Intensity Of Punishment Research Articles

An Investigation into the Mechanism of Government Embedment and Organizational Environment Influencing Farmers’ Credible Commitment in Regard to the Collective Governance of Rural Residential Land

The purpose of this study is to investigate the influence of Government Embedment and Organizational Environment on farmers’ Credible Commitment in regard to the Collective Governance of Rural Residential Land and to inform decision-making processes that promote farmers’ compliance with Rural Residential Land management regulations and enhance the effectiveness of the Collective Governance of Rural Residential Land. The research employs various models, including Oprobit, Ologit, IV-2SLS, and moderated mediation. The research results show that (1) both Government Embedment and the Cultural Environment within the Organizational Context significantly enhance Farmers’ Credible Commitment in regard to the Collective Governance of Rural Residential Land. Notably, the quality of the Cultural Environment, when improved by Government Embedment, boosts this commitment further. (2) Endogeneity issues can lead to an overestimation of the effects of these factors. (3) Punishment intensity only positively moderates the impact of the Cultural Environment on Farmers’ Credible Commitment. (4) The moderating effect of punishment intensity correlates positively with its strength, exhibiting a threshold value. In conclusion, our research underscores the need to establish a robust regulatory framework for Rural Residential Land use, foster a conducive village cultural atmosphere, and consistently enhance the punishment intensity for illegal Rural Residential Land use. These measures will encourage farmers to adhere to Credible Commitment in regard to Rural Residential Land use, thereby facilitating the effective implementation of Collective Governance over Rural Residential Land.

Comparison of the Efficacy and Welfare of Different Training Methods in Stopping Chasing Behavior in Dogs.

Controversy surrounds the efficacy and welfare implications of different forms of dog training with several studies asserting that electronic shock collars have negative welfare impacts while not being more effective than non-aversive methods. However, these studies did not specify the schedule and intensity of punishment used or the effectiveness of the training method. In the current study, we attempted to train dogs across six sessions to desist from chasing a fast-moving lure in one of three randomly assigned conditions and then tested for retention and generalization in four further test trials. Group A was trained with e-collars; Group B was trained with non-aversive methods and the lure moving as with Group A; and Group C was trained as for Group B but with the lure initially moving slowly before its speed was progressively increased. All dogs in Group A stopped running towards the lure after one or two sessions, and none chased the lure in the first three tests: 67% of these dogs chased the lure in the final test in a novel arena. None of the dogs in the either Group B or C successfully refrained from chasing the moving lure in training or any test. Video behavior coding indicated few stress-related behaviors across the training groups.

The punishment intensity for research misconduct and its related factors: An exploratory study on hospitals in Mainland China

ABSTRACT Previous studies have found that factors such as gender and academic positions do not influence the severity of administrative actions taken by institutions. However, this study provides partly inconsistent evidence. It focuses on incidents of research misconduct in hospitals across Mainland China and explores factors related to punishment using a large cross-sectional dataset (N = 815). Regression analysis revealed a significant correlation between authorship order and the punishment intensity (p < 0.05). Under specific conditions, there was a significant correlation between the professional title (senior) and punishment intensity (p = 0.001), and an interaction between professional title and types of research misbehavior. Further analysis of simple effects showed that, in cases of fabrication and falsification, and combinations of multiple research misbehavior, researchers with senior titles received significantly lighter punishments compared to those with junior, intermediate, and associate senior titles (p < 0.05). The study unveils the potential accountability patterns (collective accountability and tiered punishment) that may be adopted by hospitals in Mainland China, as well as the challenges faced in ensuring fairness, emphasizing the importance of independent investigative bodies for incidents of research misconduct, and advocating for fairness as a priority in governance of research misconduct.

Teachers' Punishment Intensity and Student Observer Trust: A Moderated Mediation Model.

During social interactions, people decide whether to trust an actor based on their punitive behaviour. Several empirical studies have indicated that punishment intensity impacts observer trust, yet the underlying mechanism remains to be elucidated. This study included 242 junior high school students and was conducted to investigate the relationship between teachers' punishment intensity and levels of student bystander trust. Additionally, the mediating role of trustworthiness and the moderating role of group relationships were explored. The results showed that the relationship between punishment intensity and observer trust follows an inverted U-shaped pattern. In addition, mild punishment boosts observer trust by improving perceived trustworthiness (ability and integrity) compared to no punishment, while harsh punishment reduces observer trust more than mild punishment by diminishing perceived trustworthiness (ability, benevolence, and integrity). More importantly, group relationships positively moderate the relationship between punishment intensity and observer trust. Specifically, compared to mild or no punishment, harsh punishment decreases trustworthiness (ability, benevolence, and integrity) in close teacher-student relationships but has less impact on neutral relationships. The above findings demonstrate that guiding educators in developing appropriate disciplinary concepts contributes to enhancing student observer trust.

Research on Stakeholder Behavior Strategy in Green PPP Project Financing

In the context of green development, while promoting green industry and sustainable development, green PPP faces the challenge of financing difficulties. Based on the evolutionary game theory of bounded rationality and taking government, social capital and financial institutions as the game players, this paper constructs an evolutionary game model for the behavioral decision-making of stakeholders in green PPP project financing. Using MATLAB software, we simulate and analyze the key factors affecting the behavioral strategies of each game player. The results indicate that: (1) The additional income obtained from participation in green PPP projects is a key factor affecting the decision-making of social capital and financial institutions, so it is necessary to improve the reasonable return mechanism of green PPP projects and attach importance to the construction of reputation mechanism; (2) Government subsidies can effectively encourage social capital and financial institutions to participate in green PPP projects, but the amount of subsidies should be within a reasonable range; (3) The government's reward and punishment intensity is a significant factor affecting the decision-making of social capital behavior. To this end, it is imperative for the government to enhance the performance evaluation system for green PPP projects and establish a balanced reward and punishment mechanism. This paper puts forward some suggestions on the decision-making of stakeholders in the financing process of green PPP projects, and provides references for the policy formulation of encouraging social capital and financial institutions to participate in green PPP projects.

Enhancing Green Port Construction through Advanced Computing: An Evolutionary Game Model under Social Accountability and Government Supervision

Ports, as pivotal hubs for global resource consumption and pollution emissions, have garnered considerable attention in the pursuit of sustainability. Despite the Chinese government’s efforts in promoting the green construction of ports and a growing public awareness of environmental protection, progress remains sluggish, with pollution and energy consumption issues still rampant. This paper introduces an evolutionary game model that leverages advanced computing techniques, including big data analytics and simulation, to optimize green port construction strategies, supervision, and enforcement under the lens of social accountability. By applying the Jacobi matrix for analyzing equilibrium paths at diverse initial settings and conducting simulations under various scenarios of punishment intensity and social accountability probabilities, this study unveils that high social accountability likelihoods naturally incentivize ports towards green practices. Conversely, in low accountability scenarios, differentiated outcomes emerge from imposing penalties on ports and local governments. Notably, increasing penalties on ports substantially elevates green construction standards, whereas local government penalties exhibit only transient efficacy. Furthermore, leveraging artificial intelligence for predictive analysis and simulation demonstrates the critical role of technological advancements in enhancing green port construction. The study proposes augmenting penalties on ports, amplifying social oversight, and diminishing green construction costs via port consortia as strategic measures to expedite China’s transition to green ports.

Research on the "multi-agent co-governance" system of unfair competition on internet platforms: Based on the perspective of evolutionary game.

Unfair competition on internet platforms (UCIP) has become a critical issue restricting the platform economy's healthy development. This paper applies evolutionary game theory to study how to utilize multiple subjects' synergy to supervise UCIP effectively. First, the "multi-agent co-governance" mode of UCIP is constructed based on the traditional "unitary supervision" mode. Second, the government and internet platform evolutionary game models are built under two supervision modes. Finally, MATLAB is used to simulate and analyze the evolutionary stage and parameter sensitivity. In addition, we match the model's evolutionary stage with China's supervisory process. The results show that (1) the Chinese government's supervision of UCIP is in the transitional stage from "campaign-style" to "normalization." (2) Moderate government supervision intensity is essential to guide the game system to evolve toward the ideal state. If the supervision intensity is too high, it will inhibit the enthusiasm for supervision. If the supervision intensity is too low, it cannot form an effective deterrent to the internet platforms. (3) When the participation of industry associations and platform users is low, it can only slow down the evolutionary speed of the game system's convergence to the unfavorable state. Nevertheless, it cannot reverse the evolutionary result. (4) Maintaining the participation level of industry associations and platform users above a specific threshold value while increasing punishment intensity will promote the transition of government supervision from the "campaign-style" to the "normalization" stage. This paper provides ideas and references for the Chinese government to design a supervision mechanism for UCIP.

Can Asymmetric Punishment Explain Norm Changes?

Abstract: We test a general theory of norm changes based on evidence that people will punish less hygienic others more strongly than more hygienic others. The theory concludes that such asymmetric punishment would result in hygiene norms becoming ever stricter. We argue that, because complaints about one’s behavior might lead to protest, norms might not always change because of such complaints. We conducted an online experiment ( N = 1,023 Swiss adults) using handwashing as the target behavior. We replicated the asymmetry in punishment intensities and found that the intensity of protests against complaints about one’s too unhygienic behavior approached the intensity of these complaints. We conclude that, while asymmetric punishment may drive norm change, protests may lead to norm stability.

An Evolutionary Game Analysis of the Main Body Collaboration of Public-Private Cooperation Projects in Rural Environment

An evolutionary game model was established to study the evolutionary stability strategy of government and social capital in the public-private cooperation model of rural environmental governance and its influencing factors, and to explore the evolution process of cooperative behavior of the main body. The research shows that income distribution, risk distribution, supervision intensity and reward and punishment amount are important factors that affect the choice of cooperative strategy of the main body in the public-private cooperation project of rural environmental governance, and determine the evolution direction of the coordination of the main body behavior. Reducing the cooperative cost, appropriately increasing the risk bearing, and improving the supervision and reward and punishment intensity are conducive to the establishment of the collaborative behavior of the main body in the public-private cooperation model of rural environmental governance.

Value co-creation in group enterprises: an evolutionary game theory-based analysis

Information barriers exist between subsidiaries in a group enterprise, where each subsidiary acts independently, and hinder rational allocation and utilisation of resources. This study proposed a value co-creation model consisting of heterogeneous subsidiaries in a group enterprise and consumers. By constructing a three-party evolutionary game model, we discussed the impact of information leakage risk, punishment intensity, consumer experience, and reputation on the strategy evolution process, which means the proportion of strategy choices for the three entities over time. We analysed and verified the evolutionary process of the value co-creation system in different scenarios. This study revealed the ‘butterfly effect’ of value co-creation within the group enterprise, highlighting how different combinations of decision-making probabilities among the three entities in the initial stage can result in diverse outcomes, even when starting from identical conditions. The study also found that under certain conditions, group subsidiaries may sacrifice their own interests for the overall interests of cooperation. This study yielded the counterintuitive conclusion that in a stable state, the choice of cooperation strategies between subsidiaries is not directly related to their willingness to share knowledge.

Memristive Neural Network Circuit of Operant Conditioning With Reward Delay and Variable Punishment Intensity

Memristive Neural Network Circuit of Operant Conditioning With Reward Delay and Variable Punishment Intensity

Enhancing cooperative evolution in spatial public goods game by particle swarm optimization based on exploration and q-learning

In evolutionary game theory, the emergence and maintenance of cooperative behavior in a population often face challenges posed by the temptation of free-riding behavior, which offers high individual payoff. Recently, apart from a range of mechanisms that promote the formation of cooperation, individual learning abilities under limited information have emerged as a key factor in adjusting agents' strategies. This paper introduces q-learning and particle swarm optimization into the realm of evolutionary dynamics. The primary focus is on investigating the impact of Exploration-based Particle Swarm Optimization (EPSO) and Q-learning-based Particle Swarm Optimization (QPSO) on the evolution of cooperation in a continuous version of the spatial public goods game (SPGG) with punishment. EPSO defines a rule for updating agents' strategies based on individual and limited population information. It also integrates an exploration mechanism to increase the diversity and directionality of the strategies. Additionally, QPSO serves to adaptively optimize the parameters of EPSO, addressing the issue of parameter control limiting the EPSO's performance. Leveraging experiential learning and iterative adjustment, QPSO progressively refines system parameters, thus rationally assimilating knowledge and updating individual strategies to attain optimal payoff. Through extensive simulation studies, it has been observed that employing QPSO's adaptively optimized parameters in EPSO significantly promotes the cooperative evolution in the SPGG with punishment. Furthermore, individual learning coefficients, when too low or too high, both facilitate the occurrence of cooperation. Simultaneously, higher inertia weight coefficients strengthen the system's cooperation level, while lower punishment intensity coefficients and higher gain intensity coefficients effectively promote the cooperation emergence and exert a significant influence on the overall cooperation level of the system. This research provides a new perspective for designing real-world schemes that encourage cooperation and offers insights into the intricate dynamics of cooperation in complex systems.

Evolutionary analysis of green credit and automobile enterprises under the mechanism of dynamic reward and punishment based on government regulation

To explore the green development of automobile enterprises and promote the achievement of the “dual carbon” target, based on the bounded rationality assumptions, this study constructed a tripartite evolutionary game model of government, commercial banks, and automobile enterprises; introduced a dynamic reward and punishment mechanism; and analyzed the development process of the three parties’ strategic behavior under the static and dynamic reward and punishment mechanism. Vensim PLE (Personal Learning Edition) was used for numerical simulation analysis. Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism. A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations. Under the dynamic reward and punishment mechanism, an increase in the initial willingness of the three parties can promote the system stability, and the government can implement effective supervision by adjusting the upper limit of the reward and punishment intensity. Finally, the implementation of green credit by commercial banks plays a significant role in promoting the green development of automobile enterprises.

Stochastic Evolutionary Game Model of Hot Topics Propagation for Network Public Opinion

Due to the rapid propagation and significant impact, the network public opinion of hot topics has become a concern of the social public and governments. The existing models based on the evolutionary game cannot reflect the real-world propagation of hot topics under uncertain environmental interference. And few researchers analyze the early intervention timing of the government on hot topics based on stochastic evolutionary game theory. To solve these problems, the government intervention parameters of punishment intensity, intervention delay, and intervention probability are introduced to build a three-party stochastic evolutionary game model of “media-netizen-government” in the multi-agent system under the scene of hot topics propagation. Then, the stochastic differential equation is expanded and simulated by the explicit forward Euler numerical method. Finally, simulation experiments are conducted to quantitatively analyze the random evolutionary process and the government intervention timing by adjusting key parameters, which can provide the optimal timing and suggestions for governments to intervene in hot topics propagation.

Intrusion into Computer Information System: Criminal Law Rule Based on Different Judicial Recognition Perspectives of State Affairs

Cybercrime refers to a new form of crime generated with the application and prevalence of computer technology. In China, there are increasingly more instances of unauthorized access to computer systems every year, which has severely affected network security and the property security of the people, and even national security. This paper delves deeper and more methodically into the problems surrounding the criminal act of unlawful access to computer information systems. The ambiguous definition and limited reach of the criminal object make Chinas punishment for unauthorised access to computer systems less effective., the crossover of the criminal law system caused by the contradiction of legislative logic, as well as the insufficient prevention of too lenient penalties. Based on the above legislative deficiencies, it is imperative to improve the criminal law system, expand the protection scope of the first clause of Article 285 of the Criminal Law, Increase the number of cases that are investigated and prosecuted, explain computer information systems in the context of state affairs, expand the definition of state affairs computer information systems, and strictly regulate the amount of crime that is legal. Additionally, it is essential to establish an independent status for data crimes by adding provisions on data security protection concerning the three major computer information systems; increasing the intensity of punishment, raising the range of statutory penalties, and adding property penalties, thereby imposing a comprehensive regulation on illegal intrusion into computer information systems.

The impact of government subsidy on photovoltaic enterprises independent innovation based on the evolutionary game theory

Achieving a green, low-carbon economy necessitates clarifying the impacts of government photovoltaic (PV) subsidies on enterprise independent innovation in China. This study constructs a tripartite evolutionary game model among government, enterprises, and energy regulatory service centers (ERSC). It analyzes equilibriums' asymptotic stability and explores mechanisms affecting the system's evolution toward an ideal state. The results indicate that the strategic choices of the government, enterprises, and ERSC interplay with each other. Specifically, the primary influencing factors for enterprise innovation are costs, benefits, and penalties which promote innovation to an extent, while government subsidies have minimal effect. Under ERSC's policy guidance and services, enterprises controlling independent innovation costs given moderate punishment intensity enables system evolution toward sustainable innovation despite subsidy cancellation, achieving enterprises' ultimate carbon reduction goal in China. The originality in this study lies in the analysis of ERSC's influence on equilibrium, which models the impact of policies on enterprises, and ERSC plays an essential role in coordinating the government-enterprise information gap. Chinese government should strengthen regulatory system construction and increase financial support. This model can generate social benefits, reduce costs, and provide policymakers with an analytical framework and insights for policy formulation in China.

Formula omitted]-player repeated evolutionary trust game under government management

Trust game is a common framework for studying trust behavior between unrelated individuals. Previous theoretical research has found that network structure or reputation can promote trust and cooperation, but these studies often assume that interactions between players are one-time and investors have no choice but to invest, which is inconsistent with reality. Here we introduce the conditional investment strategy and government management into a repeated N-player trust game, where investors can make investment decisions based on the investment environment and the government plays the role of a regulator. We consider a reporting mechanism to allow investors to report untrustworthy trustees, thereby the government punishes reported untrustworthy trustees and rewards investors who successfully report untrustworthy trustees. We find that the introduction of the conditional investment strategy and incentives can prompt the evolution of trust. Besides, we reveal that as punishment intensity increases, not only can trust emerge but investment behavior can also be maintained. Furthermore, we verify the above theoretical results by numerical simulations.

Punish or reward? How to strengthen supervision of nucleic acid testing

PurposeNucleic acid testing is an effective method of accurate prevention and control and a key measure to block the spread of the epidemic. However, the fraud in nucleic acid testing occurred frequently during epidemics. This paper aims to provide a viable scheme for the government to strengthen the supervision of nucleic acid testing and to provide a new condition for the punishment for the negative act of the government and the upper limit of the reward for nucleic acid testing institution of no data fraud.Design/methodology/approachThis paper formulates an evolutionary game model between the government and nucleic acid testing institution under four different mechanisms of reward and punishment to solve the issue of nucleic acid testing supervision. The authors discuss the stability of equilibrium points under the four distinct strategies and conduct simulation experiments.FindingsThe authors find that the strategy of dynamic reward and static penalty outperforms the strategies of static reward and static penalty, dynamic reward and static penalty, static reward and dynamic penalty, dynamic reward and dynamic penalty. The results reveal the appropriate punishment for the negative act of the government can enhance the positivity of the government's supervision in the strategy of dynamic reward and static penalty, while the upper limit of the reward for nucleic acid testing institution of no data fraud cannot be too high. Otherwise, it will backfire. Another interesting and counterintuitive result is that in the strategy of dynamic reward and dynamic penalty, the upper limit of the penalty for data fraud of nucleic acid testing institution cannot be augmented recklessly. Otherwise, it will diminish the government's positivity for supervision.Originality/valueMost of the existing evolutionary game researches related to the reward and punishment mechanism and data fraud merely highlight that increasing the intensity of reward and punishment can help improve the government's supervision initiative and can minimize data fraud of nucleic acid institution, but they fall short of the boundary conditions for the punishment and reward mechanism. Previous literature only study the supervision of nucleic acid testing qualitatively and lacks quantitative research. Moreover, they do not depict the problem scenario of testing data fraud of nucleic acid institution regulated by the government via the evolutionary game model. Thus, this study effectively bridges these gaps. This research is universal and can be extended to other industries.

Decision models of emission reduction considering CSR under reward-penalty policy.

For the two emission reduction technologies of clean process (CT Mode) and end-of-pipe pollution control technology (ET Mode), this paper constructs production and low-carbon R&D decision-making models considering consumers' green preference, and discusses the impact of social responsibility on firm's decision-making, profit and social welfare. Then, the difference of optimal decision, profit and social welfare is analyzed when the firm adopt two emission reduction technologies with or without reward-penalty policy. The main conclusions of this paper are as follows: (1) Whether using clean process technology or end-of-pipe pollution control technology, consumers' green preference behavior can increase corporate profit. When consumers' green preference is small, consumers' green preference is negatively correlated with social welfare. When consumers' green preference is large, consumers' green preference is positively correlated with social welfare. (2) Corporate social responsibility is conducive to improving the level of social welfare, not conducive to the increase of corporate profits. (3) When the reward and punishment intensity is small, the reward-penalty policy cannot effectively motivate the firm to assume social responsibility. Only when the reward and punishment reaches a certain level, the mechanism can have an incentive effect on the firm, and the government can actively implement the mechanism. (4) When the market scale is small, the adoption of end-of-pipe pollution control technology is more beneficial to the firm; When the market scale is large, it is beneficial for the firm to adopt clean technology. (5) If the efficiency of end-of-pipe pollution control and emission reduction is much higher than that of clean process, the firm should choose end-of-pipe pollution control technology, otherwise choose clean process.

Multi-Agent Evolutionary Game Analysis of Group Panic Buying in China during the COVID-19 Pandemic

With the global outbreak of COVID-19, the panic-buying incidents triggered by the variants of the Omicron strain have severely affected the normal social order. This paper considers the complex interest game and interactive relationship among multiple subjects in the mass-panic buying event caused by rumors and constructs a three-party evolution game model of local government, rumor-monger, and public. The strategy-selection process of each subject based on evolutionary game theory is studied, and the strategy selection of three game subjects in different situations and related influencing factors are analyzed. Taking the example of the montmorillonite powder panic buying caused by the XBB virus strain rumor in China, the evolutionary game model constructed in this study is simulated and analyzed. The study shows that the evolutionary process of the mass panic-buying event is characterized by six stages: the initial stage; the outbreak stage; the spread stage; the climax stage; the relief stage; and the recovery stage. There are four stable points in the evolutionary game of the three game subjects, namely (no intervention, no rumor, no panic buying), (no intervention, rumor, no panic buying), (intervention, no rumor, no panic buying), and (intervention, rumor, no panic buying). The strategy of government intervention will be adjusted according to the strategy selection of the public and the rumor-monger. Under the mechanism of reward and punishment of the higher-level government, increasing the punishment and reward intensity of the higher-level government will promote the local government to intervene in the rumor-mongering event faster, but increasing the reward intensity has a more significant impact on the intervention behavior of the local government than punishment, and increasing punishment intensity has a more significant impact on the non-rumor-mongering behavior of the rumor-monger than reward. The parameters of social risk-bearing cost, risk transmission coefficient, rumor-mongering income and cost, and public drug purchase cost have different degrees of influence on the evolutionary behavior of game subjects. Therefore, this study provides new ideas for effectively responding to mass panic buying events in the context of public emergencies.