Search Results (59)

In the digital economy, information asymmetry among individuals, data users, and governments limits the full realization of personal data value. To address this, “symmetry enhancement” strategies aim to reduce information gaps, enabling more balanced decision-making and facilitating efficient data flow. This study establishes a tripartite evolutionary game model based on personal data collection and development, conducts simulations using MATLAB R2024a, and proposes countermeasures based on equilibrium analysis and simulation results. The results highlight that individual participation is pivotal, influenced by perceived benefits, management costs, and privacy risks. Meanwhile, data users’ compliance hinges on economic incentives and regulatory burdens, with excessive costs potentially discouraging adherence. Governments must carefully weigh social benefits against regulatory expenditures. Based on these findings, this paper proposes the following recommendations: use personal data application scenarios as a guide, rely on the construction of personal trustworthy data spaces, explore and improve personal data revenue distribution mechanisms, strengthen the management of data users, and promote the maximization of personal data value through multi-party collaborative ecological incentives. Full article

Trade-in programs have become a vital mechanism for promoting sustainable consumption and reducing negative impacts on the environment, gaining substantial support from branders, e-platforms, and consumers in recent years. Concurrently, the emergence of professional recyclers has provided firms with viable alternatives for the outsourcing of recycling processes. To investigate the optimal leadership and recycling model with respect to trade-in operations, this study examines the strategy selection in a platform-based supply chain under a resale model. A two-period game-theoretic framework is developed, encompassing four models: self-recycling and outsourcing models under the leadership of the brander or platform. The main findings are as follows: (1) In markets characterized by a low consumer price sensitivity, both branders and platforms tend to choose the self-recycling model to capture the closed-loop value. In contrast, in highly price-sensitive markets, both parties exhibit a preference for “free-riding” strategies. (2) Once the recycling leader is determined, adopting a self-recycling model can lead to a relative win–win outcome in high price sensitivity contexts. (3) With a short product iteration cycle, both the brander and platform should strategically lower their prices in the first period, sacrificing short-term profits to enhance trade-in incentives and maximize long-term gains. (4) When the brander leads the recycling process, they should consider reusing the resources derived from old products; however, in platform-led models, the brander can only consider reusing the recycled resources in a low price sensitivity market. This study provides strategic insights for the sustainable development of the supply chain through the analysis of a game between a brander and an e-commerce platform, enriching the literature on CLSCs through integrating trade-in leadership selection and the choice to outsource, offering theoretical support for dynamic pricing strategies over multi-period product lifecycles. Full article

As the demand for expansive back-end systems in online applications continues to grow, novel frameworks are necessitated to address the escalating operational demands, energy consumption, and associated costs. Traditional Client–Server models, while offering centralized security and reliability, are characterized by their high deployment and maintenance expenses. Conversely, Peer-to-Peer (P2P) models, despite being cost-effective and scalable, are hindered by inherent security and data integrity challenges. Moreover, the lack of a central authority in P2P systems complicates a definitive resolution of scenarios involving stakes, where users cannot withdraw without incurring a tangible loss. In this research work, a hybrid back-end framework is introduced, combining the advantages of both models through the utilization of cryptographic algorithms and Secure Multi-Party Computation (MPC) protocols. The baseline solution is lightweight and fully composable, making it capable of utilizing different more complex slot-in MPC techniques. The proposed framework’s effectiveness is demonstrated through a simplified two-player Spades game, although it is fully generalizable to any application. Evaluations across multiple case studies reveal substantial performance enhancements compared to conventional approaches, particularly post-initialization, highlighting the scheme’s potential as a cost-effective, energy-efficient, and secure solution for modern online applications. Full article

A conflict is a situation where multiple stakeholders have different evaluations over possible scenarios or states. Conflict analysis is an essential tool for understanding and resolving complex conflicts, especially in scenarios involving multiple stakeholders and uncertainties. Confrontation analysis (ConAna) and graph model for conflict resolution (GMCR) have been integrated for dilemma reasoning and conflict resolution in region crisis analysis. This paper discusses the application of decision-theoretic rough sets (DTRS) to three-way decisions (3WD) in dilemma reasoning and conflict resolution. Three-way decisions are a strategy for making decisions under uncertain conditions, which compensates for the shortcomings of traditional two-way decisions (such as accept or reject) by introducing a “delayed decision” option. In terms of dilemma reasoning, we try to address incomplete or conflicting information and provide a more reasonable decision path for decision-makers through comprehensive evaluation of multi-criteria. In terms of conflict resolution, the DTRS model seeks a compromising solution that is acceptable to all parties by analyzing the game relationship between different stakeholders. The DTRS model combines decision-making theory and rough set theory to determine the balanced decision region by constructing a game between multiple criteria. This dynamic integration is of great significance for the study of complex international conflicts, providing a cross-disciplinary perspective for related research. In this paper, we demonstrate the application of DTRS in 3WD and discuss the relationship between DTRS and probabilistic rough sets. The research shows that the DTRS model has significant advantages in dealing with complex decision problems and can effectively deal with the conflicts and uncertainties in multi-criteria decision-making. Full article

With the shift of the global innovation model from traditional closed-loop to open ecosystems, knowledge sharing and collaborative cooperation among firms have become key to obtaining sustainable competitive advantages. However, existing studies mostly focus on the static structure, and there is an insufficient exploration of the dynamic evolutionary mechanism and multi-party game strategies. In this paper, a two-dimensional analysis framework integrating the evolutionary game and the Lotka–Volterra model is constructed to explore the behavioral and strategic evolution of core enterprises, SMEs and the government in the innovation ecosystem. Through theoretical modeling and numerical simulation, the effects of different variables on system stability are revealed. It is found that a moderately balanced benefit allocation can stimulate two-way knowledge sharing, while an over- or under-allocation ratio will inhibit the synergy efficiency of the system; a moderate difference in the knowledge stock can promote knowledge complementarity, but an over-concentration will lead to the monopoly and closure of the system; and the government subsidy needs to accurately match the cost of the openness of the enterprises with the potential benefits to the society, so as to avoid the incentive from being unused. Accordingly, it is suggested to optimize the competition structure among enterprises through the dynamic benefit distribution mechanism, knowledge sharing platform construction and classification subsidy policy, promote the evolution of the innovation ecosystem to a balanced state of mutual benefit and symbiosis, and provide theoretical basis and practical inspiration for the governance of the open innovation ecosystem. Full article

Amid accelerating population aging and the rapid evolution of digital technologies, the digital transformation of rural elderly care services has become a pivotal strategy for restructuring the rural elderly care system. This study identified the local government, rural elderly care service centers, and the elderly population as the principal stakeholders, and developed a tripartite evolutionary game-theory model to examine the dynamic strategic interactions among these actors under the influence of digital technologies. The model further investigated the evolutionary trajectories and equilibrium conditions of their behavioral strategies. Numerical simulations conducted via MATLAB were employed to validate and visualize the model outcomes. The findings revealed the following. (1) The evolutionary equilibrium of digital elderly care service development in rural areas is jointly determined by the strategic choices of the three parties, with its stability shaped by a complex interplay of cost structures, incentive mechanisms, and utility outcomes. (2) Cost factors exhibit heterogeneous effects across stakeholders. Specifically, excessive regulatory costs diminish the performance incentives of local governments, digital infrastructure and operational expenditures influence service centers’ capacity for precision-oriented service delivery, and the participation of the elderly is constrained by affordability thresholds. (3) Local government behavior demonstrates a pronounced sensitivity to incentives. In particular, rewards and social reputation conferred by higher-level governmental bodies exert a significantly stronger influence than punitive measures. (4) Government subsidies for digital transformation enhance cross-stakeholder synergy through dual transmission channels. Nonetheless, excessive subsidies may escalate fiscal risk, while moderately calibrated penalty mechanisms effectively curb moral hazard within service centers. This study advances theoretical understanding of multi-stakeholder coordination in the context of digitally enabled rural elderly care and provides actionable insights for policymakers aiming to formulate interest-aligned strategies and construct resilient, intelligent governance systems for elderly care. Full article

The intelligent connected vehicle (ICV) industry encounters substantial challenges related to technology, policies, and funding. Its development relies not only on the close collaboration and technological innovation between carmakers and technology companies but also on the support of government’s incentive policies. Therefore, this paper establishes a tripartite evolutionary game model that involves governments, carmakers, and technology companies to investigate the stability equilibrium strategy of multi-party participation in promoting the development of the ICV industry. In addition, by analyzing relevant regulations and company annual reports, this paper conducts a simulation analysis to examine how government incentive policies and benefit distribution mechanisms impact the evolutionary trajectory. Several insightful and practical conclusions are drawn. First, in the early stages of industrial development, the government’s infrastructure investment could promote the cross-border innovation cooperation between carmakers and technology companies, thereby accelerating the advancement of ICVs; however, the long-term impact of the sustained investment remains limited. Second, the incremental government subsidies for carmakers and technology companies within limits could increase the probability of them choosing to cooperate and innovate with each other. Still, the excessive subsidies could result in unstable industry growth. Finally, the increase in the benefit distribution ratio for carmakers with professional technology in automotive technology and vehicle design has a positive effect on the development of the ICV industry. This paper expands the research scope of ICVs and provides theoretical insights for promoting the sustainable development of the ICV industry from policy and market viewpoints. Full article

The river chief system (RCS) has been progressively integrated into rural river governance, resulting in notable improvements in river environments. However, the governance involves multiple stakeholders with conflicting interests and challenges, including low efficiency in collaborative governance. Based on evolutionary game theory, this paper explores the strategy evolution mechanism of multiple stakeholders in rural river governance under the RCS. A four-party evolutionary game model is constructed, involving the government, rural river chiefs, functional organizations, and villagers. By employing phase diagrams, Jacobian matrices, and Lyapunov’s first method, we investigate the evolutionary process of the four-party game and analyze its asymptotic stability. The study identifies the following two evolutionary stable strategies: lenient supervision, no patrol, governance, and participation and lenient supervision, no patrol, governance, and non-participation. Then, numerical simulation analysis is conducted using MATLAB 2024b to validate the scientific rigor and effectiveness of the evolutionary game model and analyze the impact of key parameters’ changes on the strategy choices of each stakeholder. The findings provide guidance for improving the efficiency of multi-stakeholder collaboration in rural river governance and the smooth implementation of the RCS in rural areas. Full article

Mine water is both wastewater and a valuable unconventional water resource, and its recycling is crucial for the sustainable development of coal-resource-based cities. In response to the complex interactions among multiple stakeholders in the process of mine water recycling, this study innovatively develops a four-party evolutionary game model involving local government, coal mining enterprises, mine water operators, and water users. For the first time, key variables—mine water pricing, water volume, water rights trading, water resource taxation, and objective utility of water resources—are systematically integrated into a multi-agent game framework, extending the analysis beyond conventional policies, such as penalties and subsidies, to explore their impact on recycling behavior. The results show the following: (1) There are 10 possible evolutionary stabilization strategies in the system. The current optimal strategy includes supply, input, use, active support, while the ideal strategy under the market mechanism includes supply, input, use, passive support. (2) Local governments play a leading role in collaborative governance. The decisions of coal mining enterprises and mine water operators are highly interdependent, and these upstream actors significantly influence the water users’ strategies. (3) Government subsidies exhibit an inverted U-shaped effect, while punitive measures are more effective than incentives. The tax differential between recycled and discharged mine water incentivizes coal enterprises to adopt proactive measures, and water rights trading significantly enhances the users’ willingness. (4) Mine water should be priced significantly lower than fresh water and reasonably balanced between stakeholders. Industries with lower objective utility of water tend to prioritize its use. This study provides theoretical support for policy optimization and a market-based resource utilization of mine water. Full article

At present, the high complexity of the environment, the uncertainty of income, and the choice of strategies have attracted extensive attention from all walks of life who are committed to studying the game of collaborative innovation between government and industry–university–research. Based on this, first of all, with the help of stochastic evolutionary game theory and fuzzy theory, this paper constructs a multi-party stochastic evolutionary game model of green technology innovation about the government guidelines and the joint promotion of industry, universities, and research institutes. Secondly, it discusses the evolution law of behavior strategies of each game subject and the main factors to maintain the alliance’s stability under fuzzy income. The numerical simulation results show the following: (1) Reputation gains have a significant positive correlation with the evolution stability of alliance behavior, and the incorporation of reputation gains or losses will effectively maintain the cooperation stability of the alliance. (2) Under the influence of product greenness, government subsidies, and long-term benefits, it will promote the pace consistency of cooperative decision-making between industry, universities, and research institutes, and accelerate the evolution of alliances. (3) The enterprise’s ability and the research party’s ability will restrict each other. When one party’s ability is low, its willingness to choose a cooperation strategy may be slightly low due to technology spillover and other reasons. When the two parties’ abilities match, their behavior strategies will increase their willingness to cooperate with their abilities. Compared with the traditional evolutionary game, this study fully considers the uncertainty of the environment and provides theoretical support and practical guidance for the high-quality development strategy of the industry–university–research green technology innovation alliance. Full article

Currently, some platform-based enterprises are selling users’ private information to capture high revenue, which poses a great threat to users’ privacy and security and also poses a challenge to the work of regulators. This paper constructs a tripartite evolutionary game model among platform-based enterprises, users, and regulators by combining theories of daily activities. This paper explores the equilibrium strategy for the leakage of users’ privacy information on online platforms under the concept of multiparty governance and designs four simulation experiments based on the revenue intervals of platform-based enterprises’ decisions. Finally, the model is validated by means of simulation. The results show that when platform-based enterprises make less profit from compromising users’ privacy, users are motivated to participate in shared governance with minimal incentives from the regulator. Regulators can effectively deter privacy leakage by fining platform-based enterprises for leaking user privacy information and requiring them to compensate users for their losses. At this point, they can achieve effective control over privacy leakage by using traditional regulation. When platform-based enterprises make high profits from leaking users’ privacy, they will adhere to their privacy leaking strategy. At this point, privacy security is at its most serious, and users’ privacy rights are not effectively protected. Users and regulators will tend to cooperate to form a multiparty regulatory system, but this does not influence the strategy choice of platform-based enterprises. Full article

To address the pressing challenges of quality and sustainability in agricultural product supply chains, this paper proposes a multi-stakeholder collaborative governance framework. Adopting the perspective of collaborative governance and sustainability, the paper develops an evolutionary game model of the Chinese agricultural product supply chain. This model involves four key stakeholders: agricultural enterprises, the government, NGOs, and consumers. It integrates sustainability principles to ensure that the decisions of each stakeholder contribute to the quality and safety of agricultural products while also promoting long-term environmental and social well-being. The simulation results demonstrate the critical importance of multi-stakeholder collaboration in strengthening governance and promoting sustainability. Based on these findings, the government is advised to implement technology-driven oversight mechanisms, such as AI-based inspections and blockchain traceability. Additionally, a tiered penalty system should be established, escalating penalties for repeat offenders. Regulatory cost-sharing mechanisms can also help ensure continuous enforcement without imposing excessive financial burdens on any single party. NGOs play a vital role in exposing corporate violations and can be more effective through targeted financial support and crowdsourced monitoring platforms. Consumers, as active participants in governance, should be incentivized with reward-based reporting systems and verified compliance feedback, which influence enterprise reputation. Public–private sustainability partnerships and real-time transparency platforms can further facilitate active participation from all stakeholders. By implementing these measures, the regulatory framework can evolve from traditional enforcement to a dynamic, data-driven governance model, fostering long-term sustainability and risk reduction in agricultural production. Full article

Real-time dynamic capture of a single moving target is one of the most crucial and representative tasks in UAV capture problems. This paper proposes a multi-UAV real-time dynamic capture strategy based on a differential game model to address this challenge. In this paper, the dynamic capture problem is divided into two parts: pursuit and capture. First, in the pursuit–evasion problem based on differential games, the capture UAVs and the target UAV are treated as adversarial parties engaged in a game. The current pursuit–evasion state is modeled and analyzed according to varying environmental information, allowing the capture UAVs to quickly track the target UAV. The Nash equilibrium solution in the differential game is optimal for both parties in the pursuit–evasion process. Then, a collaborative multi-UAV closed circular pipeline control method is proposed to ensure an even distribution of capture UAVs around the target, preventing excessive clustering and thereby significantly improving capture efficiency. Finally, simulations and real-flight experiments are conducted on the RflySim platform in typical scenarios to analyze the computational process and verify the effectiveness of the proposed method. Results indicate that this approach effectively provides a solution for multi-UAV dynamic capture and achieves desirable capture outcomes. Full article

The promotion of energy conservation and emission reduction involves a multi-party game among governments, enterprises, and other stakeholders. To explore the game relationships among governments, the public, and coal-fired power enterprises under the “dual carbon targets”, this paper constructs an evolutionary game model for energy conservation and emission reduction involving three parties: the government, coal-fired power enterprises, and the public. Through a theoretical analysis and simulation analysis of the case study involving a central Hebei energy enterprise in China, the impact of parameter variations on the strategic choices of all parties and the evolutionarily stable strategies of the system is thoroughly discussed. The research findings indicate that reducing public supervision costs, increasing government rewards, subsidies, and penalties, and enhancing government regulatory capabilities are crucial factors in promoting energy-saving and emission-reduction efforts by coal-fired power enterprises. After multiple evolutionary iterations, the tripartite evolutionary game system ultimately reaches an evolutionarily stable state of government regulation, public supervision, and energy-saving and emission-reduction by coal-fired power enterprises at the point $E_8(\mathrm{1,1},1)$. Based on these findings, we propose a series of policy recommendations aimed at providing theoretical support for the Chinese government to achieve its energy-saving and emission-reduction strategies under the dual-carbon targets. These recommendations also offer practical guidance for the government in formulating emission reduction policies, for enterprises in optimizing their operational strategies, and for the public in participating in emission reduction efforts. Full article

The collaborative promotion of agricultural green technology innovation and adoption (AGTIA) is essential for achieving green agriculture. However, there remains a need to raise both innovation and adoption levels, necessitating explorations of the effects of government subsidies and collaborative mechanisms. To this end, this paper builds an evolutionary game model to analyze the collaborative promotion of AGTIA. By introducing relevant parameters, such as government subsidies for AGTIA, dividends and liquidated damages within industrial technology innovation alliances (ITISAs), and cost reduction coefficients, this paper explores the impacts of the technology spillover effect, price premium of green agricultural products, and government subsidies on the strategic choices of related participants. The main findings are as follows: (1) The key factors influencing AGTIA are different and the government can implement different combinations of dynamic and static subsidy mechanisms at distinct stages of agricultural green development. Government subsidies play a major role at the initial stage, while ITISAs should take fuller advantage of AGTIA as green agriculture matures. (2) Increasing subsidies can promote AGTIA at the initial stage. However, an optimal range of subsidies exists, and when subsidies are higher than a certain threshold, government subsidy willingness fluctuations may lead to decreased stability. (3) There is a threshold of liquidated damages within ITISAs. Only when liquidated damages exceed the threshold can they facilitate the development of durable ITISAs and discourage free-rider behavior. The above findings can provide theoretical support for relevant government sectors when issuing policies to promote AGTIA and agricultural green development. Full article