Search Results (374)

Under China’s ‘Dual Carbon’ strategy, the power sector plays a central role in achieving carbon neutrality. This study develops a bi-level game-optimization model involving the government, power producers, and technology suppliers to explore the dynamic coordination between shadow carbon pricing and emission trajectories. The upper-level model, guided by the government, focuses on minimizing total costs, including emission reduction costs, technological investments, and operational costs, by dynamically adjusting emission targets and shadow carbon prices. The lower-level model employs evolutionary game theory to simulate the adaptive behaviors and strategic interactions among power producers, regulatory authorities, and technology suppliers. Three representative uncertainty scenarios, disruptive technological breakthroughs, major policy interventions, and international geopolitical shifts, are incorporated to evaluate system robustness. Simulation results indicate that an optimistic scenario is characterized by rapid technological advancement and strong policy incentives. Conversely, under a pessimistic scenario with sluggish technology development and weak regulatory frameworks, there are substantially higher transition costs. This research uniquely contributes by explicitly modeling dynamic feedback between policy and stakeholder behavior under multiple uncertainties, highlighting the critical roles of innovation-driven strategies and proactive policy interventions in shaping effective, resilient, and cost-efficient carbon pricing and low-carbon transition pathways in the power sector. Full article

Background and Objectives: Depression is a leading cause of disability globally, with treatment challenges including limited access, stigma, and poor adherence. Gamification, which applies game elements such as points, levels, and storytelling into non-game contexts, offers a promising strategy to enhance engagement and augment traditional treatments. Our research is the first study designed to explore the implementation of gamification within the Malaysian context. The objective was to explore the feasibility of implementation of gamification as an adjunctive treatment for adults with depression. Materials and Methods: Focus group discussions were held with five mental health professionals and ten patients diagnosed with moderate depression. The qualitative component assessed perceptions of gamified interventions, while quantitative measures evaluated participants’ depressive and anxiety symptomatology. Results: Three key themes were identified: (1) understanding of gamification as a treatment option, (2) factors influencing its acceptance, and (3) characteristics of a practical and feasible intervention. Clinicians saw potential in gamification to boost motivation, support psychoeducation, and encourage self-paced learning, but they expressed concerns about possible addiction, stigma, and the complexity of gameplay for some patients. Patients spoke of gaming as a source of comfort, escapism, and social connection. Acceptance was shaped by engaging storylines, intuitive design, balanced difficulty, therapist guidance, and clear safety measures. Both groups agreed that gamification should be used in conjunction with standard treatments, be culturally sensitive, and be presented as a meaningful therapeutic approach rather than merely as entertainment. Conclusions: Gamification emerges as an acceptable and feasible supplementary approach for managing depression in Malaysia. Its success depends on culturally sensitive design, robust clinical oversight, and seamless integration with existing care pathways. Future studies should investigate long-term outcomes and establish guidelines for the safe and effective implementation of this approach. We recommend targeted investment into culturally adapted gamified tools, including training, policy development, and collaboration with key stakeholders to realistically implement gamification as a mental health intervention in Malaysia. Full article

Driven by the goal of “double carbon”, we propose an investment proportion optimization method based on cooperative game theory to optimize the investment of multiple entities and evaluate the effectiveness of the new power system. The asymmetric Nash negotiation model is introduced to balance the interests of each investment entity. At the same time, a comprehensive investment benefit evaluation index system covering economic, environmental, and social benefits is constructed, and the overall investment benefit evaluation is obtained by using the Delphi method, analytic hierarchy process, and fuzzy comprehensive evaluation method. Through the case analysis of the multi-energy complementary energy system project investment, the validity of the multi-subject investment proportion optimization model and the investment benefit analysis model are verified, and the feasibility of the project investment is demonstrated to provide theoretical guidance and practical reference for the research in related fields. Full article

AI-powered health assistants offer promising opportunities to enhance health management among older adults. However, real-world uptake remains limited, not only due to individual hesitation, but also because of complex interactions among users, platforms, and public policies. This study investigates the dynamic behavioral mechanisms behind adoption in aging populations using a tripartite evolutionary game model. Based on replicator dynamics, the model simulates the strategic behaviors of older adults, platforms, and government. It identifies evolutionarily stable strategies, examines convergence patterns, and evaluates parameter sensitivity through a Jacobian matrix analysis. Results show that when adoption costs are high, platform trust is low, and government support is limited, the system tends to converge to a low-adoption equilibrium with poor service quality. In contrast, sufficient policy incentives, platform investment, and user trust can shift the system toward a high-adoption state. Trust coefficients and incentive intensity are especially influential in shaping system dynamics. This study proposes a novel framework for understanding the co-evolution of trust, service optimization, and institutional support. It emphasizes the importance of coordinated trust-building strategies and layered policy incentives to promote sustainable engagement with AI health technologies in aging societies. Full article

In the face of economic, social, and environmental pressures, the issue of sustainable development has garnered widespread attention in the Logistics Service Supply Chain (LSSC) with risk attitudes under Technical Output Uncertainty. In this regard, this paper first constructs an optimal emission reduction investment game model for an LSSC composed of Logistics Service Integrators (LSIs) and Logistics Service Providers (LSPs) against the backdrop of Technical Output Uncertainty. To this end, it quantifies the participants’ risk attitudes using a mean-variance model to analyze optimal emission reduction investment decisions for centralized and decentralized LSSC under different levels of risk tolerance. Subsequently, it designs a joint contract with altruistic preferences for sharing emission reduction costs in the LSSC. This contract analyzes the parameter constraints for achieving Pareto optimization within the supply chain. Finally, the study employs a case simulation to analyze the changes in expected revenues for centralized LSSC and joint contracts under different risk tolerance levels. The study reveals that (1) in a centralized LSSC, under risk-neutral attitudes, there exists a unique optimal emission reduction investment, which yields the highest expected return from emission reduction. However, under risk-averse attitudes, the expected return is always lower than the optimal expected return under risk neutrality. (2) In a decentralized LSSC, the emission reduction investment decisions of the Logistics Service Providers are similar to those in a centralized LSSC. (3) Under risk-neutral attitudes, the cost-sharing and altruistic preference-based joint contract can also coordinate the risk-averse LSSC under certain constraints, and by adjusting the cost-sharing and altruistic preference parameters, the expected returns can be reasonably allocated. Full article

In increasingly competitive digital markets, software firms must strategically balance cybersecurity investments and pricing decisions to attract consumers while safeguarding their platforms. This study develops a game-theoretic model in which two competing firms choose among three cybersecurity strategies—no action, bug bounty programs, and in-house protection—before setting prices. We demonstrate that cybersecurity efforts and pricing are interdependent: investment choices significantly alter market outcomes by influencing consumer trust and competitive dynamics. Our analysis reveals that a bug bounty program is preferable when consumer sensitivity to security and the probability of ethical vulnerability disclosures are high, while in-house protection becomes optimal when firms must rebuild credibility from a weaker competitive position. Furthermore, initial service quality gaps between firms critically shape both investment intensity and pricing behavior. By jointly endogenizing security efforts and prices, this study offers new insights into strategic cybersecurity management and provides practical guidance for software firms seeking to integrate security initiatives with competitive pricing strategies. Full article

This study examines how contract structures influence coordination and innovation incentives in dual-channel telecommunications supply chains. We consider a setting where a mobile network operator (MNO) supplies services both directly to consumers and indirectly through a mobile virtual network operator (MVNO), which competes in the retail market. Using a game-theoretic framework, we evaluate how different contracts—single wholesale pricing, revenue sharing, and quantity discounts—shape strategic decisions, particularly in the presence of investment spillovers between parties. A key coordination problem emerges from the externalized gains of innovation, where one party’s investment generates value for both participants. Our results show that single wholesale and revenue sharing contracts often lead to suboptimal investment and profit outcomes. In contrast, quantity discount contracts, especially when combined with appropriate transfer payments, improve coordination and enhance the total performance of the supply chain. We also find that innovation led by the MVNO, while generally less impactful, can still yield reciprocal benefits for the MNO, reinforcing the value of cooperative arrangements. These findings emphasize the importance of contract design in managing interdependence and improving efficiency in decentralized supply chains. This study offers theoretical and practical implications for telecommunications providers and policymakers aiming to promote innovation and mutually beneficial outcomes through well-aligned contractual mechanisms. Full article

Against the backdrop of increasingly severe global environmental issues, the manner in which enterprises conduct R&D investment, influenced by both government environmental policies and their own pollution levels, has become a prominent research topic. This paper employs the bilateral random frontier model of information game (SFA2tier) to analyze the influence levels and determining factors of government and market enterprises. The findings reveal that enterprises exert a stronger influence than the government, with the latter able to enhance R&D investment by 5.50% through its own influence. The disparity in influence levels between government and enterprises regarding R&D investment is significant and varies according to regional economic development levels and administrative hierarchies. Key determining factors include government subsidies, the nature of enterprise ownership, and enterprise size. The research results not only enrich relevant theories concerning the relationship between environmental policies and enterprise R&D investment but also provide valuable insights for the government to formulate more effective environmental policies and for enterprises to develop R&D strategies. Full article

Under the “Dual Carbon” strategy, collaborative governance of port atmospheric pollutants and carbon emissions is critical for low-carbon transformation. Focusing on Ningbo-Zhoushan Port (48% regional ship emissions), this study examines government, port enterprises, and public interactions. A tripartite evolutionary game model with numerical simulation reveals dynamic patterns and key factors. The results show the following: (1) A substitution effect exists between government incentive costs and penalty intensity—increased environmental governance budgets reduce the probability of government incentives, whereas higher public reporting rewards accelerate corporate emission reduction convergence. (2) Public supervision exhibits cyclical fluctuations due to conflicts between individual rationality and collective interests, with excessive reporting rewards potentially triggering free-rider behavior. (3) The system exhibits two stable equilibria: a low-efficiency equilibrium (0,0,0) and a high-efficiency equilibrium (1,1,1). The latter requires policy cost compensation, corporate emission reduction gains exceeding investments, and a supervision benefit–cost ratio greater than 1. Accordingly, the study proposes a three-dimensional “Incentive–Constraint–Collaboration” governance strategy, recommending floating penalty mechanisms, green financial instrument innovation, and community supervision network optimization to balance environmental benefits with fiscal sustainability. This research provides a dynamic decision-making framework for multi-agent collaborative emission reduction in ports, offering both methodological innovation and practical guidance value. Full article

The research and application of green fertilizers have long been constrained by financial and technical barriers. Farmers’ adoption of green fertilizers is also highly dependent on government policy support. As an intermediary organization bridging the government and farmers, the STB plays a crucial role in encouraging the use of green fertilizers. In order to explore the impact of the STB’s research and development investment, as well as government intervention on farmers’ green production behavior, this paper constructs a tripartite dynamic game model involving farmers, the STB, and the government. The study systematically analyzes the decision-making mechanisms of the different stakeholders and their evolutionary paths. The results show the following: (1) Under certain conditions, the system converges to two stable states: government withdrawal (1,1,0) and continued government participation (1,1,1). (2) Government intervention shows a phased decrease. As the green fertilizer production system matures, farmers and the STB gradually form a stable collaborative mechanism. At this stage, the government shifts from direct participation to a supervisory role, with its implementation coefficient increasing to between 0.75 and 1, indicating that government supervision becomes the primary mode of action. (3) The research and development efforts of the STB are influenced by both the intensity of government support and technological breakthroughs. During periods of high-intensity government support (with a research and development investment coefficient between 0.05 and 0.15), and when technological accumulation achieves a critical breakthrough, the growth rate of investment increases significantly (the coefficient jumps to 0.15–0.3). (4) Farmers’ demand for green fertilizers is stable and consistent, and the market-oriented collaboration between the STB and farmers tends to favor green production technology, which verifies the feasibility of the government’s withdrawal of functions in the later stage of the green agricultural transformation. This study provides a scientific basis for decision-making regarding the STB’s research and development of green fertilizers, while also laying a theoretical foundation for promoting the green transformation of farmers through green fertilizer innovation. Full article

Digital transformation is crucial for businesses to thrive in today’s rapidly evolving marketplace. It is a strategic choice that enables organizations to improve customer service, strengthen supplier relationships, and boost sales and business growth, ultimately enhancing their competitive stance. The Internet of Things (IoT) has become a transformative force across various domains, leveraging interconnected devices and sensors to gather and analyse data, thus enhancing decision making, efficiency, and innovation. This paper analyses the strategic competition between two 3PL firms integrating IoT technologies. Based on a game-theoretic model, the study uses Monte Carlo simulation and K-means clustering to identify distinct strategic groups and optimal adoption ranges. The findings highlight risks of over- or under-investments as well as asymmetric outcomes. Also, a set of recommendations and managerial insights are provided for better decision making in a tech-competitive setting. Full article

In the context of global climate governance and the International Maritime Organization’s (IMO) stringent carbon reduction targets, the transition to green shipping fuels faces systemic challenges in supply chain coordination. This study focuses on the strategic interactions between governments and enterprises in the construction of green fuel supply chains. By constructing a multidimensional scenario framework encompassing time, technological development, social attention, policy intensity, and market competition, and using evolutionary game models and system dynamics simulations, we reveal the dynamic evolution mechanism of government–enterprise decision making. System dynamics simulations reveal that (1) short-term government intervention accelerates infrastructure development but risks subsidy inefficiency; (2) medium-term policy stability and market-driven mechanisms are critical for sustaining enterprise investments; and (3) high social awareness and mature technologies significantly reduce strategic uncertainty. This research advances the application of evolutionary game theory in sustainable supply chains and offers a decision support framework for balancing governmental roles and market forces in maritime decarbonization. Full article

In response to the global goal of carbon neutrality, the tourism industry faces mounting pressure to reduce emissions. Characteristic towns that rely on traditional, high-emission models urgently require low-carbon tourism transformation strategies to meet environmental targets while preserving cultural heritage and economic vitality. This study investigates the low-carbon transition pathways of tourism in characteristic towns, using the three-dimensional impact mechanism of tourists, residents, and enterprises as a conceptual entry point. Drawing on empirical research conducted in Zhouzhuang and Tongli—two ancient towns in Suzhou—the study identifies key drivers and barriers to the development of low-carbon tourism. Results indicate that the overall low-carbon transformation score for Suzhou’s characteristic towns is 63.3, suggesting a moderate level of progress. Specifically, Zhouzhuang scored 66.9, while Tongli lagged behind at 57.6, highlighting notable disparities in transition efforts. The study applies multi-agent game theory and system dynamics to analyze the interactive mechanisms among tourists, residents, and enterprises in the low-carbon transition. Our findings reveal that tourists’ low-carbon consumption behaviors, residents’ environmental awareness, and enterprises’ green investments significantly influence the transition process. Further analysis using a chain mediation model shows that policy support positively affects low-carbon outcomes by promoting enterprise investment and influencing resident behavior. The study’s innovation lies in its development of an integrated analytical framework that captures the dynamic interplay among multiple stakeholders, offering a comprehensive perspective on low-carbon tourism transformation in characteristic towns. This study contributes to the sustainable tourism literature and provides valuable insights for policymakers and practitioners working toward carbon neutrality in tourism destinations. Full article

In the context of carbon trading policy, carbon emissions in the supply chain of new energy vehicles have received much attention in academic research and practice. Consumer preference for environmental friendliness is also growing in new energy vehicle supply chain operations, which has prompted new energy vehicle manufacturers to invest in carbon abatement technologies to improve the environmental friendliness of new energy vehicles. At the same time, the increased demand for new energy vehicles will also increase the green promotion of third-party power battery recycling companies to facilitate the recycling of power batteries. Considering these special features in the new energy vehicle supply chain, we applied a differential game model to examine the carbon emission reduction behaviors and green promotion technologies of the new energy vehicle supply chain members from a long-term and dynamic perspective. Supply chain equilibrium strategies under four different scenarios were analyzed and compared, numerical experiments were conducted to validate the theoretical results, and sensitivity analyses were performed to identify further insights. The results of the study show that a unit carbon trading price reaching a critical threshold is a prerequisite for technical cooperation between the new energy vehicle manufacturer and the third-party power battery recycling company. It provides a theoretical basis for the government to set the carbon price, and it effectively stimulates the cooperation and emission reduction drive of new energy vehicle companies. The study breaks through the traditional cost–benefit framework, internalizes the carbon price as a supply chain cooperation drive, and opens up a new paradigm for new energy vehicle industry research. Full article

The rapid development of the new energy vehicle (NEV) industry has led to concerns about battery quality and the transparency of green recycling, causing uncertainty among consumers. Many firms adopt blockchain technology to solve this problem, but blockchain adoption will bring privacy leakage risk to consumers. A Stackelberg game model of a three stage NEV supply chain is constructed to examine the impact of adapting blockchain on strategic decisions of supply chain participants. We consider a setting in which a battery supplier provides batteries to a NEV manufacturer, and a third-party recycler recovers retired batteries for a NEV manufacturer. We explore the influence of consumers’ green recycling preferences on the decisions of NEV supply chain members in three scenarios: not adopting blockchain traceability (NB), adopting blockchain with forward traceability (FB), and adopting blockchain with forward–reverse traceability (DB). We find that NEV supply chain members are more likely to adopt forward–reverse traceability under certain conditions. Moreover, the adoption of blockchain drives the battery supplier and NEV manufacture to increase wholesale price and retail price, especially under forward–reverse traceability. In addition, when consumers exhibit strong preferences for green recycling, third-party recyclers are more willing to invest in blockchain-based recycling due to its ability to enhance the accuracy and credibility of recycling data. Full article