Stochastic evolutionary game and green transformation strategy selection for multi-agent systems under the digital economy

Dun Han & Yanyi Lu

SIMULATION: Transactions of The Society for Modeling and Simulation International2026https://doi.org/10.1177/00375497261436814article
AJG 1
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0.50

What the paper says

In the process of green transformation under the context of the digital economy, stakeholders such as the government, producers, and consumers find it difficult to reach an effective consensus in the game process due to differences in their interest appeals. This study constructs a tripartite stochastic evolutionary game model among the government, producers, and consumers, and analyzes the evolutionary stable strategies and evolutionary processes of the three parties. The research finds that: The existence of stochastic disturbance factors will affect the evolutionary path and slow down the speed at which the three parties evolve to stable strategies. During the strategy evolution process, supply–demand imbalance phenomena will exist. Market product circulation volume has a significant impact on strategy selection, and differences in product circulation volume under different strategy combinations will directly affect the strategy selection process. In terms of digital green transformation input costs, producers are mainly affected by their own transformation costs, while consumers are affected not only by their own transformation costs but also by producers’ transformation investments. The development of the digital economy can reduce the difficulty for producers and consumers to evolve toward digital green strategies, and sensitivity to emission reduction effects is also an important factor influencing strategy selection. Therefore, the government should formulate reasonable subsidy–penalty policy combinations, dynamically regulate market product circulation volume, implement differentiated incentives for different industries and groups, and promote supply–demand synergy toward the evolution of digital green strategies.

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https://doi.org/https://doi.org/10.1177/00375497261436814

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@article{dun2026,
  title        = {{Stochastic evolutionary game and green transformation strategy selection for multi-agent systems under the digital economy}},
  author       = {Dun Han & Yanyi Lu},
  journal      = {SIMULATION: Transactions of The Society for Modeling and Simulation International},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/00375497261436814},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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