Punishment Mechanism Research Articles

Analysis of Enterprise Data-Driven Innovation Diffusion Supervision System Based on the Perspective of Green Supply Chain

To promote the market substitution of digital innovation technology and green products and alleviate the pressure of energy and environment, a three-party evolutionary game model of innovation diffusion based on core manufacturers, affiliated enterprises and the government is established in the article to explore the adjustment of the three-party game strategy of core manufacturers and affiliated enterprises under government supervision, and then analyze the optimal stability conditions that are conducive to the innovation diffusion of digital innovation technology. It is found that the core manufacturers would choose the diffusion strategy of digital innovation technology, which would take the initiative to adopt the diffused digital innovation technology due to cost considerations, without easily choosing independent research and development (hereafter R&D strategy); the reward and punishment mechanism made by the government for core manufacturers' digital innovation technology diffusion could effectively promote technology diffusion in the market.

Cashless Payment System Model at the Ministry of Cooperatives and Small and Medium Enterprises

To encourage the creation of effective and efficient APBN implementation, widely known by the public, and accountable, the payment mechanism in the APBN implementation process must be simplified but modern with the use of information technology that is increasingly optimal. One of the efforts made is to change shopping behavior, especially related to the use of the Money Supply mechanism which gradually shifts from fully using cash funds to cashless systems through the implementation of digital payments such as Government Credit Cards (KKP) and Cash Management System Virtual Accounts (CMS VA). This study aims to explore the factors that cause the low implementation of Cashless payment systems in the form of KKP and CMS VA within the Ministry of Cooperatives and SMEs, and find a model that can optimize it. Researchers use a qualitative approach with the case study method because they try to focus intensively on a particular object that studies it as a case, and cannot be generalized because the results of this study only apply to the case being studied. The results of this study show that leadership commitment is the factor that most influences the implementation of the cashless payment system, and also determines the influence of other factors such as human resource factors, the availability of SOPs, reward and punishment mechanisms, and the involvement of the Bank in the use of KKP and CMS VA. Satker must synergize with other parties so that in every stage of implementation starting from the signing stage of cooperation between Satker and the Bank, issuance and delivery of instruments, use transactions and accountability, until the supervision and monitoring evaluation stage can run better so that it can have an optimal impact on the implementation of Cashless payment systems within the Ministry of Cooperatives and SMEs

Sectarianism as racism: the collective punishment of Alevi communities in Turkey

Drawing on the case of state-sanctioned violence and discrimination against Alevis, a historically stigmatised and persecuted ethnosectarian community in Turkey, this article shows that sectarian identities can also be raced. The case of Alevis in Turkey not only indicates how sectarianism can function as a form of racism but also offers an example of the connection between the production of race and the politics of death. Approaching racism as a punitive mechanism and form of collective punishment that punishes racialised communities at different levels and that constantly reminds them of the possibility of what Gilmore terms ‘premature death’, the article offers a new and nuanced understanding of the multiple modalities of racism in Turkey. Rather than viewing racism in Turkey as merely an imitative form of European racism, this article shows that racism in Turkey is also informed by the country’s own imperial past. Turkey provides fertile ground for examining both western and non-western forms of racism and the intersections between the two.

The Impact of Information Asymmetry on Investment Behavior in the Stock Market

The stock market is the main component of the capital market and plays an important role in promoting the development of the national economy. Information asymmetry, as a typical issue in China’s stock market, triggers stock price fluctuations, increases stock market risks and largely influences investors’ investment behavior in stock market. Therefore, improving the information asymmetry problem is of great significance for the stable development of the stock market. This paper depends on the nature of information asymmetry, explores its specific manifestation in the stock market, and then analyses the process of information asymmetry issues on investment behavior. Studies indicate that information asymmetry leads to misdirected investment from three aspects, which include judgment on individual stock, assessment of the market value of the company and expectations of stock market developments, resulting in investor losses. Based on the above conclusions, this paper puts forward recommendations for improvement in terms of market regulation and the legal system: to improve the transparency of stock market transactions through the disclosure of information by regulators and companies. To complete the legislation of the stock market and establish strict punishment mechanisms to ease the problem of asymmetric information and maintain the stable operation of the stock market.

Evaluation of prescription review and feedback policy on rational antibiotic use in primary healthcare settings in Beijing, China: a qualitative study using the Theoretical Domains Framework and the behaviour change wheel.

To decelerate antibiotic resistance driven by inappropriate antibiotic prescribing, a prescription review and feedback (PRF) policy is implemented in primary healthcare institutions (PHIs) in Beijing, China. However, evaluation of PRF implementation in PHIs is scarce. This study aims to systematically identify the barriers and facilitators of PRF policy implementation to provide evidence for antimicrobial stewardship. We conducted key informant interviews with 40 stakeholders engaged in the implementation of PRF in Beijing, including physicians, pharmacists and administrators. Interviews were audio recorded and transcribed verbatim. We coded the interview transcripts and mapped informant views to domains of the Theoretical Domains Framework. We then used a behaviour change wheel to suggest possible behavioural interventions. Procedural knowledge (Knowledge) and skills (Skill) of PRF were possessed by stakeholders. They felt responsible to promote the appropriate use of antibiotics (Social/professional role and identity) and believed that PRF could help to change inappropriate provider behaviours (Behavioural regulation) in prescribing antibiotics (Beliefs about consequences) under increased intention on antibiotic use (Stages of change). Moreover, informants called for a more unified review standard to enhance PRF implementation (Goals). Frequently identified barriers to PRF included inadequate capacity (Skill), using punishment mechanism (Behaviour regulation), reaching consistently lower antibiotic prescription rates (Goals), lack of resources (Environmental context and resources) and perceived pressure coming from patients (Social influences). Stakeholders believed that PRF implementation promoted the rational use of antibiotics at PHIs in Beijing. Still, PRF was hampered by inconsistencies in review process and resources needed for PRF implementation.

Ternary interaction evolutionary game of rumor and anti-rumor propagation under government reward and punishment mechanism

Ternary interaction evolutionary game of rumor and anti-rumor propagation under government reward and punishment mechanism

Inspiration or perspiration: Diffusion of China's low-carbon city pilot policies nationwide

Low-carbon city pilot policy is critical for building a responsible government and achieving modernized urban governance in China. To further promote the full implementation of low-carbon city pilot policy, it is highly necessary to clarify the spatial-temporal diffusion process and influencing mechanism of the pilot policy. By taking 277 cities at the prefecture level and above as examples, this study introduces the perspective of dynamic process, and proposes the theoretical hypothesis of policy diffusion based on the analytical framework of “demand driving-pressure response-efficiency measurement”. The results demonstrate that 1) the diffusion of low-carbon city policy in China temporally shows an overall upward trend, but policy diffusion block, deviation, and variation are likely to occur during the process, and it spatially shows obvious adjacency effect, ripple effect, and hierarchical characteristics. 2) The logic for the “demand driving-pressure response-efficiency measurement” analytical framework has an important impact on the diffusion of low-carbon city pilot policies. Among them, the level of science and technology investment has a greater impact on the pilot policies of low-carbon cities. On average, each percentage of increase in the level of science and technology investment will increase the advantage for cities in adopting low-carbon policies by 404788.3%. 3) In the analysis of different stages and regions, each logical variable affects the adoption of low-carbon policies to varying degrees. In terms of different stages, the pressure response logical variable and efficiency consideration logical variable have the most and least significant effect on the adoption of low-carbon policies, respectively. In terms of different regions, the demand driven logic and pressure response logic variables have a greater impact on the central and western regions than on the eastern region. Here, we propose the following suggestions: for cities with different actual needs, the central and local governments should correctly grasp the time node of low-carbon city pilot according to local conditions; it is necessary to reconstruct the assessment system of low-carbon policies, and establish a policy reward and punishment mechanism of combining leniency and tightness in different regions; and pilot cities should establish practical programs with operability and implementation value.

Intelligent Hierarchical Admission Control for Low-Earth Orbit Satellites Based on Deep Reinforcement Learning.

Low-Earth orbit (LEO) satellites have limited on-board resources, user terminals are unevenly distributed in the constantly changing coverage area, and the service requirements vary significantly. It is urgent to optimize resource allocation under the constraint of limited satellite spectrum resources and ensure the fairness of service admission control. Therefore, we propose an intelligent hierarchical admission control (IHAC) strategy based on deep reinforcement learning (DRL). This strategy combines the deep deterministic policy gradient (DDPG) and the deep Q network (DQN) intelligent algorithm to construct upper and lower hierarchical resource allocation and admission control frameworks. The upper controller considers the state features of each ground zone and satellite resources from a global perspective, and determines the beam resource allocation ratio of each ground zone. The lower controller formulates the admission control policy based on the decision of the upper controller and the detailed information of the users' services. At the same time, a designed reward and punishment mechanism is used to optimize the decisions of the upper and lower controllers. The fairness of users' services admissions in each ground zone is achieved as far as possible while ensuring the reasonable allocation of beam resources among zones. Finally, online decision-making and offline learning were combined, so that the controller could make full use of a large number of historical data to learn and generate intelligent strategies with stronger adaptive ability while interacting with the network environment in real time. A large number of simulation results show that IHAC has better performance in terms of a successful service admission rate, service drop rate, and fair resource allocation. Among them, the number of accepted services increased by 20.36% on average, the packet loss rate decreased by 17.56% on average, and the resource fairness increased by 17.16% on average.

Developing Pricing Strategy in a Closed-Loop Supply Chain for Electric Vehicle Batteries With a Government Reward and Punishment Mechanism

Electric vehicles are expected to become a major means of transportation in the future, but entail the challenge of collecting used electric vehicle batteries. This article examines pricing strategies in a closed-loop dual-channel supply chain for electric vehicle batteries both with and without a governmental reward and punishment mechanism. The discussion considers the optimal pricing strategy considering the competition between dual collecting channels, both with the government's reward and punishment mechanism and without it. The degree of influence of government mechanisms, echelon utilization, and EV battery collection on a) collection price, b) collection capacity, and c) the profit obtained by participants are also examined. The discussion shows that collection capacity, collection price, and recycler profits in the closed-loop EV battery supply chain could be improved with a government reward and punishment mechanism. Finally, the robustness of the proposed model was verified through numerical examples.

Retracted: Third-Party Punishment Mechanism and Corporate Cooperation in Environmental Investment: Experiments on Public Goods Game

Retracted: Third-Party Punishment Mechanism and Corporate Cooperation in Environmental Investment: Experiments on Public Goods Game

Simulating urban growth by coupling macro-processes and micro-dynamics: a case study on Wuhan, China

ABSTRACT The urban form influences the quality of urban functions and is strongly correlated with the sustaining capabilities of urban development. However, in the context of rapid urbanization, unreasonable land expansion as a universal phenomenon poses a great challenge for urban management. Notably, the urban expansion process is self-organizing, and the evolving macroscopic pattern can be used to predict microscopic behavioral characteristics. Therefore, the analysis of macro- and micro-interactions can provide new ideas for urban modeling. Traditional geographic cellular automata (CA) models often have poor morphological reproducibility, and the few models that combine top-down and bottom-up CA use strict coupling constraints, resulting in inadequate self-organizing natural expressions and poor precision performances. In this study, we proposed a new land growth simulation model based on a soft constraint mechanism that couples micro-dynamics with macro-processes. Specifically, a geographic micro-process model (GMP) based on the meta-process accumulation concept was applied to capture the evolution characteristics of the macro-urban form and spatially deduce the future urban intensity gradient. The soft coupling between the macro and micro levels of the model was supported by a punishment mechanism that was developed for this study. A specially designed index, the morphology similarity (MS) index, was developed to evaluate and understand the heterogeneity of the simulated and real urban forms from a micro-perspective. The model was applied to Wuhan, the largest city in central China, to demonstrate that the proposed model has a high simulation accuracy [with a Kappa value of 0.8506 and a figure-of-merit (FoM) value of 0.3034 in the optimal parameter combination] and imitative ability [maximum sensitivity (MS) value of 0.01341 in the optimal parameter combination vs. MS value of 0.01336 in the true scenario]. The evaluation system developed in this study also demonstrated the high robustness and reliability of the future multi-scenario simulation conducted in this work.

Evolution of cooperation in spatial public goods game based on heterogenous social preferences and dynamic punishment

The mechanism of promoting cooperation in the public goods game has always been concerned by scholars. However, most of the existing studies are based on the premise that participants are self-interested. In order to explore why some sellers on e-commerce platforms voluntarily maintain the platform’s reputation, we incorporate heterogeneous social preferences of sellers into the spatial public goods game. We find that heterogeneous social preferences can enhance cooperation by improving collective rationality. Specifically, the altruistic preference of sellers can greatly reduce free-riding behavior, while the inequality aversion preference has a little inhibitory effect. Interestingly, when the benefit of maintaining the platform’s reputation is relatively high, the reciprocal preference can inhibit cooperation, but it can promote cooperation when the benefit is relatively small. This is due to the existence of some loosely connected but stable cooperative or defective clusters of sellers in e-commerce platforms. Furthermore, we propose a dynamic punishment mechanism to punish free riders. We observe that the dynamic punishment mechanism is more effective than the static punishment mechanism in solving the second-order free-riding problem faced by punishers. Increasing the enhancement factor of public goods is identified as a fundamental approach to mitigating this problem.

Factors Influencing Crowdworkers’ Continued Participation Behavior in Crowdsourcing Logistics: A Textual Analysis of Comments from Online Platforms

With the lazy economy’s rise in the digital era, the demand for crowdsourcing logistics delivery is increasing. In this process, the continued participation of crowdworkers has been a considerable challenge. In order to further clarify the influencing factors of crowdworkers’ continuous participation and better and targeted incentives for their participative behavior, we use ROST-CM 6.0 software to conduct textual analysis on 3000 comments from crowdworkers on China’s Meituan and Hummingbird crowdsourcing logistics platforms. The results show that the order dispatch system, reward and punishment system, and platforms’ service are the key factors concerned by crowdworkers. The total negative sentiment among crowdworkers regarding crowdsourcing logistics platforms is close to 20%. We also find that crowdsourcing logistics platforms still have room for improvement in the quantity and quality of orders dispatched, the evaluation factors and the appeal system for reward and punishment rules, and the freedom and flexibility of distribution work. Otherwise, this might lead to a trust issue between crowdworkers and the crowdsourcing logistics platform. Based on the research findings, we recommend that the crowdsourcing logistics platforms should enhance service awareness, provide a better work experience for crowdworkers, and optimize platform functions. The government should act as a regulator as well as a service provider. This paper’s innovations include methodologically, from the perspective of the crowdworkers, online comment texts are used to mine the behavioral factors that influence the crowdworker’s continued participation in crowdsourcing logistics; content-wise, it adds fresh insights to existing research on how the order allocation system and platform reward and punishment mechanisms affect the crowdworkers’ continuous participation behavior.

Research on the Architecture of Transactional Smart Contracts Based on Blockchains

At present, smart contracts are designed based on the application field, and their structure and functions are closely related to specific businesses. Even smart contracts within the same field and the same business have different structures and functions due to different developers, resulting in structural confusion, repeated development, and low levels of sharing. In response to this problem, this study conducts a full investigation of smart contracts in various fields, using big data technology to compare and analyze the structures of each contract and extracting the common content of their main bodies to study each feature, as well as to conduct induction and fusion. This study also generally designs a hierarchical structure and formulates structural modules such as transaction rules and the analysis of rights and responsibilities, as well as a reward and punishment mechanism. Data traceability is established, and the overall architectural specification of smart contracts is constructed. Additions, deletions, and improvements are made based on specific application environments to realize the dynamic updates of the architecture of contracts. Experiments show that the architecture of contracts can realize the various functions required in a transaction, solve the problem of the repeated development of current transactional smart contracts, and improve the sharing level.

The Macro Prudential Assessment Framework of China

This paper first introduces the basic concepts of macro-prudential assessment (MPA), and briefly introduces the background of MPA policy implementation, the key indicators of process and MPA assessment, the reward and punishment mechanism, as well as the purpose of China's macro-prudential assessment system. On this basis, this paper selected 15 listed banks as samples to analyze the achievement of the key indicators of MPA. In addition, it analyzes the influence of MPA evaluation system on bank management, introduces the broad credit standard to restrain the asset allocation mode; capital becomes the core constraint; the development mode needs to be adjusted. In addition, the countermeasures of strengthening the capital control, cultivating the awareness of enterprise capital saving, strengthening the strategic management, innovating the asset allocation system, improving the price management system, promoting reasonable pricing, innovating the development model, doing risk prevention and other improvement measures under the MPA mechanism are discussed.

Rewards, Penalties and Real Case References: Improvement of the Last Mile Delivery in USA

The growth of the platform economy has fueled the rapid growth of the cargo transportation industry. However, while it continues to scale up, many problems of the existing freight transportation industry are being exposed - environmental damage, harming consumers, and even depriving producers of profits. The last-mile problem is particularly significant. The United States and China, two of the world's largest countries, have representative platform economy enterprises, namely Amazon and Taobao. These two companies' different freight models represent the two existing mainstream freight models in the world - free home delivery and stagecoach containers. By comparing the two companies' existing last-mile delivery problems and analyzing the two countries' different cultural backgrounds, this paper tries to solve the existing last-mile problems by introducing reward and punishment mechanisms and applying the two models to each other. In this way, enterprises in each country can learn from each other's distribution models and find the optimal solution for the platform economy distribution model.

Evolutionary game analysis of rural public-private partnership older adult care project in the context of population aging in China.

Public-private partnership (PPP) older adult care project is an effective means to solve the dilemma of the aging population in China's rural areas, but there are some problems in the operation process, such as a low participation rate and poor service quality, resulting in the needs of rural older adult groups not being met. To alleviate the pressure of the aging population in rural areas, this study establishes an evolutionary game model for the PPP older adult care project, then defines the interests of local government, the private sector, and rural older adult residents, based on which it discusses the strategic choices of the three parties in the evolutionary process, and finally analyzes the influencing factors of the strategic choices of the game parties through simulation. The results suggest that whether the private sector chooses to actively participate in the project will be influenced by the willingness of local government and rural older adult residents to participate in the project. Local government could play the role of supervisor through reward and punishment mechanisms. Whether older rural residents choose to participate in the project depends on the number of benefits they would receive. Based on these findings, local governments should clarify the responsibilities of relevant stakeholders, adopt a regulatory strategy combining subsidies and penalties, improve the participation efficiency of rural older adult residents, promote the effective operation of PPP older adult care projects, and improve the quality of rural older adult care services in the new era.

A three‐stage economy optimization method for the aggregator based on electric vehicle user response volumes

AbstractWith the development of intelligent distribution networks and the proposal of the carbon peaking and carbon neutrality goals, the importance of demand‐side management for the improvement of flexible power operation systems is becoming increasingly prominent. To solve the problems of the excessive peak–valley load differences, the insufficient utilization of demand‐side resources, and the unreasonable pricing of aggregators, this paper proposes a three‐stage economy optimization method for the aggregator based on EV(electric vehicle) user response volumes. To gain the advantages of different types of EVs while increasing the dispatchable capacity, the contract mode between the aggregator and EVs is divided into three categories: complete dispatching, rolling reward and punishment mechanism dispatching, and free dispatching. Based on the cloud model, considering loss aversion, the user's own time flexibility, and the impact of the tariff set by the aggregator on the user's decision‐making, we introduced indicator weights to obtain the improved cloud model. Based on the improved cloud model, a user response volume model is obtained. Then, the aggregator performs a three‐stage pricing optimization operation for EVs based on the bid‐winning peak shaving capacity. In the first stage, the attraction between EVs and charging stations is determined based on the law of gravity, and the charging and discharging reward electricity price is set. In the second stage, the dynamic electricity price of three types of EVs and the charging punishment electricity prices of the rolling reward and punishment mechanism dispatching type are determined. In the third stage, the electricity price of the rolling reward and punishment dispatching EVs is further optimized based on their lack of peak shaving capacity. The method proposed in the paper has been verified to be effective in increasing aggregator profits, increasing EV dispatch capacity, and reducing EV charging costs through the example analysis.

Globalization and social work practice: Consequences of sanctions in health care (case study of Iran)

Economic sanctions are a punishment mechanism to ensure that governments respect human rights. However, sanctions affect nations, and pose challenges social workers in health care practice. The present note discusses the connection between health care and economic sanctions, and the challenges that health care social workers face due to the sanctions.

A three evolutionary game model for driving mechanism of industry-university-research collaborative innovation in agricultural innovation ecosystems.

Based on the current state of China's agricultural industry, this article proposes an integrated framework for the agricultural innovation ecosystem in developing countries. Furthermore, a dynamic simulation model is constructed to analyze the game process and factors influencing the agricultural innovation ecosystem. The results indicate that industry-university-research collaboration serves as the main source of innovation within the agricultural innovation ecosystem, playing a central role in its development. The willingness to participate, cost of participation, and establishment of default fees by governments, agro-related enterprises, universities, and research institutions have significant implications for the evolution of collaborative innovation within agricultural innovation ecosystems. In order to promote the evolution of the system, agriculture-related enterprises, universities, and research institutions should establish more effective reward and punishment mechanisms, as well as cost control mechanisms. Governments should set reasonable regulatory costs and incentive intervals to actively foster a collaborative innovation atmosphere. The innovation points of this paper are as follows: extending the theory of innovation ecosystems to agriculture, particularly in developing countries characterized by imbalanced and insufficient development. A game model is also constructed to represent the collaborative innovation evolution among government, agriculture-related enterprises, universities, and research institutions, with the government as the endogenous variable. Through numerical simulation, the dynamic evolution process of collaborative innovation within the agricultural innovation ecosystem is revealed. This research enriches and expands upon innovation ecosystem theory, providing guidance for the of innovation ecology in agriculture through mathematical models in developing countries. This, in turn, promotes the convergence of symbiotic, shared, and-creation development.