Search Results (1,940)

Enhancing water resource utilization efficiency is crucial for achieving sustainable development in arid and semi-arid regions. In promoting water-saving agriculture technologies, there is often a phenomenon of “willingness without behavior”. Therefore, investigating how willingness translates into behavior is of significant importance for improving water resource utilization. This study utilized data from a survey of 494 households in Ulanqab City, Inner Mongolia Autonomous Region, China, and employed Probit models to analyze the factors influencing farmers’ willingness towards water-saving technologies and their adoption. Prospect theory and mental accounting theory were introduced to understand the mechanism of transformation from farmers’ willingness to adoption. The study found that farmers’ willingness is a crucial prerequisite for their adoption. Farmers’ income perception towards adopting water-saving technologies can facilitate the transformation from willingness to adoption, while cost perception can inhibit this transformation. Both small and large-scale farmers’ perception of the benefits of water-saving technologies significantly increased their likelihood of translating their willingness to adopt into actual action. Compared with large-scale farmers, small-scale farmers are more sensitive to the perception of economic costs in the decision-making process. For both types of farmers, the perception of learning cost inhibits their willingness to adopt water-saving technologies to a certain extent. Farmers’ perception of the prospects of adopting water-saving technologies leads to a psychological segmentation effect, and the ultimate adoption depends on the psychological game between farmers’ income and cost perception. Full article

This paper presents a novel approach to optimizing the coordination between renewable energy generation enterprises and power grid companies using evolutionary game theory. The research focuses on resolving conflicts and distributing benefits between these key stakeholders in the context of large-scale renewable energy integration. A theoretical model based on replicator dynamics is developed to simulate and analyze the evolutionary stable strategies of power generation enterprises and grid companies with particular emphasis on peak shaving services and electricity bidding. These simulations are based on theoretical models and do not incorporate real-world data directly, but they aim to replicate scenarios that reflect realistic behaviors within the electricity market. The model is validated through dynamic simulation under various scenarios, demonstrating that the final strategic choices of both thermal power and renewable energy enterprises tend to evolve towards either high-price or low-price bidding strategies, significantly influenced by initial system parameters. Additionally, this study explores how the introduction of peak shaving compensation affects the coordination process and stability of renewable energy integration, providing insights into improving grid efficiency and enhancing renewable energy adoption. Although the results are simulation-based, they are designed to offer practical recommendations for grid management and policy development, particularly for the integration of renewable energies such as wind power in competitive electricity markets. The findings suggest that effective government regulation, alongside well-designed compensation mechanisms, can help establish a balanced interest distribution between stakeholders. By offering a clear framework for analyzing the dynamics of renewable energy integration, this work provides valuable policy recommendations to promote cooperation and stability in electricity markets. This study contributes to the understanding of the complex interactions in the electricity market and offers practical solutions for enhancing the integration of renewable energy into the grid. Full article

Since existing studies primarily explore green development measures from the static perspective of a single airport stakeholder, this paper constructs an evolutionary game model to analyze the strategic choices of three key stakeholders: airport authorities, third-party organizations, and government departments, based on evolutionary game theory. By solving the stable strategy of the tripartite evolution using the Jacobian matrix, the green transition of airport development can be divided into three stages: “initiation”, “development”, and “maturity”, allowing for the exploration of key factors influencing the green transition of airport development. A simulation analysis is conducted based on real Guangzhou Baiyun International Airport data. The results indicate that the tripartite evolutionary game strategy is stable at $E_4(0,0,1)$ and the green transition of Baiyun Airport remains in the development stage. By improving the reward and punishment mechanisms of government departments, the evolutionary game strategy can be stabilized at $E_8(1,1,1)$, promoting the green transition of airport development toward the mature stage. By adjusting the game parameters, the dynamic process of green transition in airports at different levels of development and under varying regulatory environments can be effectively captured, supporting the precise formulation of corresponding policies. Full article

This paper investigates the impact of tariff escalation on multinational suppliers relocating their production capacity to tariff-preferential regions with unreliable supply caused by low-production technology. We build a game theory model to analyze this issue based on three decisions for supplier-capacity relocation: no relocation, partial relocation, and full relocation. Our analysis finds that when tariffs are low or the production technology of the base in a preferential tariff region is not advanced, the supplier tends to adopt a partial-relocation strategy, but this strategy may be hindered by a manufacturer’s order-allocation decision, leading to a no-relocation strategy as the supply chain’s equilibrium. This may result in greater losses for the supplier. When tariffs are high or the production technology of the base in the preferential tariff region is advanced, the equilibrium strategy for the supply chain shifts to a full-relocation strategy. Interestingly, in the partial-relocation strategy, the higher production technology in the preferential tariff region negatively impacts the manufacturer’s expected profits but benefits the supplier’s expected profits due to the increased double marginalization. Finally, we find that the supplier can reduce the impact of tariffs by relocating their production capacity, especially with the partial-relocation strategy, as the supplier is always motivated to improve the production technology of the base in the preferential tariff region, with a potential purpose of transferring tariff costs to the manufacturer and consumers. Full article

The shared energy storage device acts as an energy hub between multiple microgrids to better play the complementary characteristics of the microgrid power cycle. In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. In the second stage, the income distribution problem is transformed into a negotiation bargaining process. The island microgrid and the shared energy storage are the two sides of the game. Combined with the non-cooperative game theory, the alternating direction multiplier method is used to reduce the shared energy storage service cost. The simulation results show that shared energy storage can optimize the allocation of multi-party resources by flexibly adjusting the control mode, improving the efficiency of resource utilization while improving the consumption of renewable energy, meeting the power demand of all parties, and realizing the sharing of energy storage resources. Simulation results show that compared with the traditional PSO algorithm, the iterative times of the GWO algorithm proposed in this paper are reduced by 35.62%, and the calculation time is shortened by 34.34%. Compared with the common GWO algorithm, the number of iterations is reduced by 18.97%, and the calculation time is shortened by 22.31%. Full article

Green technology innovation (GTI) promotes the green, low-carbon transformation of equipment-manufacturing enterprises, helping to achieve sustainable development. Providing financial support for GTI can help alleviate firms’ financing constraints. Based on evolutionary game theory, this study analyzes the effect of financial support on GTI using a sample of listed Chinese equipment-manufacturing companies spanning 2015–2022. The results show that the combined support of financial institutions and the government can support enterprises’ GTI. Furthermore, the strength of financial support and the quality of environmental information disclosure affect firms’ willingness to undertake GTI. The empirical study shows that while credit support and government support positively affect firms’ GTI, equity support has a significant negative effect. Heterogeneity analysis shows that credit and government support can more effectively promote firms’ GTI when there is high-quality environmental information disclosure and intense market competition; equity support, meanwhile, has an inhibiting effect. This study enriches the literature on financial support’s effect on GTI in the equipment-manufacturing industry and can help guide governments and financial institutions to formulate policies and strategies to support firms’ GTI. Full article

Recently, the Nash equilibrium, known from game theory, was used for steady state calculation of pressurized pipe systems with general flow and pressure control devices. The concept is now applied to pumping stations. It is assumed that at least one of the pumps has a frequency controller that enables the pump to deliver a given set flow or set pressure by adaptation of pump speed. For hydraulic calculation, the system is decomposed into the local pumping station and a surrogate link with flow or pressure constraints at one of its end nodes. This method is demonstrated for a small example system. Full article

The rational selection of subway station locations is an interdisciplinary problem encompassing architecture, transportation, and other fields. Few evaluation index systems and quantitative evaluation methods exist for choosing subway station locations; thus, this paper establishes a novel evaluation framework. Overall, 21 indicators covering the construction and operation phases are selected by a literature review, providing a basis for planning decision makers. The Projection Pursuit Method (PPM) and the Bald Eagle Search (BES) algorithm are employed to assign objective weights. The Continuous Ordered Weighted Averaging (COWA) operator is utilized to obtain subjective weights. A combination weighting method is used based on game theory to improve the accuracy of weight calculation. Game theory and extension cloud theory are applied to develop an improved extension cloud model and evaluate the suitability based on optimal cloud entropy. We conduct a case study of 15 stations on the Chengdu Metro Line 11, China. The results reveal that the coordination of the development plans, the alignment with the land use plan, and regional population density are the most crucial tertiary indicators that should be considered in selecting subway station locations. These findings agree with the actual conditions, demonstrating the scientific validity of the proposed evaluation method, which outperforms classical evaluation methods. The proposed method is efficient and feasible for selecting subway station locations. Full article

We consider a two-group social conflict under the corporates’ research and development (R&D) business processes. Conflict participants are divided into two groups depending on their attitude to new ideas, technologies, and behavioral style for R&D creative problems—innovators and adapters. We reveal the contradiction that arises between the need to include both types of employees in one project team and their objectively antagonistic positions regarding the methods and approaches to R&D processes. The proposed research methodology is based on a modern post-non-classical paradigm formed on the principles of coherence, interdisciplinarity, openness, and nonlinearity, as well as a sociophysical approach to the social conflicts modeling. We use the general theories of magnetism, paramagnetism, and functions of P. Langevin and L. Brillouin to describe the dynamics of group participants’ preferences regarding the style of conflict behavior. The analogy of paramagnetism, consisting in the orienting effect of the magnetic field, is used to describe social groups interactions that have not only their own interests, but are also influenced by the opinions of opposite social groups. A two-dimensional, four-parameter map represents the dynamics of group conflict. Modeling results show that regardless of the initial states and with certain parameters of intra-group and intergroup interactions, the trajectories eventually converge to an attractor (limit cycle) in a two-dimensional space. No non-periodic or chaotic modes are identified in the two-group conflict, which determines the controllability of the described conflict. The results of the simulation experiments are used as decision support and contradictions resolution aimed at forming the required modes of the corporates’ research and development business processes and ensuring the group participants’ cohesion and depolarization. The results of testing the model at an industrial enterprise are presented. Full article

The chemical industry, a cornerstone of the global economy essential for modern life, has raised significant concerns due to its unique nature. Chemical technologies often require high energy inputs, involving ecotoxic reagents thus assessing risks from an economic standpoint becomes complex. While the economic aspects of chemical technologies have been discussed and economic tools have been used to inform investment decisions in this field, many fundamental issues remain unexplored, such as the clear definition of chemical technology economics and the reasons for its importance. The primary contribution of this article is to synthesize insights into these fundamental issues and propose pathways for future research in chemical technology economics. This review is divided into two sections: the first provides an overview of the significance of economic factors in chemical technologies, and the second explores the fundamentals of economics and their application to chemical technology considerations. Our research underscores that economic theories significantly influence the profile of chemical technologies, viewing the chemical sector as a dual asset. First, the sector has a unique opportunity to lead the way in promoting sustainable economic development, and second, it can adopt economic behaviors that align with environmental and societal needs. Full article

The Game Theory is aiding global tourism research to leverage destination appeal and competitiveness in the context of climate change advocacy. As global tourism continues to play a vital role in economic development and cultural exchange, there is a growing need to unravel the complexities of tourist behavior and destination competitiveness. Therefore, this study aims to utilize the Game Theory to investigate the relationships between Fear of Missing Out (FOMO), Regenerative Tourism Destination Competitiveness (RTDC), Tourist Visit Intention (TVI), and Destination Loyalty (DL) within the UAE, with the moderating role of Climate Advocacy. An online survey (using Google Forms) was distributed via social media platforms (primarily Facebook groups), resulting in data collection from 296 respondents. Smart PLS 4 and SPSS were utilized for data analysis. The findings revealed that RTDC had significant positive relationships with FOMO, DL, and TVI, thus supporting hypotheses 1 to 10. However, the hypothesis regarding Climate Advocacy moderating DL and TVI was not supported. Based on the Game Theory, this study contributes to the theoretical understanding of regenerative tourism destination competitiveness and offers practical implications for destination management strategies. Limitations include reliance on self-reported data and context-specific considerations. Future studies should also consider cultural contexts, to enhance the external validity of research outcomes. Full article

With the advent of big data, the swift advancement of diverse algorithmic technologies has enhanced the transaction efficiency of the e-commerce business. Nevertheless, it is crucial to acknowledge that e-commerce platforms might employ algorithmic technology to enforce differential pricing for various consumers with the aim of maximizing profits, thus infringing upon the lawful rights and interests of consumers. This paper focuses on the algorithmic price discrimination commonly observed on e-commerce platforms. To effectively regulate this behavior, the paper utilizes evolutionary game theory (EGT) to analyze the strategies employed by e-commerce platforms, consumers, and market regulators to achieve stability. This research employs a real-life situation and utilizes parametric simulation to visualize and analyze the process and outcomes of the three-party evolutionary game. The results demonstrate the credibility and feasibility of the article’s findings. Based on our research, we have reached the following findings: During the process of evolution, the strategic decisions made by the game participants from the three parties will mutually impact each other, and various elements exert varying degrees of influence on the strategic choices made by the game participants from each party. Collaborative governance can enable consumers and market regulators to regulate the discriminatory pricing behavior of e-commerce platforms effectively. This article offers valuable insights into the governance of violations in the e-commerce sector based on robust data and model research. Full article

Systematic management of corporate safety risks in industrial parks has become a hot topic. And risk prevention and control mutual aid is a brand-new model in the risk and emergency management of the park. In the context of blockchain, how to incentivize enterprises to actively invest in safety risk prevention and control mutual aid has become a series of key issues facing government regulators. This paper innovatively combines Prospect Theory, Mental Accounting, and Evolutionary Game Theory to create a hypothetical model of limited rationality for the behavior of key stakeholders (core enterprises, supporting enterprises, and government regulatory departments) in mutual aid for safety risk prevention and control. Under the static prize punishment mechanism and dynamic punishment mechanism, the evolutionary stabilization strategy of stakeholders was analyzed, and numerical simulation analysis was performed through examples. The results show: (1) Mutual aid for risk prevention and control among park enterprises is influenced by various factors, including external and subjective elements, and evolves through complex evolutionary paths (e.g., reference points, value perception). (2) Government departments are increasingly implementing dynamic reward and punishment measures to address the shortcomings of static mechanisms. Government departments should dynamically adjust reward and punishment strategies, determine clearly the highest standards for rewards and punishments, and the combination of various incentives and penalties can significantly improve the effectiveness of investment decisions in mutual aid for safety risk prevention and control. (3) Continuously optimizing the design of reward and punishment mechanisms, integrating blockchain technology with management strategies to motivate enterprise participation, and leveraging participant feedback are strategies and recommendations that provide new insights for promoting active enterprise investment in mutual aid for safety risk prevention and control. The marginal contribution of this paper is to reveal the evolutionary pattern of mutual safety risk prevention and control behaviors of enterprises in chemical parks in the context of blockchain. Full article

Experiences of occupational participation of adults with Intellectual Disabilities (IDs) were explored through the lens of the Model of Occupational Justice (MOJ) and Critical Theory in order to shape and develop an occupation-centered model of quality of life (QoL). This qualitative study involved thirteen adults with IDs (N = 13). A semi-structured interview, constructed based on MOJ and Critical Theory principles, was administered to explore perspectives on QoL, as well as injustices regarding occupational participation. The interviews were analyzed using QSR NVivo8 and followed a content analysis methodology. A preliminary model of Occupational Quality of Life (O-QoL), with an everyday occupations core component, has been formed. The model includes three core O-QoL domains: (i) social well-being, (ii) emotional–physical well-being, and (iii) material adequacy. Key indicators of O-QoL were identified as leisure and social activities, while socioenvironmental factors such as occupational deprivation were noted as aggravating. Specific occupations, including leisure activities, physical exercise/sports, art, video games, and vocational training, were found to be beneficial for O-QoL. Moreover, the importance of promoting and supporting the rights of people with IDs for employment, independent living, and sexual expression was highlighted. The model of O-QoL (version 1) could be a valuable alternative conceptual framework of QoL in the field of IDs; however, further research is needed to validate and refine the model. Full article

The utilization of conventional energy sources commonly leads to heightened energy consumption and the generation of specific forms of environmental pollution. As an innovative power management and dispatch system, virtual power plants (VPPs) have the potential to significantly enhance the flexibility and stability of power systems, while supporting carbon reduction targets by integrating distributed energy resources (DERs), energy management systems (EMSs), and energy storage systems (ESSs), which have attracted much attention in the power industry in recent years. Consequently, it can effectively address the variability and management challenges introduced by renewable energy. Furthermore, optimizing power market dispatch and user-side power management plays a pivotal role in promoting the transition of the energy industry towards sustainable development. The current study highlights the unresolved issue of strategic decision-making among market participants, such as energy companies, generation companies, and power distribution companies, despite the potentially significant benefits of VPPs. These entities must carefully evaluate the costs and benefits associated with adopting a VPP. Additionally, governments face the complex task of assessing the feasibility and effectiveness of providing subsidies to incentivize VPP adoption. Previous research has not adequately explored the long-term evolution of these decisions in a dynamic market environment, leading to a lack of adequate understanding of optimal strategies for market participants and regulators. This paper addresses this critical research gap by introducing an innovative bilateral evolutionary game model that integrates VPP and carbon trading markets. By utilizing the model, simulation experiments are carried out to compare different strategic decisions and analyze the stability and long-term evolution of these strategies. Research findings indicate that the adoption of VPP technology by market participants, in conjunction with government policies, results in an average 90% increase in market participants’ earnings, while government revenues see a 35% rise. This approach provides an alternative method for understanding the dynamic interactions between market participants and government policy, offering both theoretical and practical insights. The findings significantly contribute to the literature by proposing a robust framework for integrating VPPs into electricity markets, while offering valuable guidance to policymakers and market participants in developing effective strategies to support the sustainable energy transition. The application of this model has not only enhanced the understanding of market dynamics in theory, but also provided quantitative support for strategic decisions under different market conditions in practice. Full article