Search Results (2,446)

Against the backdrop of intensifying global technological competition and the deepening of the national innovation-driven strategy, private technology enterprises, as the core entities of technological innovation, have their sustainable innovation dynamics profoundly influenced by the strategic interactions among multiple parties such as the government, enterprises, and users. Based on evolutionary game theory, this paper constructs a tripartite evolutionary game model involving the government, private technology enterprises, and market users in the Chinese context. Through theoretical deduction and multi-scenario numerical simulation using Matlab, it systematically analyzes the logic of strategic choices and the laws of dynamic equilibrium of the three parties in the process of sustainable innovation. The research shows that the strategic evolution of multiple entities presents multiple equilibrium states. There exist critical thresholds for the intensity of policy support, the concentration of market competition, and users’ willingness to choose innovative products; beyond these thresholds, the marginal impact on sustainable innovation dynamics increases significantly. Further research finds that the government and enterprises need to compensate for the profit gap between users’ choice of innovative products and traditional products through a subsidy mechanism to form a positive cycle of “active innovation–market recognition–profit improvement”. This study enriches the theoretical system of multi-entity innovation dynamics by incorporating user behavior and provides a decision-making reference for optimizing innovation governance and fostering the development of sustainable innovation dynamics in private enterprises in China and other similar economies. Full article

Small local museums play a crucial role in safeguarding cultural heritage, but often lack the necessary resources and digital capabilities to engage younger visitors effectively. This study examines whether a mobile serious game can enhance engagement, intrinsic motivation, and cultural knowledge among Generation Z museum visitors. This study introduces Thai-Craft-To-Go, a mobile serious game that mediates intangible cultural heritage—specifically Thai textiles and handicrafts—for Generation Z. Grounded in Self-Determination Theory (SDT) and Flow Theory and operationalized through the Mechanics–Dynamics–Aesthetics (MDA) framework, the game translates cultural content into interactive play. We conducted an exploratory evaluation with 30 Generation Z participants using the Game Engagement Questionnaire (GEQ), the Intrinsic Motivation Inventory (IMI), and a 10-item knowledge test administered before and after gameplay. Results indicated high engagement—particularly Presence and Absorption on the GEQ—strong intrinsic motivation on the IMI (notably perceived competence and value), and significant knowledge gains (mean scores increased from 4.40 to 8.03; t(29) = 8.39, p < 0.001, d = 1.53). These findings suggest that a well-designed serious game can align museum learning with the digital habits of younger audiences, enhancing engagement, motivation, and cultural understanding. For small local museums, serious games provide a feasible and cost-conscious pathway to revitalize visitor experiences and support the intergenerational transmission of intangible cultural heritage in the digital age. Full article

When a technology provider (entrant) enters an emerging end market, he may outsource critical components from a competing conventional manufacturer (incumbent) or insource critical components. Under the outsourcing strategy, brand reputation spills over from the incumbent to the entrant—a phenomenon termed brand spillover. This paper investigates the sourcing strategy (insourcing or outsourcing) and contract choice (wholesale price contract or revenue share contract) in markets subject to brand spillover. We develop a game theoretic model consisting of one entrant with a new technology and one incumbent who sells the traditional product in the end market and the critical component to the entrant. We find that the entrant adopts the insourcing strategy only if his optimal quantity, including original market power and brand spillover, is intermediate. Otherwise, the outsourcing strategy with wholesale price contract is selected when his optimal quantity is low, while revenue-sharing contracts dominate at high quantity. Interestingly, when brand spillover intensity exceeds a threshold, both parties benefit from a higher level of brand spillover under the wholesale price contract. Full article

The decision-making regarding the development of intelligent construction in construction enterprises is crucial for the transformation and upgrading of the construction industry. This paper constructs an evolutionary game model among construction enterprises and applies system dynamics for simulation analysis of the game model. It explores the impact of key factors on the strategy choices of the game participants. The research findings indicate that the initial state of construction enterprises’ willingness to transition to intelligent construction in the evolutionary game model influences the final stable strategy. Direct benefits, the strength of government incentives, penalty intensity, and reduced costs through joint transition positively affect the probability of construction enterprises implementing intelligent construction, while incremental transition costs and positive spillover effect are negatively correlated. When the direct benefit rate exceeds 5%, costs are jointly reduced by more than 2%, and transition costs are below 35 CNY/m², it can significantly motivate enterprises to adopt intelligent construction. A certain level of government incentives (at least greater than 5 CNY/m²) has a positive effect on the transformation process; however, once the incentives exceed 10 CNY/m², their impact stabilizes. Penalties only affect the speed at which the system evolves toward a stable point. Current policy incentives do not require further enhancement. Meanwhile, reducing incremental transition costs is more effective than increasing the intensity of government incentives. The research conclusions contribute to the quantitative analysis of how changes in different key factors affect the dynamic evolution of strategy adjustments by construction enterprises over time, thereby providing corresponding recommendations for transformation and upgrading. Full article

The contradiction between economic development and ecological protection has become a common challenge for territorial governance in developing countries around the world. However, extant studies have neglected the coupling and symbiotic relationship between humans and nature, resulting in significant functional conflicts, insufficient stability, and imbalances in ecological and economic benefits in the reconstruction of territorial spatial functional pattern (TSFP), making it difficult to achieve synergies between development and protection. The question that arises is how the TSFP can be reconstructed in order to achieve harmonious coexistence between humans and nature. This remains a challenging problem in the context of the synergizing development and protection of the TSFP. This study innovatively integrates set-theoretic principles and functional mappings with game-theoretic analysis to develop Territorial Spatial Functional Pattern Reconstruction (TSFPR) model designed to foster harmonious human–nature coexistence, and validates the model using geospatial data from Qionglai City, China. Empirical evidence demonstrates that, in comparison with conventional methods, TSFPR model significantly mitigates the territorial spatial functional conflicts (TSFCs), enhances stability and ecological and economic benefits, and achieves the expected harmonious coexistence between humans and nature. The analysis confirms that the territorial spatial functional conflict (TSFC) coordination index established in this study provides a reliable criterion for identifying superior territorial spatial functions (TSFs). The proposed TSFPR model is an expansion of the theory of spatial optimization modelling, and it provides a tool for reconstructing the TSFP for the harmonious coexistence between humans and nature. In summary, the utilization of the TSFPR model to reconstruct the TSFP for harmonious coexistence between humans and nature provides a novel solution for coordinating the development and protection of territorial space governance. Full article

This paper investigates cooperative behavior among Autonomous Systems (ASs) within a federated network environment designed to support collaborative shared-technology deployment. It makes use of the concept of an AS federation, where independently managed systems adhere to a shared standard while maintaining implementation flexibility. Using a systematic game-theoretic framework, the study models various coalition structures—including full cooperation, partial coalitions, and defection—across several canonical cooperative games. The analysis evaluates the effects of different cooperation strategies and resource-sharing schemes on payoff distribution and coalition stability. Simulation results over short- and medium-to-long-term horizons demonstrate that cooperative coalition formation, especially with fair payoff allocation, consistently outperforms solitary strategies. The study also identifies key thresholds affecting partial coalition viability and explores the impact of defection on overall federation performance. By linking theoretical game models with practical deployment challenges in heterogeneous networked systems, this work offers valuable insights for designing mechanisms that promote effective cooperation in complex, resource-constrained environments. Full article

Cities worldwide are transitioning from demolition–redevelopment-driven expansion to high-quality regeneration centered on stock upgrading, cultural continuity, and long-term operations. Against the backdrop of China’s high-quality urban renewal phase guided by the “anti-massive demolition and construction” policy, this study constructs a calibrated tripartite evolutionary game among government, investors, and residents. By embedding culture–economy parameters—cultural renovation intensity (k), operational profit-sharing ratio between investors and residents (j), cultural identification coefficient (i), and cost-sharing coefficient (w)—we establish a behavioral interaction mechanism of “cultural value conversion–benefit-sharing–cultural identification–cost-sharing.” Simulations based on replicator dynamics demonstrate that sustained tripartite cooperation requires four conditions: cultural intensity surpasses the cost threshold (k ∈ [0.6, 0.7]); the profit-sharing ratio preserves market incentives (j ∈ [0.25, 0.35]); cultural identification reaches a minimum threshold (i ≥ 0.4); and residents’ cost-sharing does not exceed their benefit capacity (w ≤ 0.2). These findings reveal the core tension in China’s high-quality urban renewal stage—namely, the challenge of instituting sustainable operational mechanisms under cultural protection constraints—and globally provide a quantifiable policy toolbox for culture-led urban regeneration. Full article

This research enhances and evaluates the performance of a Decentralized Nash Bargaining (DNB) adaptive traffic signal controller that operates a flexible National Electrical Manufacturers Association (NEMA) phasing and timing scheme responding dynamically to fluctuating traffic demands. The DNB controller is enhanced to (1) use traffic density estimates instead of queues to optimize signal timings; (2) to consider the eight-phase two-ring NEMA controller configuration within the game-theoretic approach; and (3) to consider dynamically adaptable control time steps. The enhanced DNB controller is benchmarked against (1) a fixed-time traffic signal control using the state-of-practice Webster’s method and an emerging Laguna-Du-Rakha (LDR) method for computing the optimum cycle length; (2) a state-of-the-practice actuated traffic signal control; and (3) a state-of-the-art reinforcement learning (RL) traffic signal controller presented in the literature. The controller is tested on two isolated signalized intersections, demonstrating enhanced overall intersection performance compared to the baseline pretimed and actuated controllers at various demand levels, and offers better performance than a previously developed RL controller. Specifically, the DNB controller results in a decrease in the average vehicle delay and queue size by up to 54% and 63%, respectively, compared to Webster’s state-of-the-practice pretimed control. Unlike the RL controller, the DNB controller requires no pre-training while adapting to fluctuating traffic conditions, thereby providing a flexible framework for reducing traffic congestion at signalized intersections. As such, this research contributes to the development of smarter and more responsive urban traffic control systems. Full article

The study of attack–defense game decision making in critical infrastructure systems confronting intelligent adversaries, grounded in complex network theory, has emerged as a prominent topic in the field of network security. Most existing research centers on game-theoretic analysis under conditions of complete information and assumes that the attacker and defender share congruent criteria for evaluating target values. However, in reality, asymmetric value perception may lead to different evaluation criteria for both the offensive and defensive sides. This paper examines the game problem wherein the attacker and defender possess distinct target value evaluation criteria. The research findings reveal that both the attacker and defender have their own “advantage ranges” for value assessment, and topological heterogeneity is the reason for this phenomenon. Within their respective advantage ranges, the attacker or defender can adopt clear-cut strategies to secure optimal benefits—without needing to consider their opponents’ decisions. Outside these ranges, we explore how the attacker can leverage small-sample detection outcomes to probabilistically infer defenders’ strategies, and we further analyze the attackers’ preference strategy selections under varying acceptable security thresholds and penalty coefficients. The research results deliver more practical solutions for games involving uncertain value criteria. Full article

Gacha games, particularly those using Free-to-Play (F2P) models, have become increasingly popular yet controversial due to their addictive mechanics, often likened to gambling. This study investigates the inherent addictive mechanisms of Gacha games, focusing on Genshin Impact, a leading title in the genre. We analyze the interplay between reward frequency, game attractiveness, and player addiction using the Game Refinement theory and the Motion in Mind framework. Our analysis identifies a critical threshold at approximately 55 pulls per rare item ($N\approx 55$), with a corresponding gravity-in-mind value of 7.4. Beyond this point, the system exhibits gambling-like dynamics, as indicated by Game Refinement and Motion in Mind metrics. This threshold was measured using empirical gacha data collected from Genshin Impact players and analyzed through theoretical models. While not claiming direct causal evidence of player behavior change, the results highlight a measurable boundary where structural design risks fostering addiction-like compulsion. The study contributes theoretical insights with ethical implications for game design, by identifying critical thresholds in reward frequency and game dynamics that mark the shift toward gambling-like reinforcement. The methodologies, including quantitative analysis and empirical data, ensure robust results contributing to responsible digital entertainment discourse. Full article

In this paper, we propose a load-aware, load-balancing procedure for fifth-generation (5G) New Radio-Unlicensed (NR-U) networks in order to address performance degradation and resource inefficiencies caused by load imbalance. Load imbalances frequently occur in NR-U networks due to factors such as the dynamic spectrum, user mobility, and varying traffic demand. To tackle these challenges, a load-aware, load-balancing procedure utilizing game theoretic reinforcement learning (GT-RL) is introduced. For load awareness, an extended System Information Block (SIB) is incorporated within the framework of 5G wireless networks. The load-balancing problem is addressed as a game theoretic cost-minimization task combining conditional offloading with reinforcement learning traffic-steering to dynamically distribute loads. Reinforcement learning applies a game theoretic policy to move users from overloaded cells to less congested cells that best serve their needs. Analytically, the proposed method is proven to spread the network load toward equilibrium. The proposed method is validated through simulations that show the effectiveness of its load balancing. The proposed method achieved better performance than previous work by attaining lower load variances while achieving higher throughput and greater quality of service satisfaction. Especially under high-load dynamics, the proposed method achieved an 8% gain in UE satisfaction with QoS and a 7.61% gain in network throughput compared to existing RL-based approach, whereas compared to the non-AI approaches, UE QoS satisfaction and the network throughput were enhanced by more than 15%. Full article

Drawing from practices at Walmart, we model a supply chain where the manufacturer conducts product R&D while the retailer distributes products to two distinct consumer segments: green-conscious consumers who translate environmental principles into purchasing decisions, and non-green-conscious consumers who are deterred by perceived high costs and information deficits. The retailer engages in green education targeted at non-green-conscious consumers, providing clear product explanations to improve their willingness to pay for sustainable products, though this education is motivated by profit maximization rather than altruistic environmental responsibility. Our analysis reveals that while retailer green education can boost product R&D and adoption under certain conditions, this creates a ‘consumer education paradox’—a situation where green education could further enhance product R&D and adoption, but the retailer forgoes it because doing so does not contribute to profit. This occurs because profit-driven retailers limit education to self-beneficial ranges, creating tension between individual profit maximization and overall environmental performance. We then propose two government subsidy solutions—green product quantity subsidies and product R&D subsidies—to resolve this paradox. Both effectively alleviate the tension, but green innovation subsidies, despite requiring greater government investment, consistently outperform in fostering innovation and adoption, offering superior environmental outcomes. Full article

This article focuses on the negative evaluation losses resulting from consumers’ dissatisfaction with the traceability level in agricultural product logistics activities. Based on the supply chain (SC) under the “agricultural product cooperative + live-streaming e-commerce” model, and in accordance with previous research, combined with the differences in the dominant role and the bearers of profit and loss in the SC. By applying Stackelberg game theory, different types of decisions are analyzed and solved. The research results show: (1) Centralized decision-making has advantages in terms of traceability level and SC profit performance. (2) In non-centralized decision-making models, when manufacturers bear negative evaluation losses and retailers act as the leaders of the SC, the overall decision-making effect is more ideal. When manufacturers or retailers act as the leaders of the SC and both bear the traceability costs, the decision-making effect is basically the same. (3) The traceability level sensitivity coefficient and the traceability level effect on traceability both have positive effects on the growth of SC profits and the improvement of the traceability level. (4) The maximization of profits for both parties can be achieved through the coordination of contracts. This study can enhance the traceability level of the agricultural product SC, encourage SC members to increase their investment in the traceability, reduce the profit impact from negative evaluations, and provide a reference for the sustainable development of the agricultural product SC. Full article

The wind–solar–storage–thermal combined power generation system is one of the key measures for China’s energy structure transition, and rational capacity planning of each generation entity within the system is of critical importance. First, this paper addresses the uncertainty of wind and photovoltaic (PV) power outputs through scenario-based analysis. Considering the diversity of generation entities and their complex interest demands, a bi-level capacity optimization framework based on game theory is proposed. In the upper-level framework, a game-theoretic method is designed to analyze the multi-agent decision-making process, and the objective function of capacity allocation for multiple entities is established. In the lower-level framework, multi-objective optimization is performed on utility functions and node voltage deviations. The Nash equilibrium of the non-cooperative game and the Shapley value of the cooperative game are solved to study the differences in the capacity allocation, economic benefits, and power supply stability of the combined power generation system under different game modes. The case study results indicate that under the cooperative game mode, when the four generation entities form a coalition, the overall system achieves the highest supply stability, the lowest carbon emissions at 30,195.29 tons, and the highest renewable energy consumption rate at 53.93%. Moreover, both overall and individual economic and environmental performance are superior to those under the non-cooperative game mode. By investigating the capacity configuration and joint operation strategies of the combined generation system, this study effectively enhances the enthusiasm of each generation entity to participate in the energy market; reduces carbon emissions; and promotes the development of a more efficient, environmentally friendly, and economical power generation model. Full article

Blockchain technology has become a game changer in sectors like accounting and auditing. Its usage is still restricted due to a lack of insight into what drives people to adopt it for financial services like accounting and auditing. This research delves into the factors that influence the adoption of blockchain systems in accounting and auditing services by utilizing an enhanced edition of the Theory of Planned Behavior. In this study, alongside the previously established elements like Attitude, subjective norm, and Perceived Behavioral Control, self-perception and personal moral values are included to reflect how identity and ethics impact decision-making processes. Data were gathered via an online survey (N = 751) conducted on the Prolific platform, and the hypotheses were tested using Structural Equation Modeling. The hypotheses were examined through the Structural Equation Modeling method. The findings indicate that each of the five predictors plays a significant role in influencing Behavioral Intention, with personal moral values being the influential factor followed by subjective norm and Perceived Behavioral Control. Attitude plays an important role in shaping adoption choices and showcases the complexity involved in such decisions. As such, it is crucial to take into account ethical factors when encouraging the use of blockchain technology. This study adds to the existing knowledge of the Theory of Planned Behavior framework, offering insights for companies aiming to boost the implementation of blockchain systems in professional settings. Future research avenues and real-world implications are explored with an emphasis placed on developing targeted strategies that align technological adoption with personal values and organizational objectives. Full article