Search Results (63)

Credit supervision of practitioners in the water conservancy construction market, a vital pillar of national infrastructure development, significantly impacts project safety and the maintenance of order in the industry. From the perspective of indirect supervision, this study constructs a tripartite evolutionary game model involving government departments, enterprises, and practitioners to analyze the dynamic evolution mechanism of credit supervision. By examining the strategic interactions among the three parties under different regulatory scenarios, we identify key factors influencing the stable equilibrium of evolution and verify the theoretical conclusions through numerical simulations. The study yields several key insights. First, while government regulation and social supervision can substantially increase the likelihood of practitioners’ integrity, relying solely on administrative regulation has an efficiency limit. Second, the effectiveness of the reward and punishment mechanism of the direct manager plays a crucial leveraging role in credit evolution. Lastly, under differentiated regulatory strategies, high-credit practitioners respond more strongly to long-term cost optimization, while low-credit practitioners are more effectively deterred by short-term, high-intensity disciplinary actions. Based on these findings, this study proposes a systematic governance framework of “regulatory model innovation–corporate responsibility enhancement–social supervision deepening.” Unlike previous studies, this framework adopts a comprehensive approach from three dimensions: regulatory model innovation, corporate responsibility enhancement, and social supervision deepening. It offers a more holistic and systematic solution for refining the credit system in the water conservancy construction market, providing both theoretical support and practical approaches. Full article

This study adopts an evolutionary game theory framework and focuses on the strategic interaction between brands and KOLs. It examines how the two parties interact under conditions of uncertainty and risk, especially when the KOLs’ contract fulfillment capability is low, and how they adjust strategies to achieve sustainable collaboration. Different from previous studies, this paper not only examines objective parameters such as commission rate, brand value, return cost, and reputation risk, but also introduces behavioral factors, including risk preference, loss aversion, and the psychological perception of gains and losses. By modeling the decision-making process of KOLs and brands under uncertainty and risk, the key factors affecting the evolution of cooperation strategies are identified. The simulation results show that although the cooperation strategy (such as information disclosure and truthful promotion) can achieve stability under certain conditions, the system is highly sensitive to external factors (such as environmental uncertainty) and internal psychological factors (such as risk preference and loss sensitivity). This study provides practical suggestions for brands and KOLs to promote long-term cooperation, emphasizing the importance of incentive coordination, reputation risk management, commission structure optimization, and psychological perception regulation. These findings provide practical guidance for enhancing the sustainability of brand–KOL collaborations. Full article

The intelligent connected vehicle (ICV) industry encounters substantial challenges related to technology, policies, and funding. Its development relies not only on the close collaboration and technological innovation between carmakers and technology companies but also on the support of government’s incentive policies. Therefore, this paper establishes a tripartite evolutionary game model that involves governments, carmakers, and technology companies to investigate the stability equilibrium strategy of multi-party participation in promoting the development of the ICV industry. In addition, by analyzing relevant regulations and company annual reports, this paper conducts a simulation analysis to examine how government incentive policies and benefit distribution mechanisms impact the evolutionary trajectory. Several insightful and practical conclusions are drawn. First, in the early stages of industrial development, the government’s infrastructure investment could promote the cross-border innovation cooperation between carmakers and technology companies, thereby accelerating the advancement of ICVs; however, the long-term impact of the sustained investment remains limited. Second, the incremental government subsidies for carmakers and technology companies within limits could increase the probability of them choosing to cooperate and innovate with each other. Still, the excessive subsidies could result in unstable industry growth. Finally, the increase in the benefit distribution ratio for carmakers with professional technology in automotive technology and vehicle design has a positive effect on the development of the ICV industry. This paper expands the research scope of ICVs and provides theoretical insights for promoting the sustainable development of the ICV industry from policy and market viewpoints. Full article

With the booming development of the new energy vehicle (NEV) industry, the issue of power battery recycling has increasingly attracted attention. Standardized recycling of power batteries can reduce environmental pollution and promote sustainable resource utilization. This paper employs evolutionary game theory to construct two models of deposit systems for the recycling of new energy vehicle power batteries: one under market mechanisms and the other with government participation. The evolutionary stable strategies among vehicle manufacturers, consumers, and the government are examined, and the stable equilibrium points of the models are analyzed. Finally, Matlab is used to conduct a simulation analysis of the deposit system with government participation. The results indicate that the deposit system under market mechanisms is difficult to constrain consumer behavior, while the deposit system with government participation is conducive to promoting the achievement of long-term environmental protection goals. These findings provide valuable insights for policymakers in designing deposit–refund systems and contribute to advancing the sustainable development of the NEV industry. Full article

Today, the digital economy has pursued the required social and economic development, and enterprises can achieve green transition and long-term sustainability by relying on the digital platform ecosystem. However, the development of the digital economy and the rapid growth of platform governance have also generated some problems. This study’s purpose was to explore the issue of green governance of the digital platform ecosystem and to find effective methods of such governance under different life cycle stages based on multiple parties. This study used the tripartite evolutionary game method and analyzed the changes and effects of platform green governance under different development stages from the perspectives of government, platforms, and enterprises. The results indicate that in the early stages, digital platforms primarily relied on the government’s obligation to regulate. With the digital platform ecosystem’s evolution, the platform organization green governance and settled enterprises’ green transition effects gradually appeared, establishing the three common constraints of governance mode. Finally, when the digital platform ecosystem is in its self-renewal period, the government effect is reduced, with the platform itself and settled enterprises taking primary roles. The goal of this study is to enrich the theoretical basis of platform green governance and enlighten the management of different governance subjects. Full article

China’s power generation system has undergone reforms, leading to a competitive electricity market where independent producers participate through competitive bidding. With the rise of low-carbon policies, producers must optimize bidding strategies while reducing carbon emissions, creating complex interactions with local governments. Evolutionary game theory (EGT) is well-suited to analyze these dynamics. This study begins by summarizing the fundamental concepts of electricity trading markets, including transaction models, bidding mechanisms, and carbon reduction strategies. Existing research on the application of evolutionary game theory in power markets is reviewed, with a focus on theoretical constructs such as evolutionary stable strategies and replicator dynamics. Based on this foundation, the study conducts a detailed mathematical analysis of symmetric and asymmetric two-group evolutionary game models in general market scenarios. Building upon these models, a three-group evolutionary game framework is developed to analyze interactions within power producer groups and between producers and regulators under low-carbon mechanisms. A core innovation of this study is the incorporation of a case study based on China’s electricity market, which examines the evolutionary dynamics between local governments and power producers regarding carbon reduction strategies. This includes analyzing how regulatory incentives, market-clearing prices, and demand-side factors influence producers’ bidding and emission reduction behaviors. The study also provides a detailed analysis of the bidding strategies for small, medium, and large power producers, revealing the significant impact of carbon pricing and market-clearing prices on strategic decision-making. Specifically, the study finds that small producers tend to adopt more conservative bidding strategies, aligning closely with market-clearing prices, while large producers take advantage of economies of scale, adjusting their strategies at higher capacities. The study explores the conditions under which carbon emission reduction strategies achieve stable equilibrium, as well as the implications of these equilibria for both market efficiency and environmental sustainability. The study reveals that integrating carbon reduction strategies into power market dynamics significantly impacts bidding behaviors and long-term market stability, especially under the influence of governmental penalties and incentives. The findings provide actionable insights for both power producers and policymakers, contributing to the advancement of low-carbon market theories and supporting the global transition to sustainable energy systems. Full article

Under the low carbon goal, recycling power batteries (PBs) from new energy vehicles (NEVs) is a crucial measure to address resource shortages and reduce carbon emissions. This study examined the insufficient collaboration among the responsible entities and the imperfections in market mechanisms within the PB recycling system. We overcome the limitations of traditional tripartite evolutionary game models by developing a four-party evolutionary game model that incorporates the government, manufacturers, recyclers, and consumers to investigate the strategic interactions within the extended producer responsibility (EPR) framework. Using MATLAB 2023a numerical simulations and Lyapunov stability analysis, we found that the system’s stability and efficiency depend on stakeholder collaboration and effective government policy guidance. The system evolves toward a Pareto optimal state when all parties adopt proactive recycling strategies. Meanwhile, ensuring substantial profits for manufacturers and recyclers is critical for the feasibility and stable operation of compliant recycling channels. While manufacturers and recyclers are more sensitive to subsidies than consumers, consumer decision-making is key to market stability. Long-term excessive subsidies may lead to diminishing marginal benefits. Strategic recommendations are provided for policymakers and stakeholders to enhance the efficiency and sustainability of the PB recycling system. Full article

Herein, an evolutionary game model involving the government and practitioners during the registration phase was constructed based on the bounded rationality assumption of prospect theory. The evolutionary stability of equilibrium points was explored under scenarios of ineffective, effective, and highly effective regulation, respectively. The construction industry is a vital pillar of the national economy, and the credit regulation of practitioners in the engineering and construction sector is an essential component of the social credit system. This model forges the foundation for maintaining a well-ordered construction market. In order to illustrate the dynamic decision-making process of working professionals in the engineering and construction fields, numerical experiments were hereby conducted to examine important factors influencing the evolutionary stable outcomes, and comparative experiments were performed by adjusting the discount factor parameter settings. The research findings include the following: (1) evolutionary trends are consistently influenced by the risk preferences of the subjects; (2) inspection intensity exerts a stronger short-term impact on low-credit groups, yet unilaterally increasing inspection intensity has limited policy effectiveness; (3) process restructuring and technological advancements significantly influence the behavior of high-credit groups but have a limited impact on low-credit groups. Additionally, this paper suggests specific regulatory strategies from three perspectives: the role of industry associations, the design of short-term disciplinary mechanisms, and the adjustment of long-term regulatory costs. These strategies are grounded on the experimental results and adapted to the distinct characteristics of high- and low-credit groups. Full article

At present, the high complexity of the environment, the uncertainty of income, and the choice of strategies have attracted extensive attention from all walks of life who are committed to studying the game of collaborative innovation between government and industry–university–research. Based on this, first of all, with the help of stochastic evolutionary game theory and fuzzy theory, this paper constructs a multi-party stochastic evolutionary game model of green technology innovation about the government guidelines and the joint promotion of industry, universities, and research institutes. Secondly, it discusses the evolution law of behavior strategies of each game subject and the main factors to maintain the alliance’s stability under fuzzy income. The numerical simulation results show the following: (1) Reputation gains have a significant positive correlation with the evolution stability of alliance behavior, and the incorporation of reputation gains or losses will effectively maintain the cooperation stability of the alliance. (2) Under the influence of product greenness, government subsidies, and long-term benefits, it will promote the pace consistency of cooperative decision-making between industry, universities, and research institutes, and accelerate the evolution of alliances. (3) The enterprise’s ability and the research party’s ability will restrict each other. When one party’s ability is low, its willingness to choose a cooperation strategy may be slightly low due to technology spillover and other reasons. When the two parties’ abilities match, their behavior strategies will increase their willingness to cooperate with their abilities. Compared with the traditional evolutionary game, this study fully considers the uncertainty of the environment and provides theoretical support and practical guidance for the high-quality development strategy of the industry–university–research green technology innovation alliance. Full article

To address the pressing challenges of quality and sustainability in agricultural product supply chains, this paper proposes a multi-stakeholder collaborative governance framework. Adopting the perspective of collaborative governance and sustainability, the paper develops an evolutionary game model of the Chinese agricultural product supply chain. This model involves four key stakeholders: agricultural enterprises, the government, NGOs, and consumers. It integrates sustainability principles to ensure that the decisions of each stakeholder contribute to the quality and safety of agricultural products while also promoting long-term environmental and social well-being. The simulation results demonstrate the critical importance of multi-stakeholder collaboration in strengthening governance and promoting sustainability. Based on these findings, the government is advised to implement technology-driven oversight mechanisms, such as AI-based inspections and blockchain traceability. Additionally, a tiered penalty system should be established, escalating penalties for repeat offenders. Regulatory cost-sharing mechanisms can also help ensure continuous enforcement without imposing excessive financial burdens on any single party. NGOs play a vital role in exposing corporate violations and can be more effective through targeted financial support and crowdsourced monitoring platforms. Consumers, as active participants in governance, should be incentivized with reward-based reporting systems and verified compliance feedback, which influence enterprise reputation. Public–private sustainability partnerships and real-time transparency platforms can further facilitate active participation from all stakeholders. By implementing these measures, the regulatory framework can evolve from traditional enforcement to a dynamic, data-driven governance model, fostering long-term sustainability and risk reduction in agricultural production. Full article

Work safety governance is a critical component of corporate ESG (Environmental, Social, and Governance) performance, particularly in high-risk industries. Effective safety supervision systems not only protect workers’ wellbeing, a key social metric in ESG frameworks, but also enhance corporate governance through improved risk management and regulatory compliance. The supervisory system represents a major institutional innovation in China’s approach to addressing increasingly complex work safety governance challenges. This study constructs an evolutionary game model involving the central government, local government, and high-risk enterprises to analyze the evolutionary characteristics of stakeholder behaviors. Through system simulation, we examine how key parameter changes affect the stability of system equilibrium points. Our findings reveal that (1) the current supervisory system effectively incentivizes both local governments to conduct safety supervision and high-risk enterprises to comply with safety investment requirements. (2) While government penalty levels do not affect strategy combinations, both insufficient and excessive penalties slow the system’s evolution toward optimal states. (3) Local governments tend to choose non-regulatory strategies when transfer payments and enterprise subsidies are inadequate. (4) Insufficient supervision intensity from the central government leads to local government non-regulation, and although this can be addressed by increasing supervision intensity, excessive supervision reduces the system’s evolution speed toward ideal states. Based on these findings, we propose policy recommendations for rational supervision intensity control, scientific reward–punishment mechanisms, and enhanced safety information transparency. This framework provides insights into the relationship between governance mechanisms and corporate long-term sustainability, which has been shown to improve ESG standards. Full article

Digital intelligent supply chains strengthen industrial resilience and optimize economic efficiency in the timber industry. Information asymmetry and low collaboration efficiency remain key challenges across the timber supply chain. This study develops a three-party evolutionary game model examining digital collaboration between timber production and processing enterprises, finished product distribution and retail enterprises, and third-party service providers, introducing third-party service providers alongside traditional production and distribution enterprises. The model incorporates novel parameters including information sharing degree, value-added reliability gains, and free-riding coefficients to reflect real-world circumstances. Through equilibrium simulation and analysis, we identify four possible evolutionary states. The results demonstrate that successful digital collaboration in timber supply chains relies on three conditions: a high level of initial stakeholder involvement accelerates the formation of supply chain digital intelligent collaborative mechanisms, equitable benefit distribution maintains long-term cooperation, and integrated third-party services reduce implementation costs while improving information reliability. These findings provide a new perspective and reference for timber enterprises to implement digital transformation strategies. Full article

This paper constructs an evolutionary game model involving the “central government–local government–coal enterprises” to explore the impact mechanism of central environmental protection inspection on green coal mining. By analyzing the strategic behaviors of the key actors, this study identifies critical factors that influence their decisions. System simulations are conducted to assess the effects of key parameters on system stability and convergence. The findings indicate the following: (1) Increasing inspection costs weaken the central government’s support for green mining, with excessive costs potentially causing regulatory fatigue. Moderating inspection investments is key to sustaining long-term effectiveness. (2) Higher penalties for local governments improve the enforcement of green mining policies, particularly in the mid-term, showing that stringent penalties are an effective regulatory tool. (3) Lower technical costs and greater economic incentives encourage coal enterprises to adopt green mining practices, highlighting the role of innovation and profitability in driving green transitions. (4) Central government subsidies enhance local governments’ short-term enforcement but may lead to dependence if overused. Balanced subsidy policies are essential for sustained policy implementation at the local level. Based on these findings, the paper proposes policy recommendations to improve inspection mechanisms, optimize policy tools, and establish a collaborative regulatory system to ensure the long-term effectiveness of green coal mining. Full article

In the process of promoting demand-side management, the core stakeholder groups are government departments, power grid companies, and electricity users. Due to the different positions and conflicting interests of the three parties in the game, intense and complex battles will occur. This paper investigates a tripartite evolutionary game involving government, power grid companies, and electricity users in the context of demand-side management (DSM) and analyzes the dynamic interactions between government departments, power grid companies, and electricity users within the framework of DSM using evolutionary game theory. Using evolutionary game theory, we explore how incentives and strategic interactions among these three stakeholders evolve over time, affecting the stability of DSM policies. The model addresses the asymmetry in the decision-making process and examines the dynamic equilibrium outcomes under various scenarios. The results provide insights into the optimal design of incentive mechanisms to enhance DSM adoption. The findings offer practical recommendations to improve DSM policies, fostering balanced interests between government, grid companies, and users. This research contributes to a deeper understanding of strategic interactions in DSM, revealing how adaptive behaviors can enhance energy efficiency. It also underscores the importance of carefully designed incentive mechanisms in achieving long-term stability and cooperation among key stakeholders. Full article

With the rapid development of smart grids, the strategic behavior evolution in user-side electricity market transactions has become increasingly complex. To explore the dynamic evolution mechanisms in this area, this paper systematically reviews the application of evolutionary game theory in user-side electricity markets, focusing on its unique advantages in modeling multi-agent interactions and dynamic strategy optimization. While evolutionary game theory excels in explaining the formation of long-term stable strategies, it faces limitations when dealing with real-time dynamic changes and high-dimensional state spaces. Thus, this paper further investigates the integration of deep reinforcement learning, particularly the deep Q-learning network (DQN), with evolutionary game theory, aiming to enhance its adaptability in electricity market applications. The introduction of the DQN enables market participants to perform adaptive strategy optimization in rapidly changing environments, thereby more effectively responding to supply–demand fluctuations in electricity markets. Through simulations based on a multi-agent model, this study reveals the dynamic characteristics of strategy evolution under different market conditions, highlighting the changing interaction patterns among participants in complex market environments. In summary, this comprehensive review not only demonstrates the broad applicability of evolutionary game theory in user-side electricity markets but also extends its potential in real-time decision making through the integration of modern algorithms, providing new theoretical foundations and practical insights for future market optimization and policy formulation. Full article