Search Results (136)

Value co-creation among diverse actors in digital innovation ecosystems (DIEs) exhibits characteristics of high complexity and dynamic evolution. Grounded in the Quadruple Helix Theory, this study develops a conceptual model that interlinks “supervisory guides, knowledge providers, technology transformers, and user demand parties.” This model is defined by organizational oversight as its nexus, knowledge and technology as its foundation, outcome transformation as its core, and user needs as its orientation. Building upon this conceptual foundation, we establish a four-party evolutionary game model involving “innovation regulators (government), innovation producers (academic/research institutions), innovation decomposers (enterprises), and innovation consumers (users).” This analytical framework is then applied to systematically investigate the dynamic evolutionary mechanisms and collaborative pathways for value co-creation in DIEs. We construct the payoff matrix and replicator dynamics to derive the system’s Evolutionarily Stable Strategies (ESSs). Numerical simulations via MATLAB R2023b identify the stability conditions for each party’s strategic choices and unravel the influence mechanisms of key parameters. The results demonstrate nine distinct ESSs, categorized into three types: low-level stability, regulation-dominated transitional stability, and high-level cooperative stability. While the agents’ initial strategies do not alter the system’s final equilibrium state, they significantly impact the speed of evolutionary convergence. Critical factors—including regulators’ intervention costs, subsidy and penalty mechanisms, producers’ and decomposers’ cooperation and default costs, and consumer feedback behaviors—collectively drive the system toward the ideal (1, 1, 1, 1) equilibrium. Theoretically, this study enriches the perspective on multi-agent collaboration in value co-creation by introducing a dynamic quantitative analytical framework, thereby addressing a notable gap in the literature. Practically, it provides actionable insights for mechanism design and a solid foundation for policy optimization, aiming to foster a synergistic governance system that integrates “regulatory guidance, market incentives, and social feedback.” Full article

To explore the evolutionary dynamics of green product markets under bounded rationality, this study develops a tripartite evolutionary game model involving the government, passenger vehicle enterprises, and consumers, using China’s new energy vehicle (NEV) market as a case study. By integrating system dynamics with real-world data and policies, the paper simulates strategy evolution paths and identifies equilibrium conditions. The results show a unique evolutionarily stable strategy: the government refrains from regulation, enterprises actively produce NEVs, and consumers actively purchase green products. The government’s strategy is primarily influenced by enterprises, while enterprises’ strategy is mainly driven by consumers. Numerical analysis reveals that when the premium payment ratio of green products (price difference relative to conventional vehicles) is controlled between 27.27% and 31.82%, the market evolves most rapidly toward the ideal equilibrium. Furthermore, when the additional positive benefit ratio of green consumption falls below 36.36%, market formation and development are severely hindered; raising this ratio to 40.91% yields significant promotion effects, beyond which marginal benefits diminish. These findings provide quantitative benchmarks for policy design and strategic decision-making to foster self-sustaining green product markets. Full article

As major sources of pollution and carbon emissions, energy enterprises have long faced challenges in their technological transformation due to the industry’s characteristics of high investment costs and strong lock-in effects. While formal mechanisms such as government subsidies can impose short-term constraints, they fail to stimulate the sector’s intrinsic motivation. Can the reputation incentive mechanism be the key to breaking the deadlock? This paper constructs a three-party evolutionary game model involving energy enterprises, the public, and the government from the perspective of informal institutions. For the first time, it incorporates the dual effects of reputation gains and losses into a unified framework. The results show that reputation incentives are not merely a “cherry on top,” but rather independently drive transformation by moderating enterprises’ cost–benefit structures. The evolution of the three-party strategies exhibits dynamic synergy, and the system equilibrium depends on the threshold matching of key parameters. Subsidy policies are effective in the short term, but may crowd out the role of reputation in the long term. This paper reveals the underlying logic by which the integration of informal institutions and formal regulations drives profound transformation, offering new theoretical perspectives and practical guidance for designing incentive-compatible multi-stakeholder governance frameworks. Full article

Against the dual backdrop of worsening air pollution and industrial intelligent transformation, industrial robot technology has become an important means to promote air pollution synergistic governance. This study innovatively incorporates public environmental satisfaction and industrial robot application as dynamic mechanism variables, constructing an evolutionary game model involving the government, industrial enterprises, and the public. Through theoretical analysis and numerical simulation, the study reveals the influence mechanism of key cost–benefit parameters on stakeholders’ strategic interaction and the system’s evolution path. The conclusions are as follows: (1) The government’s environmental supervision directly affects enterprises’ green transformation willingness, and enterprises’ behavior reversely impacts public satisfaction and supervision effectiveness, forming a “supervision–response–feedback” closed-loop. (2) The cost and benefit parameters related to industrial robots are crucial for the evolution of the game system, and there is significant heterogeneity in their impact on the strategic choices of the three parties. The robot adaptation transformation of enterprise industrial depends on the comprehensive consideration of the transformation cost and the green benefits. Public supervision is regulated by both the supervision cost and the incentive benefit. The government regulation takes into account both the regulatory cost and the loss of social reputation. Various parameters dynamically regulate the system’s equilibrium by altering the party’s cost–benefit structure. (3) The application of industrial robots and the feedback of public environmental satisfaction form a coupling effect, jointly determining the long-term evolution direction of the game system. When the cost benefit and supervision incentives are well-matched, enterprises will actively promote the green transformation of industrial robots in order to achieve intelligent pollution control. The effectiveness of public supervision has also been fully realized. The dynamic adaptation of the two components can lead the system towards an efficient and stable equilibrium in air pollution governance. Full article

Against the background of carbon neutrality, the government’s carbon regulations have had a profound impact on the distributed energy sharing behavior of industrial parks. To deeply explore the interactive relationship between distributed energy sharing in industrial parks and government regulation, this paper constructs a three-party evolutionary game model composed of the government, core enterprises and supporting enterprises; endogenizes government behavior; and integrates inter-enterprise contractual mechanisms into the evolutionary framework. By establishing a revenue payment matrix and a replication dynamic equation, the stability conditions and system evolution paths of the strategy choices of each subject are analyzed, and numerical simulations are conducted. The results show that there are multiple evolutionary stable equilibria in the system, among which the equilibrium where core enterprises actively share, supporting enterprises actively share, and the government actively regulates carbon is the ideal state. Cost-sharing contracts and cooperative penalty contracts play a significant role in promoting the participation of supporting enterprises in sharing and curbing “free-riding” behavior, respectively. The changes in government subsidy rates and carbon tax rates have a crucial impact on the evolution of corporate strategies. Quantitatively, the carbon tax rate exhibits a threshold effect; enterprises shift to positive energy sharing when the tax rate exceeds 0.8, while a subsidy rate above 0.4 leads the government to withdraw from regulation. This indicates that a reasonable design of carbon regulations can help achieve coordinated energy emission reduction between the government and enterprises. The findings provide theoretical support for optimizing carbon regulations and designing cooperation strategies. Full article

The rapid rise of live-streaming e-commerce has fostered a new “content clipping” model, in which secondary creators edit and republish anchors’ live-streaming content to promote product sales. While this model can expand market reach and enhance revenue, it also introduces copyright disputes, regulatory challenges, and profit-sharing conflicts among platforms, anchors, and secondary creators. This study develops a three-party evolutionary game model to examine strategic choices regarding platform regulation, anchor authorization, and secondary content creation. Results reveal that excessive regulation may undermine equilibrium and profitability, while appropriate authorization can balance risk and reward. Secondary creators’ participation is sensitive to commission rates and cost–benefit trade-offs. This research contributes to the literature by integrating copyright governance into live-streaming e-commerce game theory and offers actionable insights for designing regulatory mechanisms, optimizing authorization policies, and fostering sustainable multi-party collaboration. Full article

To enhance cross-border logistics service quality and build a trustworthy and transparent service ecosystem, this paper constructs a tripartite evolutionary game model involving cross-border logistics enterprises, governments, and consumers. Considering operational reliability and information transparency, this paper explores the strategic interactions among stakeholders and the sensitivity of key influencing factors through evolutionary stable strategy analysis and numerical simulation. The results indicate four typical evolutionary scenarios: regulatory silos, feedback failure, administrative dominance, and collaborative governance. The government’s willingness to regulate is positively correlated with the service quality provided by logistics enterprises. Positive consumer feedback strengthens social supervision and exerts a substitution effect on government regulation. Improving operational reliability reduces enterprises compliance costs, driving improvements in logistics service quality. Information transparency can increase the implicit costs of low-quality service providers by empowering consumers’ feedback. While simple reward–punishment mechanisms or consumer compensation may generate short-term benefits, they may weaken the governance effectiveness of other stakeholders, potentially inducing regulatory inertia or false feedback. Full article

This study examines retailers’ information sharing aimed at enhancing product greenness within green supply chains, with consumer participation as a pivotal factor and the overarching goal of advancing the sustainable development of the whole supply chain ecosystem. Each supply chain comprises a green product supplier and a retailer with uncertain demand information. A tripartite evolutionary game model involving manufacturers, retailers, and consumers is constructed to analyze the factors influencing information sharing behavior, which serves as a critical pathway to achieve environmental and economic sustainability in green supply chain operations. The findings highlight two key insights: First, strong consumer willingness to purchase green products may inhibit retailers’ inclination towards information sharing, a counterintuitive outcome that needs to be addressed to align individual stakeholder behaviors with long-term sustainable development goals. Second, lower information sharing costs can motivate retailers to share information with manufacturers; otherwise, manufacturers must adopt technological measures to assist retailers in reducing information sharing-related costs, thereby achieving win–win outcomes across the supply chain and fostering a sustainable and collaborative green supply chain system that balances ecological benefits, economic gains, and social value co-creation. Full article

The promotion of shore power is a key pathway for reducing port-related emissions and achieving sustainable maritime development. This study analyzes the strategic interactions among governments, ports, and shipping companies by constructing a tripartite evolutionary game model. Specifically, it addresses three core questions: (1) how stakeholders’ initial intentions and strategic choices influence the system’s evolutionary path and eventual equilibrium; (2) how critical parameters—including subsidies for shore power infrastructure, wind turbine installation, and ship retrofitting, as well as electricity price support, carbon pricing, and policy implementation costs—shape the dynamics of the system and the equilibrium strategies of the three parties; and (3) how heterogeneity in national energy mixes, particularly the roles of wind turbine, affects decision-making behaviors across different countries. Simulation experiments are conducted to explore the effects of varying policy interventions and energy conditions on the stability of cooperative strategies. The results provide insights into the design of differentiated policy instruments that promote shore power adoption while accounting for the structural characteristics of national energy systems. This research enriches the theoretical application of evolutionary game theory to maritime sustainability and offers practical guidance for governments and stakeholders in advancing decarbonization in the port and shipping sectors. Full article

With the continuous expansion of data trading, the data supply chain system has gradually developed and improved. However, frequent security issues during the data transaction process have seriously hindered the development of the digital economy. As a key link in the data supply chain, the data trading market needs to use blockchain technology to achieve full-chain supervision of the data supply chain, which has become a top priority. Based on prospect theory, this paper constructs an evolutionary game model composed of data suppliers, consumers and data trading markets at all levels. The main factors affecting the system game strategy are discussed. The results show that: (1) The development of the data supply chain system can be divided into three stages, and blockchain technology plays a key role in realizing full-chain supervision of the data transaction process. The costs of blockchain adoption, market rewards, and penalties significantly affect the behavior of all parties. (2) The behavior of data suppliers has strong negative externalities and affects other participants. In addition, the larger the size of the data transaction, the lower the probability of breach by the data provider. (3) Adopting blockchain technology and implementing effective incentives can promote the development of the data supply chain. Full article

With the significant increase in users’ privacy awareness and strict regulatory response, user privacy protection faces a dilemma between platform operational flexibility and commercial potential. The personal data use authorization has become an important mechanism influencing platform data transactions and government regulation, thereby shaping the development trajectory of the data trading market. Previous literature has yet to fully elucidate the complex interactions and evolutionary equilibrium strategies among the parties involved in data transactions. This study builds an evolutionary game model involving three parties—users, platforms, and the government—to explore the evolutionary equilibrium of users’ personal data use authorization strategy, platforms’ data trading strategy, and the government’s regulatory strategy. The findings reveal that: (1) User authorization does not always promote platform data transactions. Under the personal data use authorization mechanism, user authorization facilitates platform data transactions only when either the data transaction price is low and the value of user behavioral data exceeds a certain threshold, or the data transaction price is high and the value of user behavioral data falls within a specific range. (2) User authorization is not a sufficient condition for the government to impose strict regulatory measures on platform data transactions. When the regulatory cost is low, the government’s strict regulatory strategy is influenced by both the data transaction price and the value of user behavioral data. Specifically, under low-price–medium-value or high-price–high-value conditions, the government tends to strictly regulate platform data transactions when users do not authorize the use of personal data. Conversely, under low-price–high-value or high-price–medium-value conditions, the government is more inclined to enforce strict regulation when users authorize the use of personal data. This study contributes to evaluating the role of the personal data use authorization mechanism, offering valuable insights to platforms and the government on data transactions and regulation. Full article

The retrofit of vacant buildings into sustainable integrated medical and elderly care facilities represents an important pathway for promoting urban regeneration and addressing population aging challenges. However, conflicts of interest among key stakeholders frequently compromise the quality of retrofit and long-term operational sustainability. To address this issue, this study develops a tripartite evolutionary game model comprising investors, builders, and operators to examine the behavioral evolution and cooperative mechanisms of these stakeholders across the investment, construction, and operation phases. Simulations were conducted based on a real-world retrofit project in Lanzhou, China, and the results suggest that: (1) Policy preference or reputational incentives alone appear insufficient to maintain cooperation, whereas their integration with economic incentives can effectively enhance the stability of cooperation among the three parties. (2) Builders exhibit higher sensitivity to penalties than operators, underscoring the pivotal role of the construction phase in ensuring retrofit quality. (3) When investors shift their role from short-term compliance regulation to long-term governance, it is more conducive to promoting operators to provide high-quality services in the long run. This paper proposes several suggestions and countermeasures, to provide practical guidance for the multi-party collaborative governance and sustainable operation of integrated medical and elderly care retrofit projects in China under the background of urban renewal. Full article

This study involves the construction of a dynamic evolutionary game model involving three key participants, including the Group Purchasing Organization (GPO), medical institutions, and pharmaceutical suppliers, while comprehensively considering critical factors such as benefit compensation, bad debt risk, and fiscal costs. The model characterizes the strategy evolution of each participant under bounded rationality and imitation learning mechanisms. Based on the replicator dynamics equations, the evolutionary trajectories and equilibrium conditions of the three parties’ strategies are systematically derived. The Jacobian matrix is then used to analyze the local stability of eight boundary equilibria and potential internal mixed equilibria. Furthermore, to capture the optimal adjustment process of the compensation mechanism, the GPO’s compensation level is introduced into an optimal control framework. A controlled evolutionary system is formulated, and the dynamic optimal relationship between compensation intensity and system state is described using the Hamilton–Jacobi–Bellman (HJB) equation. Through analytical linearization and numerical simulations, the optimal feedback compensation law and its closed-loop evolutionary trajectory are obtained, allowing for a comparative analysis between the “fixed compensation” and “optimal compensation” scenarios. The results reveal that an appropriately designed dynamic compensation mechanism can significantly enhance system cooperation stability and overall social welfare. This provides a quantitative theoretical foundation and methodological tool for the refined design and dynamic regulation of pharmaceutical group purchasing policies. Full article

This study constructs a tripartite evolutionary game model within China’s rural tourism context, analyzing strategic interactions among government, tourism enterprises, and local residents to optimize sustainability. By performing an initial examination of the evolutionary game involving three parties, we identify key stakeholder variables and propose enhancement strategies. Findings suggest incentivizing governmental engagement, rewarding enterprises for scenic maintenance, and prioritizing resident knowledge improvement. These insights offer practical cooperation models for structured development while providing an innovative methodological framework for future research. The approach demonstrates potential to inform policy decisions and validate conclusions using AI models, thereby contributing to sustainable rural tourism development. Full article

This study focuses on highway service areas. Building upon prior research that identified key influencing factors through surveys and ISM–MICMAC analysis, it constructs a tripartite evolutionary game model involving the government, service area operators, and carbon reduction technology providers based on stakeholder theory. Combined with MATLAB simulations, the model reveals the dynamic patterns of the carbon reduction system. The results indicate that government strategies exert the strongest influence on the system and catalyze the other two parties, followed by service area operators. Carbon reduction technology providers adopt a more cautious stance in decision-making. Government actions shape system evolution through a “cost-benefit-incentive” triple mechanism, with its strategies exhibiting significant spillover effects on other actors. Enterprise behavior is markedly influenced by Xinjiang’s regional characteristics, where the core barriers to corporate carbon reduction lie in the costs of proactive equipment and technological investments. The willingness of technology providers to cooperate primarily depends on two drivers: incremental baseline benefits and enhanced economies of scale. The core trade-off in government decision-making lies between the cost of strong regulation (Cg1) and the cost of environmental governance under weak regulation (Cg2). An increase in Cg1 prolongs the government’s convergence time by 233.3% and indirectly suppresses the willingness of enterprises and technology providers due to weakened subsidy capacity. Enterprises are relatively sensitive to the investment costs of carbon reduction equipment and technology, with convergence time extending by 120%. Technology providers are highly sensitive to incremental baseline returns (Rt), with stabilization time extending by 500%. Compared to existing research, this model quantitatively reveals the “cost-benefit-incentive” triple transmission mechanism for carbon reduction coordination in “grid-end” regions, identifying key parameters for strategic shifts among stakeholders. Based on this, corresponding policy recommendations are provided for all three parties, offering precise and actionable directions for the sustainable advancement of carbon reduction efforts in service areas. The research conclusions can provide a replicable collaborative framework for decarbonizing transportation infra-structure in grid-end regions with high clean energy endowments. Full article