Evolutionary Game Theoretic Analysis Research Articles

An evolutionary game-theoretic analysis of the "multi-agent co-governance" system of unfair competition on internet platforms.

The increasingly prominent issue of unfair competition on Internet platforms (IPUC) severely restricts the healthy and sustainable development of the platform economy. Based on the IPUC "multi-agent co-governance" scenario, this paper introduces stochastic disturbances and continuous strategy set to improve the classical binary deterministic evolutionary game system. The results show that after considering stochastic disturbances, the positive state corresponding to the equilibrium point (1,1) is no longer stable, and the required parameter conditions are more stringent. The IPUC "multi-agent co-governance" system under stochastic disturbances exhibits specific vulnerability. In the continuous strategy set evolutionary game system, government departments and Internet platforms can flexibly make optimal decisions based on maximizing expected returns, and strategy selection has better elasticity. Regardless of the evolutionary game scenario, maintaining the participation level of NGOs and the public above a certain threshold while increasing the penalty intensity is conducive to the evolution of the game system toward the positive state. The analysis process and conclusions provide insights and guidance for the governments to design the IPUC regulatory system and frameworks.

Research on Power Battery Recycling in the Green Closed-Loop Supply Chain: An Evolutionary Game-Theoretic Analysis

The used power batteries of new energy vehicles have become a combined issue of environmental pollution, resource scarcity, and economic sustainability. Power battery recycling is inevitably becoming the key link in the formation of the green closed-loop supply chain for new energy vehicles and the green cycle of the new energy vehicles industry. This study establishes a three-party evolutionary game model of “new energy vehicle manufacturers, power battery manufacturers, and power battery recyclers”, simulates the dynamic evolution process of each game player’s strategy, and analyzes the effects of the digital transformation factor and other factors leading to the evolution trend. The main results show that: (i) in the absence of sufficient incentives and constraints, the green closed-loop power battery supply chain cannot be formed naturally; (ii) digital transformation is an important factor in the journey of the green closed-loop supply chain for power battery recycling, and (iii) government rewards and penalties can promote the formation of the green closed-loop supply chain for power batteries. This research innovatively investigates the concept of the green closed-loop power battery supply chain and its formation mechanism, which provides theoretical support to promote the recycling of used power batteries to achieve sustainability.

CDC (Cindy and David’s Conversations) game: Advising President to survive pandemic

Ongoing debates on anti-COVID19 policies have been focused on coexistence-with vs. zero-out (virus) strategies, which can be simplified as "always open (AO)" vs. "always closed (AC)." We postulate that a middle ground, dubbed LOHC (low-risk-open and high-risk-closed), is likely favorable, precluding obviously irrational HOLC (high-risk-open and low-risk-closed). From a meta-strategy perspective, these four policies cover the full spectrum of anti-pandemic policies. By emulating the reality of anti-pandemic policies today, the study aims to identify possible cognitive gaps and traps by harnessing the power of evolutionary game-theoretic analysis and simulations, which suggest that (i) AO and AC seems to be "high-probability" events (0.412-0.533); (ii) counter-intuitively, the middle ground-LOHC-seems to be small-probability event (0.053), possibly mirroring its wide adoptions but broad failures. Besides devising specific policies, an equally important challenge seems to deal with often hardly avoidable policy transitions along the process from emergence, epidemic, through pandemic, to endemic state.

An Evolutionary Game Theoretic Analysis of Cybersecurity Investment Strategies for Smart-Home Users against Cyberattacks

In the digital era, smart-home users face growing threats from cyberattacks that threaten their privacy and security. Hence, it is essential for smart-home users to prioritize cybersecurity education and training to secure their homes. Despite this, the high cost of such training often presents a barrier to widespread adoption and accessibility. This study aims to analyze the costs and benefits associated with various cybersecurity investment strategies for smart-home users in the context of cyberattacks. The study utilizes evolutionary game theory to model a game comprised of three populations: smart-home users, stakeholders, and attackers. We derive and analyze the replicator dynamics of this game to determine the evolutionarily stable strategy (ESS). Furthermore, we investigate the impacts of the costs and benefits of cybersecurity investment and cyberattack costs on the ESS. The findings indicate that incurring costs for cybersecurity training is beneficial for smart-home users to protect their homes and families. However, the training costs must be low and affordable for smart-home users in order to ensure their participation and engagement. Additionally, providing rewards for commitment to cybersecurity is crucial in sustaining interest and investment over the long term. To promote cybersecurity awareness and training for smart-home users, governments can incorporate it as a priority in national cybersecurity plans, provide subsidies for training costs, and incentivize good cybersecurity practices.

An evolutionary game-theoretic analysis of cooperation strategy between SMEs and cross-border e-commerce platforms considering the cross-network effect

PurposeThis paper aims to propose the mechanism of cross-network effect embedded, which can help cross-border e-commerce (CBEC) platforms strengthen cooperative relationships with sellers more equitably and effectively by using the network structural characteristics of the platforms themselves.Design/methodology/approachA two-stage evolutionary game model has been used to confirm the influence factors. The mathematical derivation of evolutionary game analysis is combined with the simulation method to examine the role of cross-network effect in cooperation. The evolutionary game model based on the cross-network effect is proposed to achieve better adaptability to the study of cooperation strategy from the two-sided market perspective.FindingsThe evolutionary game model captures the interactions of cross-network effect and the influence factors from a dynamic perspective. The cross-network effect has a certain substitution on the revenue-sharing rate of SMEs. CBEC platforms can enhance the connection between consumers and the website by improving the level of construction, which is a good way to attract sellers more cost-effectively and efficiently.Research limitations/implicationsThis study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specificCBEC platforms.Practical implications This study provides a new method for the validation of the cross-network effect, especially when data collection is difficult. But this method is only a numerical simulation. So the conclusions still need to be further tested empirically. Besides, researchers are advised to explore the relationship between the added user scale and the cross-network effect in some specific CBEC platforms.Originality/valueInvestigations that study cooperation strategy from the cross-network effect perspective in CBEC are limited. The research figured out which influence factors are affected by the cross-network effect in cooperation. A two-stage evolutionary game model was proposed to explain the interaction of the factors. The evolutionary game analysis with a simulation method was combined to highlight the role of cross-network effect on cooperation strategy to give a deeper investigation into the sustainable cooperation ofCBEC.

An evolutionary game-theoretic analysis of construction workers' unsafe behavior: Considering incentive and risk loss.

The behavior of construction workers has a significant impact on the overall safety climate of a project. The purpose of this paper is to figure out the evolutionary pattern of workers' unsafe behavior and to minimize its occurrence. We constructed a two-sided evolutionary game model consisting of workers and managers to explore the focal point of interest, strategy equilibrium conditions, and behavior evolution process. The experimental results of stability analysis and system dynamics show that there are two stable states in all four cases, (Safe behavior, Negative management) as well as (Unsafe behavior, Negative management). The lower the initial willingness of workers to behave unsafely, the faster they reach a safe steady state. By contrast, managers' strategy choices have a certain lag. Workers are discouraged from choosing unsafe behavior under both the positive incentive of raising bonuses and the negative incentive of raising fines. And the sensitivity of the two incentives is similar. For indirect effect risk loss, when it is effectively controlled during safe construction, workers quickly gravitate toward safe behavior. These findings provide a reference for construction safety management. Several practical suggestions were proposed from three perspectives: the worker, the manager, and the site safety climate, focus on the theme of reducing unsafe behavior and achieving a virtuous cycle of safety climate.

A profit surplus distribution mechanism for supply chain coordination: An evolutionary game-theoretic analysis

In supply chain (SC) systems, channel coordination can be achieved by incentive alignment contracts. The contracting mechanisms reported in the literature are usually “short-term-based” and the respective decisions are assumed to be static. However, real world supply chains (SCs) operate in the long term and decisions may evolve when time passes. As a result, this paper analytically explores the instability of the short-term coordination strategies and examines the evolutionary behaviors of SC members towards SC coordination. Moreover, it incorporates the effects of SC members’ evolutionary strategy adoption into profit surplus distribution among them. To be specific, an evolutionary game theory-based model, namely the “profit surplus distribution (PSD) mechanism for supply chain coordination”, is proposed to investigate how long-term behaviors of SC members will affect the coordination decisions (i.e., choosing to collaborate) and their share of coordination profit surplus. Based on a real case in consumer electronics, we analytically investigate a two-level SC consisting of a retailer investing in sales-effort and a population of manufacturers investing in innovation effort. Using the evolutionary game theory, we examine the relationship between the evolutionary strategies of SC members towards channel coordination and the profit surplus distribution among them. The results reveal that the coordination strategy is preferred by a great percentage of manufacturers in the long term and their share of coordination profit surplus plays a critical role in affecting their evolutionary preference (and vice versa).

Financial incentives to poor countries promote net emissions reductions in multilateral climate agreements

Financial incentives to poor countries promote net emissions reductions in multilateral climate agreements

Evolutionary Game-theoretic Analysis for Residential Users Considering Integrated Demand Response

As an important part of demand side, residential users have the characteristics of imperfect rationality and strong randomness, which are rarely considered in the existing study. Moreover, to effectively improve the energy efficiency, integrated demand response (IDR) is proposed as an effective measure to reduce the local energy supply pressure. This paper focuses on a scenario for IDR programs, in which the intelligent building aggregator (IBA) wants to encourage residential users to participate in IDR according to a proper contract price policy. To analyze how the participation degree tendency evolves over time, an evolutionary game approach is proposed considering residential users' bounded-rationality. A symmetric evolutionary game model and an asymmetric evolutionary game model are established, and the stability of equilibrium points in the above models is proven. Simulation results show that different contract price policies will obviously influence residential users' strategy, and affect the stable equilibrium points of the evolutionary game. The simulation results provide an effective reference for IBA to set proper and effective price incentives.

An Evolutionary Game Theoretical Analysis to Conflicts among Stakeholders Involved in the Operation of Municipal Waste Incineration

This study presents an evolutionary game to model interactions among stakeholders with potential conflicts, including the operational enterprise of incineration plant, the local government, and the residents nearby. System dynamics is used to simulate the change of strategic actions corresponding to the three players, in order to seek for the evolutionary stability strategies. A numerical case is proposed to demonstrate the game theory application, in which the impacts of governmental incentive and punishment on the player’s actions are investigated. The results indicated that administrative penalty is effective not only in motivating the enterprises to upgrade treatment facilities for ensuring environmental quality but also in helping the local government and residents to approach dominant strategies. Policy implications are given based on the results to lay out a foundation for the alleviation of the conflicts.

Understanding the Interaction between Cyclists' Traffic Violations and Enforcement Strategies: An Evolutionary Game-Theoretic Analysis.

An evolutionary game-theoretic analysis method is developed in this study to understand the interactions between cyclists’ traffic violations and the enforcement strategies. The evolutionary equilibrium stabilities were analysed under a fixed (FPS) and a dynamic penalty strategy (DPS). The simulation-based numerical experiments show that: (i) the proposed method can be used to study the interactions between traffic violations and the enforcement strategies; (ii) FPS and DPS can reduce cyclists’ probability of committing traffic violations when the perceived traffic violations’ relative benefit is less than the traffic violation penalty and the enforcement cost is less than the enforcement benefit, and using DPS can yield a stable enforcement outcome for law enforcement compared to using FPS; and (iii) strategy-related (penalty amount, enforcement effectiveness, and enforcement cost) and attitudinal factors (perceived relative benefit, relative public image cost, and cyclists’ attitude towards risk) can affect the enforcement strategy’s impacts on reducing cyclists’ traffic violations.

Evolutionary game theoretic analysis on low-carbon strategy for supply chain enterprises

The focus of this research is evolutionary low-carbon supply chain enterprise behavior and the strategic issues associated with government low-carbon policies and the emerging low-carbon market. A two-level supply chain consisting of a retailer and a manufacturer is established. A Stackelberg game approach employed to solve four retailer and manufacturer low-carbon strategy combinations, after which these strategies are further analyzed using an evolutionary theoretical game approach, from which an evolutionary stability strategy (ESS) is determined. The ESS indicated that: 1) in the low-carbon technology development stage, only one player (the manufacturer or the retailer) should employ low-carbon behavior; and 2) in the advanced low-carbon technology stage, only the retailer should employ low-carbon behavior. These positive results achieved economic, environmental and social Pareto improvements that complied with the government low-carbon requirements, catered to the low-carbon consumer demand, and improved supply chain economic and environmental performances. Finally, the impact of the changes from the government low-carbon policies, consumer sensitivities, and retailer carbon financing interest/subsidy rates on the ESS were analyzed, from which it was found: 1) the government could encourage enterprises to reduce carbon emissions by controlling carbon prices rather than imposing a carbon cap; 2) the enterprises need to focus on consumer sensitivities as the increase of these will reduce the long-term operational carbon emissions; and 3) retailers could stabilize the evolutionary supply chain system by lowering the carbon financing interest rate.

Impact of policy incentives on electric vehicles development: a system dynamics-based evolutionary game theoretical analysis

A system dynamics-based evolutionary game theoretical analysis is proposed to examine the impact of policy incentives, i.e., price subsidy and taxation preference on electric vehicles (EVs) industry development. Two case scenarios were used to distinguish policy performance by dividing it into a static and dynamic incentive. The result reflected that the game in implementation of the static incentive policy did not achieve stable equilibrium, indicating that such a policy is not effective for driving the development of the EVs industry. However, the game had stable equilibrium when dynamic incentive policy was implemented. The taxation preference had better performance in incentivizing EVs production than the direct subsidy. The study is expected to provide insight into policy making in the industrial transition toward low-carbon consumption. Limitations are given to indicate opportunities for further research.

Mining Pool Manipulation in Blockchain Network Over Evolutionary Block Withholding Attack

In the current blockchain network, many participants rationally migrate the pool to receive a better compensation according to their contribution in situations where the pools they engage encounter undesirable attacks. The Nash equilibria of attacked pool has been widely analyzed, but the analysis of practical methodology for obtaining it is still inadequate. In this paper, we propose an evolutionary game theoretic analysis of Proof-of-Work (PoW) based blockchain network in order to investigate the mining pool dynamics affected by malicious infiltrators and the feasibility of autonomous migration among individual miners. We formulate a revenue model for mining pools which are implicitly allowed to launch a block withholding attack. Under our mining game, we analyze the evolutionary stability of Nash equilibrium with replicator dynamics, which can explain the population change with time between participated pools. Further, we explore the statistical approximation of successful mining events to show the necessity of artificial manipulation for migrating. Finally, we construct a better response learning based on the required block size which can lead to our evolutionarily stable strategy (ESS) with numerical results that support our theoretical discoveries.

The Evolutionary Game Theoretic Analysis for Sustainable Cooperation Relationship of Collaborative Innovation Network in Strategic Emerging Industries

Strategic emerging industries (SEIs) represent the future direction of industrial developments and are crucial in stimulating the overall and long-term development for economy and society. The government plays a key role in promoting the development of SEIs. This paper, for the first time, investigates the cooperation relationship among innovation members, such as enterprises, universities and research institutes in a collaborative innovation network of strategic emerging industries under government intervention. A three-population evolutionary game theory approach was employed under different scenarios for the government acting as the stakeholder, considering the non-profit, definite fit as well as uncertain profit when incentive and punishment policies are adopted. A novel evolutionary game model of the cooperation relationship among collaborative innovation network members under government’s intervention is established. The results of the simulation experiments show that government’s intervention significantly influences the cooperation relationship between enterprises, universities and research institutes. When the sum of financial incentives and punishments is greater than the total additional cost (TAC), enterprises, universities and research institutes should pay for collaborative innovation. Moreover, government’s financial intervention can effectively promote the cooperation between enterprises, universities and research institutes.

Evolutionary Game Theoretic Analysis of Low Carbon Investment in Supply Chains under Governmental Subsidies.

With the rapid development of global industry and economy, excessive carbon dioxide emission has emerged as a critical issue in both developed and developing countries. Using an evolutionary game framework in which game players can adjust their strategies constantly, this paper investigates how to optimize the strategy of low carbon investment for suppliers and manufacturers in supply chains, and discuss the impacts of various factors on evolutionarily stable strategies. Additionally, we examine an incentive mechanism based on governmental subsidies to eliminate free riding and motivate co-investment. Furthermore, a case study and numerical examples are provided for illustration and simulation purposes, leading to several countermeasures and suggestions. Our analytical results show that the strategic choice of low carbon investment is correlated with profit growth coefficients, investment costs and profits from free riding. Investment costs have more significant impacts than other factors on evolutionarily stable strategies, while profit growth coefficients are more important at initial stages in the evolutionary process. The incentive mechanism based on governmental subsidies is an effective solution to motivate co-investment, and governments should take some measures to improve the assess accuracy and supervisory efficiency of investment strategy.

The Evolutionary Game Theoretic Analysis for Emission Reduction and Promotion in Low-Carbon Supply Chains

Aiming at exploring the interplay principles of operations strategies among members of dvertising and emission reduction cost sharing contracts and coordination in low-carbon sulow-carbon supply chain, as well as their impact on system performance, we develop an evolutionary game model to capture emission reduction and low-carbon promotion actions, which are typically conducted by one manufacturer and one retailer in every two-echelon supply chain, respectively. We exploit the evolutionary game model to analyze players’ behavioral patterns of their interacting strategies, whereby we attain the evolutionary stable strategies and their associated existing preconditions under various scenarios. We acquire a number of managerial insights, and particularly find that the evolutionary stable strategies of the channel carbon reduction and promotion are remarkably influenced by incremental profits resulted from causes, such as every player’s unilateral participation in emission reduction. In addition, we investigate a player’s free-rider opportunistic practice in cooperative carbon reduction and joint participation in emission reduction. However, the magnitude of profit increment will heavily influence the result of Evolutionary Stable Strategy (ESS). Finally, the extensive computational studies enable us to verify the effectiveness of preceding models.

Evolutionary Game Theory Perspective on Dynamic Spectrum Access Etiquette

In this paper, we describe the long-term evolution of societies of secondary users in dynamic spectrum access networks. Such an understanding is important to help us anticipate future trends in the organization of large-scale distributed networked deployments. Such deployments are expected to arise in support of a wide variety of applications, including vehicular networks and the Internet of Things. Two new biologically-inspired spectrum access strategies are presented here, and compared with a random access baseline strategy. The proposed strategies embody a range of plausible assumptions concerning the sensing capabilities and social characteristics of individual secondary users. Considering these strategies as the basis of a game against the field, we use replicator dynamics within an evolutionary game-theoretic analysis to derive insights into the physical conditions necessary for each of the strategies to be evolutionarily stable. Somewhat surprisingly, we find that the physical channel conditions almost always uniquely determine which one of the three (pure) strategies is selected, and that no mixed strategy ever survives. We show that social tendencies naturally become advantageous for secondary users as they find themselves situated in network environments with heterogeneous channel resources. Hardware test-bed experiments confirm the validity of the analytic conclusions. Taken together, these results predict the emergence of social behavior in the spectrum access etiquette of secondary users as cognitive radio technology continues to advance and improve. The experimental results show an increase in the throughput of up to 90%, when strategy evolution is continuously operational, compared with any static strategy. We present use cases to envision the potential application of the proposed evolutionary framework in real-world scenarios.

The impact of social network on the adoption of real-time electricity pricing mechanism

The option menu of electricity tariffs is a compromise way for introducing real-time pricing (RTP) to consumers while remain the alternative fixed pricing (FP). Since it is difficult for a consumer to evaluate RTP and FP two tariffs because of the information asymmetry, and the acquaintances’ opinions may play an important role when making a choice. This study aims to evaluate the impact of the social network on the diffusion of real-time electricity price using evolutionary game theoretical analysis. Consumers with heterogeneities in demand response capability and relationships in the social network are considered in an electricity market RTP and FP simultaneously. The consumers who adopt RTP can response to the varying price by shifting their electricity consumption to minimize their expenditures and inversely influence the price. As a case study, hundreds of scenarios of different initial conditions including social networks structures and update rules were analyzed and inter-compared using the developed model. The results show that: (i) the higher degree of the consumers social network, the slower the diffusion of RTP; (ii) increasing the proportion of consumers with high demand response capability can promote the adoption of RTP, implying the worth of promoting the utilization of smart home technology; (iii) a small exogenous probability (e.g. 1%) of the tariff choice mutation can accelerate the diffusion of RTP, indicating that the advertisement of RTP can be useful.

Interaction between enterprises and consumers in a market of carbon-labeled products: a game theoretical analysis.

This paper applies an evolutionary game theoretical analysis combined with system dynamics to model strategic interaction between enterprises and consumers with bounded rationality in a carbon-labeled product market. Through the game theoretical analysis, possible equilibriums are predicted between these two players, in order to provide market recommendations for promotion of carbon-labeled products. The simulation results indicated that it is impossible to promote the carbon-labeled products relying on the market's inherent functions. After incorporating dynamic subsidies, both of the players have evolutionary stable strategies, revealing it has an incentive impact on the market. Limitations of the game theoretical analysis are discussed to lay out a foundation for further study.