Evolutionary Game Model Research Articles

Evolutionary Dynamics of Passive Housing Initiatives in New Rural Construction

In the context of China’s ambitious dual carbon goals, this study introduces an innovative reward–penalty incentive mechanism, grounded in evolutionary game theory, to develop a tripartite evolutionary game model concerning the construction of passive rural housing. This research meticulously analyzes the equilibrium and stability strategies of all involved parties and employs data simulation to examine the influence of varying parameters on the game dynamics. Our findings reveal that the government’s cost–benefit calculations significantly influence its decisions regarding passive housing initiatives. The study identifies optimal cost and benefit strategies for various developmental phases. Furthermore, the level of governmental rewards and penalties plays a crucial role in determining whether enterprises and farmers opt for passive housing solutions. The study establishes the efficacy of different incentive schemes at various stages. Importantly, the economic interests of enterprises and farmers are pivotal in their decision-making process regarding passive housing. The study advocates for a comprehensive set of measures to safeguard these interests, with a special emphasis on protecting farmers. In conclusion, this research offers substantial guidance for policy decisions aimed at transforming existing rural housing into passive housing, thereby aligning with China’s environmental and sustainability objectives.

How to escape the dilemma of carbon emission reduction policies implementation under Chinese fiscal decentralization?

As the world's largest energy consumer and carbon emitter, China has undertaken a series of low-carbon policies. However, its top-down authoritarian governance, coupled with economic decentralization, challenges policy effectiveness. To facilitate the implementation of incentive-compatible carbon emission reduction policies, this study proposes a tripartite stochastic evolutionary game model involving the central government, local governments, and enterprises. Replicator dynamic equations are then employed to assess how uncertainty shapes participants' behavioral choices. Furthermore, a real-case example validates the theoretical findings and supports subsequent arguments: (1) initial strategy choices by stakeholders influence their transitions but have minimal long-term impact on the final convergence pattern; (2) stakeholders' dedicated efforts, especially central government supervision, shape evolutionary outcomes during policy implementation; (3) the escalation of penalties contributes to policy execution, while transfer payment allocation warrants thorough evaluation as it affects the strategies of both local governments and enterprises; and (4) the incorporation of random elements introduces disruptions in stakeholder evolutionary paths, resulting in deviations and fluctuations from expected patterns. This study not only highlights the importance of resolving the dilemma in implementing emission reduction policies through effective coordination among stakeholders but also reduces uncertainty related to unobserved factors, ensuring a comprehensive range of game outcomes.

Does government policy matter in the digital transformation of farmers’ cooperatives?—A tripartite evolutionary game analysis

Farmers’ cooperatives, as one of the new types of agricultural businesses, are an effective carrier for the digital transformation of agriculture, yet existing studies have paid less attention to how farmers’ cooperatives realize digital transformation. As agricultural economic organizations embedded in social networks, the digital transformation of farmers’ cooperatives requires the joint efforts of governments and companies. Based on the evolutionary game theory, this paper constructs a tripartite evolutionary game model of the government, digital technology companies and farmers’ cooperatives, and simulates and analyzes the behavioral decisions of different participants in the digital transformation of farmers’ cooperatives from the perspective of government policy. The results show: Medium government subsidies can effectively promote the digital transformation of farmers’ cooperatives, and strong subsidy policies increase the government’s financial burden, which is not conducive to policy sustainability. Strong government regulation facilitates digital technology companies to actively provide high-quality services for the digital transformation of farmers’ cooperatives, but government regulation does not have a significant impact on the strategic choices of the government and farmers’ cooperatives. When farmer cooperatives and digital technology companies are in a medium or high level of cooperative trust or when the number of labors saved by digital transformation reaches a certain level, farmers’ cooperatives opt for digital transformation even if the government withdraws from policy intervention.

Healthcare Supply Chain Resilience Investment Strategy Analysis Based on Evolutionary Game

Healthcare is considered one of the necessities for sustaining life. However, frequent emergencies raise the risk of supply chain disruption, seriously threatening people’s lives and health security. Therefore, building a resilient healthcare supply chain is an important initiative to manage the healthcare crisis effectively. Based on the secondary supply chain formed by medical supply manufacturers and retailers, this paper constructs an evolution game model of resilience investment decisions under the non-disruption and disruption symmetry scenarios of the supply chain and analyzes the stabilization strategies employed by both parties based on their asymmetry strategy choices. Subsequently, the numerical simulation is used to analyze the impact of various parameters on the evolutionary results and their evolutionary trends. The results of the study show that additional benefits from resilience investment, potential costs, disruption losses, market encroachment revenue, “free-rider” benefits, additional benefit increase coefficient, resilience investment reduction coefficient, disruption loss reduction coefficient, additional unit cost reduction coefficient, and market encroachment revenue coefficient all influence the resilience investment decisions. Finally, based on the simulation results, specific recommendations are formulated to improve the resilience of the healthcare supply chain.

Research on collaborative innovation behavior of enterprise innovation ecosystem under evolutionary game

Establishing an innovation ecosystem revitalizes enterprises by fostering collaboration with other entities within the system. This collaboration results in increased resources for innovation and development, further strengthening participants' innovation and survival capacities. As the existing literature on collaborative innovation behavior within innovation ecosystems is relatively limited, the primary objective of this study is to investigate the evolutionary process and impact factors of players' collaborative innovation behavior in the enterprise innovation ecosystem (EIE). This study establishes an evolutionary game (EG) model that includes three players in an EIE to analyze their collaborative innovation behaviors in scenarios where their initial strategic probabilities are low, medium, and high. The simulation results indicate the existence of six potential evolutionary stable strategies (ESSs) within the system. The ideal ESS identified in this three-party evolutionary game model is characterized by “active collaboration, active collaboration, participation”. Furthermore, the player's behaviors in different states are affected by initial probability, synergy sensitivity, transformation efficiency, output elasticity, subsidy, punishment, and public impact. The results of this study reveal the mechanism of collaborative innovation behavior among different players in the EIE, providing beneficial references for its sustainable development.

The Effect of Marine Pastures on Green Aquaculture in China

Under the double pressures of economic growth and ecological environment protection, sea green transformation and the sustainable development of mariculture are critical. This paper constructs an evolutionary game model with the government as the main body and mariculture farmers (enterprises) as the main body and puts forward the research hypothesis. Based on 2006–2019 longitudinal data of nine provinces along China’s coast, using multi-period Difference-in-Difference (DID) and dual robust estimation, we empirically investigate the national oceanic ranch demonstration zones for the influence of the green sea aquaculture and their mechanism of action. The results showed that (1) the efficiency of green level of mariculture industry in China is not high, and the establishment of national marine pasture demonstration zone has not effectively promoted the improvement of green level of mariculture industry; (2) the institutional environment, unreasonable industrial structure, and lack of scientific and technological innovation have an effect on the national oceanic ranch demonstration area as the main causes of failure to effectively promote marine green farming; (3) the establishment of the national multi-period demonstration area in the north significantly hindered the growth of the green level of mariculture and fell into the “policy trap”, while the establishment of the national multi-period demonstration area in the south significantly promoted the growth of the green level of mariculture. The conclusions of this paper provide an empirical basis and reference for the improvement of the national marine pasture demonstration zone policy and the green transformation of mariculture to a certain extent.

A study on the evolutionary game theory of third-party governance of environmental pollution based on the quasi-co-owned relationship of pollution rights

The third-party governance of environmental pollution and the pollution rights trading system are two typical examples of modern environmental governance systems. In China, the quasi-co-owned relationship of pollution rights between pollution-discharging and pollution-control enterprises is the link through which to achieve synergy between the two factors. To explore how to achieve such synergy, first, the “principle of no-fault liability” is introduced, and the responsibilities of pollution-discharging enterprises and pollution-control enterprises are defined. Second, based on the quasi-co-owned relationship of pollution rights, a revenue-sharing mechanism for pollution rights trading is designed. Finally, a tripartite evolutionary game model consisting of pollution-discharging enterprises, pollution-control enterprises and local governments is constructed, and numerical simulation is performed. The results are as follows. 1) By setting a reasonable market trading price for pollution rights, a reward and punishment distribution coefficient, an improvement in reputation gains, and a saving in pollution rights indicators become conducive to the formation of cooperative relationships between pollution-discharging and pollution-control enterprises, for which the reasonable range of the reward and punishment distribution coefficient is (0.3, 0.4]. 2) Regardless of whether a government subsidy is provided, the optimal range of the revenue-sharing coefficient from pollution rights trading is [0.5, 0.6]. 3) When a government subsidy is withdrawn, increasing the market trading price and surplus indicators of pollution rights can promote the stable operation of the third-party governance model. 4) An increase in policy support and administrative accountability of higher levels of government and a reduction in supervision costs for local governments can help these parties effectively avoid addressing the absence of local government supervision. It is recommended that third-party governance enterprises participate in pollution rights trading to implement the main responsibilities of pollution-discharging and pollution-control enterprises and to set a reasonable revenue-sharing coefficient and reward and punishment distribution coefficient of pollution rights.

How to improve the quality of emergency supplies? A tripartite evolutionary game model

How to improve the quality of emergency supplies? A tripartite evolutionary game model

Evolutionary analysis of nuclear wastewater collaborative governance based on prospect theory

Dealing nuclear wastewater into the sea significantly threatens the global ecological environment and public health. Existing research primarily focuses on the roles of emission and regulatory bodies, often overlooking the collaborative interactions between these entities. This study extends traditional marine governance strategies by considering upstream and downstream countries as research subjects. We first establish an evolutionary game model for the collaborative governance of nuclear wastewater between upstream and downstream countries, utilizing the Prospect theory and Evolutionary Game Theory. Subsequently, numerical simulations are employed to explore different entities' decision-making behaviors and influencing factors. Our findings indicate that: (1) initial willingness affects the time it takes for the system to reach a stable state; (2) the benefits and costs of proactive governance strategies influence decision-maker's behaviors; (3) subjective factors (risk preference, loss aversion) affect the strategic choices. This research provides a scientific basis for understanding different countries' selection of nuclear wastewater governance strategies.

How can the recycling of power batteries for EVs be promoted in China? A multiparty cooperative game analysis

While electric vehicles (EVs) are developing at a high speed in China, the power battery market is facing a decommissioning peak. The problem is that the recycling situation of domestic power batteries is not ideal, partly due to neglect by consumers. By considering the recycling system, mode, and policy of China’s EV power batteries, we construct a tripartite evolutionary game model of the government, consumers and EV manufacturers; analyse the stable strategy adjustment mechanisms of tripartite participation in this recycling cooperation game; and simulate the tripartite evolutionary game. The results show that when the initial willingness of the government, consumers and EV manufacturers to recycle power batteries is not strong, the government takes the lead, driving EV manufacturers and consumers to participate in power battery recycling. When the government, consumers and EV manufacturers have medium or high levels of initial willingness, the government evolves and chooses a nonregulation strategy. In addition, by simulating the impact of changes in consumer-related influencing factors on this tripartite evolutionary game, we find that subsidies for recycling power batteries are a key factor affecting consumers’ strategy choices and that boosting recycling compensation for consumers can improve their enthusiasm to participate in such recycling. Therefore, to improve the recycling of power batteries for EVs, in terms of both efficiency and percentage of deployment, the Chinese government should strengthen public education on power battery recycling, further integrate informal recycling channels, and balance the distribution of profits among consumers for recycling compensation.

Impact of dual-credit policy on diffusion of technology R & D among automakers: Based on an evolutionary game model with technology-spillover in complex network

Dual-credit policy promotes new-energy vehicle (NEV) automakers to invest in technology R & D by granting NEV with better technological performance to higher NEV-credit. Based on the complex network evolutionary game theory, this paper constructs a technology R & D diffusion model of automakers considering the technology spillover effects, and explores the dynamic impact of adjusting different dual-credit policy parameters on technology R & D diffusion among automakers. Our results show that: (1) increasing the annual increment of NEV-credit requirement ratio can encourage more NEV automakers to invest in technology R & D, but also lead to significant increase in NEV-credit price. (2) Reducing the CAFE target coefficient can simultaneously promote the diffusion of NEV technology R & D and GV green-technology R & D, but excessive reduction can hinder GV automakers from entering NEV market. (3) Lowering the upper limit of credit per unit NEV suppresses the diffusion of NEV technology R & D. (4) Reducing technology-spillover is conducive to the incentive of dual-credit policy on the diffusion of technology R & D.

Can government subsidy promote the light-blue fishery upgrade to deep-blue fishery?

IntroductionThe expansion of fishery development from offshore to deep-sea areas has become essential for countries to address environmental constraints and ensure food security. This study aims to establish a cooperative development model for deep-blue fishery involving the government, fishery enterprises, and consumers.MethodsWe constructed an evolutionary game and simulation model to analyze the government's deep-blue fishery subsidy strategy. The model considers the interactions between the government, fishery enterprises, and consumers, evaluating how different subsidy strategies influence the development of deep-blue fishery.ResultsOur results demonstrate that government subsidies can stimulate the growth of deep-blue fishery from both the demand and supply sides. Specifically, the likelihood of government subsidies positively affects fishery enterprises' engagement in deep-blue fishery development and consumers' willingness to purchase deep-blue fishery products. The evolutionary game system reaches different steady states based on the cost-benefit changes for the government, fishery enterprises, and consumers, leading to various optimal subsidy strategies.DiscussionThe findings indicate that the amount of government subsidy should be optimized rather than maximized, as excessive subsidies may not yield proportionate benefits. Additionally, subsidizing fishery enterprises proves to be more effective in promoting the development of deep-blue fishery compared to subsidizing consumers. These insights can guide policymakers in designing efficient subsidy strategies to foster sustainable deep-sea fishery development.

How to promote the application of green pesticides by farmers? Evolutionary game analysis based on “government–farmer–consumer”

Green pesticide use, as a key means to reduce pesticide use, plays a crucial role in promoting environmental and food safety. However, the effectiveness of green pesticide use policies in China falls short of expectations. Existing research mainly examines the policy promotion issues of green pesticide use from a static and single-agent perspective. However, green pesticide use behavior is a dynamic process influenced by multiple factors, including the government, farmers, and consumers. This paper builds an evolutionary tripartite game model of the government, farmers, and consumers from the perspective of dynamic strategy evolution and explores the evolutionary conditions that affect the stability of the tripartite game strategy during green pesticide application. The results show that 1) through different partnership models, the government, farmers, and consumers can evolve to a stable state. 2) Keeping the government’s regulatory intensity in the market for green agricultural products within a reasonable range will help farmers apply green pesticides. 3) Users’ preference for high-quality vegetables will increase the market selling price of green products. 4) Maintaining the government’s ecological subsidies for green pesticides will help stimulate farmers’ enthusiasm for using green pesticides. Therefore, the government should appropriately strengthen ecological subsidies and market supervision, guide consumers’ green consumption behavior, and encourage farmers to use green pesticides.

How to select green technology acquisition paths for enterprises: An analysis based on evolutionary game theory

AbstractAs an important method of reducing pollution, green technology innovation (GTI) is receiving more attention. However, facing the challenges in conducting GTI, it is crucial for enterprises to find the optimal path to acquire green technology. This paper investigates how high‐pollution manufacturing enterprises make decisions on independent innovation and green technology introduction under government intervention and public involvement. The influences of other factors, such as media attention and product market competition, have also been considered in the tripartite evolutionary game model. The simulation after applying MATLAB indicates that government intervention and public participation have a significant impact on the decision‐making of green technology acquisition paths for enterprises. Government subsidies and penalties are important policy tools for enterprises to make decisions on the selection of green technology acquisition paths. Meanwhile, reputational incentives or losses brought from public involvement are also essential in encouraging government intervention and green technology acquisition of enterprises. Finally, the extent to which the changes in various influencing factors affect the selection of enterprises' green technology acquisition paths have been tested and simulated. This paper aims to provide policy implications for governments, as well as decision‐making strategies for enterprises that urgently require green transition to achieve sustainable development.

LSTEG: An evolutionary game model leveraging deep reinforcement learning for privacy behavior analysis on social networks

With the investment of third-party companies, various accurate recommendation services have emerged on social network platforms, making convenience and privacy concerns coexist for users. Platforms, users, and third-party companies have conflicts of interest around privacy issues, and privacy protection is not the only goal for them. For the analysis of multi-party behaviors related to privacy, a long short-term evolutionary game model (LSTEG) is proposed, where the long-term and short-term evolutionary processes describe the dynamics between three parties and between users, respectively. Their dynamic evolutionary processes are described by mean dynamic equations and all possible stationary-state conditions are analyzed theoretically. Deep reinforcement learning is adopted to solve these evolutionary stationary states and to reveal the rules of interdependence between long-term evolution and short-term evolution. Experiments conducted on real-world datasets show that this work can help platforms, users, and third-party companies to get a better sense of what is occurring in dynamic network environments.

Agent-Network-Computation-Based Evolutionary Game Model in Language Competition

Agent-Network-Computation-Based Evolutionary Game Model in Language Competition

How to promote cooperative innovation in environmentally friendly technology: a case of agricultural biotechnology in China

This study explored the factors influencing cooperative innovation in environmentally friendly agricultural biotechnology in China. First, we constructed an evolutionary game model comprising the factors of net income of cooperative innovation, net income of independent innovation, market constraints, and government subsidies. Using MATLAB simulation, we assigned different values to the aforementioned variables to explore the evolutionary trend of innovators’ willingness to cooperate. Results showed that when the values of net income of cooperative innovation, net income of independent innovation, market constraints, and government subsidies exceeded the threshold, innovators’ willingness to cooperate was significantly enhanced. Furthermore, the proportion of innovators who cooperated with others gradually increased to 100%; otherwise, it gradually decreased to 0%. Comparing the simulation curve with the real evolution curve of cooperative innovation in agricultural biotechnology in China, we found that the gradual decline in the willingness to cooperate could be due to insufficient subsidies for cooperative innovation, low income from cooperative innovation, weak profitability of innovators, and weak market constraints.

Game analysis on PPP model operation of abandoned mines ecological restoration under the innovation of central government's reward and punishment system in China.

There is a huge funding gap in the abandoned mines ecological restoration in China. It is of great research value to explore how PPP model can better introduce social capital into the low-profit ecological restoration of abandoned mines. Based on the innovation perspective of the central government's reward and punishment system, this paper constructs an evolutionary game model of "local government-social capital", analyzes the interaction and behavior mechanism of core stakeholders in the operation process of abandoned mines ecological restoration PPP mode, and discusses the influence of evolutionary equilibrium strategy and parameters change on evolutionary strategy under different scenarios by Matlab simulation. The research shows that the abandoned mines ecological restoration needs the support of the central government. When the local government lightly punishes the low-quality service of social capital, the central government needs to pay higher costs to promote all parties to actively participate in the operation and supervision of the PPP project. The revenue and cost of government supervision, the operating subsidy for social capital and the cost saved by social capital in providing bad service are the key factors affecting the evolution of the game between government and social capital. Punishment can effectively spur social capital to keep the contract and operate in the project, but the punishment effect will be ineffective without government supervision. Finally, some suggestions are put forward, such as establishing a long-term supervision mechanism and a reasonable income mechanism for PPP projects, increasing penalties for violations, attracting third parties to reduce supervision costs and strengthening communication between the two parties, so as to make the project take into account the economic performance of social capital and the social welfare of government departments, and achieve dual Pareto improvement.

The Centralized Meal Service Delivery Mode

Meal delivery with high delivery timeliness requirements in demand-intensive areas often leads to several issues such as chaotic terminal management and low efficiency during peak times, reducing consumer satisfaction and increasing complaints. This study constructs a dynamic model of meal delivery systems to analyse the operational models and centralized dispatching modes in Guangzhou University City, and applies an evolutionary game model to explore the decisions from the perspectives of government, meal suppliers, riders, and consumers. The study analyses how centralized dispatching mode affects the performance of delivery systems and its impact on the willingness of government, merchants, and riders to participate. The results indicate that demand-intensive areas, centralized dispatching modes have sustainable advantages in terms of cost and efficiency. The effectiveness is closely related to the intensity of government intervention (supervision and support), but weakly related to the timing of intervention. Consumer preferences, shaped by consumer type and perceived value, affect the benefits of participating in a centralized dispatch mode, but not the willingness of meal suppliers to participate. The evolutionary framework in this study provides valuable references for the quantitative evaluation of the meal delivery system, theoretical support for the decision-making of the participants of the meal delivery system, and a research framework for the relevant decision-making scenarios, so as to optimize the allocation of meal resources and promote the sustainable development of meal delivery.

Risk-averse behavior and incentive policies: A new perspective on spatial–temporal traceability supervision in construction logistics supply chains

Spatial-temporal decision support systems (STDSS) serve as a crucial strategy for enhancing operational governance and mitigating risk within construction logistics. However, construction supply chains involve many opaque stakeholders, hindering whole industry compliance monitoring. This research formulates a tripartite evolutionary game model that scrutinizes the strategic interactions among government regulators, carriers, and contractors, thereby offering insights into the collaborative supervision outcomes shaped by these stakeholder engagements. Government regulators choose intelligent supervision incentives versus regular oversight. Carriers decide whether to invest in STDSS or not. Contractors cooperate by enrolling or declining STDSS. As key STDSS investors, carriers’ decisions are investigated under varying risk preferences in an extension model. This examines how government incentives influence long-term intelligent supervision and risk aversion behavior emergence to improve safety and quality across construction supply chains. Our findings indicate that increased adverse events motivate government regulators to adopt STDSS incentives for oversight, though carriers and contractors are not necessarily prompted to implement STDSS themselves. Escalating risk aversion reduces carrier STDSS adoption likelihood as they maintain basic services. Carriers perceiving contractor free riding as unfair competition also demotivates STDSS rollout. Although larger subsidies initially raise STDSS implementation probability, carriers become unwilling to adopt STDSS over time even with greater subsidies. In summary, adverse events drive regulator but not necessarily carrier and contractor STDSS adoption, while risk aversion, perceived fairness and changing subsidy effectiveness over time shape carrier decisions.