Punishment Mechanism Research Articles

Evolutionary game study on information nodes setting in supply chain tracing based on compensation mechanism

Consumption compensation is the driving force for motivating each supply chain link to set up information nodes, which is of great significance for promoting informatization, modernization, transformation, and upgrading of the supply chain system. This study simulates the evolution process of strategic selection for each supply chain link to set information nodes independently or collectively under the unconstrained government rewards conditions and punishments. The main conclusions are as follows: (1) When each link in the supply chain provides source tracing information independently, the vendor chooses to set up information nodes for the links with large information cost compensation coefficients. (2) When the vendor provides source tracing information cooperatively if the collaborative benefit is less than the cooperation cost, the information node will be set to the link with the large compensation coefficient. If not, information nodes will be set in each link. (3) Under the government incentive mechanism, enterprises are willing to cooperate. The punishment mechanism helps avoid situations where neither side sets up information nodes. The compensation coefficient is a prerequisite for mechanisms to work.

Circular economy practices in the waste electrical and electronic equipment (WEEE) industry: A systematic review and future research agendas

Circular economy is a sustainable economic development model. It replaces the traditional economic development model that relies heavily on resource consumption and waste generation. Circular economy is particularly important to the waste electrical and electronic equipment industry as e-waste contains toxic substances and precious metals. While previous review studies focused on specific aspects of the WEEE industry (e.g., “4R” circular economy strategies), these studies offer little details on how circular economy practices affect the development of the environment and economy in the waste electrical and electronic equipment industry. This study examines “10R” circular economy strategies to advance knowledge of the existing literature that focuses on “4R” circular economy strategies. To improve the methodology used in the previous review studies that apply subjective methods (e.g., content analysis), this paper conducts a systematic literature review on 208 studies and uses citation network analysis to examine specific circular economy practices in the waste electrical and electronic equipment industry. The citation network analysis identified five major research domains (i.e., “e-waste management systems and practices”, “e-waste legislation and its components”, “extended producer responsibility schemes”, “recycling critical materials from e-waste”, “circular economy strategies for the waste electrical and electronic equipment industry”). Based on these results, this study conducts a main path analysis to reveal ten major topics (i.e., e-waste recycling system; exploring untapped e-waste; compliance assurance of stakeholders; e-waste reverse logistics; reward and punishment mechanisms in extended producer responsibility system; verifying the rationality of product classification; recycling critical materials from urban mines; setting a specific target for preparation for reuse; “10R” strategies applied in the smart factory; consumer attitude toward remanufactured/refurbished/repurposed strategies and the resultant products) in the identified research domain. Finally, this paper proposes future research directions and provides managerial and policy implications for researchers and practitioners. • “10R” strategies for the waste electrical and electronic equipment industry. • Effect of circular economy practices on environmental and economic performance. • Related publications evolution characteristics in 2003–2020. • Five key research domains of circular economy practices and their major topics. • Research directions for future studies.

Detection and Prediction of FDI Attacks in IoT Systems via Hidden Markov Model

False data injection (FDI) attacks aim to threaten the security of Internet of Things (IoT) systems by falsifying a device's measurements without being detected. In this paper, we propose a process for detecting and predicting FDI attacks, which aims to predict future attacks before they occur and induce IoT devices to behave reliably. First, we propose a novel artificial intelligence (AI)-based detection and prediction module that uses a hidden Markov model (HMM) to observe the behavior of IoT devices and predict their future actions. Next, we design a distributed trust management module that establishes trust between devices using a set of weighted votes. To defend against FDI attacks in communication channels, we formulate a bandwidth optimization problem to meticulously allocate bandwidth to trusted devices. In addition, we propose an efficient incentive mechanism that uses reputation rewards to encourage trustworthy behavior and uses a punishment mechanism to neutralize malicious behavior. Simulations show that the proposed process outperforms recent benchmark FDI attack detection algorithms in the literature in terms of significantly improving attack detection accuracy and reducing attack detection latency.

Multi-stakeholders energy management and control method of integrated energy system considering carbon trading mechanism

With the proposal of global energy conservation and emission reduction policies, the scale of grid connection of Integrated Energy System (IES) is gradually increasing. How to formulate a carbon trading mechanism to guide the system’s carbon emissions and realize the operation of the system’s low-carbon economy has become the main problem to be solved urgently. Based on this background, this paper proposes a multi-stakeholders energy management and control method of IES considering carbon trading scheme. First, a dynamic multi-energy coupling energy flow model of electricity, heat and gas in IES is established. Second, carbon emissions are limited by introducing the carbon trading scheme with a punishment mechanism into the IES control mode. Finally, a hierarchical model is established based on the system trading framework, and energy flow management and the control model of IES under multi-stakeholders is established by quoting mixed game theory. A simulation example is given to verify that the proposed control method can make IES run in a low-carbon economy.

A Tripartite Evolutionary Game and Simulation Analysis of Transportation Carbon Emission Reduction across Regions under Government Reward and Punishment Mechanism

Pollution and carbon reduction is a key strategic direction for ecological civilization in China, and a hot issue of concern for the government and the whole society. The main goal of this paper was to consider the regional externalities of traffic emissions and clarify the relationship between provincial and central government strategies under the government reward and punishment mechanism. This paper considers the unevenness of regional transportation emissions, constructs a three-party evolutionary game model among transportation carbon deficit provinces, transportation carbon surplus provinces, and the central government, discusses the evolutionary stability of the game under different strategies of the three parties, and analyzes the influence of each element on the game structure. The study shows that: Environmental losses can increase the evolutionary speed of active emission reduction in transportation carbon deficit provinces, and the probability of supporting cross-regional carbon emission reduction in transportation carbon surplus provinces decreases slightly with the increase and the probability of central government regulation increases. The central government has a certain binding effect on transportation carbon deficit provinces and carbon surplus provinces through fines, and cross-zone cooperation subsidies are conducive to promoting carbon deficit provinces to actively reduce emissions. The cross-region compensation of carbon deficit provinces can promote the governments of carbon surplus provinces to support cross-region carbon emission abatement, and the cost of regulation will reduce the probability of central government regulation. Finally, Matlab simulation is used to verify the conclusions and provide countermeasures and suggestions for cross-regional abatement of regional transportation emissions by the central government.

Evolutionary Game of Knowledge Sharing in the Advanced Manufacturing Industry

With the advent of the era of knowledge economy, knowledge resources have gradually become the core resources for industrial development. For advanced manufacturing, strengthening the knowledge sharing between enterprises has become a key factor of the industry to maintain their core competitiveness. Based on the perspective of knowledge sharing, this study constructs an evolutionary game model among advanced manufacturing enterprises and analyzes the dynamic evolution process of enterprises. The result shows that knowledge spillover effects, excess return distribution, knowledge costs, hidden income, and punishment mechanisms are the main factors influencing the choice of evolutionary strategies for knowledge sharing among enterprises. Based on the analysis results, the study gives some suggestions to encourage advanced manufacturing companies to choose knowledge sharing strategies, to promote the rapid development of advanced manufacturing.

A Comparative Analysis of the Legislation on Maritime Militia Between China and Vietnam

In recent years, the maritime militia and their activities in the South China Sea have attracted mounting attention from the international community. To date, only China and Vietnam have established rules relating to maritime militia. The maritime militia systems in both China and Vietnam result from national traditional militia systems and are extended reflections of the “People’s War” ideology in the field of modern defense. They are similar in aspects such as their definitions and nature, type of activities and scope, and leadership. Also, both militias play an affiliated role in their protection of maritime rights and military systems. Nonetheless, there are distinct differences between the legislation of maritime militia in China and Vietnam, particularly in relation to the political role they play, welfare and treatment, and punishment mechanisms. Through the comparison of the legislation on maritime militia in China and Vietnam, this article aims to define the legal status of maritime militia and to propose approaches to improving China’s legislation on maritime militia.

Research on energy management strategy of heavy-duty fuel cell hybrid vehicles based on dueling-double-deep Q-network

Fuel cell hybrid vehicle (FCHV) is an effective way to improve emissions and fuel economy. Energy management strategy (EMS), as a core assignment of FCHV, its most significant challenge is to achieve a sensible trade-off between system degradation and hydrogen consumption with less computational cost under diverse environments. Although most strategies can employ finite-density discretization to approach the optimum solutions, it brings poor performance. Herein, an advanced dueling-double-deep Q-network (D3QN) EMS based on a deep reinforcement learning framework is developed to solve the challenges, which can process higher-dimensional space and output dominant actions for an agent to obtain higher cumulative rewards. By adopting a dueling neural network, a better policy is acquired via generalizing learning across actions in the presence of similar value-actions. Moreover, an evaluation mechanism of Allowable Approach Punishment is introduced into rewards to mitigate system degradation. Simulation experiments reveal the prominence of the D3QN algorithm. Results demonstrate D3QN achieves less hydrogen consumption and retards fuel cell degradation on the premise of meeting power balance. Furthermore, adaptability and robustness are verified. Outcomes show D3QN can not only adapt to complex surroundings but also overcome noise and instability. Finally, real-time applicability is validated via the HIL test-bench.

Evolutionary Game of Group Cooperation Institutions for Chaoshan Businessmen in Ming and Qing Dynasties

Chaoshan businessmen were widely involved in internal group cooperation. Based on historical and comparative institutional analysis, it is found that the cooperative behavior of Chaoshan businessmen in the Ming and Qing Dynasties is not simply an economic behavior. It reflects the historical evolution of the interaction between the regional cultures concerning the sea, clan and Confucianism, the governance of merchant groups with blood and geographical characteristics, and the beliefs of merchants in Mazu and Guan Yu. The evolutionary game theory is used to investigate the evolutionary process and the evolutionary stable strategy of the internal cooperative behavior of Chaoshan businessmen. It shows that due to the joint influence of regional culture, governance of merchant groups and beliefs of merchants, a multilateral collective punishment mechanism for untrustworthy merchants and a loss compensation mechanism for trustworthy merchants are established through channels such as chambers of commerce and ancestral temples. Thus, it reinforces the group cooperation institutions of integrity within Chaoshan merchant groups in the Ming and Qing Dynasties.

Stability Analysis of Low-Carbon Technology Innovation Cooperation under a Reward and Punishment Mechanism

In this study, we constructed a tripartite evolutionary game model for a large-scale enterprise (A), a small-scale enterprise (B), and a government, based on finite rationality and information asymmetry. First, we investigated and analyzed the stakeholders of low-carbon technology innovation (LCTI) and constructed a tripartite evolutionary game model. Then, we analyzed the conditions for the stability of different equilibrium points. Finally, we carried out numerical simulations using MATLAB 2020b to analyze the evolutionary processes and patterns of the different parameters. We found that the government’s strategic choice is always to participate in LCTI, which is conducive to a healthy LCTI environment. Governments can participate in LCTI consortiums through policy-driven reward and punishment mechanisms. Our simulation demonstrated that the size of enterprises influences their choice of LCTI strategy, and government reward and punishment mechanisms influence both large and small firms. Large firms are more prepared to accept the risks of LCTI and maintain a reciprocal LCTI strategy even in a high-cost scenario, while small firms are more sensitive to the costs and benefits. Thus, government reward and punishment mechanisms should take full account of small-scale enterprises. We propose a sound reward and punishment mechanism for LCTI that limits the opportunistic behavior of enterprises. Therefore, this paper is a complement to theories such as innovation systems and provides new thinking for low-carbon technology innovation cooperation of enterprises. Meanwhile, the reward and punishment mechanism proposed in this paper has important practical value for the government.

Exploring the driving mechanism of environmental mass incidents

Environmental mass incidents caused by pollution of enterprises seriously threaten the government's credibility and social stability. Thus, this paper tries to explore the driving mechanism of environmental mass incidents and to master critical factors for coping with it. Firstly, the spatial public goods game model on complex networks are applied to study the cooperation drive mechanism among individuals within the surrounding people. Secondly, a tripartite evolutionary game model including the government departments, polluting enterprises, and surrounding people is established to learn the complex conflict-of-interest relationships and behavior mechanism among them. Finally, the influence of key factors on system evolution is simulated. The results are as follows: In a complex network, individuals in the surrounding people work together for the common good. The driving factors of collective protest are common goal, strategic interaction, emotional contagion and the payoff of collective protest. The economic benefits related to environmental subsidies generated positive effect on surrounding people's collective action. In addition, the economic punishment mechanism of government departments has not shown influence on the strategic choices of surrounding people and polluting enterprises. Furthermore, the rectification burden of polluting enterprises and profit of collective protest are the key factors affecting the equilibrium of system evolution.

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.

A comprehensive analysis of package tour quality: A stochastic evolutionary game

This study sheds light on the shaping and evolution of package tour supply strategies by examining package tour quality variance under various information conditions using evolutionary game and stochastic processes. The findings indicate that demand elasticity is critical in package tours' quality when the market information is symmetric. In an asymmetric information tourism market, adverse selection and moral hazard are the primary causes of degraded package tour quality. This study develops a compound relief mechanism comprised of stratification, reputation, and punishment mechanisms to address issues with the quality of package tours. The compound relief mechanism can assist policymakers in developing practical market regulations and policies by providing a theoretical basis for package tour quality control.

From Neighbors to Partners: A quantum game model for analyzing collaborative environmental governance in China

Promoting the collaborative governance of regional environmental pollution is a key issue of the “14th Five-Year Plan” period of China, which has great significance in accelerating the construction of Chinese ecological civilization. Given this, this paper uses quantum game theory to analyze the interaction between two heterogeneous governments in environmental governance and to discuss the impact of heterogeneity difference of local governments on the game system. As an embodiment of the innovation of this paper, an interpretation of entanglement and quantum strategy under the context of environmental governance is presented, and the impact of the heterogeneity difference between local governments on the quantum game system is studied. The results show that the entanglement can effectively prevent the free-riding behavior of local governments, and the heterogeneity difference does not change the equilibrium of the quantum game. As a byproduct, this paper reveals the control effect of the combination of punishment mechanism and information disclosure mechanism on free-riding behavior to a certain extent. Finally, we construct the “Entanglement Agreement” of regional environmental collaborative governance according to the interpretation of entanglement and quantum strategy. In addition, it is an important guarantee for incentive enthusiasm of local governments to improve their governance capability. This study provides a quantitative basis and decision-making reference for promoting regional collaborative governance in China. The approach used in this paper can also be applied to similar situations in other countries or regions with suitable modifications.

Blockchain Rental Platform for College Students Driven by Reward and Punishment Mechanism

For those who are employed nowadays, the living environment largely affects the quality of work. In order to access employment opportunities in first-tier cities, renting an apartment has become a hot social issue for the new generation of youth, and therefore the development of the rental market has gradually become an important part of the economic development. In order to ensure the stable growth of China's market economy and a favorable employment environment for the new generation of Chinese talents, it is necessary to help the new youth group with insufficient social experience to avoid falling into the trap of rental agents and to match with suitable housing, this paper proposes a solution based on a blockchain rental platform driven by reward and punishment mechanisms for college students, focusing on the innovation of specific reward and punishment mechanisms, through the design of coin issuance mechanism, workload determination By designing key components such as coin issuance mechanism, workload determination mechanism, and reputation mechanism, combined with the design of personalized platform functional blocks for college students, the functional operation of this platform is envisioned based on smart contracts, which fills the gap of blockchain renting for college students as well as the refinement of reward mechanism of blockchain renting platform. This design can be applied to build a practical scenario of a blockchain rental platform serving college students and promote the process of upgrading and transforming the traditional rental industry using blockchain technology.

Marine Ecological Governance Under New Media Environment: Tripartite Evolutionary Game and Simulation Analysis

Based on the general reality that new media with massive information and strong interactivity play an increasingly prominent role in marine ecological governance, this study introduces the coastal public participation mechanism under the new media environment. Furthermore, based on the assumption of limited rationality, an evolutionary game model among local governments, marine enterprises, and the coastal public is constructed to explore the changes in game strategies among the three participating subjects over time. Then, we used MATLAB to simulate and analyze the evolutionary stabilization strategies under different parameters by combining our research data on governments at all levels, marine enterprises, and the coastal public in 14 cities in coastal areas of China. The study shows that: 1) an objective and a fair new media environment exert a positive guiding effect on marine ecological governance, whereas a false and distorted one will lead to chaos in marine ecological governance. 2) Considering the high accuracy of new media reports, the higher the sensitivity of the local governments and marine enterprises to media reports, the more inclined they are toward strong regulation and active governance. 3) The local governments can effectively restrain the marine hazard behavior of the marine enterprises by increasing penalties and environmental protection taxes, and it is equally important to guide marine enterprises to fully utilize high and new technology in the marine industry for improving economic benefits and reducing governance costs. 4) Coastal public participation can effectively compensate for the local governments’ regulatory loopholes and can reduce the cost of government regulation. Therefore, for ensuring objective reports of new media by establishing reward and punishment mechanisms and regularly selecting excellent new media, using new media to enhance the level of marine publicity and education to encourage the coastal public to widely and fully participate in marine ecological governance is an effective means.

Impacts of special cooperation strategy with reward and punishment mechanism on cooperation evolution

This paper introduces a special cooperation strategy with both punishment and reward capabilities and analyzes the effect of this strategy on cooperation evolution. The results show that the evolutionary stable states include full defection, the coexistence of ordinary cooperators and defectors, the coexistence of special cooperators and defectors, the coexistence of special cooperators and ordinary cooperators, and the coexistence of the three strategies. Punishment can induce cooperation. Under moderate punishment, the greater the reward the more conducive to cooperation, while under larger punishment, higher rewards conversely weaken the facilitative effect on cooperation. As the temptation increases, ordinary cooperators decrease to zero, while special cooperators increase first and start to decrease or even die out when the ordinary cooperators disappear. The coexistence of the three strategies presents that the ordinary cooperator group is exploited by the defectors, the special cooperator group is invaded by the ordinary cooperators, and the defector group is suppressed by the special cooperators, making the three strategies mutually suppressive and interdependent, and ultimately stable coexistence. The presence of special cooperators significantly promotes cooperation evolution in systems. This contributes to a better understanding of the origins and transformations of social norms and institutions.

News headline generation based on improved decoder from transformer

Most of the news headline generation models that use the sequence-to-sequence model or recurrent network have two shortcomings: the lack of parallel ability of the model and easily repeated generation of words. It is difficult to select the important words in news and reproduce these expressions, resulting in the headline that inaccurately summarizes the news. In this work, we propose a TD-NHG model, which stands for news headline generation based on an improved decoder from the transformer. The TD-NHG uses masked multi-head self-attention to learn the feature information of different representation subspaces of news texts and uses decoding selection strategy of top-k, top-p, and punishment mechanisms (repetition-penalty) in the decoding stage. We conducted a comparative experiment on the LCSTS dataset and CSTS dataset. Rouge-1, Rouge-2, and Rouge-L on the LCSTS dataset and CSTS dataset are 31.28/38.73, 12.68/24.97, and 28.31/37.47, respectively. The experimental results demonstrate that the proposed method can improve the accuracy and diversity of news headlines.

Evolutionary Game Analysis of Shared Manufacturing Quality Synergy under Dynamic Reward and Punishment Mechanism

Quality improvement is crucial for manufacturing, and existing research has paid less attention to the influence of regulatory factors and irrational factors of decision makers. Considering the impact of the reward and punishment strategy of the shared platform on quality decision-making, this paper introduces prospect theory and mental account theory into the process of multi-agent evolutionary game of shared manufacturing, constructs a co-evolutionary game model of shared manufacturing quality synergistic improvement under the dynamic reward and punishment mechanism, and analyzes the dynamic evolution law of each game agent. The research results show that: (1) The synergistic improvement of shared manufacturing quality is the consequence of the combined action of numerous interrelated and interacting factors, rather than the linear effect of a single element. (2) Although the combination of multiple incentive and punishment methods can significantly alter the effect of shared manufacturing quality synergy, there are certain effectiveness gaps. (3) The subsidy mechanism can effectively compensate for the effectiveness gap of the reward and punishment mechanism, and it can also strengthen the internal driving force of shared manufacturing quality coordination. The main management insights are as follows: (1) Consider strong external regulation to be the framework constraint, and positive internal control to be the detail specification. (2) Create a reliable reward and punishment mechanism and dynamically alter the intensity of rewards and penalties. (3) To close the effectiveness gap, strengthen the subsidy mechanism as an essential addition to the incentive and punishment mechanisms. This study can give a new reference path for quality improvement of shared manufacturing, allowing shared manufacturing to play a more constructive role in supporting the transformation and development of the manufacturing industry.

FAWPA: A FAW Attack Protection Algorithm Based on the Behavior of Blockchain Miners.

Blockchain has become one of the key techniques for the security of the industrial internet. However, the blockchain is vulnerable to FAW (Fork after Withholding) attacks. To protect the industrial internet from FAW attacks, this paper proposes a novel FAW attack protection algorithm (FAWPA) based on the behavior of blockchain miners. Firstly, FAWPA performs miner data preprocessing based on the behavior of the miners. Then, FAWPA proposes a behavioral reward and punishment mechanism and a credit scoring model to obtain cumulative credit value with the processed data. Moreover, we propose a miner’s credit classification mechanism based on fuzzy C-means (FCM), which combines the improved Aquila optimizer (AO) with strong solving ability. That is, FAWPA combines the miner’s accumulated credit value and multiple attack features as the basis for classification, and optimizes cluster center selection by simulating Aquila’s predation behavior. It can improve the solution update mechanism in different optimization stages. FAWPA can realize the rapid classification of miners’ credit levels by improving the speed of identifying malicious miners. To evaluate the protective effect of the target mining pool, FAWPA finally establishes a mining pool and miner revenue model under FAW attack. The simulation results show that FAWPA can thoroughly and efficiently detect malicious miners in the target mining pool. FAWPA also improves the recall rate and precision rate of malicious miner detection, and it improves the cumulative revenue of the target mining pool. The proposed algorithm performs better than ND, RSCM, AWRS, and ICRDS.