The quality control of remanufactured products in a closed-loop supply chain (CLSC) can significantly influence consumers’ decision-making, and the contract coordination of CLSC has also become a research hotspot. This paper explores the quality control problem in a three-level remanufacturing CLSC consisting of a remanufacturer, a retailer, and a recycler by constructing a system dynamics (SD) model, which contains two contract schemes: quality control contract and quality control–revenue-sharing contract. Subsequently, the proposed SD model is analyzed using various schemes. The findings suggest that without mandatory contracts, CLSC members are frequently unable to fulfill their quality improvement commitments. Among them, recyclers are less likely to improve quality and more prone to breaking promises. The quality control problem in CLSC can be addressed through contract coordination, and the quality control contract scheme can avoid non-compliance with quality improvement commitments. The application of the quality control–revenue-sharing combination contract scheme not only resolves the quality control issue but also promotes profit improvement in the CLSC.
{"title":"Remanufacturing Closed-Loop Supply Chain Contract Coordination Considering Quality Control","authors":"Wei Duan, Mingli Liu, Desheng Xu, Liping Han","doi":"10.3390/systems12090350","DOIUrl":"https://doi.org/10.3390/systems12090350","url":null,"abstract":"The quality control of remanufactured products in a closed-loop supply chain (CLSC) can significantly influence consumers’ decision-making, and the contract coordination of CLSC has also become a research hotspot. This paper explores the quality control problem in a three-level remanufacturing CLSC consisting of a remanufacturer, a retailer, and a recycler by constructing a system dynamics (SD) model, which contains two contract schemes: quality control contract and quality control–revenue-sharing contract. Subsequently, the proposed SD model is analyzed using various schemes. The findings suggest that without mandatory contracts, CLSC members are frequently unable to fulfill their quality improvement commitments. Among them, recyclers are less likely to improve quality and more prone to breaking promises. The quality control problem in CLSC can be addressed through contract coordination, and the quality control contract scheme can avoid non-compliance with quality improvement commitments. The application of the quality control–revenue-sharing combination contract scheme not only resolves the quality control issue but also promotes profit improvement in the CLSC.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"53 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chang Su, Jun Deng, Xiaoyang Li, Fangming Cheng, Wenhong Huang, Caiping Wang, Wangbo He, Xinping Wang
Systematic management of corporate safety risks in industrial parks has become a hot topic. And risk prevention and control mutual aid is a brand-new model in the risk and emergency management of the park. In the context of blockchain, how to incentivize enterprises to actively invest in safety risk prevention and control mutual aid has become a series of key issues facing government regulators. This paper innovatively combines Prospect Theory, Mental Accounting, and Evolutionary Game Theory to create a hypothetical model of limited rationality for the behavior of key stakeholders (core enterprises, supporting enterprises, and government regulatory departments) in mutual aid for safety risk prevention and control. Under the static prize punishment mechanism and dynamic punishment mechanism, the evolutionary stabilization strategy of stakeholders was analyzed, and numerical simulation analysis was performed through examples. The results show: (1) Mutual aid for risk prevention and control among park enterprises is influenced by various factors, including external and subjective elements, and evolves through complex evolutionary paths (e.g., reference points, value perception). (2) Government departments are increasingly implementing dynamic reward and punishment measures to address the shortcomings of static mechanisms. Government departments should dynamically adjust reward and punishment strategies, determine clearly the highest standards for rewards and punishments, and the combination of various incentives and penalties can significantly improve the effectiveness of investment decisions in mutual aid for safety risk prevention and control. (3) Continuously optimizing the design of reward and punishment mechanisms, integrating blockchain technology with management strategies to motivate enterprise participation, and leveraging participant feedback are strategies and recommendations that provide new insights for promoting active enterprise investment in mutual aid for safety risk prevention and control. The marginal contribution of this paper is to reveal the evolutionary pattern of mutual safety risk prevention and control behaviors of enterprises in chemical parks in the context of blockchain.
{"title":"Research on the Game Strategy of Mutual Safety Risk Prevention and Control of Industrial Park Enterprises under Blockchain Technology","authors":"Chang Su, Jun Deng, Xiaoyang Li, Fangming Cheng, Wenhong Huang, Caiping Wang, Wangbo He, Xinping Wang","doi":"10.3390/systems12090351","DOIUrl":"https://doi.org/10.3390/systems12090351","url":null,"abstract":"Systematic management of corporate safety risks in industrial parks has become a hot topic. And risk prevention and control mutual aid is a brand-new model in the risk and emergency management of the park. In the context of blockchain, how to incentivize enterprises to actively invest in safety risk prevention and control mutual aid has become a series of key issues facing government regulators. This paper innovatively combines Prospect Theory, Mental Accounting, and Evolutionary Game Theory to create a hypothetical model of limited rationality for the behavior of key stakeholders (core enterprises, supporting enterprises, and government regulatory departments) in mutual aid for safety risk prevention and control. Under the static prize punishment mechanism and dynamic punishment mechanism, the evolutionary stabilization strategy of stakeholders was analyzed, and numerical simulation analysis was performed through examples. The results show: (1) Mutual aid for risk prevention and control among park enterprises is influenced by various factors, including external and subjective elements, and evolves through complex evolutionary paths (e.g., reference points, value perception). (2) Government departments are increasingly implementing dynamic reward and punishment measures to address the shortcomings of static mechanisms. Government departments should dynamically adjust reward and punishment strategies, determine clearly the highest standards for rewards and punishments, and the combination of various incentives and penalties can significantly improve the effectiveness of investment decisions in mutual aid for safety risk prevention and control. (3) Continuously optimizing the design of reward and punishment mechanisms, integrating blockchain technology with management strategies to motivate enterprise participation, and leveraging participant feedback are strategies and recommendations that provide new insights for promoting active enterprise investment in mutual aid for safety risk prevention and control. The marginal contribution of this paper is to reveal the evolutionary pattern of mutual safety risk prevention and control behaviors of enterprises in chemical parks in the context of blockchain.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"11 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Socio-technical systems (STSs) are systems of systems, synthesising human and IT components that jointly operate to achieve specific goals. Such systems are overly complex but, if designed optimally, they can significantly improve STS performance. Critical phases in STS design are defining the functional requirements for automated or software-supported human activities and addressing social and human interaction issues. To define automation support for human operations, STS designers need to ensure that specifications will satisfy not only the non-functional requirements (NFR) of the system but also of its human actors such as human reliability/workload. However, such human factors aspects are not addressed sufficiently with traditional STS design approaches, which could lead to STS failure or rejection. This paper proposes a new STS design method that addresses this problem and introduces a novel type of requirements, namely, Task Support Requirements (TSR) that assists in specifying the functionality that IT systems should have to support human agents in undertaking their tasks by addressing human limitations. The proposed method synthesises a requirements/software engineering approach to STS design with functional allocation and an HCI perspective, which facilitates the application of human factors knowledge in conceptual models and evaluation through VR simulation. A case study methodology is employed in this work that allows in-depth, multi-faceted explorations of the complex issues that characterise STSs. Two case studies are presented in this work; the first is a detailed illustration of how the method is applied during the design of an in-vehicle information system to enhance drivers’ situation awareness. The second is an empirical evaluation of the method using participants that apply it to design a mobile application to minimise the risk of pedestrian travellers conceiving a contagious disease while commuting in public space. The results from the empirical evaluation showed that the method positively contributes to STS design by addressing human factors issues effectively.
{"title":"Using Task Support Requirements during Socio-Technical Systems Design","authors":"Andreas Gregoriades, Alistair Sutcliffe","doi":"10.3390/systems12090348","DOIUrl":"https://doi.org/10.3390/systems12090348","url":null,"abstract":"Socio-technical systems (STSs) are systems of systems, synthesising human and IT components that jointly operate to achieve specific goals. Such systems are overly complex but, if designed optimally, they can significantly improve STS performance. Critical phases in STS design are defining the functional requirements for automated or software-supported human activities and addressing social and human interaction issues. To define automation support for human operations, STS designers need to ensure that specifications will satisfy not only the non-functional requirements (NFR) of the system but also of its human actors such as human reliability/workload. However, such human factors aspects are not addressed sufficiently with traditional STS design approaches, which could lead to STS failure or rejection. This paper proposes a new STS design method that addresses this problem and introduces a novel type of requirements, namely, Task Support Requirements (TSR) that assists in specifying the functionality that IT systems should have to support human agents in undertaking their tasks by addressing human limitations. The proposed method synthesises a requirements/software engineering approach to STS design with functional allocation and an HCI perspective, which facilitates the application of human factors knowledge in conceptual models and evaluation through VR simulation. A case study methodology is employed in this work that allows in-depth, multi-faceted explorations of the complex issues that characterise STSs. Two case studies are presented in this work; the first is a detailed illustration of how the method is applied during the design of an in-vehicle information system to enhance drivers’ situation awareness. The second is an empirical evaluation of the method using participants that apply it to design a mobile application to minimise the risk of pedestrian travellers conceiving a contagious disease while commuting in public space. The results from the empirical evaluation showed that the method positively contributes to STS design by addressing human factors issues effectively.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"2 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Accurately quantifying the complexity of nodes in a network is crucial for revealing their roles and network complexity, as well as predicting network emergent phenomena. In this paper, we propose three novel complexity metrics for nodes to reflect the extent to which they participate in organized, structured interactions in higher-order networks. Our higher-order network is built using the BuildHON+ model, where communities are detected using the Infomap algorithm. Since a physical node may contain one or more higher-order nodes in higher-order networks, it may simultaneously exist in one or more communities. The complexity of a physical node is defined by the number and size of the communities to which it belongs, as well as the number of higher-order nodes it contains within the same community. Empirical flow datasets are used to evaluate the effectiveness of the proposed metrics, and the results demonstrate their efficacy in characterizing node complexity in higher-order networks.
{"title":"Quantifying the Complexity of Nodes in Higher-Order Networks Using the Infomap Algorithm","authors":"Yude Fu, Xiongyi Lu, Caixia Yu, Jichao Li, Xiang Li, Qizi Huangpeng","doi":"10.3390/systems12090347","DOIUrl":"https://doi.org/10.3390/systems12090347","url":null,"abstract":"Accurately quantifying the complexity of nodes in a network is crucial for revealing their roles and network complexity, as well as predicting network emergent phenomena. In this paper, we propose three novel complexity metrics for nodes to reflect the extent to which they participate in organized, structured interactions in higher-order networks. Our higher-order network is built using the BuildHON+ model, where communities are detected using the Infomap algorithm. Since a physical node may contain one or more higher-order nodes in higher-order networks, it may simultaneously exist in one or more communities. The complexity of a physical node is defined by the number and size of the communities to which it belongs, as well as the number of higher-order nodes it contains within the same community. Empirical flow datasets are used to evaluate the effectiveness of the proposed metrics, and the results demonstrate their efficacy in characterizing node complexity in higher-order networks.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"7 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How to efficiently and greenly dismantle abandoned buildings and reuse them is a dilemma facing the building material industry’s low-carbon objective. However, relevant studies ignore the influence mechanism of altruistic preferences of enterprises on green dismantling technology in supply chains. Driven by filling this theoretical gap, this paper firstly integrates reciprocal altruism theory and the Stackalberg game method and constructs a construction and demolition waste (CDW) recycling supply chain system consisting of a recycler and a remanufacturer, in which enterprises’ altruistic preferences are considered. The main theoretical outcomes of this paper are as follows. (1) In the case of unilateral altruism, enterprises’ altruistic preference behaviors help in increasing the green dismantling technological level and the amount of CDW recycling. Under the mutual altruism model, the influence of the recycler’s altruistic preference degree on the amount of CDW recycled hinges on the remanufacturer’s altruistic preference degree. (2) The utility of the enterprises and the green dismantling technological level are optimized under the mutual altruism model. (3) In a system of unequal power, unilateral “goodwill” by the follower will have a negative effect on their own interests; the leader plays a crucial role in facilitating equal cooperation and realizing win–win situations. This paper enriches the reciprocal altruism theory in waste management. It also helps in providing guidance for the recycler and remanufacturer in making operational decisions.
{"title":"Operational Decisions of Construction and Demolition Waste Recycling Supply Chain Members under Altruistic Preferences","authors":"Junlin Zhu, Hao Zhang, Weihong Chen, Xingwei Li","doi":"10.3390/systems12090346","DOIUrl":"https://doi.org/10.3390/systems12090346","url":null,"abstract":"How to efficiently and greenly dismantle abandoned buildings and reuse them is a dilemma facing the building material industry’s low-carbon objective. However, relevant studies ignore the influence mechanism of altruistic preferences of enterprises on green dismantling technology in supply chains. Driven by filling this theoretical gap, this paper firstly integrates reciprocal altruism theory and the Stackalberg game method and constructs a construction and demolition waste (CDW) recycling supply chain system consisting of a recycler and a remanufacturer, in which enterprises’ altruistic preferences are considered. The main theoretical outcomes of this paper are as follows. (1) In the case of unilateral altruism, enterprises’ altruistic preference behaviors help in increasing the green dismantling technological level and the amount of CDW recycling. Under the mutual altruism model, the influence of the recycler’s altruistic preference degree on the amount of CDW recycled hinges on the remanufacturer’s altruistic preference degree. (2) The utility of the enterprises and the green dismantling technological level are optimized under the mutual altruism model. (3) In a system of unequal power, unilateral “goodwill” by the follower will have a negative effect on their own interests; the leader plays a crucial role in facilitating equal cooperation and realizing win–win situations. This paper enriches the reciprocal altruism theory in waste management. It also helps in providing guidance for the recycler and remanufacturer in making operational decisions.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"1 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Samer Al-Rabeei, Michal Hovanec, Volodymyr Tymofiiv, Juraj Horkay
In this article, we point out that luggage disinfection is a key step in stopping the spread of infectious diseases that can be contracted at airports due to viruses and bacteria, which can spread through passenger luggage at airports. To prevent the spread of respiratory infections at airports, in this research study, we compare two types of baggage disinfection system. The first method uses UV light to disinfect luggage while selectively checking it for the presence of bacteria and viruses. The second system uses non-selective disinfection, taking into account the possibility of the spread of disease from the aircraft’s home country. An analysis and simulation of a specific airport security procedure was carried out on the model under study, which is an automated system for disinfecting baggage at airports in two variants. The aim is to reduce the transmission of harmful diseases and, at the same time, to ensure the accuracy of passenger security screening by efficiently exhausting each of the proposed models. This research shows that the suggested measures to stop the spread of infectious diseases that travelers’ luggage can bring in will enhance screening procedures and, in particular, boost overall security while lowering the risk of infection transmission at airports.
{"title":"Innovating Airport Luggage Disinfection Systems with Advanced Technologies and Automation","authors":"Samer Al-Rabeei, Michal Hovanec, Volodymyr Tymofiiv, Juraj Horkay","doi":"10.3390/systems12090345","DOIUrl":"https://doi.org/10.3390/systems12090345","url":null,"abstract":"In this article, we point out that luggage disinfection is a key step in stopping the spread of infectious diseases that can be contracted at airports due to viruses and bacteria, which can spread through passenger luggage at airports. To prevent the spread of respiratory infections at airports, in this research study, we compare two types of baggage disinfection system. The first method uses UV light to disinfect luggage while selectively checking it for the presence of bacteria and viruses. The second system uses non-selective disinfection, taking into account the possibility of the spread of disease from the aircraft’s home country. An analysis and simulation of a specific airport security procedure was carried out on the model under study, which is an automated system for disinfecting baggage at airports in two variants. The aim is to reduce the transmission of harmful diseases and, at the same time, to ensure the accuracy of passenger security screening by efficiently exhausting each of the proposed models. This research shows that the suggested measures to stop the spread of infectious diseases that travelers’ luggage can bring in will enhance screening procedures and, in particular, boost overall security while lowering the risk of infection transmission at airports.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"1 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Word-of-mouth (WOM) can be considered one form of public opinion, reflecting consumers’ views towards product or service quality. With the development of social media, WOM holds influence over investors and subsequently impacts the stock prices of companies. The purpose of this study is to uncover the dynamics encompassing the factors that influence WOM, its propagation mechanisms, and the consequential impact on reality illustrated through fluctuations in stock prices. The mathematical model to describe the whole process can be separated into two components: information propagation model and stock price fluctuation model. The cumulative abnormal return (CAR) is used to demonstrate fluctuations in stock prices. Utilizing a Lyapunov function, it is proven that the equilibrium point of the model is globally asymptotically stable. As for the real world, it suggests that WOM will eventually prevail online, leading to fluctuations in stock prices. Based on the event study method, the empirical examination of 43 real events shows that our model can effectively predict the CAR and reflect the influence on stock prices caused by WOM in real-world scenarios.
{"title":"Research on the Dynamics of Word-of-Mouth Influencing Stock Prices","authors":"Wanglai Li, Huizhang Shen, Zhangxue Huang, Hanzhe Yang, Jidi Zhao","doi":"10.3390/systems12090344","DOIUrl":"https://doi.org/10.3390/systems12090344","url":null,"abstract":"Word-of-mouth (WOM) can be considered one form of public opinion, reflecting consumers’ views towards product or service quality. With the development of social media, WOM holds influence over investors and subsequently impacts the stock prices of companies. The purpose of this study is to uncover the dynamics encompassing the factors that influence WOM, its propagation mechanisms, and the consequential impact on reality illustrated through fluctuations in stock prices. The mathematical model to describe the whole process can be separated into two components: information propagation model and stock price fluctuation model. The cumulative abnormal return (CAR) is used to demonstrate fluctuations in stock prices. Utilizing a Lyapunov function, it is proven that the equilibrium point of the model is globally asymptotically stable. As for the real world, it suggests that WOM will eventually prevail online, leading to fluctuations in stock prices. Based on the event study method, the empirical examination of 43 real events shows that our model can effectively predict the CAR and reflect the influence on stock prices caused by WOM in real-world scenarios.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"44 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A system of incentives can be established to encourage several parties to unite as a community of interest and become jointly committed to the platform economic governance. The platform economy involves progressively more complex subjects of interest and relationships, which are not the typical principal–agent one-time cooperative relationship. This study investigates the problem of regulatory incentives in the platform economy, specifically focusing on the relationship between the government, platform enterprises, and merchants. It analyzes this issue under conditions of asymmetric information by constructing and solving a dual principal–agent model. The findings indicate the following: (1) the government’s incentives and regulatory mechanisms can be considered as interchangeable to some extent, with decisions made by evaluating their respective costs; (2) the government’s optimal incentives and regulations ultimately shape the self-regulatory behavior of merchants through platform enterprises; and (3) the optimal level of incentives for both the government and the platform enterprise is influenced by factors such as the ability coefficient, the social transformation coefficient, and the merchants’ reliance on the platform enterprise. Additionally, the optimal effort level of the platform enterprise and the merchants increases with higher levels of the regulatory effort, risk sensitivity coefficient, and ability coefficient. A win–win scenario and a long-term, stable cooperative partnership can be reached by the three parties under the ideal incentive intensity. The study’s conclusions can serve as a theoretical foundation and support for the creation of incentive contracts for platform economy regulation.
{"title":"A Study on the Design of Incentive Contracts for Platform Economy Regulation Based on Dual Principal–Agents","authors":"Ruibi Zhang, Jinhe Zhu, Ming Lei","doi":"10.3390/systems12090343","DOIUrl":"https://doi.org/10.3390/systems12090343","url":null,"abstract":"A system of incentives can be established to encourage several parties to unite as a community of interest and become jointly committed to the platform economic governance. The platform economy involves progressively more complex subjects of interest and relationships, which are not the typical principal–agent one-time cooperative relationship. This study investigates the problem of regulatory incentives in the platform economy, specifically focusing on the relationship between the government, platform enterprises, and merchants. It analyzes this issue under conditions of asymmetric information by constructing and solving a dual principal–agent model. The findings indicate the following: (1) the government’s incentives and regulatory mechanisms can be considered as interchangeable to some extent, with decisions made by evaluating their respective costs; (2) the government’s optimal incentives and regulations ultimately shape the self-regulatory behavior of merchants through platform enterprises; and (3) the optimal level of incentives for both the government and the platform enterprise is influenced by factors such as the ability coefficient, the social transformation coefficient, and the merchants’ reliance on the platform enterprise. Additionally, the optimal effort level of the platform enterprise and the merchants increases with higher levels of the regulatory effort, risk sensitivity coefficient, and ability coefficient. A win–win scenario and a long-term, stable cooperative partnership can be reached by the three parties under the ideal incentive intensity. The study’s conclusions can serve as a theoretical foundation and support for the creation of incentive contracts for platform economy regulation.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"63 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, the focus of flow shops is the adoption of customized demand in the context of service-oriented manufacturing. Since production tasks are often characterized by multi-variety, low volume, and a short lead time, it becomes an indispensable factor to include supporting logistics in practical scheduling decisions to reflect the frequent transport of jobs between resources. Motivated by the above background, a hybrid method based on dual back propagation (BP) neural networks is proposed to meet the real-time scheduling requirements with the aim of integrating production and transport activities. First, according to different resource attributes, the hierarchical structure of a flow shop is divided into three layers, respectively: the operation task layer, the job logistics layer, and the production resource layer. Based on the process logic relationships between intra-layer and inter-layer elements, an operation task–logistics–resource supernetwork model is established. Secondly, a dual BP neural network scheduling algorithm is designed for determining an operations sequence involving the transport time. The neural network 1 is used for the initial classification of operation tasks’ priority; and the neural network 2 is used for the sorting of conflicting tasks in the same priority, which can effectively reduce the amount of computational time and dramatically accelerate the solution speed. Finally, the effectiveness of the proposed method is verified by comparing the completion time and computational time for different examples. The numerical simulation results show that with the increase in problem scale, the solution ability of the traditional method gradually deteriorates, while the dual BP neural network has a stable performance and fast computational time.
如今，流程车间的重点是在以服务为导向的制造过程中采用定制需求。由于生产任务通常具有多品种、小批量和短交货期的特点，因此在实际调度决策中纳入配套物流以反映资源间频繁的作业运输成为一个不可或缺的因素。基于上述背景，本文提出了一种基于双反向传播（BP）神经网络的混合方法，以满足实时调度的要求，实现生产与运输活动一体化的目标。首先，根据不同的资源属性，将流水车间的层次结构分为三层，分别是操作任务层、作业物流层和生产资源层。根据层内要素和层间要素之间的流程逻辑关系，建立了操作任务-物流-资源超网络模型。其次，设计了一种双 BP 神经网络调度算法，用于确定涉及运输时间的作业序列。利用神经网络 1 对操作任务的优先级进行初步划分，利用神经网络 2 对优先级相同的冲突任务进行排序，从而有效减少了计算时间，大大加快了求解速度。最后，通过比较不同实例的完成时间和计算时间，验证了所提方法的有效性。数值模拟结果表明，随着问题规模的增大，传统方法的求解能力逐渐下降，而双 BP 神经网络性能稳定，计算时间快。
{"title":"A Flow Shop Scheduling Method Based on Dual BP Neural Networks with Multi-Layer Topology Feature Parameters","authors":"Hui Mu, Zinuo Wang, Jiaqi Chen, Guoqiang Zhang, Shaocun Wang, Fuqiang Zhang","doi":"10.3390/systems12090339","DOIUrl":"https://doi.org/10.3390/systems12090339","url":null,"abstract":"Nowadays, the focus of flow shops is the adoption of customized demand in the context of service-oriented manufacturing. Since production tasks are often characterized by multi-variety, low volume, and a short lead time, it becomes an indispensable factor to include supporting logistics in practical scheduling decisions to reflect the frequent transport of jobs between resources. Motivated by the above background, a hybrid method based on dual back propagation (BP) neural networks is proposed to meet the real-time scheduling requirements with the aim of integrating production and transport activities. First, according to different resource attributes, the hierarchical structure of a flow shop is divided into three layers, respectively: the operation task layer, the job logistics layer, and the production resource layer. Based on the process logic relationships between intra-layer and inter-layer elements, an operation task–logistics–resource supernetwork model is established. Secondly, a dual BP neural network scheduling algorithm is designed for determining an operations sequence involving the transport time. The neural network 1 is used for the initial classification of operation tasks’ priority; and the neural network 2 is used for the sorting of conflicting tasks in the same priority, which can effectively reduce the amount of computational time and dramatically accelerate the solution speed. Finally, the effectiveness of the proposed method is verified by comparing the completion time and computational time for different examples. The numerical simulation results show that with the increase in problem scale, the solution ability of the traditional method gradually deteriorates, while the dual BP neural network has a stable performance and fast computational time.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"36 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Noise and error are usually considered to be disturbances negatively affecting the behavior of a system. Nevertheless, from a systemic perspective, taking into account openness and incompleteness of complex systems, noise and error may assume a creative, constructive, and positive role in that they are a source of novelty that can trigger the reorganization of the system, the growth of complexity, and the emergence of new meaning. Examples of this phenomenon can be found in evolutionary phenomena driven by affordances, the formation of new attractors in dynamic systems responding to external perturbations, and improvisation in music. We argue that it is possible to identify general properties that enable the positive effect of noise and errors in complex systems, namely, multilevel organization, redundancy, incompleteness, and criticality. These properties play a major role in living systems and can guide the design of robust and adaptive artificial systems.
{"title":"On the Positive Role of Noise and Error in Complex Systems","authors":"Andrea Roli, Michele Braccini, Pasquale Stano","doi":"10.3390/systems12090338","DOIUrl":"https://doi.org/10.3390/systems12090338","url":null,"abstract":"Noise and error are usually considered to be disturbances negatively affecting the behavior of a system. Nevertheless, from a systemic perspective, taking into account openness and incompleteness of complex systems, noise and error may assume a creative, constructive, and positive role in that they are a source of novelty that can trigger the reorganization of the system, the growth of complexity, and the emergence of new meaning. Examples of this phenomenon can be found in evolutionary phenomena driven by affordances, the formation of new attractors in dynamic systems responding to external perturbations, and improvisation in music. We argue that it is possible to identify general properties that enable the positive effect of noise and errors in complex systems, namely, multilevel organization, redundancy, incompleteness, and criticality. These properties play a major role in living systems and can guide the design of robust and adaptive artificial systems.","PeriodicalId":36394,"journal":{"name":"Systems","volume":"5 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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