Search Results (820)

The governance of the rural water environment is essential for improving the quality of life of rural residents and advancing the construction of ecological civilization. However, the current governance system faces issues such as fragmented governance entities and low collaborative efficiency. Therefore, in this study, we focus on the intergovernmental collaborative governance mechanism for rural water environments. Drawing on complex network theory and evolutionary game theory, we employ complex network analysis and construct a complex network evolutionary game model among government departments, and we further conduct numerical simulations to examine the evolutionary dynamics of intergovernmental collaboration in rural water environmental governance. The findings show the following: (1) The reward and punishment mechanism, collaborative gain coefficient, and loss intensification trend coefficient all positively influence the participation rates of local governments. When these parameters exceed certain thresholds, they can rapidly and stably increase the proportion of participating nodes. (2) Nodes with stronger environmental preferences respond more directly to the collaborative gain coefficient, while the loss intensification trend coefficient promotes cooperation by amplifying the cost of non-cooperation. (3) The heterogeneity in economic preferences of local governments affects the stability of cooperation. Governments with stronger environmental priorities are more inclined to form the core of cooperation, whereas those driven by stronger economic priorities are more vulnerable to parameter fluctuations, leading to instability in overall participation levels. Reducing or eliminating this heterogeneity can improve both participation rates and the stability of cooperation. These findings offer theoretical support for designing intergovernmental collaborative governance mechanisms for rural water environments and provide practical guidance for calibrating reward–punishment schemes, identifying key coordinating departments, and stabilizing cross-departmental participation, thereby facilitating an efficient transition in rural water environmental governance models. Full article

The government’s scientific disclosure of food safety inspection information can guide consumers toward rational substitution choices, thereby improving food safety while transforming individual decision-making into collective action, thereby achieving social co-governance. This process activates the “voting with their feet” market mechanism, which exerts pressure on supply chain enterprises to improve quality control. However, the current mismatch between disclosed information and consumer demand significantly weakens this effect. Drawing on evolutionary game theory, this study constructs an evolutionary game model involving producers, sellers, and consumers to explore how information alignment shapes stakeholder behavior. The findings indicate that improving information alignment effectively nudges consumers toward informed substitution choices, reinforcing the market-driven pressure on supply chain enterprises to strengthen quality control; reducing quality control costs is a more effective short-term incentive for sellers than increasing market returns; and when information alignment is low, prioritizing inspections of sellers more efficiently enhances co-governance performance, whereas under high alignment, stronger regulation of producers becomes more effective. Aligning the content, channels, and presentation of government-disclosed inspection information with consumer needs is critical to empowering effective social co-governance. These findings provide theoretical foundations and policy insights to optimize information disclosure strategies and regulatory resource allocation. Full article

Rumour propagation in online social networks poses significant risks to public trust, economic stability, and crisis management. Existing models often struggle with heterogeneous feature spaces, adversarial dynamics between rumours and debunking information, and data sparsity in early outbreak stages. This study introduces a cross-domain framework for group behaviour prediction that integrates unified representation learning, game-theoretic adversarial modelling, and transfer adaptation. A hybrid BERT–Node2Vec encoder captures both semantic richness and structural influence, while evolutionary game theory quantifies competitive interactions between rumour-spreaders and refuters. To alleviate data scarcity, Joint Distribution Adaptation (JDA) aligns heterogeneous feature spaces across domains, enabling robust transfer learning. Evaluated on simulated and real-world social media datasets, the proposed model demonstrates improved accuracy and interpretability in predicting rumour diffusion trends under adversarial conditions. These findings highlight the value of integrating semantic, structural, and behavioural signals into a scalable architecture, offering a practical solution for safeguarding digital ecosystems against misinformation. Full article

Optimizing layout schemes for multi-branch river hubs is complex due to the need to balance conflicting goals—safety, ecology, and economy—under significant uncertainty. To address these challenges, this study proposes a comprehensive evaluation method integrating a dynamic weighting mechanism and a two-dimensional cloud model. First, we constructed an evaluation index system covering engineering safety and benefits. A multi-agent game theory approach was employed for combination weighting to reconcile the diverse interests of government, environmental, and community agents. Furthermore, a dynamic mechanism was introduced to adjust indicator importance across three key stages: dam site selection, hub layout, and detail optimization. Subsequently, the schemes’ uncertainty and risk status were quantified using a two-dimensional cloud model within a “probability-loss” framework. The methodology was validated using the Ganjiang River Hub Project. The results demonstrate that the method effectively captures the evolutionary path of decision-making priorities, transitioning from “safety-first” in early stages to “benefit-maximization” later. This study provides robust, stage-aware, and visual decision support for complex hydraulic engineering layouts, ensuring a scientific trade-off between risk control and comprehensive benefits. Full article

Digital transformation (DT) is reshaping manufacturing, with core enterprises (CEs) leveraging their resources to build industrial Internet platforms (IIPs) that support ordinary enterprises (OEs) in adopting DT. Differences in enterprise roles lead to varying impacts of government subsidies, necessitating careful policy design. Crucially, IIP adoption involves higher-order, multi-player interactions beyond conventional pairwise relationships—a dimension often overlooked in existing quantitative studies. This research employs hypergraph theory to model these complex interactions on IIPs and applies evolutionary game theory to analyze how enterprise decisions and government subsidies shape DT dynamics in manufacturing supply chains. The findings reveal that: (1) The network effect is the primary driver for DT via IIPs, but its promotional impact exhibits diminishing marginal returns. (2) Governments should prioritize subsidizing CEs for platform establishment, as subsidies directed at OEs for DT adoption are less effective. (3) Before withdrawing subsidies, governments must ensure a sufficiently high IIP adoption rate to sustain DT autonomously. This study introduces a novel methodology for examining DT and offers theoretical insights to guide enterprise strategy and policy implementation. Full article

Soil erosion control is an important aspect of promoting ecological civilization and a key support mechanism for achieving the ‘dual-carbon’ goals. The successful implementation of PPP (Public–Private Partnership) projects for soil erosion control requires widespread participation from farmers. Therefore, it is necessary to study the evolutionary mechanisms of farmer participation behavior and the process of their state transformation, as well as exploring how to enhance farmers’ participation willingness. First, a dynamic group model of farmers’ participation behavior was constructed by dividing them into five states: unknown, observing, participating, rejecting, and immune. Then, the strategic interactions between the government, social capital, and farmers under the PPP model were considered, and this was coupled with the dynamic group model. Finally, Chongqing City was taken as a typical case for numerical simulation to analyze the evolutionary patterns of farmers participation behavior. The results indicate that: (1) synergistic effective government regulation and active enterprise governance can elevate the farmer participation rate to approximately 71% and facilitate the convergence of the system toward a stable high-participation equilibrium; (2) government subsidies need to be controlled within a reasonable range to ensure policy effectiveness; (3) improving government publicity and enhancing the social atmosphere can increase farmers’ participation rate to approximately 71% and 78%, respectively, significantly boosting their willingness to participate; (4) improving the social security system and reducing perceived risks can help increase farmers’ participation rate. The research conclusions can provide a valuable reference for local governments in China in formulating soil erosion control policies. Full article

At the critical juncture where Chinese cities are transitioning toward intensive urban renewal and sustainable development, the revitalization and adaptive reuse of industrial heritage face a collective action dilemma stemming from the misaligned interests among three key stakeholders: the Local Government (LG), the Industrial Heritage Developer (IHD), and the Neighboring Complementary Merchants (NCMs). To address this challenge, this study constructs a tripartite evolutionary game model and innovatively proposes an analytical framework of a Multi-Dimensional Policy Lever System, which integrates spatial synergy (k, w, v), economic incentives (p₁, p₂, q), and behavioral regulation (m, n). Numerical simulations reveal that the successful regeneration of industrial heritage does not rely on any single policy but fundamentally depends on the systematic coordination and dynamic adaptation of these three-dimensional levers. The nonlinear coupling of spatial elements forms the foundation for value leapfrogging. The economic driving force requires a critical shift from government subsidies (p) towards a market-based value capture and recycling mechanism (q). Behavioral interventions provide the necessary cognitive and normative safeguards for cooperation. The research elucidates a three-phase evolutionary pattern of the system, transitioning from a stalemate to synergy, and emphasizes the need for an adaptive and sequential combination of policies. The theoretical contribution of this study lies in providing an integrative quantitative analytical framework. Its practical significance is to offer a scientific basis for decision-makers to construct a dynamic policy toolbox and promote the sustainable collaborative governance of industrial heritage. Full article

Under the constraints of China’s “Dual Carbon” targets, promoting green consumption has emerged as a critical market-based strategy to drive industrial decarbonization and achieve sustainable development. However, the existing literature primarily focuses on supply-side government regulation, leaving the mechanism of how demand-side constraints influence the strategic interaction between the government and enterprises under-explored. To bridge this gap, this paper constructs an evolutionary game model incorporating performance-based government incentives, consumer low-carbon preferences, and corporate abatement costs. Unlike theoretical models with hypothetical parameters, this study calibrates the simulation parameters using empirical data from the steel industry in Zhejiang Province, a pilot zone for China’s ecological civilization construction. The simulation results indicate that: First, under the current empirical parameters, the system fails to spontaneously converge to the ideal equilibrium state, highlighting a “governance deadlock”; second, consumer preference intensity serves as a vital external force that can effectively break this deadlock and reduce the government’s regulatory burden; and finally, sensitivity analysis reveals the critical thresholds for the synergistic effect between regulatory policies and market demand. Based on these findings, policy recommendations are proposed to foster a collaborative governance mechanism integrating government guidance, market-driven approaches, and demand-side driving forces. Full article

Background: From the perspective of product liability, this study explores how agricultural product e-commerce enterprises can enhance the quality of the agricultural product supply chain through quality incentive strategies. Methods: Based on a tripartite evolutionary game model, the strategic interactions among farmers, agricultural product e-commerce enterprises, and the government are analyzed. Results: The research finds that whether the system converges to the ideal equilibrium of “high-quality production—ex-ante quality cost-sharing—collaborative governance” depends on the combined effects of revenue distribution, liability costs, and external incentives or penalties. Among these, government-led collaborative governance plays a key guiding role in incentivizing enterprises and influencing farmers’ behaviors. The incentive measures implemented by e-commerce enterprises and government penalties can effectively curb farmers’ low-quality production behaviors. Conclusions: The study further reveals how factors such as ex-ante cost-sharing, liability allocation, and farmers’ conformity psychology affect the stability of agricultural product supply chain quality, thereby providing theoretical support for constructing a “policy-platform-farmer” collaborative governance framework. Full article

The development of the new energy vehicle (NEV) industry has become a key driver of the global low-carbon transition. Understanding the policy effect on NEV diffusion is essential to promote sustainable growth. In this study, we propose a new approach that combines a two-layer small-world network involving consumers and enterprises and evolutionary game theory to study the diffusion effect of industrial and trade policies on enterprises’ low-carbon production strategies and consumer preferences. Different from existing diffusion models, we integrate reinforcement learning (RL) into the decision-making process of enterprises and use SHapley Additive exPlanations (SHAP) to decode the micro-level decision logic of enterprises. In terms of the decision-making mechanism, the simulation results show that the Q-learning algorithm better fits the real market diffusion trend of NEVs compared with traditional algorithms; in terms of policy effects, industrial policies and trade policies exhibit a synergistic effect. SHAP analysis reveals that enterprises are more concerned about NEV market maturity than the impact of policy parameters on decision-making; Sobol sensitivity analysis indicates that consumer subsidies have a greater impact on the market diffusion of NEVs than trade policies. Full article

To address collaborative decision-making challenges in the pharmaceutical logistics supply chain amid public health emergencies, this study integrates disappointment aversion, delay effects, and pharmaceutical value attenuation, constructing a three-echelon system. It adopts a “differential game-system dynamics (SD)” two-layer dynamic research method for in-depth synergy. The differential game model focuses on multi-agent dynamic strategic interactions, deriving time-series equilibrium solutions for the optimal effort levels, transportation efficiency, and profits under four decision modes (decentralized, government subsidy, cost-sharing, centralized) to clarify the dynamic impact laws of the core parameters. Compensating for its limitations in complex environmental coupling and practical variable integration, the SD model incorporates the patient consumption rate, inventory fluctuations, weather disturbances and other real factors to build a dynamic feedback system. It not only verifies the practical adaptability of the differential game equilibrium solutions but also reveals the evolutionary laws of supply chain performance and the amplified inter-mode performance differences under multi-factor superposition. This study finds that centralized decision-making performs the best in terms of transportation efficiency peaking, profit stability, and attenuation control. Pharmaceutical stability and enterprise effort levels positively drive benefits, while disappointment aversion and excessive delays exert inhibitory effects. Government subsidies need to be paired with collaborative mechanisms to avoid policy dependence. Management implications suggest that enterprises should prioritize the collaborative centralized-decision-making mode, establish risk-sharing and benefit-sharing mechanisms, precisely regulate key variables, and implement gradient subsidies with exit mechanisms to enhance the supply chain’s dynamic adaptability and achieve the triple optimization of “efficiency–profit–stability”. 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

The unbridled pursuit of statistical rationality has precipitated a crisis of value rationality in e-commerce ecosystems, leading to algorithmic involution—a dilemma characterized by destructive hyper-competition. To reconcile this theoretical paradox and explore effective governance pathways, this paper constructs a tripartite evolutionary game model involving e-commerce platforms, government regulators, and consumers. Simulation results indicate that high-intensity government deterrence constitutes the necessary stability foundation of hard constraints, while consumer activism acts as the decisive accelerator of the soft environment contingent on high synergistic gains and low information screening costs. Furthermore, a platform’s pivot toward “algorithm for good” is not driven by altruism, but by the rational calibration between short-term extractive gains and long-term benevolent returns. Sensitivity analysis confirms that reducing the ratio of these two factors is the effective lever to speed up system convergence. Finally, effective governance requires restructuring this payoff matrix by establishing dynamic penalty mechanisms and transparent low-cost feedback channels to render ethical algorithmic behavior a dominant strategy in terms of economic rationality. This research aims to guide the e-commerce ecosystem from a zero-sum game of involution toward a sustainable equilibrium of multi-party value co-creation. Full article

Driven by the “dual carbon” goal and the strategy for cultivating new productive forces, China’s economy is undergoing a crucial transformation from high-speed growth to high-quality development. As a typical high-energy consumption and high-emission sector, the green and low-carbon transformation of the building materials industry directly affects the optimization of the national energy structure and the realization of ecological goals. However, traditional building material enterprises generally face practical challenges such as low resource utilization efficiency, insufficient digitalization and greening integration of the industrial chain, and weak green innovation momentum. The transformation actions of a single entity are difficult to break through systemic bottlenecks, and it is urgently necessary to establish a dynamic evolution mechanism involving multiple entities in collaboration. This paper aims to explore the evolutionary rules and stability of digital green (DG) transformation strategies of building materials enterprises (BMEs) under multi-agent interactions involving government, universities, and consumers. Centering on BMEs, a four-party evolutionary game model among the government, enterprises, universities, and consumers is constructed, and the evolutionary processes of strategic behaviors are characterized through replicator dynamic equations. Using MATLAB R2022 (Version number: 9.13.0.2049777) bnumerical simulations, this study investigates how key parameters, such as government subsidies, penalty intensity, and consumers’ green preferences, affect the transformation pathways of enterprises. The results reveal that the DG transformation behavior of BMEs is significantly influenced by governmental policy incentives and universities’ knowledge innovation. Stronger subsidies and penalties enhance enterprises’ willingness to adopt proactive DG strategies, while consumers’ green preferences further accelerate transformation through market mechanisms. Among multiple strategic combinations, active DG transformation emerges as the main evolutionarily stable strategy. This study provides a systematic multi-agent collaborative analysis framework for the transformation of BME DG, revealing the mechanisms by which policies, knowledge, and market demands influence enterprise decisions. Thus, it offers theoretical and decision-making references for the green and low-carbon transformation of the building materials industry. Full article

Intermittently Connected Wireless Networks (ICWNs) are characterized by dynamic node mobility and the absence of persistent end-to-end paths, making them highly susceptible to security threats. This paper proposes a novel secure routing protocol, called the Evolutionary Game Theoretic model with Reinforcement Learning (EGT-RL), designed to provide adaptive and resilient protection against blackhole attacks in such networks. EGT-RL integrates Q-learning for dynamic threat assessment with evolutionary game theory to model and influence node behavior over time. Simulation results, based on both synthetic and real-world mobility traces, show that EGT-RL significantly outperforms three benchmark protocols in delivery ratio, packet drops, end-to-end latency, and communication overhead. Full article