Search Results (967)

Background/Objectives: In soccer, scanning before receiving the ball helps players better perceive and interpret their surroundings, enabling faster and more effective passes. Despite its importance, no standardized tests currently incorporate scanning actions into assessments of passing abilities. In this study, we test the reliability and validity of a battery of passing tests that assess a player’s ability to control and pass the ball while also scanning for the appropriate target. Methods: We designed three passing tests that reflect different scanning demands that are routinely placed upon players during matches. Using players from the first and reserve teams of two professional clubs in Ghana (Club A, first-team n = 11, reserve-team n = 10; Club B, first-team n = 16, reserve-team n = 17), we: (i) tested the repeatability of each passing test (intraclass correlations), (ii) assessed whether the tests could distinguish between first and reserve team players (linear mixed-effects model), and (iii) examined whether players who were better in the passing tests had higher performances in 3v1 Rondo possession games (linear models). Results: All passing tests were significantly repeatable (ICCs = 0.77–0.85). Performance was highest in the 120-degree test (30.11 ± 7.22 passes/min), where scanning was not required, and was lowest in the 360-degree test (25.55 ± 5.94 passes/min), where players needed to constantly scan behind them. When players were scanning through an arc of 180 degrees, their average performance was 27.41 ± 6.14 passes/min. Overall passing performance significantly distinguished first from reserve team players (β = −1.47, t (51) = −4.32, p < 0.001)) and was positively associated with 3v1 Rondo possession performance (R² = 0.51, p < 0.001). Conclusions: Our results show that these passing tests are reliable, distinguish players across competitive levels, and correlate with performance in possession games. These tests offer a simple, ecologically valid way to assess scanning and passing abilities for elite players. Full article

In line with the goals of “peak carbon emissions and carbon neutrality”, this study aims to develop a market-coordinated operation mechanism to promote renewable energy adoption and consumption, addressing the challenges of integrating medium- and long-term trading with spot markets in power systems with high renewable energy penetration. A three-stage joint operation framework is proposed. First, a medium- and long-term trading game model is established, considering multiple energy types to optimize the benefits of market participants. Second, machine learning algorithms are employed to predict renewable energy output, and a contract decomposition mechanism is developed to ensure a smooth transition from medium- and long-term contracts to real-time market operations. Finally, a day-ahead market-clearing strategy and an incentive-compatible settlement mechanism, incorporating the constraints from contract decomposition, are proposed to link the two markets effectively. Simulation results demonstrate that the proposed mechanism effectively enhances resource allocation and stabilizes market operations, leading to significant revenue improvements across various generation units and increased renewable energy utilization. Specifically, thermal power units achieve a 19.12% increase in revenue, while wind and photovoltaic units show more substantial gains of 38.76% and 47.52%, respectively. Concurrently, the mechanism drives a 10.61% increase in renewable energy absorption capacity and yields a 13.47% improvement in Tradable Green Certificate (TGC) utilization efficiency, confirming its overall effectiveness. This research shows that coordinated optimization between medium- and long-term/spot markets, combined with a well-designed settlement mechanism, significantly strengthens the market competitiveness of renewable energy, providing theoretical support for the market-based operation of the new power system. Full article

Considering the supply chain of new energy vehicles composed of a local manufacturer, an authorized distributor in the domestic market, and a competitive manufacturer in the export market, this paper studies three different cases of parallel export as well as their decisions about prices, sales scale, and the degree of production differentiation. Three game models are constructed and solved under the cases of no parallel exports (CN), authorized distributors’ parallel exports (CR), and third-party parallel exports (CT), respectively, and the equilibrium analysis is carried out, and finally, the influence of relevant parameters is explored through numerical simulation. It is found that (1) the manufacturer’s decisions on production and sales are influenced by the characteristics of consumer preferences in local and export markets, the cost of differentiated production, and the consumer recognition of parallel exports; (2) the manufacturers’ profits will always be damaged by parallel exports; (3) differentiated production can reduce the negative impact of parallel exports under certain conditions, and then improve the profits of manufacturers; (4) manufacturers can increase their profits by improving the purchase intention of consumers in the local market, improve the level of production differentiation in the export market, or reducing the cost of differentiation. Full article

The green renovation of existing residential buildings is a key way for the construction industry to achieve sustainable development and the dual carbon goals of China, which makes it urgent to make collaborative decisions among multiple stakeholders. However, because of divergent interests and risk perceptions among governments, energy service companies (ESCOs), and owners, the implementation of green renovation is hindered by numerous obstacles. In this study, we integrated prospect theory and evolutionary game theory by incorporating core prospect-theory parameters such as loss aversion and perceived value sensitivity, and developed a psychologically informed tripartite evolutionary game model. The objective was to provide a theoretical foundation and analytical framework for collaborative governance among stakeholders. Numerical simulations were conducted to validate the model’s effectiveness and explore how government regulation intensity, subsidy policies, market competition, and individual psychological factors influence the system’s evolutionary dynamics. The findings indicate that (1) government regulation and subsidy policies play central guiding roles in the early stages of green renovation, but the effectiveness has clear limitations; (2) ESCOs are most sensitive to policy incentives and market competition, and moderately increasing their risk costs can effectively deter opportunistic behavior associated with low-quality renovation; (3) owners’ willingness to participate is primarily influenced by expected returns and perceived renovation risks, while economic incentives alone have limited impact; and (4) the evolutionary outcomes are highly sensitive to parameters from prospect theory, The system’s evolutionary outcomes are highly sensitive to prospect theory parameters. High levels of loss aversion (λ) and loss sensitivity (β) tend to drive the system into a suboptimal equilibrium characterized by insufficient demand, while high gain sensitivity (α) serves as a key driving force for the system’s evolution toward the ideal equilibrium. This study offers theoretical support for optimizing green renovation policies for existing residential buildings in China and provides practical recommendations for improving market competition mechanisms, thereby promoting the healthy development of the green renovation market. Full article

The integration of renewable energy into power grids is imperative for reducing carbon emissions and mitigating reliance on depleting fossil fuels. In this paper, we develop symmetric and asymmetric evolutionary game-theoretic models to analyze how user–grid cooperation in peak shaving can be enhanced by incorporating whole-process democracy (deliberative governance) into decision-making. Our framework captures excess returns, cooperation-driven profits, energy pricing, participation costs, and benefit-sharing coefficients to identify equilibrium conditions under varied subsidy, cost, and market scenarios. Furthermore, this study integrates the theory, path, and mechanism of deliberative procedures under the perspective of whole-process democracy, exploring how inclusive and participatory decision-making processes can enhance cooperation in renewable energy systems. We simulate seven scenarios that systematically adjust subsidy rates, cost–benefit structures, dynamic pricing, and renewable-versus-conventional competitiveness, revealing that robust cooperation emerges only under well-aligned incentives, equitable profit sharing, and targeted financial policies. These scenarios systematically vary these key parameters to assess the robustness of cooperative equilibria under diverse economic and policy conditions. Our findings indicate that policy efficacy hinges on deliberative stakeholder engagement, fair profit allocation, and adaptive subsidy mechanisms. These results furnish actionable guidelines for regulators and grid operators to foster sustainable, low-carbon energy systems and inform future research on demand response and multi-source integration. Full article

This paper addresses the challenge of fostering cooperation among virtual power plant (VPP) operators in competitive electricity markets, focusing on the application of evolutionary game theory (EGT) and static reward–punishment mechanisms. This investigation resolves four critical questions: the minimum reward–punishment thresholds triggering stable cooperation, the influence of initial market composition on equilibrium selection, the sufficiency of static versus dynamic mechanisms, and the quantitative mapping between regulatory parameters and market outcomes. The study establishes the mathematical conditions under which static reward–punishment mechanisms transform competitive VPP markets into stable cooperative systems, quantifying efficiency improvements of 15–23% and renewable integration gains of 18–31%. Through rigorous evolutionary game-theoretic analysis, we identify critical parameter thresholds that guarantee cooperation emergence, resolving longstanding market coordination failures documented across multiple jurisdictions. Numerical simulations and sensitivity analysis demonstrate that static reward–punishment systems enhance cooperation, optimize resources, and increase renewable energy utilization. Key findings include: (1) Reward–punishment mechanisms effectively promote cooperation and system performance; (2) A critical region exists where cooperation dominates, enhancing market outcomes; and (3) Parameter adjustments significantly impact VPP performance and market behavior. The theoretical contributions of this research address documented market failures observed across operational VPP implementations. Our findings provide quantitative foundations for regulatory frameworks currently under development in seven national energy markets, including the European Union’s proposed Digital Single Market for Energy and Japan’s emerging VPP aggregation standards. The model’s predictions align with successful cooperation rates achieved by established VPP operators, suggesting practical applicability for scaled implementations. Overall, through evolutionary game-theoretic analysis of 156 VPP implementations, we establish precise conditions under which static mechanisms achieve 85%+ cooperation rates. Based on this, future work could explore dynamic adjustments, uncertainty modeling, and technologies like blockchain to further improve VPP resilience. Full article

This study analyses the physical performance variables involved in different training tasks aimed at replicating the worst-case scenarios (WCSs) observed during official matches in professional football, with a focus on playing positions and occurrences within a 1 min period. Data were collected from 188 training sessions and 42 matches of a Spanish Second Division team during the 2021/2022 season. All data were reported on a per-player basis. GPS tracking devices were used to record physical variables such as total distance, high-speed running (HSR), sprints, accelerations, decelerations, and high metabolic load distance (HMLD). Players were grouped according to their match positions: central defenders, wide players, midfielders and forwards. The results showed that none of the training tasks fully replicated the physical demands of match play. However, task TYPEs 11 (Large-Sided Games) and 9 (small-sided games with orientation and transition) were the closest to match demands, particularly in terms of accelerations and decelerations. Although differences were observed across all variables, the most pronounced discrepancies were observed in sprint and HSR variables, where training tasksfailed to reach 60% of match demands. These findings highlight the need to design more specific drills that simulate the intensity of WCS, allowing for more accurate weekly training load planning. This study offers valuable contributions for optimising performance and reducing injury risk in professional footballers during the competitive period. Full article

Basketball referees play a crucial role in game management, yet the physical and physiological demands placed on them during a game remain understudied. This study analyzed the workload of 35 group 1 referees during a U-18 Spanish championship, examining the effects of refereeing technique (two referees vs. three referees) and competition sex (male vs. female) across game quarters. Physical and physiological demands were measured using inertial devices and heart rate monitors during 37 matches (18 men’s and 19 women’s). The results revealed that 2-referee teams experienced significantly greater physical demands, covering approximately 25% more total distance and demonstrating higher values in high-intensity running compared to 3-referee teams. Female competition elicited higher demands in specific variables, particularly in the distance covered above 16 km/h and average speed. Analysis across quarters showed distinct temporal patterns, with the first and third quarters presenting the highest demands, especially for 2-referee teams. These findings suggest that basketball referees’ physical preparation should be tailored to the officiating technique and competition sex, with a particular emphasis on developing specific conditioning programs for the 2-referee technique and implementing targeted recovery strategies between quarters to maintain optimal performance throughout the game. Full article

The decarbonization of electricity generation by 2030 and the realization of a net-zero economy by 2050 are central to the United States’ climate strategy. However, large-scale renewable integration introduces operational challenges, including extreme ramping, unsafe dispatch, and price volatility. This review investigates how demand–response (DR) aggregators and distributed loads can support these climate goals while addressing critical operational challenges. We hypothesize that current DR aggregator frameworks fall short in the areas of distributed load operational flexibility, scalability with the number of distributed loads (prosumers), prosumer privacy preservation, DR aggregator and prosumer competition, and uncertainty management, limiting their potential to enable large-scale prosumer participation. Using a systematic review methodology, we evaluate existing DR aggregator and prosumer frameworks through the proposed FCUPS criteria—flexibility, competition, uncertainty quantification, privacy, and scalability. The main results highlight significant gaps in current frameworks: limited support for decentralized operations; inadequate privacy protections for prosumers; and insufficient capabilities for managing competition, uncertainty, and flexibility at scale. We conclude by identifying open research directions, including the need for game-theoretic and machine learning approaches that ensure privacy, scalability, and robust market participation. Addressing these gaps is essential to shape future research agendas and to enable DR aggregators to contribute meaningfully to US climate targets. Full article

The study examines the impact of pricing strategies on the competition and cooperation of cross-border ports, focusing on unified pricing and differential pricing. The results show that the inside border port can adopt a differentiation strategy to enhance its benefits, as this strategy allows for better control. Additionally, while the differentiated pricing strategy is an equilibrium strategy for the inside border port, blockchain technology can enhance the economic benefits of the inside border port under certain conditions, which also demonstrates the commercial value of blockchain in data sharing. Moreover, the expansion of port capacity can reduce the congestion of the inside border port to some extent under specific conditions. Finally, the study analyzes the environmental impact, tariff impact, and influence of port cooperation, which provides some management implications for inside border port. In summary, the findings highlight the potential of blockchain to optimize pricing strategy and promote cooperation between regional ports, thus improving economic benefits. Full article

Evidence from the lab suggests that women perform less well than men under competitive conditions, but the majority of this evidence relates to Western countries. Our study explores gender differences in performance in competitive environments among Chinese individuals. Using a five-round online experimental design, we recruited undergraduate and postgraduate students from a Shanghai university. Participants completed a series of word memory games under varying incentive schemes, including baseline, piece-rate, risk-based, and tournament-style competition. The results of this study suggest that there are no differences in performance under competitive conditions between Chinese men and women. However, women perform slightly better than men when the element of risk is added in a competitive environment. This study underscores the importance of examining cultural nuances when evaluating gender dynamics in competition and contributes to a more comprehensive understanding of these dynamics in the Chinese context. Full article

In response to the problem of cooperative steering control between drivers and intelligent driving systems, a master–slave Game-Based human–machine cooperative steering control framework with adaptive weight fuzzy decision-making is constructed. Firstly, within this framework, a dynamic weight approach is established. This approach takes into account the driver’s state, traffic environment risks, and the vehicle’s global control deviation to adjust the driving weights between humans and machines. Secondly, the human–machine cooperative relationship with unconscious competition is characterized as a master–slave game interaction. The cooperative steering control under the master–slave game scenario is then transformed into an optimization problem of model predictive control. Through theoretical derivation, the optimal control strategies for both parties at equilibrium in the human–machine master–slave game are obtained. Coordination of the manipulation actions of the driver and the intelligent driving system is achieved by balancing the master–slave game. Finally, different types of drivers are simulated by varying the parameters of the driver models. The effectiveness of the proposed driving weight allocation scheme was validated on the constructed simulation test platform. The results indicate that the human–machine collaborative control strategy can effectively mitigate conflicts between humans and machines. By giving due consideration to the driver’s operational intentions, this strategy reduces the driver’s workload. Under high-risk scenarios, while ensuring driving safety and providing the driver with a satisfactory experience, this strategy significantly enhances the stability of vehicle motion. 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

Green and low-carbon development of supply chains represents a practical approach to addressing climate change and enhancing corporate competitiveness. From the perspective of the relationship between policy subsidies and channel power structures, this paper constructs Stackelberg game models under four different scenarios to conduct theoretical analyses of the optimal strategies, supported by numerical simulations. The research findings reveal the following. (1) Under the product subsidy policy, the enhancement of consumers’ green preference will lead to a green premium, and in the case of the technology subsidy policy, consumers’ green preference will inhibit wholesale prices and retail prices. However, there is a threshold in the manufacturer-led case, and a “green premium” is also claimed when this threshold is exceeded. (2) The effects of the product subsidy policy and the green technology level subsidy policy on prices are opposite, where an increase in the product subsidy will increase the wholesale price and retail price, while an increase in the green technology level subsidy will reduce the wholesale price. The technology subsidy policy has a more significant effect on the promotion of green technology. (3) The power of supply chain channels will directly affect corporate profits, and the leader of the supply chain often has higher profits. Compared with product subsidies, technology subsidies can inhibit the channel power of retailers. Full article

In recent years, online retailing platforms (ORPs) have increasingly introduced private brand (PB) products as a new profit source, reshaping market dynamics and affecting their commission revenues. This shift creates a strategic trade-off for the platform: maximizing PB product profits while maintaining commission income from national brand (NB) retailers. This paper examines the platform’s pricing and quality strategies for PB products, as well as its incentives to introduce them. We develop a game-theoretic model featuring a platform and a retailer, and derive results through equilibrium analysis and comparative statics. Special attention is given to the platform’s strategy when market power is asymmetric and the PB product is homogeneous. The analysis yields three key findings. Firstly, the platform is always incentivized to introduce a PB product, regardless of its brand value. Even when direct profit is limited, the platform can leverage the PB product to increase competitive pressure on the retailer and boost commission revenue. Secondly, when the PB product has low brand value, the platform adopts a cost-saving strategy with low quality for extremely low brand value, and a function-enhancing strategy with high quality for moderately low brand value. Thirdly, when the PB product has high brand value, the platform consistently prefers a function-enhancing strategy. This study contributes to the literature by systematically characterizing the platform’s strategic trade-offs in introducing PB products, highlighting its varied pricing and quality strategies across categories, and revealing the critical role of brand value in supply chain competition. Full article