Intensity Of Punishment Research Articles

Facilitating the evolution of cooperation through altruistic punishment with adaptive feedback

The stability and persistence of cooperation are often threatened by the selfish behavior of self-interested individuals. One possible solution to this problem is to punish self-interested individuals. However, previous research always assumes that the strength of punishment is constant and independent of the game environment, which does not align with many real-world situations. Hence, it remains unclear whether altruistic punishment strategy with adaptive feedback can promote the evolution of cooperation effectively. Here we introduce the punishment strategy with adaptive feedback into the public goods game and develop a coevolutionary game model where the strength of punishment is dynamically adjusted based on the level of cooperation in a population. We adopt a linear feedback form to characterize the impact of strategies on punishment intensity. Through theoretical analysis and numerical calculations, we identify an evolutionary oscillation dynamics, in which the system cycle between high-intensity and low-intensity punishment, as well as cooperation and defection behaviors. Furthermore, we find that a high level of cooperation can be sustained with the use of only a low-intensity punishment.

Evolution Game and Simulation Analysis of Disturbance Emergency Disposal of In-Flight Cabin: China Civil Aviation Security Strategy Study

The disturbance of disruptive passengers in the cabin seriously affects aviation security in China. Reducing the occurrence of disturbances in the cabin is an inevitable choice to strengthen the security of civil aviation in China and improve the emergency disposal of airlines. Therefore, this paper investigates the strength of government support, the benefits of cooperation and the punishment of disposers, and uses the event tree method to analyze the relevant subjects affecting the consequences of cabin disruptions. To this end, a cabin disturbance emergency management game model comprised of regulatory authority, airline security and disruptive passengers was then established. The results of the game playing and simulation highlight the inherent relationships in emergency management in China’s civil aviation. First, the choice of behavior of the regulatory authority and disruptive passengers are mainly influenced by the strategy of airline security. Second, the strength of support from the regulatory authority determines whether the airline security can dispose of the passengers successfully. Third, the disruptive inclination of disruptive passengers is directly influenced by the intensity of punishment by airport police. Finally, an empirical analysis and simulation is conducted with the example of using an open flame or smoking in the cabin. This study provides new ideas for enhancing aviation security and improving emergency management.

Evolution of cooperation driven by sampling punishment

Punishment is a key incentive to maintain cooperation. But it is costly, hence its effectiveness is under permanent debate. To overcome this difficulty, we here introduce a sampling punishment method and explore its consequences on public goods game and collective-risk social dilemma. In our model, just a small portion of participants are sampled and defectors are punished only if their portion exceeds a certain threshold. We show that the cooperation level can be effectively improved under low punishment threshold and small sample size when the punishment intensity is considerable. To identify the optimal conditions of sampling punishment, we monitor the punishment probability and related cost. We find that the adoption of a low punishment threshold and a small sample size under a considerable punishment intensity is the best, which always leads to a high cooperation level with a low related cost. Our observations are both valid in these two games.

A Tripartite Evolutionary Game Analysis of Participant Decision-Making Behavior in Mobile Crowdsourcing

With the rapid development of the Internet of Things and the popularity of numerous sensing devices, Mobile crowdsourcing (MCS) has become a paradigm for collecting sensing data and solving problems. However, most early studies focused on schemes of incentive mechanisms, task allocation and data quality control, which did not consider the influence and restriction of different behavioral strategies of stakeholders on the behaviors of other participants, and rarely applied dynamic system theory to analysis of participant behavior in mobile crowdsourcing. In this paper, we first propose a tripartite evolutionary game model of crowdsourcing workers, crowdsourcing platforms and task requesters. Secondly, we focus on the evolutionary stability strategies and evolutionary trends of different participants, as well as the influential factors, such as participants’ irrational personality, conflict of interest, punishment intensity, technical level and awareness of rights protection, to analyze the influence of different behavioral strategies on other participants. Thirdly, we verify the stability of the equilibrium point of the tripartite game system through simulation experiments. Finally, we summarize our work and provide related recommendations for governing agencies and different stakeholders to facilitate the continuous operation of the mobile crowdsourcing market and maximize social welfare.

The coordination of collective and individual solutions in risk-resistant scenarios.

Human societies are constantly coping with global risks. In the face of these risks, people typically have two options, that is, to respond together as a whole (collective solution) or to respond independently (individual solution). Based on these two solutions, individuals have a variety of behavioral strategies. On the other hand, various regulatory bodies supported by the population limit people's choices and punish individuals who do not contribute to collective solutions. So with different risks, how do the two solutions, the various individual strategies, and the constraints from regulators affect the group's response to risk? This paper proposes an extended public goods game model involving opportunists and the regulator to explore the effectiveness of collective and individual solutions against risks. The results show that requiring individuals to invest more in the collective solution reduces the group' s success in resisting risk. To improve the group's ability to resist risk, investment in individual solution should be at least no less than that in collective solution. The establishment fund and punishment intensity of the regulatory agency have no significant effect on the success of collective and individual solutions. This inspires us to contemplate the role and measures of various types of authorities in coping with global risks.

Evolutionary game analysis of low-carbon technology innovation diffusion under PPP mode in China.

With the Public-Private Partnership (PPP) mode playing an increasingly important role in the investment of infrastructure, promoting the diffusion of low-carbon technology innovation in PPP projects not only helps to reduce the carbon emissions of infrastructure, but also plays an important demonstration role in the low-carbon transformation of construction industry. In order to clarify the evolutionary mechanism of low-carbon technology innovation diffusion among stakeholders under the unique payment mechanism of PPP projects in China, the paper builds two different evolutionary game models respectively under government payment mechanism and consumer payment mechanism based on evolutionary game theory. The evolutionary relationship between the choice of behavior strategies and the change of influencing factors under different payment mechanisms are analyzed by numerical simulation. It is found that under government payment mechanism, the regulation cost of government to promote low-carbon technology innovation and the punishment of the superior regulatory authority for non-regulation behavior are the important factors affecting government's behavioral strategies. The low-carbon technology innovation cost of social capital and the intensity of government subsidy and punishment are the main factors affecting social capital's behavioral strategies; Under consumer payment mechanism, consumer becomes the ultimate payer of low-carbon products, and the income they get from purchasing low-carbon products and the subsidy provided by the government become the main factors determining consumer's behavioral strategies. Finally, from the perspective of government, social capital and consumer, countermeasures and management implications are put forward to effectively promote the diffusion of low-carbon technology innovation under different payment mechanism in PPP projects.

Influence of the Government Department on the Production Capacity Reserve of Emergency Enterprises Based on Multi-Scenario Evolutionary Game

With the frequent occurrence of world emergency events, the emergency management of government departments in various countries is facing great challenges. In the context of the COVID-19 pandemic, the shortage of various emergency resources is prominent, and the emergency supplies reserve combined by governments and enterprises is an important guarantee for dealing with emergency management problems. This paper mainly studies the impact of a government sustainability-oriented innovation policy on the production capacity reserve of security emergency enterprises (SEEs), and constructs an evolutionary game model between the local government and SEEs. Then, it focuses on the impact of a reputation mechanism on the government enterprise cooperative reserve. According to the condition of a country, the central government’s punishment mechanism is introduced, and the evolutionary and stable strategies of the behavior choices of the local government and SEEs are compared and analyzed. Combined with the evolution degree of emergency events, the numerical simulation analysis is used to deduce and simulate the multi scenario of the example model. The results show that the reputation mechanism can effectively promote the evolution of government and enterprises to the ideal state under various scenarios. When the punishment intensity of the central government is higher than the total benefit of the implementation of the mere formality policy by the local government, it can effectively prevent the omission of the local government. This study provides a new idea for the government to formulate reasonable policies to promote SEEs to reserve production capacity, which is more conducive to government enterprise cooperation to deal with emergency events.

Reputation-based probabilistic punishment on the evolution of cooperation in the spatial public goods game

Low-reputation defectors are more likely to be punished than defectors with high reputations. Motivated by this reality, this paper proposes a new mechanism, the reputation-based probabilistic punishment, into the spatial public goods game model. In this mechanism, players with time-dependent reputations are divided into two types, good players with reputations higher than the reputation threshold and bad players with reputations lower than the threshold. A defector considered a good player is less likely to be punished than a defector considered a bad player. Based on these assumptions, we systematically explore how this mechanism influences the evolution of cooperation. Through extensive simulations, we verify that a higher value of the reputation threshold is more conducive to promoting and maintaining cooperation. Moreover, increasing the cost of being punished could effectively encourage players to take cooperative behaviors. Simulation results show that both increasing the punishment intensity and increasing the punishment fine could increase the cost of being punished and are beneficial to the promotion of cooperation. Additionally, in the structured population, the distributions of strategies, reputation, and payoff in the evolutionary stable state are mainly present in the form of clusters.

Dynamic Analysis and Optimal Control of Rumor Propagation Model with Reporting Effect

Media reports and the number of rumors in the media have an important impact on the spread of rumors. Currently, studies that consider these two factors comprehensively on rumor propagation are uncommon. It is better to consider both effects comprehensively than to consider one of them alone. In this paper, we established a new propagation model, which regards the number of rumors in the media as a subclass that changes with time, and then comprehensively considered the effect of these two factors on the process of rumor propagation. We proved the existence and stability of equilibrium points of the model. Then, we selected two reasonable control variables: science popularization intensity and punishment intensity. We find that the control effects are optimal when these two control variables take the maximum value. Theoretical analysis and numerical simulation results showed that positive media publicity can reduce the spread of rumors, but cannot stop the spread of rumors. And under the parameters given in this paper, the optimal control parameter values satisfying the constraints can be calculated through quantitative analysis. This method provided a new idea for studying the optimal control of rumor propagation.

Negative Feedback Punishment Approach Helps Sanctioning Institutions Achieve Stable, Time-Saving and Low-Cost Performances

Sanctioning institutions widely exist in human society. Although these institutions play an important role in the management of social affairs, sanctions are often seen to be costly in terms of both time and money. To enable sanctioning institutions to develop effective sanctions, we propose a negative feedback punishment approach for these institutions that combines the feedback control principle and the negative correlation principle. In the negative feedback punishment approach, the punishment intensity imposed on the group is negatively correlated with the current group cooperation proportion. Through evolutionary simulation and theoretical analysis, we found that the negative feedback punishment approach facilitates more stable, time-saving and low-cost performance by sanctioning institutions than other punishment methods. This work offers a feasible solution for sanctioning institutions to solve social dilemmas and provides a possible theoretical starting point for investigating effective pool punishment measures.

How Does the Government Promote the Collaborative Innovation of Green Building Projects? An Evolutionary Game Perspective

In order to study how to promote the collaborative innovation of green building projects of construction enterprises, this paper establishes an evolutionary game model of suppliers’ participation in collaborative innovation of green building projects of construction enterprises under government governance. Through a numerical simulation, our research analyzes the influence of government tax preference, government infrastructure construction, and environmental pollution punishment on the behavior of the government, suppliers, and construction enterprises. The empirical research shows that the government’s tax incentives will continue to encourage suppliers to choose collaborative innovation. If the government’s short-term tax incentives are small, construction enterprises will evolve in the direction of midway betrayal. When the government’s long-term tax incentives are large, construction enterprises will evolve in the direction of the collaborative innovation of green building projects. Furthermore, the government’s infrastructure support for suppliers to participate in collaborative innovation of green building projects of construction enterprises will encourage suppliers and construction enterprises to choose green building projects for collaborative innovation. With the continuous maturity of green building projects in the construction market, the government has evolved from positive governance to negative governance. The government will take the opportunity to give up infrastructure construction and turn to other supporting policies. Lastly, a low intensity of environmental pollution punishment makes it difficult to promote the construction enterprises to evolve in the direction of collaborative innovation. A moderate intensity of environmental pollution punishment can encourage construction enterprises to evolve in the direction of collaborative innovation, while high-intensity environmental pollution punishment can encourage construction enterprises to choose the direction of midway betrayal. Environmental pollution punishment has no significant impact on suppliers’ selection of collaborative innovation of green building projects in the short term.

Evolutionary Game Analysis between Local Government and Enterprises on Bridge Employment from the Perspective of Dynamic Incentive and Punishment

The popularization of bridge employment is conducive to the realization of active aging, which requires not only the subjective initiative of retirees but also the active cooperation of local governments and relevant enterprises. This study combined evolutionary game theory with system dynamics to model and simulate the behavior of local government and enterprises on bridge employment, aiming to highlight the importance of government behavior and enterprise actions in the process of active aging and to analyze the effectiveness of different incentive and punishment mechanisms in promoting bridge employment. Results show that the system with dynamic incentive and punishment is easier to keep stable than the system with static incentive and punishment; specifically, the dynamic mechanism with low incentive intensity and high punishment intensity is better than other mechanisms. Finally, this study emphasized the importance of government policy to bridge employment and put forward relevant management implications.

Evolution of trust in a hierarchical population with punishing investors

Trust plays an essential role in the development of human society. According to the standard trust game, an investor decides whether to keep or transfer a certain portion of initial stake to a trustee. In the latter case, the stake is enhanced to signal the value of trust. The trustee then chooses how much to return to the investor. We here distinguish two types of investors and two types of trustees who can learn from each other. While a trustee can be trustworthy or untrustworthy, an investor could be normal or punishing one. The latter strategy punishes both untrustworthy trustees and normal investors who are reluctant to control misbehaving trustees. Importantly, we assume a hierarchical population where the portion of investors and trustees is fixed. By means of replicator equation approach, we study the N-player trust game and calculate the level of trust and trustworthiness. We find that the introduction of punishment can induce a stable coexistence state between punishing investors and trustworthy trustees. Furthermore, an intermediate fraction of investors can better promote the evolution of trust when the punishment intensity is low. For more intensive punishment, however, a higher fraction of investors can be more efficient to elevate the trust level. In addition, we reveal that appropriate increase of the punishment intensity can enlarge the attraction domain of the coexistence state.

Personality Difference and Strong-Strong Coalition—Experimental Research Based on Punishment Mechanism

Research on social value orientation divides rational people into three categories: individualist, pro-social, and competitor. This kind of research does not focus on network structure. Network exchange theory emphasizes that power comes from an exclusive structure, but it ignores the personality characteristics of people. This paper combines these two studies to explore how punishment mechanisms affect individual coalition strategies in an exclusive structure. The experimental results prove that: (1) when the strong is not in the coalition, there is no significant difference in the benefits of the strong power individualist person and the strong power pro-social person; (2) when two people with different social value orientations are strong-strong coalition, the two will form a “betrayal chain” whose benefit is close to the equilibrium value of the “compromise chain”. The strong power individualists are more likely to “betray” and “take advantage” more than the strong power pro-socialists; (3) the intensity of punishment is inversely related to the frequency of “betrayer”. Analysis of the dialogue data revealed that (4) the strong will properly take care of the weak, and the weak will “approach” the strong; (5) heavy punishment will have a deterrent effect, allowing the actors, especially pro-social to internalize the “punishment mechanism”. This study incorporates both personality and structure into the model, and such studies can explain many power phenomena.

Evolutionary game study on the governance and development of online car-hailing based on blockchain technology

Changes in the online car-hailing industry have brought new challenges to government governance. Effectively enhancing governance efficiency has become the focus of academic research. Based on the technical governance perspective, this paper introduces the consortium blockchain to construct an evolutionary game model between the online car-hailing platform and the government under blockchain technology. By solving the replicated dynamic equations and the Jacobian matrix, the influences of the change in initial conditions and decision parameters on the evolutionary stability results are revealed, and numerical experiments are carried out by using the Python programming language. This paper claims that the system presents three evolutionary stable results and a periodic stochastic state when the key parameters are located in different thresholds. The additional cost of the platform’s negative regulation and the government’s punishment intensity have a positive effect on the evolution of the system to the ideal state (active regulation, active governance). Platform technology R&D cost and government innovation input have a negative effect on the evolution of the system to the ideal state. Therefore, using blockchain to increase the additional cost of the platform’s negative regulation, appropriately increasing the government’s punishment intensity, reasonably controlling the government’s innovation input to the platform, and reducing the technology R&D cost of the platform will help the system evolve into an ideal state. This paper provides useful references to implement effective governance and the innovative and healthy development of the online car-hailing industry.

A dynamic game model for the study of food safety regulation based on sampling probability and penalty intensity

ABSTRACT By constructing a dynamic game model, this article explores the ‘optimal regulation’ and the food safety regulatory mechanism to be adopted when the food safety regulatory authority has to implement a certain level of regulation. In the short term, the actual quality of food can be improved by increasing the probability of sampling or the intensity of punishment. However, in the long term, the optimal path is to improve the production technology of sellers. A moderate level of supervision makes regulation more effective, while a threshold level of regulation can reduce welfare.

Supervision for the Public Health Services for Older Adults Under the Background of Government Purchasing: An Evolutionary Game Analysis Framework.

As an important measure to involve services for older adults, the government procurement practices have become a key link for public health services. However, the information asymmetry between public health service purchasers and public health service undertakers triggers a supervision dilemma. Based on this background, this study uses the evolutionary game theory to analyze the symbiotic evolution between local governments and public health service institutions under different reward and punishment mechanisms, explore game evolution, strategy adjustment, and influencing factors of different game subjects, and analyze the necessity and appropriate intensity of dynamic rewards and punishment mechanisms. The results show that: under the static condition, the penalty can change the strategies of local governments to a certain extent, but it is still difficult to achieve complete self-discipline management of public health service institutions. If local governments implement a dynamic reward or penalty mechanism in the supervision process of public health services for older adults, the equilibrium between them tends to be evolutionary stable. For three dynamic mechanisms, a dynamic reward mechanism is more conducive to adopting a self-discipline behavior of public health service institutions, which is helpful to realize the supervision of public health services for older adults. Also, there is a positive correlation between the proportion of public health service institutions who adopt a “self-discipline behavior” strategy and the maximum punishment intensity, and a negative correlation with the reward intensity. This study provides theoretical and decision-making references for governments to explore the promotion and implementation of public health services in older adults.

Effects of repeated exposure to escalating versus constant punishment intensity on response allocation.

The present experiment investigated the effects of 1) repeated exposures to escalating punishment intensities and 2) repeated exposure to punishment after periods of vacation on response allocation between punished and unpunished responding in three groups of rats. The first group (intensity + vacation) experienced repeated exposures to escalating punishment intensities after a period of vacation (i.e., return to baseline) from punishment. The second group (intensity-only) experienced repeated exposures to escalating punishment intensities without vacation from punishment. The third group (vacation-only) experienced repeated exposures to a constant punishment intensity after a period of vacation from punishment. Results showed that superimposition of punishment on one of two concurrently available responses decreased allocation toward the punished response and increased allocation toward the unpunished response. Furthermore, greater changes in allocation were observed with the introduction of a moderate constant intensity than with the introduction of a low intensity that increased across sessions. Reexposure to punishment had different effects between the groups. Although there was evidence that high shock intensities can enhance the efficacy of lower intensities to shift allocation away from the punished response and toward the unpunished response, there was little evidence of changes in response allocation with reintroduction of punishment after a period of vacation.

Impact of pollution-related punitive measures on the adoption of cleaner production technology: Simulation based on an evolutionary game model

China has recently implemented strict punitive measures on the polluting behavior of enterprises. These measures have had immediate benefits, but their long-term effects remain unknown. This study determined the potential impact of punitive measures on the clean transition behavior of enterprises under different policy scenarios in order to explore a framework for optimizing punitive measures. We built a network-based evolutionary game model to simulate the group behavior of enterprises regarding their adoption of cleaner production technology (CPT). The model is multi-dimensional and considers punitive measures by introducing three key attributes: intensity, coverage, and accuracy. The results indicate that enhancing the intensity and coverage of punishment can promote the diffusion of CPT in enterprises. However, it will reduce the average revenue of such enterprises, with adverse effects on economic development. By contrast, improving the accuracy of punitive measures will promote the diffusion of CPT without negative effects on revenue. Moreover, improving accuracy alongside the other two attributes conjointly will help to enlarge the comprehensive benefits. Therefore, we argue that the short-term performance and long-term benefits of clean transition should be considered when designing punitive measures, while the optimization of attribute parameters is crucial.

Tight-Loose Culture: A Compass for Social Norms

Tight-loose culture gives a new interpretation to cross-cultural differences by focusing on external social norms and punishment intensity. Culture exists in social norms which are an important factor to further guide human behavior. This paper mainly discusses the definition and theory of tight-loose culture, as well as the cutting-edge research results of tight-loose culture and socialization, organizational culture, personality, subjective well-being, prejudice and COVID-19, in order to provide some references for future research.