Initial Willingness Research Articles

Research on Knowledge Payment Product Supply Chain Governance Based on Blockchain: An Evolutionary Game Model

ABSTRACTBlockchain provides a new opportunity to govern the dilemmas in the knowledge payment product supply chain. This paper introduces blockchain into the evolutionary game to explore the behavioral strategies of knowledge providers, platforms, and consumers and to analyze in depth the influence of initial willingness and blockchain‐related factors by the system dynamics. The analysis shows that (1) improving the tripartite initial willingness is conducive to accelerating the process of supply chain governance and making the system reach an ideal state: knowledge providers choose compliance creation, platforms adopt blockchain, and consumers buy authorized product; (2) there are specific thresholds for the blockchain adoption cost and the premium of product brought by blockchain, only when the cost and premium are lower than the thresholds, the system evolves towards the ideal state; (3) when blockchain is adopted, it can effectively inhibit knowledge providers' illegal creation behavior and consumers' piracy behavior by increasing the punishments of platforms on knowledge providers and consumers. The results provide guidance to implement effective governance and the orderly development of knowledge payment industry.

Evolutionary game analysis of multi-agent cooperation strategy analysis in agricultural water conservancy PPP project under digitization background

This study constructed a system dynamics (SD) evolutionary game model, from which we analyzed the conditions that need to be met by multi-agents to achieve cooperation in agricultural water conservancy (AWC) Public-Private Partnership (PPP) projects. Simultaneously, this study used numerical simulation to depict the impact of initial participation willingness, reward, punishment, income, and other parameters of local governments, project enterprises, and farmers on the evolution strategy. The results firstly showed that the basic conditions for tripartite cooperation are to strengthen the rewards and punishments for project enterprises and improve the participation benefits of farmers. Secondly, it showed that increasing the rewards for farmers and improving the project dividend benefits can effectively motivate farmers to participate. Thirdly, it showed that enhancing the incentive subsidies and reputation benefits for project enterprise’s participation, as well as strengthening the supervision of local government, boosts the motivation of project enterprises significantly. However, it is vital to ensure that the reward amounts are not too high to allow local government to play its guiding role efficiently. Lastly, the results indicated that digital technology can help reduce the participation cost of local government, project enterprises and farmers, and improve the external reputation benefits of each participant, thus forming a win-win situation for all three participants. Analyzing the cooperation strategies of the three parties in AWC PPP projects provides theoretical support and a decision-making basis for the efficient operation of AWC PPP projects under the digital background, and also provides practical policy recommendations for the high-quality development of AWC.

Criminal Genius or Everyday Villain? A Comparison of Malevolent Creativity Among Prisoners, Police Officers, and the General Population

ABSTRACTCriminals allegedly use effective novelty to intentionally exploit and harm others (creative fraud, theft, and murder). However, empirical evidence that criminals possess higher malevolent creativity than individuals without criminal backgrounds is lacking. We compared a male sample of prisoners in a maximum‐security penitentiary (n = 140), police officers (n = 122), and the general population (n = 106) on three different aspects of malevolent creativity: self‐reported malevolent creativity behavior (MCBS), willingness to engage in malevolent creativity on a test (MCT), and malevolent creativity potential on that test (reduced n = 285). Group comparisons (ANOVAs) differed for different malevolent creativity aspects: Prisoners reported more malevolent creativity behavior in daily life (MCBS) than nonprisoners, which may reflect their alleged criminal personality or the effects of confinement on creative coping with threat. However, prisoners also performed worse than police officers in generating creative ideas for taking revenge on others (MCT). No differences in initial willingness to engage in malevolent creativity (MCT) emerged. This discrepancy of self‐report and ability is discussed from several angles, including suitability of the applied measures and heterogeneity of prison populations. This study constitutes the first empirical insights into the often hypothesized but rarely tested malevolent creativity expression in the criminal mind.

Dynamic Research on the Collaborative Governance in Urban and Rural Black-Odorous Water: A Tripartite Stochastic Evolutionary Game Perspective

The issue of black-odorous water (BOW) represents a formidable challenge to the current aquatic ecosystems, and its governance exhibits characteristics of low efficiency, susceptibility to relapse, and fragmented management under the Central Environmental Protection Inspection, thereby emerging as a dynamically complex issue in the ecological governance of urban and rural settings. This study introduces Gaussian white noise to simulate environmental uncertainty and design a stochastic evolutionary game model encompassing the central government, local governments, and societal forces based on evolutionary game theory and classical governance theories and concepts. Numerical simulations are conducted to explore trajectories of the strategic evolution of various subjects influenced by numerous factors. Results indicate that under the environment of random disturbances, the strategies of the game subjects show significant fluctuations, but actively cultivating the subject’s initial willingness facilitates collaboration governance in inspection. Moreover, joint construction of a “belief system” by multi-subjects, the intensity of inspection interventions, the integration of heterogeneous resources, and effective punitive measures all influence the governance of BOW, but the efficiency of resource allocation should be considered throughout the governance process. Recommendations are made finally for collaborative governance of urban and rural BOW, promoting the sustainable development of the ecological environment.

An evolutionary game model for indirect data sharing in manufacturing big data consortium

In the context of the explosive growth of manufacturing data, a manufacturing big data consortium is a collaborative organization aimed at promoting efficient decision-making and technological innovation. It is of vital significance to study how to effectively promote the data sharing among the members of manufacturing big data consortium. In this paper, we propose an evolutionary game model to investigate how to facilitate data sharing in the manufacturing big data consortium. Then, we analyze the synergistic revenue allocation method based on the indirect data sharing mode, and calculate the probability of the ideal event. We explore the influencing factors of data sharing in the manufacturing big data consortium by simulating Evolutionary Stable Strategies. Our findings reveal that the initial willingness of participants has a profound impact on their sharing behavior. Furthermore, the optimal interval revenue allocation coefficient can improve the probability of the manufacturing big data consortium to share data. Factors such as incentive revenue and social penalties positively influence the evolution towards active sharing strategies. In contrast, factors such as speculative revenue and data sharing costs inhibit the evolution towards active sharing strategies.

Cultural rice fields in the wave of climate change: a multilateral evolutionary game framework for adaptive management of agricultural heritage systems

Agricultural Heritage Systems (AHS) are pivotal in preserving rich agricultural production experience and traditional culture, as well as in maintaining biodiversity and promoting sustainable development in agriculture and rural economies. However, climate change poses significant threats to these systems, such as ecological degradation, biodiversity loss, and shifts in agricultural production patterns. This study, grounded in theories of information asymmetry and bounded rationality, constructs evolutionary game models for adaptive management of AHS under market mechanisms and government guidance. By employing stability analysis and numerical simulation with Delay Differential Equations (DDE) that consider historical delays, and through sensitivity analysis, this research delves into the strategic evolutionary outcomes of stakeholders under various scenarios. It aims to provide theoretical insights and policy recommendations for the dynamic protection and adaptive management of AHS in the face of climate change. The findings indicate that the public goods nature of AHS, alongside externalities and information asymmetry, leads to market failure. Sole reliance on autonomous actions by farmers and meteorological departments is insufficient for optimal resource allocation and effective protection. Government intervention, through regulatory and incentive measures, can effectively mitigate market failures and steer adaptive management of AHS towards efficiency and sustainability. Moreover, the study identifies key factors for adaptive management, such as enhancing stakeholders’ initial willingness to participate, reducing the costs of adapting to climate change, optimizing cooperative benefit distribution mechanisms, and increasing the profitability of resource cooperation. Sensitivity analysis of government subsidies and penalty mechanisms further reveals the complex and critical role these policy tools play in fostering stakeholder engagement. Based on these findings, the study recommends enhancing initial participation willingness, controlling transformation costs to alleviate economic burdens, optimizing benefit distribution mechanisms to boost cooperative resource profitability, and establishing dynamic subsidy and penalty mechanisms for optimal resource allocation. The theoretical and practical contributions of this research lie in applying theories of information asymmetry and bounded rationality to the adaptive management of AHS under climate change, enriching the theoretical framework in this field, and providing scientific decision-making support for policymakers. By demonstrating an effective path for AHS protection through combined government and market mechanisms in the context of global climate change, this research holds significant theoretical and practical implications for enhancing the efficiency of adaptive management of AHS, protecting, and inheriting valuable agricultural cultural heritage.

Government‐industrial‐research cooperation in virtual water strategy: A multi‐agent evolutionary game analysis

AbstractThe virtual water strategy (VWS) is an effective tool to balance regional water resource endowments and guarantee water supply security. However, because of self‐interested games around VWS (human decision bias), there is a need for methods to maintain reliable cooperation between governments, virtual water (VW) enterprises and research institutions. This study builds a multi‐agent evolutionary game model to analyse the relationship of players and their impacts on VWS through changing decision mechanisms and the paths to enhance their confidence in cooperation. Considering differences in initial willingness to cooperate and changing factors affecting payoffs, an evolutionary game can produce changing stable equilibriums or stable cooperations, even if some players are reluctant to cooperate. Therefore, to promote the development of VWS, a multistep support mechanism can be built for the VW industry, which fosters model enterprises and optimizes the cooperation framework to stimulate research innovations at scientific institutions.

How can the recycling of power batteries for EVs be promoted in China? A multiparty cooperative game analysis

While electric vehicles (EVs) are developing at a high speed in China, the power battery market is facing a decommissioning peak. The problem is that the recycling situation of domestic power batteries is not ideal, partly due to neglect by consumers. By considering the recycling system, mode, and policy of China’s EV power batteries, we construct a tripartite evolutionary game model of the government, consumers and EV manufacturers; analyse the stable strategy adjustment mechanisms of tripartite participation in this recycling cooperation game; and simulate the tripartite evolutionary game. The results show that when the initial willingness of the government, consumers and EV manufacturers to recycle power batteries is not strong, the government takes the lead, driving EV manufacturers and consumers to participate in power battery recycling. When the government, consumers and EV manufacturers have medium or high levels of initial willingness, the government evolves and chooses a nonregulation strategy. In addition, by simulating the impact of changes in consumer-related influencing factors on this tripartite evolutionary game, we find that subsidies for recycling power batteries are a key factor affecting consumers’ strategy choices and that boosting recycling compensation for consumers can improve their enthusiasm to participate in such recycling. Therefore, to improve the recycling of power batteries for EVs, in terms of both efficiency and percentage of deployment, the Chinese government should strengthen public education on power battery recycling, further integrate informal recycling channels, and balance the distribution of profits among consumers for recycling compensation.

Evolutionary analysis of nuclear wastewater collaborative governance based on prospect theory

Dealing nuclear wastewater into the sea significantly threatens the global ecological environment and public health. Existing research primarily focuses on the roles of emission and regulatory bodies, often overlooking the collaborative interactions between these entities. This study extends traditional marine governance strategies by considering upstream and downstream countries as research subjects. We first establish an evolutionary game model for the collaborative governance of nuclear wastewater between upstream and downstream countries, utilizing the Prospect theory and Evolutionary Game Theory. Subsequently, numerical simulations are employed to explore different entities' decision-making behaviors and influencing factors. Our findings indicate that: (1) initial willingness affects the time it takes for the system to reach a stable state; (2) the benefits and costs of proactive governance strategies influence decision-maker's behaviors; (3) subjective factors (risk preference, loss aversion) affect the strategic choices. This research provides a scientific basis for understanding different countries' selection of nuclear wastewater governance strategies.

The future of sustainable farming: An evolutionary game framework for the promotion of agricultural green production technologies

In the context of global climate change and increasing population, transitioning to resource-efficient, environmentally friendly agricultural technologies is essential for sustainability. In this context, the present study is anchored in the theories of information asymmetry and bounded rationality. It constructs a tripartite evolutionary game model under market mechanisms and government guidance, facing the challenges of promoting green agricultural technologies among multiple actors. This model explores the strategic choices and dynamic evolution of these actors under economic incentives and risk perception. The objective of the research is to reveal the dynamic evolutionary trends of stakeholder behavior under different policy intervention conditions and how governments can propel the promotion of green agricultural production technologies through policy instruments. To encompass the impact of historical decisions on the evolutionary process of green technology dissemination, this study employs a Delay Differential Equations (DDE) algorithm that considers historical time lags in its numerical simulations. Through stability analysis and DDE numerical simulations, the research identifies factors influencing the promotion of green agricultural production technologies. The findings indicate that under market mechanisms, there is a risk of “market failure” in the dissemination model of green agricultural technologies. Government participation can provide external incentive support, effectively enhancing the stability and efficiency of the evolutionary game system for promoting green technologies. Simulation results further suggest that government intervention can significantly improve the stability and efficiency of technology promotion. Economies of scale, initial willingness, risk perception, and subsidy intensity are decisive factors in technology adoption. Consequently, policymakers are advised to formulate precise and multifaceted subsidy strategies based on the varying needs of different actors, to stimulate engagement, reduce risk, and encourage widespread adoption of green technologies. This study lays a theoretical groundwork for smallholders and family farms to overcome technology adoption barriers, crucial for sustainable agricultural development. It provides a framework for understanding and addressing these challenges, guiding policymakers in crafting effective green agriculture policies to improve farming efficiency and sustainability.

Research on the evolution game of low-carbon operations in cold chain logistics considering environmental regulations and green credit

To solve the problem of insufficient low-carbon operational motivation among cold chain logistics enterprises due to the high investment costs of low-carbon assets and considering the promotional effect of environmental regulatory policies and green credit, an evolutionary game model was constructed for the government, cold chain logistics enterprises, and financial institutions. The stability strategies of each participating entity and the stability of the system equilibrium point were analyzed, and the relevant conclusions were verified through numerical simulations. The research results indicated the following: (1) the initial willingness of the three parties to participate increased, the low-carbon operation of cold chain logistics enterprises and the speed of green credit services provided by financial institutions accelerated, and the rate of strict government regulation slowed down. (2) Moderate subsidies and taxes were conducive to the joint participation of the three parties. (3) Increasing the subsidy for green credit provided positive incentives for financial institutions to provide green credit services, while reducing credit interest rates accelerated the low-carbon operation rate of cold chain logistics enterprises.

The Green Development in Saline–Alkali Lands: The Evolutionary Game Framework of Small Farmers, Family Farms, and Seed Industry Enterprises

Amid global climate change and population growth, the prevalence of saline–alkali lands significantly hampers sustainable agricultural development. This study employs theories of asymmetric information and bounded rationality to construct an evolutionary game model, analyzing the interactions among small farmers, family farms, and seed industry enterprises in the context of saline–alkali land management. It investigates the strategic choices and dynamics of these stakeholders under the influence of economic incentives and risk perceptions, with a focus on how government policies can foster green development. Utilizing Delay Differential Equations (DDEs) for simulations, this study highlights the risk of “market failure” without government intervention and underscores the need for government participation to stabilize and improve the efficiency of the green development process. The findings reveal that factors such as initial willingness to participate, the economic viability of salt-tolerant crops, seed pricing, research and development costs, and the design of incentive policies are crucial for sustainable land use. Accordingly, the paper proposes specific policy measures to enhance green development, including strengthening information dissemination and technical training, increasing the economic attractiveness of salt-tolerant crops, alleviating research and development pressures on seed companies, and optimizing economic incentives. This study provides a theoretical and policy framework for the sustainable management of saline–alkali lands, offering insights into the behavioral choices of agricultural stakeholders and supporting government strategies for agricultural and environmental protection.

Patients' Perspectives on Plans Generated During Primary Care Visits and Self-Reported Adherence at 3 Months: Data From a Randomized Trial.

Effective primary care necessitates follow-up actions by the patient beyond the visit. Prior research suggests room for improvement in patient adherence. This study sought to understand patients' views on their primary care visits, the plans generated therein, and their self-reported adherence after 3 months. As part of a large multisite cluster randomized pragmatic trial in 3 health care organizations, patients completed 2 surveys-the first within 7 days after the index primary care visit and another 3 months later. For this analysis of secondary outcomes, we combined the results across all study participants to understand patient adherence to care plans. We recorded patient characteristics and survey responses. Cross-tabulation and chi-square statistics were used to examine bivariate associations, adjusting for multiple comparisons when appropriate. We used multivariable logistic regression to assess how patients' intention to follow, agreement, and understanding of their plans impacted their plan adherence, allowing for differences in individual characteristics. Qualitative content analysis was conducted to characterize the patient's self-reported plans and reasons for adhering (or not) to the plan 3 months later. Of 2555 patients, most selected the top box option (9=definitely agree) that they felt they had a clear plan (n=2011, 78%), agreed with the plan (n=2049, 80%), and intended to follow the plan (n=2108, 83%) discussed with their provider at the primary care visit. The most common elements of the plans reported included reference to exercise (n=359, 14.1%), testing (laboratory, imaging, etc; n=328, 12.8%), diet (n=296, 11.6%), and initiation or adjustment of medications; (n=284, 11.1%). Patients who strongly agreed that they had a clear plan, agreed with the plan, and intended to follow the plan were all more likely to report plan completion 3 months later (P<.001) than those providing less positive ratings. Patients who reported plans related to following up with the primary care provider (P=.008) to initiate or adjust medications (P≤.001) and to have a specialist visit were more likely to report that they had completely followed the plan (P=.003). Adjusting for demographic variables, patients who indicated intent to follow their plan were more likely to follow-through 3 months later (P<.001). Patients' reasons for completely following the plan were mainly that the plan was clear (n=1114, 69.5%), consistent with what mattered (n=1060, 66.1%), and they were determined to carry through with the plan (n=887, 53.3%). The most common reasons for not following the plan were lack of time (n=217, 22.8%), having decided to try a different approach (n=105, 11%), and the COVID-19 pandemic impacted the plan (n=105, 11%). Patients' initial assessment of their plan as clear, their agreement with the plan, and their initial willingness to follow the plan were all strongly related to their self-reported completion of the plan 3 months later. Patients whose plans involved lifestyle changes were less likely to report that they had "completely" followed their plan. ClinicalTrials.gov NCT03385512; https://clinicaltrials.gov/study/NCT03385512. RR2-10.2196/30431.

Fostering fintech innovation: A tripartite evolutionary game analysis of regulatory sandbox experiments

The rapid integration of next-gen information technologies in finance has spurred FinTech innovation, posing challenges to regulation. Regulatory sandboxes are pivotal for fostering innovation. This study employs a FinTech innovation regulatory sandbox to analyze a tripartite evolutionary game involving government, FinTech enterprises, and the public. It examines strategic choices, equilibrium points, and the interplay of incentives and costs. Results highlight the pivotal role of FinTech companies. Recommendations include consistent government incentives to optimize resource allocation. In tepid engagement scenarios, FinTech companies and government entities lead the innovation adoption. In a context of significant technology spending, increasing initial willingness is crucial for optimize development.

Study on the symbiosis evolution mechanism of the digital innovation ecosystem: considering government regulation

PurposeThe purpose of this paper is to analyze the symbiotic evolution decisions of digital innovation enterprises, research institutes and the government in the digital innovation ecosystem.Design/methodology/approachBased on innovation ecosystem theory and an evolutionary game model, this study constructs a tripartite symbiotic evolution game model of digital innovation ecosystems with digital innovation enterprises, research institutes and the government as the main bodies and analyzes the influencing factors as well as the evolution paths of the different behavioral strategies of each subject through numerical simulation.FindingsThe research shows that the digital innovation ecosystem has the characteristic of self-organization, which requires the symbiotic cooperation of each subject. The government plays an active role in any stage of symbiotic evolution, and the system cannot enter symbiosis under a low level of subsidies and penalties. Only when the initial willingness to cooperate of digital innovation enterprises and scientific research institutes is at a medium or high level is the system likely to become symbiotic. While digital innovation enterprises are more sensitive to government subsidies and punishments, scientific research institutes are more sensitive to the distribution proportion of cooperation income.Originality/valueThis study includes government regulation into the research scope, expands the research mode of the digital innovation ecosystem and overcomes the difficulties of empirical research in collecting dynamic large sample data. It vividly and systematically simulates the symbiotic evolution process of the digital innovation ecosystem, which provides a theoretical and practical reference for digital innovation ecosystem governance.

Multi-agent collaborative management of coastal pollution from land-based sources from the perspective of emissions trading: An evolutionary game theory approach

Emissions trading has been playing a very important role in addressing pollution of estuarine and coastal waters. This paper aims to explain mechanism of the multi-agent collaborative management of coastal pollution from land-based sources from the perspective of emissions trading and identify its influencing factors. Given the current participation of polluting enterprises in emissions trading, this paper constructs a tripartite evolutionary game model consisting of local governments, polluting enterprises, and the public. Drawing on this model and the ABM (agent-based modeling) for simulation and using artificial neural networks for error corrections, the numerical simulation of the data of Dongying, a pilot city of emissions trading is conducted, to examine the influence of different factors on the evolutionarily stable strategy. The results show that: ➀ increasing each agent’s initial willingness of participating in collaborative management can facilitate the evolution of their behavioral strategies towards collaborative management. Specifically, compared with the public, polluter’s stronger willingness for emission reduction and the government’s more proactive willingness for regulation can better promote collaborative management in land-based pollution; ➁ the increase in the reward standard for emissions cutters has a positive impact on enterprises and the public’s proactive participation in collaborative management, yet a negative impact on local governments; ➂ higher reward from the provincial government and the increase in the emissions trading price have a positive impact on the enthusiasm of local governments, enterprises and the public in collaborative management; ➃ the increase in the unit cost of emission reduction will undermine polluting enterprises’ enthusiasm in emission reduction. Policy suggestions are thus proposed, such as increasing the subsidies for emission reduction, promoting and perfecting the emission trading market, cutting the emission reduction cost of enterprises and the supervision cost of local governments, and increasing the public’s concern on the governance of marine pollution from land-based sources. The conclusion will provide a theoretical underpinning for and guide related practice of future preservation of coastal ecologies and management of coastal pollution from land-based sources.

A study on the evolution of tripartite collaborative prevention and control under public health emergencies using COVID-19 as an example

The problem of repeated epidemic fluctuations in the normalized prevention and control stage is revealed by data from January 20, 2020, to January 30, 2023. In order to improve the collaborative response of the public and government departments to public health emergencies and avoid repeated fluctuations of the epidemic, a tripartite evolutionary game model of the public, local government, and central government departments is constructed, focusing on the evolutionary paths and evolutionary stabilization strategies of the three subjects, and the influence of each element on the evolutionary results is simulated by numerical simulation in Matlab, and based on the inadequacy of the static reward and punishment mechanism, a dynamic Based on the shortcomings of static reward and punishment mechanism, dynamic reward and punishment mechanism is introduced to control the stability of the evolving system. The study shows that (1) with the increase of the initial willingness of the three parties, the rate of the public choosing the discretionary flow strategy slows down, and the collaborative prevention and control process can be accelerated. (2) The reward and punishment mechanism of central government departments has a positive incentive effect on the local government's strict prevention and control and the public's conscious isolation. Appropriately increasing rewards, formulating reasonable subsidy strategies, and increasing penalties for violations are conducive to the overall optimization of the system, and the punishment mechanism is most sensitive to the regulation of the public's discretionary mobility behavior. (3) Government departments' prevention and control costs can influence their enthusiasm for strict prevention and control and real-time supervision. Reducing the human resources cost, time cost, and financial cost of prevention and control is conducive to government departments performing their duties more responsibly. (4) The static punishment mechanism fails to make timely adjustments according to the strategy choice of each actor. It cannot control the stability of the evolving system. In contrast, the dynamic punishment mechanism considers the punishment parameters to link the casual isolation rate with the lenient prevention and control rate, which can effectively control the system's fluctuating instability and is the system's stability control strategy. Finally, combining theoretical and simulation analysis, management suggestions are made for controlling repeated fluctuations of the epidemic in practice, and the research limitations of this paper are explained.

Study on the evolution of collaborative innovation in marine economy considering the participation of financial institutions and two types of cooperation

In the realm of significant technological research and innovation within the marine economy, enterprises and academic research institutions often grapple with a lack of innovation motivation due to financial constraints. This paper introduces the factor of "capital constraints" into the marine innovation chain, establishing a technological innovation chain within the marine economy. Utilizing a three-party evolutionary game model, the study delves into the strategy selection and evolution of financial institutions, marine enterprises, and academic research institutions. In contrast to previous studies, this paper categorizes technological innovation cooperation into two types: "cooperative tackling type" and "market-oriented promotion type." Additionally, it posits that collaboration between academic research institutions and marine enterprises establishes an implicit guarantee relationship, facilitating access to higher loan amounts for both parties. The research reveals that the behavior of governments and marine enterprises is influenced by the initial willingness of participants. Higher basic benefits of cooperation and innovation between academic research institutions and marine enterprises lead to a quicker attainment of an evolutionary stable state. Moreover, in collaborations between marine enterprises and research institutions, an excessively high proportion of funds occupied by marine enterprises proves disadvantageous. The paper suggests that pure market-oriented promotion innovation cooperation could serve as a supplementary approach to traditional cooperation and innovation. Finally, numerical examples are presented to elucidate the outcomes of the theoretical model, accompanied by policy suggestions.

An Evolutionary Game Study on Green Technology Innovation of Coal Power Firms under the Dual-Regulatory System

The transformation of Chinese coal power firms is crucial for achieving carbon emission reduction (CER) goals, and promoting green technology innovation (GTI) is the key for the achievement. To examine the interactive mechanism of central and local government regulatory behavior and coal power firms’ GTI behavior under China’s dual-regulatory system, this paper introduces environmental impact coefficients and develops a tripartite evolutionary game model (EGM) from the perspective of CER. The influencing factors and interactive relationships among them are analyzed. Additionally, through numerical simulation, the impacts of changes in central and local government S&amp;P (subsidies and penalties) on the evolution of the system are also obtained. The findings indicate the following: (1) Enhancing the initial willingness can accelerate the system’s attainment of an optimal state. The local government exhibits a slower pace of evolution. Coal power firms are more sensitive to changes in the initial willingness of the central government. (2) The local government is more sensitive to changes in the central government’s S&amp;P intensity rather than changes in the central government’s initial willingness. Low levels of central government S&amp;P and high penalties are ineffective, while high subsidies can lead to a sudden decrease in the local government’s willingness. (3) Local government penalties have a positive correlation with their effectiveness in promoting GTI, whereas high subsidies are ineffective. (4) The separate implementation of subsidies or penalties by either the central or the local government is detrimental to achieving the optimal state. Such an approach renders the fluctuant or negative behavior of the local government and coal power firms.

The Influence of Perceived Trust, Perceived Value, Perceived Usefulness, and Perceived Risk on College Students' Initial Willingness to Pay for Online Knowledge

The Influence of Perceived Trust, Perceived Value, Perceived Usefulness, and Perceived Risk on College Students' Initial Willingness to Pay for Online Knowledge