Evolutionary Game Analysis Research Articles

Digitalization drives green transformation of supply chains: a two-stage evolutionary game analysis

Digitalization drives green transformation of supply chains: a two-stage evolutionary game analysis

WIPO initiative of transforming traditional resources and sharing rights: An evolutionary game analysis and a Chinese context.

WIPO-GRTKF specifies, for the first time, how traditional resources embodied by traditional knowledge, genetic resources, and folklore can be defined, and what the relationship between original rights, and rights arising from the transformation and utilisation of traditional resources can be understood. Committed to promoting innovation, shared benefits and balanced interests, WIPO tries to achieve a balance between preventing users from violating holders' original rights through the acquisition of patent, trademark and copyright, and incentivizing all stakeholders to transform traditional resources to improve the greater good. The document triggers a new round of disputes among interest groups over how to share rights arising from the transformation and utilisation of traditional resources. Using an evolutionary game model to simulate how holders and users transform traditional resources, and share rights, we find that when the two sides choose to cooperate to apply for transformation and give consent to use, their benefits are maximised and strategies stabilised. We suggest that in the transforming process, holders' rights and users' interests be given equal emphasis, and an autonomous and open mode combining statutory licensing, and justified utilisation of original rights be employed. We advocate for a hybrid legislative arrangement that integrates the incentive of IPRs as private rights, and the safeguard of public rights. In the dual subject system, both users and holders enjoy multiple rights in the process of protecting and transforming traditional resources. The Chinese approach to transforming traditional resources and sharing their rights will contribute to sustainable development of traditional resource industry across the globe.

Evolutionary game analysis of data sharing among large and medium-sized enterprises in the perspective of platform empowerment

With the swift advancement of the global digital economy, data has emerged as a critical component in fostering the integration of large enterprises with small and medium-sized enterprises (SMEs). Nevertheless, due to disparities in resources and capabilities between these entities, there is a deficiency in the willingness to share data, hindering the full actualization of data’s potential value. Hence, it is imperative to facilitate a novel cooperative development paradigm wherein platforms enable data sharing among large enterprises and SMEs. In this paper, we construct a tripartite evolutionary game model encompassing large enterprises, SMEs, and digital platforms, examine the evolutionary stable strategies adopted by these entities in the data sharing, and use numerical simulation to explore the system’s evolutionary stability under various influencing factors. Contrasting with prior research, this study considers the heterogeneity of enterprise scale and delves into the data sharing dynamics between large enterprises and SMEs. Simultaneously, it positions the digital platform as a player in the game, examining its impact on data sharing among the enterprises. Findings indicate that: (1) SMEs exhibit greater eagerness for data sharing compared to large enterprises, which display a U-shaped influence during the process; (2) Digital platforms are particularly sensitive to costs, with the platform’s initiative and the service quality will affect enterprises strategic choices; (3) Government subsidies positively encourage tripartite cooperation, and robust data security governance framework is crucial for enterprises. Finally, based on the results of the study and combining with the current situation of digital economy development, it puts forward the suggestions for promoting platforms to empower large enterprises and SMEs to realize data sharing and the prospects for future research.

Tripartite evolutionary game analysis of carbon emission reduction behavior strategies under government regulation

Tripartite evolutionary game analysis of carbon emission reduction behavior strategies under government regulation

An evolutionary game analysis of algorithmic indirect copyright infringement from the perspective of collusion between UGC platforms and direct infringers.

User-generated content (UGC) is developing rapidly as an emerging platform form, however, the problem of indirect copyright infringement by algorithms is becoming more and more prominent, and infringement governance has become a key act in the development of UGC platforms. When infringement occurs, recommendation algorithms expand the scope and results of infringement, while platforms choose to conspire with direct infringers for their own interests, making it difficult for infringed persons to defend their rights. In order to analyse the influence of different factors in the platform ecosystem on the subject's behavioural strategies, a "platform-infringer" evolutionary game model is constructed, and numerical simulation is used to verify the correctness of the stable results. Based on the simulation results, it is concluded that the factors of uncertain revenue, punishment and reputation loss have important influence on the decision-making behaviour of the subject of infringement governance, and accordingly, the proposed measures on the publishers, platforms and the legal level of the government are conducive to the evolution of the system to the point of positive regulation and stability of rights protection, with a view to promoting the healthier and more stable development of the UGC platforms.

Research on the mechanism of consumer participation in value co-creation by innovative enterprises: An evolutionary game analysis framework.

The profound changes brought about by informatization and digitalization have given rise to the user-centered innovation concept, and value co-creation by enterprises has become an inevitable trend. It has become a pressing issue for scholars to analyze the mechanism of consumer participation in the value co-creation of innovative enterprises. In this paper, by establishing an evolutionary game model between consumers and innovative enterprises, we analyze in depth the mechanism of consumer participation in the value co-creation of innovative enterprises. The results show that the initial cooperation probability between consumers and innovative enterprises directly affects their strategic choices; the establishment of reward mechanisms makes consumers more inclined to choose active participation in value co-creation strategies; as the probability of non-cooperation between the two parties being reported increases, the probability of consumers and innovative enterprises choosing cooperation also increases. Studying the mechanism of consumer participation in the value co-creation of innovative enterprises has essential theoretical and practical significance for enterprises to achieve value creation, enhance competitiveness, and promote innovation. This study not only enriches and develops relevant theories but also provides guidance and support for the practice of enterprises, promoting sustainable development and successful co-creation.

Carbon emission allowances purchasing decisions in supply chains under the cap-and-trade mechanism in China: an evolutionary game analysis

PurposeThe importance of carbon reduction has become a global consensus, and more and more countries are implementing the cap-and-trade mechanism, including China. The purpose of this paper is to investigate the optimal carbon emission allowances (CEA) purchasing decisions of supply chain members under the cap-and-trade mechanism in China.Design/methodology/approachAn evolutionary game model is established to analyze the CEA purchase strategy choices of suppliers and manufacturers in the supply chain. The influence of the key parameters on the evolutionary game results is analyzed by numerical simulations.FindingsThe supply chain system always evolves towards neither supplier nor manufacturer purchasing CEA or both purchasing CEA. Illegal production behavior and excessive CEA costs are key factors that hinder parties from purchasing CEA. High revenue from purchasing CEA for production, high supply chain losses and high governmental penalties can promote parties to purchase CEA.Originality/valueThe results help supply chain members make better CEA purchasing decisions and also benefit the development of China’s carbon trading market and environmental protection.

Evolutionary game analysis of emission-dependent supply chain carbon abatement behaviours considering cap-and-trade mechanism

Evolutionary game analysis of emission-dependent supply chain carbon abatement behaviours considering cap-and-trade mechanism

Evolutionary game analysis on cross-border cooperative R&D of intelligent new energy vehicle industry

PurposeIntelligent new energy vehicles (INEVs) are becoming the competitive hotspot for the automobile industry. The major purpose of this study is to determine how to increase innovation efficiency through knowledge sharing and technology spill between new energy vehicle (NEV) enterprises and technology enterprises. This will help to improve the core competence of the automobile industry in China. Also, it serves as a guide for the growth of other strategic.Design/methodology/approachThe authors construct a tripartite evolutionary game model to study the cross-border cooperative innovation problem. Firstly, the payment matrix of NEV enterprise, technology enterprise and government is established, and the expected revenue of each participant is determined. Then, the replication dynamic equations and evolutionary stability strategies are analyzed. Finally, the theoretical research is validated through numerical simulation.FindingsResults showed that: (1) An optimal range of revenue distribution coefficient exists in the cross-border cooperation. (2) Factors like research and development (R&D) success rate, subsidies, resource and technology complementarity, and vehicles intelligence positively influence the evolution towards cooperative strategies. (3) Factors like technology spillover risk cost inhibit the evolution towards cooperative strategies. To be specific, when the technology spillover risk cost is greater than 2.5, two enterprises are inclined to choose independent R&D, and the government chooses to provide subsidy.Research limitations/implicationsThe research perspective and theoretical analysis are helpful to further explore the cross-border cooperation of the intelligent automobile industry. The findings suggest that the government can optimize the subsidy policy according to the R&D capability and resource allocation of automobile industry. Moreover, measures are needed to reduce the risk of technology spillovers to encourage enterprise to collaborate and innovate. The results can provide reference for enterprises’ strategic choice and government’s policy making.Originality/valueThe INEV industry has become an important development direction of the global automobile industry. However, there is limited research on cross-border cooperation of INEV industry. Hence, authors construct a tripartite evolutionary game model involving NEV enterprise, technology enterprise and the government, and explore the relationship of cooperation and competition among players in the INEV industry, which provides a new perspective for the development of the INEV industry.

How to promote data sharing among enterprises based on dynamic evolutionary game analysis

ABSTRACT In traditional contexts, enterprises often hesitate to engage in data sharing due to the associated heightened risks and transaction costs. Blockchain technology, leveraging its encryption algorithms and smart contracts, effectively alleviates these challenges, thereby encouraging enterprises to actively participate in data sharing. The adoption of reasonable reward and penalty mechanisms can prevent opportunistic behaviours and stimulate data sharing among businesses. It is noteworthy that blockchain technology and data alliance have a mutually substitutive effect in terms of risk and communication costs, while they complement each other in regulatory and transaction costs. The integration of blockchain technology with data alliance can enhance collaborative revenue and reduce various costs. When distributing collaborative revenue, it is crucial to adhere to the guiding principle of ‘prioritizing efficiency while considering fairness’. Collaboration becomes a reality when all parties collectively achieve a substantial overall revenue threshold. Subsequently, in-depth exploration of fair resource allocation principles is crucial to ensure the equitable distribution of resources.

Evolutionary game analysis on collaborative logistics diffusion considering diminishing marginal utility under dynamic productivity

Reducing carbon emissions in the transportation sector is crucial for sustainable practices, with collaborative logistics diffusion playing a significant role in promoting energy-saving and emission-reduction strategies. This paper introduces an evolutionary game model to analyze collaboration between manufacturers and logistics service providers (LSPs), using the Hotelling quadratic curve model to measure the diminishing marginal utility of basic profits. Initially, a static strategy leads to a cyclic evolution without reaching the evolutionary stable strategy (ESS), reflecting competitive dynamics under static productivity conditions where neither party gains a lasting advantage, leading to periodic adjustments in strategies. The Cobb-Douglas function models a dynamic productivity strategy that regulates the extra benefits of collaborative logistics and penalties for 'free-riding.' This strategy demonstrates an inward spiral convergence towards the ESS, showing that adaptive mechanisms enable manufacturers and LSPs to align interests and achieve equilibrium. Enhanced benefits from collaborative logistics promote a stable and cooperative ecosystem, discouraging free-riding and enhancing cost efficiency. Moreover, increased investment by manufacturers not only strengthens their position but also fosters an environment conducive for LSP participation, expediting collaborative logistics diffusion and minimizing potential losses.

Evolutionary Game Analysis on Cooperative Behavior of Major Projects’ Technology Innovation Subjects under General Contracting Mode

Major projects are the important platform for enhancing a country’s comprehensive national power and strengthening its capacity for independent innovation. Although major projects in China have made remarkable achievements, willingness to cooperate and innovate has not achieved the desired target. In this paper, the evolutionary game model of cooperative innovation behavior of general contractors and subcontractors is constructed by considering reputational factors. Through theoretical derivation, the influence of the distribution ratio of collaborative innovation benefit, spillover technology absorption capacity, and reputation discounting coefficient on innovation behavior is analyzed. Finally, MATLAB software is used to simulate the dynamic evolution process of strategy selection. The results show that (1) a reasonable benefit distribution coefficient can promote the evolution of innovation behavior in a positive direction; (2) both the reduction of innovation cost and the increase of spillover technology absorption capacity can make the innovation subject more inclined to choose the active collaborative innovation strategy; and (3) it is the higher-than-threshold reputation loss that can effectively inhibit the “free-rider” behavior. The research conclusions and managerial implications can provide reference for improving the willingness to cooperate in major projects’ technology innovation.

Evolutionary game and simulation analysis of three parties of electricity market regulation under government participation mechanism

Promoting the widespread access and integration of new energy generation into existing power markets is a key strategy for China to achieve peak carbon and carbon neutrality. A joint regulatory mechanism composed of government regulators, power generation enterprises, and third-party testing organizations has become an effective way to ensure the stable operation of the power market and safeguard the economic interest of all parties. In order to analyze the key factors affecting the mechanism and improve the regulatory efficiency, this paper constructs a three-party evolutionary game model, explores the motivations of the participants under different strategy choices, and establishes a set of indicator systems for evaluating producers. The evolutionary game model is numerically simulated using the unified dynamics method, and the evolutionary stable strategy analysis is used to reveal how the key parameters affect the outcome of the game and its dynamic process, so as to find out the potential driving factors affecting the strategy choices. The results of the study show that in the early stage of market development, it is crucial to improve the profitability of firms, and the government needs to impose strict penalties and high incentives. As the market gradually matures and becomes more transparent, the government can gradually reduce the level of penalties. At the same time, ensuring accountability mechanisms from higher authorities to the government is key to ensure the effectiveness of regulation. This study provides an important theoretical basis and policy recommendations for constructing a new regulatory structure for the electricity market.

Evolutionary Game Analysis of Optimal Strategies for Construction Stakeholders in Promoting the Adoption of Green Building Technology Innovation

Evolutionary Game Analysis of Optimal Strategies for Construction Stakeholders in Promoting the Adoption of Green Building Technology Innovation

Evolutionary Game Analysis of Green Supply Chain Management Diffusion under Environmental Regulation

The continuous deterioration of the ecological environment and the increasing scarcity of resources have posed a serious challenge to the survival and development of human beings, and the implementation of green supply chain management (GSCM) in this context is an effective means to ensure the sustainable development of society and the economy. In order to seek the optimal strategy of evolutionary game in the implementation of green supply chain management and explore the influence of environmental regulation intensity and public preference degree on the evolution process of green supply chain management diffusion development, this paper takes the study of green supply chain management diffusion as the core innovation point, and under the premise of environmental regulation, selects the government, the core enterprise, and the public as the participating bodies of green supply chain management diffusion, and uses the theory of evolutionary game to construct a diffusion model of green supply chain management. Using evolutionary game theory to construct a diffusion model, and with the help of MATLAB and other mathematical tools for numerical simulation analysis, we discuss the diffusion of the green supply chain and derive the optimal combination strategy. The results of the study show that: (1) there are four evolutionary stable states in the process of green supply chain management diffusion: preliminary diffusion, extinction, semi-diffusion, and full diffusion; (2) it will be beneficial for the government to promote the evolutionary diffusion of green supply chain management by implementing a higher intensity of pollution tax policy while implementing green supply chain incentive strategies; (3) the government, while implementing environmental regulation policies, should also pay attention to the guidance of the public’s awareness of environmental friendliness and greenness, and focus on the role of the comprehensive strategy selection of the three parties of the game in reaching the optimal state. The conclusions of the study provide theoretical guidance and decision support for the implementation and diffusion of green supply chain management under environmental regulation.

Supply and demand behaviors in the Chinese emission allowances pledge credit market under different value type: An evolutionary game analysis

Chinese Emission Allowances (CEAs) pledge credit provides a new way for banks to reduce green credit risks and for low-carbon enterprises to improve the credit availability. However, insufficient supply and demand is the main dilemma of CEAs pledge credit in China. One of the reasons for this dilemma may be the neglect of the forward value of CEAs in value assessment. This research explores the decision-making behavior of the supply and demand subjects in the CEAs pledge credit market under different value types of CEAs. First, the improved B–S options pricing model with consideration of transaction costs is used in the construction of the payoff matrix to measure the option value of CEAs. The new matrix aims to place both the option value (corresponding to forward value) and the market value (corresponding to spot value) in the CEAs pledge value evaluation framework. Then, based on the new matrix, an evolutionary game model between key emission enterprises (KEEs) and commercial banks (CBs) is built to dynamically analyze the equilibrium state of supply and demand as well as the strategic interaction of participants in CEAs pledge credit market. Finally, numerical simulations demonstrate the driving factors of supply and demand for CEAs pledge credit. The research results show that compared to market value, the option value of CEAs is more conducive to stimulating the supply and demand of CEA pledge credit; and the shorter the remaining valid period of CEAs, the higher the participation enthusiasm of supply and demand parties. Furthermore, reducing low-carbon technology risks and increasing the carbon emissions trading prices at the end of pledge period can significantly improve the supply and demand of CEAs pledge credit, but the loan and deposit interest rates of CEAs pledge credit are ineffective.

Evolutionary game analysis of violation regulation in the electricity market based on blockchain technology

Electricity market violations affect the overall operations of the electricity market. This paper explores the evolutionary stability strategies of electricity generation enterprises and electricity consumers under two modes: traditional regulation and blockchain regulation to analyze blockchain technology’s mechanism and conditions in solving electricity market violations. The experimental results indicate that the likelihood of consumers accepting electricity and the regulatory capacity of regulatory agencies play a crucial role in determining the violation approach adopted by electricity generation enterprises. Under traditional regulatory models, due to information asymmetry, regulatory agencies may not be able to detect violations promptly. Meanwhile, electricity consumers may choose to accept violations by power generation companies due to high appeal costs. Blockchain technology enables regulatory agencies to improve their regulatory capabilities by eliminating information asymmetry, reducing the cost of complaints from electricity consumers, thereby elevating the risk for enterprises engaging in market violations and optimizing the evolutionary game towards an optimum state.

Evolutionary game analysis of multiple subjects in the management of major public health emergencies

The frequent occurrence of major public health emergencies (MPHEs) significantly challenges national security, economic stability, social operation and the safety of people's lives and property worldwide. Consequently, enhancing the emergency management of MPHEs is critically urgent. This paper constructs a game model involving local government, social organisations, and the public for MPHE management, exploring strategy combinations and influencing factors across various scenarios. Several results were obtained. (1) Local government, social organisations, and the public each have positive and negative strategy choices based on cost–benefit analysis, leading to eight different strategy combinations. Furthermore, all three take positive strategies as the optimal way to achieve the game equilibrium. (2) The transformation of strategy combinations is primarily influenced by the cost-benefit gap and the strategic decisions of local government. (3) Altering a subject's initial strategy value doesn't change its final choice but impacts the time to achieve a stable strategy equilibrium. The severity of local government punishments on social organisations influences their strategic choices and the time to optimal strategy, whereas rewards to the public or social organisations only affect the time to achieve this strategy. The findings of this study can not only help improve the collaborative governance system of MPHEs but also provide scientific guidance on how governments can manage MPHEs.

How to reduce construction risks in rural areas: an evolutionary game analysis

PurposeThe construction industry is widely recognized as one of the most hazardous sectors in the world. Despite extensive research on safety management, a critical issue remains that insufficient attention is devoted to safety practices in rural areas. Notably, accidents frequently occur during the construction of rural self-built houses (RSH) in China. Safety management tends to be overlooked due to the perceived simplicity of the construction process. Furthermore, it is essential to acknowledge that China currently lacks comprehensive laws and regulations governing safety management in RSH construction. This paper aims to analyze the behavior of key stakeholders (including households, workmen, rural village committee and the government) and propose recommendations to mitigate safety risks associated with RSH construction.Design/methodology/approachThis paper applies evolutionary game theory to analyze the symbiotic evolution among households, workmen and rural village committee, in situations with or without government participation. Additionally, numerical simulation is utilized to examine the outcomes of various strategies implemented by the government.FindingsWithout government participation, households, workmen, and rural village committee tend to prioritize maximizing apparent benefits, often overlooking the potential safety risks. Numerical simulations reveal that while government involvement can guide these parties towards safer decisions, achieving the desired outcomes necessitates the adoption of reasonable and effective strategies. Thus, the government needs to offer targeted subsidies to these stakeholders.Originality/valueConsidering that during the construction phase, stakeholders are the main administrators accountable for safety management. However, there exists insufficient research examining the impact of stakeholder behavior on RSH construction safety. This study aims to analyze the behavior of stakeholders about how to reduce the safety risks in building RSH. Thus, the authors intend to contribute to knowledge in this area by establishing evolutionary game model. Firstly, this study carried out a theoretical by using tripartite evolutionary game to reveal the reasons for the high safety risk during building RSH. Practically, this research points out the important role of households, workmen and rural village committee in improving safety management in rural areas. Besides, some suggestions are proposed to the government about how to reduce construction safety risks in rural areas.

Evolutionary Game and Simulation Analysis of Food Safety Regulation under Time Delay Effect

This study develops a tripartite evolutionary game dynamic model with a time delay effect to analyze the interactions among food enterprise, government regulatory, and food inspection agencies in managing food safety risks. This model enables government regulatory agencies to more accurately assess and predict food safety risks, thereby implementing more effective preventative measures, ensuring the maximization of policy effectiveness and reducing food safety incidents. The results emphasize the significance of recent company performance by showing that regulatory and inspection entities’ strategic decisions are significantly impacted by delay effects from food companies. This study also shows that negative self-feedback intensity drives food enterprises to develop safer products and encourages tighter government oversight. Recommendations include improving consumer reporting channels, changing government incentives and penalties, allocating resources efficiently, and advancing information technology to decrease the effects of time delays and improve food safety management. Governments can improve food safety regulation by using strategic insights from numerical simulations.