Game Analysis Research Articles

Evolutionary Game Analysis of Government Regulation on Green Innovation Behavior Decision-Making of Energy Enterprises

Encouraging environmentally friendly innovation in energy companies is an essential way to stop global warming. Through ingenious integration of reputation and fairness preference, this research develops an evolutionary game model between the government and energy companies. This research investigates the dynamic evolution of green innovation strategy selection by energy firms operating under government supervision, using an evolutionary game model as a basis. This study examines how government regulations, including their subsidies and penalties, reputation, and fairness preference, affect the green innovation behavior of energy enterprises. The research shows that without considering the fairness preference, the subsidy and punishment of government regulation can improve the tendency of energy enterprises to choose green innovation behavior. At the same time, considering the reputation of energy enterprises to assume social responsibility can improve the tendency of energy enterprises to choose green innovation behavior. In the case of considering fairness preference, energy companies with strong fairness preference are more likely not to adopt green innovation and need more subsidies and penalties to choose green innovation; energy enterprises with weak fairness preference are more likely to adopt green innovation; green innovation will take place with fewer subsidies and penalties; reputation plays a stronger role in energy companies with weak fairness preferences. The study can give the government a theoretical foundation on which to build precise regulatory plans for various energy firms and encourage green innovation in those enterprises.

Game analysis of future rice yield changes in China based on explainable machine-learning and planting date optimization

ContextGlobal warming's escalating severity necessitates sophisticated approaches for predicting rice yield. Research QuestionCombining crop models with data-driven techniques, such as machine learning, can more effectively grasp the complex interplay of variables influencing crop growth. It remains a significant challenge to balance accuracy and interpretability in such hybrid models. MethodsThe research integrated the Decision Support System for Agrotechnology Transfer (DSSAT) with statistical and machine learning models respectively, to assess rice yield changes in China under four future Shared Socio-economic Pathway (SSP). SSPs are scenarios that integrate socioeconomic trends with greenhouse gas emissions and radiative forcing pathways, which affect the phenology and yield of rice. The Shapley Additive Explanation (SHAP) method was employed to interpret the model, effectively determining the interplay among variables influenced rice yields. Mitigated the negative impacts of climate change on rice yield through the planting date optimization. ResultsProjections indicate significant rice yield losses in China without CO2, worsening with increased radiative forcing (p < 0.001). Considering rising CO2, single-season rice yields are projected to increase by 0.1–3.6 %, early rice by 4.6–9.5 %, while late rice yields are still decrease by 2.3–8.8 %. The rising CO2 can offset yield losses for single and early rice but not for late rice. The hybrid approach which combined the Random Forest (RF) with the DSSAT performed best in predicting rice yield. Studies showed that rising temperatures caused rice yield losses in China, yet we found that Growing Degree Days (GDD) exerted a more negative impact (p < 0.001). In high-precipitation regions, deep soil moisture is more influential than shallow soil moisture, whereas the reverse was true in drier areas (p < 0.001). Advancing planting dates for early and single rice and delaying for late rice can increase yields (p < 0.001). Adjusting to optimal planting dates, single-season rice yields increased by 3.3–6.3 %, early rice increased by 9.7–18.3 %, while late rice still decreased by 1.0–4.7 %. ConclusionsWithout considering the impact of CO2, significant rice yield losses in China are projected. Even with the fertilization effect of CO2, rice yields remain negatively impacted by climate change. However, implementing appropriate measures, such as optimizing planting dates, can help Chinese rice production benefit under changing climate. ImplicationsThis study offers insights into balancing accuracy and interpretability in hybrid models and provides guidance for local policymakers to address future climate change.

Evolutionary game and simulation analysis of construction waste recycling from the perspective of stakeholders.

In current construction waste resource management processes, the effect of government supervision is unclear, and illegal treatment and low-quality reproduction of recycling and reprocessing enterprises by construction units are common. To improve the degree of resource utilization of construction waste and deeply explore the role of its key influencing factors, a tripartite evolutionary game model of construction waste resource treatment in which the government, construction units, and recycling and reprocessing enterprises are the research objects that considers public participation factors to be established. MATLAB is used to simulate the sensitivity of relevant parameters. The results show that: (1) An increase in government fines can regulate the behavior of enterprises; (2) Low government subsidies are conducive to the development of a tripartite stability strategy; and (3) An increase in the cost difference between the two strategies of the enterprise will weaken its willingness to carry out green operations (and after the cost difference exceeds the threshold, the enterprise will refuse to carry out green operations); (4) The reputation value brought by the public and the additional value added by reputation under the contrast effect have an incentive effect on the enterprise and the government; and (5) The peak value of the inverted U-shaped curve of government strategy choice is affected by the degree of public participation. Therefore, the government should propose rectifications in terms of fines and subsidies, and both companies can use technological innovation to reduce costs. At the same time, it is necessary to raise stakeholders' awareness of resource utilization and encourage the public to actively participate in supervision. The research conclusions can provide a decision-making reference for improving the utilization of construction waste resources and the efficient treatment of construction waste resources.

An evolutionary game analysis of incentive of industrial parks, government support and enterprise innovation willingness in China

Industrial parks are the important carriers to promote regional innovation and economic development. The policy preferences of the government, the support orientation of the industrial park and the innovation willingness of the enterprises in the park play a significant role in promoting the high-quality development of the industrial parks. In order to clarify the decision-making process of each subject, this paper constructs a triple evolutionary game model between the government, industrial park and enterprises in the park, Matlab software is used to conduct simulation research, and the strategy selection of each subject in the process of promoting high-quality development of the park is analyzed, as well as the influence of variables on the evolutionary game. Through numerical simulation, this study finds that the strategy choice of the government and the industrial park is influenced by the cost of innovation management for enterprises. In addition, the innovation willingness of enterprises is affected by the policy preference of the government and the support orientation of the industrial park, the excessive tax preference of the government will lead to negative innovation behaviors of the enterprises, the “inward incentives” support orientation of the industrial park can stimulate the enterprises’ innovation willingness on “active innovation”, the enterprises behavior of “active innovation” will strengthen the “inward incentives” support orientation of the industrial park in turn. The difference of the benefits and the costs between the two support orientations by the industrial park will lead to the equilibrium points stabilized at different strategy combinations. Based on these findings, countermeasures and suggestions are proposed in this study.

How to Promote Traditional Automobile Companies’ Intelligent-Connected Transformation under the New Dual-Credit Policy? A Tripartite Evolutionary Game Analysis Combined with Funding Time Delay

How to Promote Traditional Automobile Companies’ Intelligent-Connected Transformation under the New Dual-Credit Policy? A Tripartite Evolutionary Game Analysis Combined with Funding Time Delay

Are Residents Willing to Pay for Electric Cars? An Evolutionary Game Analysis of Electric Vehicle Promotion in Macao

This study uses an evolutionary game model to analyze the interplay between Macao residents’ willingness to purchase electric vehicles (EVs) and the government’s promotion strategies. It assesses the effectiveness of incentives like tax exemptions and price reductions. Despite these initiatives, challenges such as high initial costs, limited vehicle range, and long charging times continue to hinder the widespread adoption of EVs in Macao. Government subsidies increase the appeal of EV purchases, but if not managed carefully, they risk creating dependency. Simulation analysis shows that an active purchasing strategy by Macao residents can stabilize the model’s development. However, to achieve wider market penetration and environmental goals, this study highlights the need for the government to align subsidies with market dynamics and for residents to increase their environmental awareness. This study outlines actionable strategies for policy-makers, emphasizing the importance of infrastructure improvements and financial incentives in promoting electric mobility. Policy-makers should focus on expanding the network of charging stations to enhance the convenience and viability of EV usage. Additionally, implementing targeted financial incentives, such as subsidies or tax breaks, can lower the cost barrier for potential EV buyers, thereby increasing the attractiveness and adoption of electric vehicles.

Research on Agricultural Machinery Services for the Purpose of Promoting Conservation Agriculture: An Evolutionary Game Analysis Involving Farmers, Agricultural Machinery Service Organizations and Governments

Research on Agricultural Machinery Services for the Purpose of Promoting Conservation Agriculture: An Evolutionary Game Analysis Involving Farmers, Agricultural Machinery Service Organizations and Governments

Tripartite evolutionary game and simulation analysis of electric bus charging facility sharing under the governmental reward and punishment mechanism

Electric vehicles (EVs) are environmentally friendly with the features of low noise levels and zero tailpipe emissions. However, limited charging facilities have restricted the large-scale development of EVs, and electric bus charging facility sharing is a promising solution to this issue. While reducing charging time and improving facility utilization, this measure involves the interests of the government, bus operators, and electric car owners, requiring a systemic analysis of their interactions. Therefore, this study constructs a tripartite evolutionary game model under the governmental reward and punishment mechanism. The model examines the strategic decision-making process, influential factors, and evolutionary stability of three players, followed by simulation analysis. The results show that: (1) The evolutionary system may exhibit three stable states: (0,0,0), (1,0,0) and (1,1,1), and enhance the initial ratio of the three stakeholders will help evolve towards the ideal state. (2) Increasing rewards and penalties can both be meaningful, when penalties exceed rewards, the measures can be more effective. (3) Bus operators are more sensitive to incentive and penalty measures than electric car owners, and governments should pay more attention to them in the implementation process. The findings can provide references for the policy formulation on electric bus charging facility sharing.

The Impact of Transaction Credit on Credit Enhancement of Supply Chain Financing of Small and Micro-Logistics Based on Evolutionary Game Analysis

The issue of credit enhancement in supply chain financing for small and micro-logistics enterprises (SMLEs), as well as the factors that affect the decision-making of participants in supply chain financing transaction credit enhancement, is analyzed in this study. First, an evolutionary game model between financial institutions (FIs) and SMLEs was built. In contrast to bank loans, a novel mechanism for achieving credit enhancement based on transaction data in the transportation supply chain was established through a strict environment and an increase in default penalties to compel SMLEs to uphold their obligations. Furthermore, the stability analysis shows that the stable state convergence of the evolutionary game between FIs and SMLEs evolves to the stage where FIs offer loans to SMLEs. Finally, according to the simulation analysis on the real data collected from CHZL logistics park survey data, this work demonstrates that the fluctuation ranges of the strategy evolution process for the FIs and SMLEs are positively correlated with the intensity of the stochastic perturbation.

The Role of the Military in the 2023 Zimbabwe Elections: A Nested Game Analysis of Civil-Military Relations

The Role of the Military in the 2023 Zimbabwe Elections: A Nested Game Analysis of Civil-Military Relations

Evolutionary game analysis and efficiency test of water pollution control driven by emission trading: Evidence from Zhejiang Province, China

Presently, China is actively endorsing the pilot initiative for the remunerative use and trading of emission. By examining the operation and efficacy of emission trading in the context of water pollution control, one can contribute to the advancement and refinement of this system, thereby facilitating the attainment of regional pollution reduction, carbon reduction, and high-quality development objectives. In pursuit of this objective, we develop a theoretical framework for the local government and sewage enterprises evolutionary game of water pollution control, which includes two scenarios without considering and considering emission trading for studying the influencing factors and evolution trajectory of the game subject's. Through the stability analysis, the game interactive mechanism, the difference in evolutionary trajectory, and the response logic of the decision-making body in different situations become clearly visible. Further, the system sensitivity factors are analyzed by solving the partial derivation of the area formula of the phase diagram. And the efficacy of the sewage trading system in water pollution control in Zhejiang Province is empirically examined at the micro level by adopting the trading data of the first pilot area of sewage trading in the country and the case of pollution control in Jinhua City. The research reveals the following conclusions: Under specific circumstances, emission trading can incentivize businesses and even industries to enhance pollution control measures as a whole. The performance and degree of sensitivity factors vary across gaming systems, with public reputation evaluation and central government inspection serving as positive constraints. The initial cost of paid use of emission permits, as a fixed cost component for firms to address pollution, has no effect on the enterprises' behavioral actions to satisfy emission regulations. The findings can furnish local governments with a theoretical foundation and decision support in order to optimize regulatory strategies and enhance pollution control policies.

Evolutionary Game Analysis for Promoting the Realization of Construction Waste Recycling and Resource Utilization: Based on a Multi-Agent Collaboration Perspective

Evolutionary Game Analysis for Promoting the Realization of Construction Waste Recycling and Resource Utilization: Based on a Multi-Agent Collaboration Perspective

Equilibrium analysis in majority-based coalitional bargaining games

This paper introduces majority rule into coalitional bargaining games, adapting traditional models that rely on unanimous consent to more accurately mirror decision-making processes in real-world scenarios. We introduce a majority-based coalitional bargaining game (MBCBG), wherein coalitions pass proposals via majority votes. Our analysis of the stationary subgame perfect equilibrium (SSPE) not only establishes the necessary and sufficient conditions for SSPE strategy profiles but also confirms the existence of no-delay SSPEs in MBCBGs. We further delve into symmetric MBCBGs, delineating conditions that ensure equitable outcomes for homogeneous players. Furthermore, we provide a necessary and sufficient condition for the formation of the grand coalition under SSPEs. Additionally, we briefly explore how asymmetries in coalition values, proposal probabilities, and voting weights may influence both the dynamics of coalition formation and the expected equilibrium payoffs.

Evolutionary Game Analysis of Government–Enterprise Collaboration in Coping with Natech Risks

The synergistic interaction between emergency management departments and enterprises constitutes a fundamental mechanism for mitigating the risks of technological accidents caused by natural disasters (Natech). The efficacy of this collaborative approach is impacted by comprehensive risk analyses and the game between government and enterprise. Predicated on these premises, the evolutionary game analysis of government–enterprise collaboration in coping with Natech risk was carried out. Firstly, an evolutionary game model of government–enterprise collaboration in coping with Natech risk was constructed. Secondly, the evolutionary stability strategy (ESS) was developed. Finally, these strategies were substantiated through numerical simulations. The findings revealed that at lower levels of Natech risk, enterprises will choose low investment in coping capacity building, and emergency management departments will choose delayed disposal. Under moderate Natech risk, enterprises will increase their investments if emergency management departments persist with delayed strategies, and emergency management departments will react proactively if enterprises persist with low investment. Under a high Natech risk, a pattern of strategic misalignment emerges between the two entities. This study contributes a theoretical basis for the optimization of government–enterprise collaboration in coping with Natech risks.

Application of the game analysis method using the example of the second class in para table tennis

Application of the game analysis method using the example of the second class in para table tennis

Research on the Development of Green Supply Chain Finance Empowered by Blockchain: A Three-party Evolutionary Game Analysis Based on the Cost Perspective

Research on the Development of Green Supply Chain Finance Empowered by Blockchain: A Three-party Evolutionary Game Analysis Based on the Cost Perspective

Two-stage evolutionary game model on complex networks for emergency logistics based on blockchain platform

Enhancing the efficiency of emergency logistics is essential to reinforce the response capacity to emergencies. It requires collaborative efforts from both the emergency management departments and logistics enterprises. However, the capability for information docking between these organizations substantially influences the efficiency of emergency materials transportation. Blockchain, as an emerging information technology, has the potential to substantially enhance the efficiency and security of information docking through its unique characteristics. Additionally, logistics enterprises share information and resources based on the blockchain platform, aiming to ensure fast, efficient, and reliable collaborative transportation of emergency materials to impacted regions. Therefore, we propose a two-stage evolutionary game analysis of emergency materials collaborative transportation based on this platform. First, we develop a first-stage evolutionary game model to analyze the challenges associated with building a blockchain platform among emergency management departments and logistics enterprises. Subsequently, a second-stage evolutionary game model is devised to bolster the willingness of logistics enterprises based on this platform for collaborative transportation of emergency materials. Third, to validate the theoretical findings of the two-stage game model, two scale-free networks are employed for numerical simulations. As those networks evolve, the edges among nodes and the strategy choices of nodes in those networks likewise change. Numerical simulations are performed based on those networks to scrutinize the sensitivity of factors influencing strategic choice among game stakeholders. Ultimately, certain management insights gleaned from the findings can assist emergency management departments and logistics enterprises in making more informed decisions in the future.

Differential Game Analysis of Cross-Border Data Flow Regulation Under Technological Progress

Differential Game Analysis of Cross-Border Data Flow Regulation Under Technological Progress

Game Analysis of Different Transportation Modes in a Corridor Considering Carbon Emission Costs

Game Analysis of Different Transportation Modes in a Corridor Considering Carbon Emission Costs

The Impacts of Centralized Control on Mixed Traffic Network Performance: A Strategic Games Analysis

Cooperative Intelligent Transport Systems (C-ITS) address contemporary transportation challenges, as Connected Vehicles (CVs) can play a pivotal role in enhancing efficiency and safety. The role of central governing authorities in shaping traffic management policies for CVs influences decision-making processes and system performance. In this work, the role of central governing authorities in the traffic management of a mixed traffic network is examined, integrating System Optimum principles with game theory. More specifically, we introduce and develop a framework that models and analyses the strategic interactions between different stakeholders in a mixed traffic environment, considering central governing authorities with varying levels of control. The results indicate how the various levels of control of a central governing authority may have an impact on the network in terms of traffic measures. Through a strategic games analysis, the trade-offs associated with centralized control mechanisms are demonstrated and recommendations are offered for policymakers and practitioners to optimize traffic management strategies.