Game Perspective Research Articles

The charge‐discharge compensation pricing strategy of electric vehicle aggregator considering users response willingness from the perspective of Stackelberg game

AbstractWith the rapid increase of electric vehicle (EV) ownership, the impact of EV charging load on the power grid is becoming more and more prominent. To reasonably guide EV charging/discharging to participate in Demand Response (DR) and help the power grid achieve peak cutting and valley filling, the charge‐discharge compensation pricing strategy of EV Aggregator (EVA) considering user response willingness from the perspective of Stackelberg game is proposed. Firstly, EVA, as the leader, provides charge‐discharge compensation price, to maximise its income within a day, taking into account user satisfaction constraints. Secondly, a user response willingness model is established. User engagement is used to describe the change in the number of EV responses with the change of the charge‐discharge compensation price by EVA and select the random EV set that accepts EVA charge‐discharge guidance. Finally, EV, as a follower, conducts charging/discharging behaviour to minimise the charging cost. By using the Karush–Kuhn–Tucker (KKT) condition, strong duality theory and iterative method, the strategy equilibrium solution is solved. The results show that considering the user response willingness can effectively reduce the decision risk when EVA participates in bidding. Although EVA income slightly decreases considering the response willingness, the average user satisfaction increases by 0.1.

Research on road congestion analysis strategy based on combined weights of game perspective

In recent years, the vehicle carrying demand of urban roads has been growing, and in order to prevent road congestion, this paper conducts a road congestion analysis based on the game perspective of AHP-EWM combined weights, and the analysis shows that drivers have a great relationship with the congestion degree of roads when choosing routes in urban roads, so establishing a more perfect visualization of induced information can play a significant role in alleviating urban traffic congestion and guiding drivers to choose more appropriate roads.

How does autonomous vehicles affect taxi industry? A two-stage Van Damme based tripartite evolutionary game perspective

As urban passenger transportation focuses more on economic efficiency and road safety, autonomous driving technology is being introduced in the taxi industry. Interests differ among automobile manufacturers, taxi companies, and the government in promoting the adoption of autonomous taxis (ATs). This paper investigates the impact of multiple factors in the mixed traffic operation mode on the tripartite game using the two-stage Van Damme model. It also analyzes the game-breaking key to automobile manufactures' decision in the dual stable situation. The findings are as follows: (1) Under government non-promotion, independent R&D guides taxi companies to adopt ATs more effectively. Under government promotion, the social acceptance and loss of technology dominance have varying impacts on the game results. (2) Adjusting infrastructure cost and subsidy intensity can lead to a single stable situation when taxi companies and the government adopt a wait-and-see approach. (3) The loss of technology dominance shifts game leader from automobile manufacturers to the government. (4) Taxi companies would only adopt ATs when the social acceptance is moderate, as it exhibits an inverted U-shaped relationship. These findings provide valuable insights for how to better promote the adoption of ATs under both promotion and non-promotion by the government.

Promoting the resource utilization of agricultural wastes in China with public-private-partnership mode: An evolutionary game perspective

The agricultural waste is large in number and the utilization rate is extremely low in China, requiring remediated. Formatting the project system and introducing the Public-Private-Partnership (PPP) mode are inevitable to realize the specialization and socialization in resource utilization of agricultural wastes. However, the confusion of financing, management, responsibilities of participants and difficulties in coordinating interests limit the expected effect of the resource utilization of agricultural wastes (RUAW). To this end, combined with the examination of actual cases, this paper constructs a tripartite evolutionary game model of RUAW PPP projects among local government, social capital and farmers, then conducts simulation and case study. We find that the local government does not supervise, social capital acts opportunistically, and farmers choose to cooperate is the evolutionary stable situation, and the cost of supervision for local government and the reward and punishment mechanism of local government to social capital will largely influence the strategy choice of the stakeholders. Strengthening the local government's sense of responsibility and regulatory capacity, optimizing the reward and punishment system, vigorously making technological innovations, and improving the operational capacity of the special purpose vehicle can effectively improve the efficiency of cooperation. The results of the study have some guiding significance for further improving the level of circular agriculture in China even in developing countries and forming a more complete system of resource utilization of agricultural wastes.

Retracted: Operation and Management Strategy of Online Car-Hailing Platforms Based on Big Data Diagnosis and Game Perspective

Retracted: Operation and Management Strategy of Online Car-Hailing Platforms Based on Big Data Diagnosis and Game Perspective

National or third-party manufacturer? Sourcing strategy of a dominant platform: Signaling game's perspective

The dominant online platforms (e.g., Amazon and JD) in practice have adopted a strategy of introducing their own store brands as a means to engage in competition with national brands inside consumer markets. However, whether to source store brands from national or third-party manufacturers is still a dilemma for platforms. This paper investigates the online platform's optimal sourcing decision for the store brand when the platform possesses private information about the degree of consumer acceptance of the store brand. This paper develops a signaling game in which the better-informed dominant-platform may reveal its private information through profit margins and highlight the signaling effect of price on the sourcing strategy. Due to the signaling cost, we find that asymmetric information has the potential to inhibit the platform from cooperating with the national manufacturer to produce the store brand. Furthermore, the existence of information asymmetry reduces the profit of the platform with superior information, while simultaneously boosting the profit of the less-informed national manufacturer. Interestingly, our findings reveal that under an asymmetric information setting, a higher level of information asymmetry might negatively impact the platform, which contrasts with the situation when information is symmetric. Consequently, the platform gains more advantages by cooperating with a third-party manufacturer with a moderate level of information asymmetry.

Bitcoin Price Manipulation Regulation from a Game Perspective

Bitcoin Price Manipulation Regulation from a Game Perspective

Optimal Polarization Design for Distributed MIMO Radar Networks: A Stackelberg Game Perspective

Optimal Polarization Design for Distributed MIMO Radar Networks: A Stackelberg Game Perspective

Research on OTA Platform Supervision and Management Based on Game Theory Background

In the era of big data, the OTA platform uses information advantages to abuse data to seek more "big data price discrimination" behaviors of consumers' more benefits. The low information on the market has become a profitable tool for "price discrimination" on the OTA platform. Under the circumstances of this kind of information, it is difficult for consumers to not only be "price discrimination", but also it is difficult to protect their rights after being aware. At this time, the government's active intervention is required to regulate the "big data price discrimination" behavior of the OTA platform. In order to curb the further flooding of "price discrimination", this article has established a game tree model to analyze from the dynamic game perspective of the government and the OTA platform, and the impact of changes in the transparency of information on the stability of the evolution game system. In addition, the relevant suggestions on the OTA platform of government supervision and governance are explained from different levels of information transparency.

Exploring the evolutionary mechanism of the cross-regional cooperation of construction waste recycling enterprises: A perspective of complex network evolutionary game

Cooperation and information sharing among various regional departments play a crucial role in facilitating the equitable disposal of construction waste across regions, fostering regional coordination in waste management. This paper establishes the complex network evolutionary game model of cross-regional cooperation of construction waste recycling enterprises, and conducts numerical simulation to analyze the strategic adjustment process of recycling enterprises under the coordination and complementarity of market mechanism and government mechanism, and explores the Pareto optimal conditions that are conducive to cross-regional cooperation of recycling enterprises. The result indicates that with the increase of the market scale of cross-regional treatment of construction waste, it can effectively improve the willingness of cross-regional cooperation of recycling enterprises. In the market mechanism, both the profit distribution and synergistic benefit have a significant impact on the cross-regional cooperation behavior of construction waste recycling enterprises, while the impact of spillover benefit is relatively minor in comparison. In various network scales, the profit distribution coefficients exhibit threshold values within the ranges of 0.3–0.35, 0.25 to 0.3, and 0.25 to 0.3, respectively. Within the government mechanism, the government subsidy coefficient falls within the threshold of 0.3–0.4. Notably, greater government support proves more conducive to advancing cross-regional cooperation among recycling enterprises. For small-scale and medium-scale markets, there exists a threshold for default penalties ranging between 4 and 5. In contrast, large-scale markets have a default penalty threshold between 3 and 4. Imposing reasonable penalties for contract breaches can effectively stimulate the sustainable and consistent development of cross-regional cooperation among recycling enterprises. These findings establish a foundation for shaping cross-regional cooperation strategies for recycling enterprises, enhancing the efficiency of construction waste treatment, and fostering the coordinated development of urban areas.

Shared energy storage-assisted and tolerance-based alliance strategy for wind power generators based on cooperative game and resource dependence theories

The variability of wind power will affect the market performance of wind power generators (WPGs) and make them suffer energy deviation settlement. Energy storage, as a controllable resource, is widely used to cope with the problem. However, independent construction of large-scale energy storage will bring high investment costs and risks to WPGs. The sharing of energy storage in the alliance formed by different types of WPGs provides a new solution to the problem, but alliance cooperation and alliance selection are crucial issues that warrant diligent attention by WPGs from the perspective of the cooperative game. Given this background, a shared energy storage (SES)-assisted and tolerance-based alliance strategy based on cooperative game and resource dependence theories is formulated for WPGs. First, a robust-based market profit model of WPGs is developed. On this basis, transaction cost theory is implemented to analyze cooperation costs, and the dual theory-based alliance profit model considering SES is developed. Then, a modified profit allocation approach based on multiple indexes and deviation minimization algorithm (MI-DMA) is innovatively developed to allocate alliance profits. Finally, since the difficulty in meeting the maximum interests of all WPGs within an alliance simultaneously, the tolerance index is proposed to assist WPGs in making concession decisions for cooperation and the tolerance-based alliance strategy is formulated to balance the satisfactions of WPGs and formations of alliances. Compared to the strategies based on non-cooperative games, the proposed strategy based on cooperative games can fully leverage the complementary advantages of each WPG, consider the interests of all WPGs, and foster cooperation and fairness. Simulation results show that WPGs can obtain satisfactory returns by selecting appropriate cooperators under the tolerance-based alliance strategy. It also demonstrates that the proposed MI-DMA-based profit allocation method is more targeted and comprehensive than commonly used cooperative game-based methods.

Game Analysis of Digital Inclusive Financial Platform and Family Entrepreneurial Choice

The difficulty and cost of financing for family entrepreneurship are becoming increasingly prominent, and the issue of how to alleviate the financing constraints of family entrepreneurship has attracted widespread social attention. The financial services provided by digital inclusive finance platforms are beneficial in addressing the negative impact of financing constraints on households' entrepreneurial behaviour. They can contribute to the inclusive growth of China's economy. Thus the financial policies of digital inclusive finance platforms influence households' entrepreneurial choices. This paper constructs a dynamic game model of incomplete information between the platform and families based on the game perspective of micro subjects and explains the impact of the decision of the digital inclusive finance platform on households' choice of entrepreneurship by solving the equilibrium solution in the game tree, and explores the effects of factors such as the government subsidy system, costs and benefits, and the risk of platform loans on the decision-making behaviour of households and the platform by analysing the conditions required for the decision-making subjects to change their decisions in each sub-game. This essay explores the impact of government subsidies, costs, benefits, and the risk of lending to the platform on the decision-making behaviour of households so that the digital inclusive finance platform and families choose the "no support" and "no business" decisions. According to the dynamic game analysis, the government and the digital inclusive finance platform should increase subsidies to the platform, reduce the cost of household entrepreneurship and improve the guarantee system for household entrepreneurship; the digital inclusive finance platform should make use of digital information technology to enhance the platform construction, alleviate information asymmetry, reduce the cost of platform services, actively support household entrepreneurship and promote the increase of household entrepreneurship.

Ecological Compensation Assessment from the Perspective of Spatial Game: a Case Study of the Watershed Ecological Compensation in Anhui Section of the Huaihe River Basin, China

Ecological Compensation Assessment from the Perspective of Spatial Game: a Case Study of the Watershed Ecological Compensation in Anhui Section of the Huaihe River Basin, China

Data Freshness Optimization Under CAA in the UAV-Aided MECN: A Potential Game Perspective

As a promising enabler for edge intelligence, Unmanned Aerial Vehicles (UAV) have become more and more important in Mobile Edge Computing Networks (MECN), such as communication, computation, collection and control service supply. Although Age of Information (AoI) minimization is indispensable for fresh information collection and computation in the UAV-aided MECN, some attackers can launch attacks to deteriorate the availability of precious channel resources, such as revealed channel access attacks (CAAs). Moreover, recent research has not considered the system's active probability and security issues concurrently, e.g., CAA, in the average AoI minimization process. In this paper, to deal with this problem, we consider an AoI-oriented channel access problem under CAA with a game theory viewpoint. Firstly, to obtain a MECN-based AoI indicator under CAA, the system model with active probability consideration is established. Next, the channel access-based AoI minimization problem is formulated from the viewpoint of the Ordinary Potential Game (OPG). Furthermore, two algorithms called AACSD and DCASD are proposed to determine channel access strategies, by which the Nash Equilibrium (NE) solution of the OPG could be reached. Finally, experiments are conducted under homogeneous and heterogeneous parameter settings, and the simulation results evaluate the correctness and effectiveness of our proposals.

Research on ESG Investment Efficiency Regulation from the Perspective of Reciprocity and Evolutionary Game

Research on ESG Investment Efficiency Regulation from the Perspective of Reciprocity and Evolutionary Game

Coverage Strategy for Small-Cell UAV-Based Networks in IoT Environment

In wireless communication, small cells are low-powered cellular base stations that can be used to enhance the coverage and capacity of wireless networks in areas where traditional cell towers may not be practical or cost-effective. Unmanned aerial vehicles (UAVs) can be used to quickly deploy and position small cells in areas that are difficult to access or where traditional infrastructure is not feasible. UAVs are deployed by telecommunication service providers to provide aerial network access in remote rural areas, disaster-affected areas, or massive-attendance events. In this paper, we focus on the scheduling of beaconing periods as an efficient means of energy consumption optimization. The conducted study provides a sub-modular game perspective of the problem and investigates its structural properties. We also provide a learning algorithm that ensures convergence of the considered UAV network to a Nash equilibrium operating point. Finally, we conduct extensive numerical investigations to assist our claims about the energy and data rate efficiency of the strategic beaconing policy (at Nash equilibrium).

Farmers’ Cognition of and Satisfaction with Policy Affect Willingness of Returning Straw to Field: Based on Evolutionary Game Perspective

As an important measure to promote the black soil protection strategy, returning straw to the fields is the choice of government policy to affect the decision-making behavior of farmers, and the policy implementation process is a dynamic game equilibrium process between farmers and the government. In order to explore the influence of policies on farmers’ straw-returning decision-making and stability processes, this paper used a logit model to analyze the influencing factors on farmers’ straw-returning decision-making behavior based on the survey data of 397 farmers in Hailun City, Heilongjiang Province. This study also constructs the evolutionary game model between farmers and government, carrying out a stability strategy analysis and numerical simulation. The results evidence that farmers’ cognition of fertilization technology, ecological protection, policy satisfaction and cognition of straw returning recipients have a significant negative influence on their willingness to return to the field, and the effect intensity decreases successively. What is more, cognition of crop disease resistance has a positive effect on the willingness of returning straw to the field. It is found that the game balancing process of farmers’ behavior and government straw returning policy evolution can be divided into three stages. At present, China’s straw returning policy is in the intermediate stage, and government needs to provide comprehensive compensation for returning straw to the field according to local conditions such as farmers’ willingness, crop conditions and so on.

Retracted: The Equilibrium Mechanism of Interest Distribution in Farmland Transfer: Based on the Perspective of the Three-Party Game

Retracted: The Equilibrium Mechanism of Interest Distribution in Farmland Transfer: Based on the Perspective of the Three-Party Game

Environmental regulation, green credit, and farmers’ adoption of agricultural green production technology based on the perspective of tripartite evolutionary game

The adoption of agricultural green production technologies (AGPTs) is crucial for achieving agricultural green development in developing countries. This paper establishes a tripartite game model to explore the evolutionary influence mechanism of government environmental regulation policies and bank green credit policies on farmers’ adoption of AGPT under different initial conditions and strategy choices. Through theoretical analysis and numerical simulation, we systematically deduce the evolutionary path and equilibrium conditions, as well as examine the synergistic evolutionary effect of these policies. The results demonstrate that government environmental regulation and banks’ implementation of the green credit policies effectively encourage farmers to adopt AGPT. However, conflicts may arise during the dynamic evolution process when banks choose to implement the green credit policy. These conflicts can be mitigated by utilizing market-oriented mechanisms such as loan interest rates, improving bank supervision efficiency, and enhancing farmers’ expected income. The findings of this research provide valuable insights into the development of external incentive mechanisms to promote the adoption of AGPT among farmers and foster green agricultural development.

Green Development of Traditional Villages: Stakeholder Game Perspectives Under Reward and Punishment Policies

Green Development of Traditional Villages: Stakeholder Game Perspectives Under Reward and Punishment Policies