 2) appropriate reward and punishment mechanisms can affect decision-making speed, which takes less time to reach stable evolution, and 3) related costs are acritical factors for every player in strategy selection. High supervision costs are severe impediments to governments aiming to enforce regulations, but lower certification and production costs could prompt manufacturers and certification authorities to choose appropriate strategies. This paper provides a theoretical explanation for GWBs, makes constructive suggestions for preventing manufacturers’ greenwashing, and sheds new light on an effective governance model for EVs.

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  • Liu, Changyu & Song, Yadong & Wang, Wei & Shi, Xunpeng, 2023. "The governance of manufacturers’ greenwashing behaviors: A tripartite evolutionary game analysis of electric vehicles," Applied Energy, Elsevier, vol. 333(C).
  • Handle: RePEc:eee:appene:v:333:y:2023:i:c:s030626192201755x
    DOI: 10.1016/j.apenergy.2022.120498
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