Zelin Wang , Xiangbin Wang , Weizhong Wang , Muhammet Deveci , Zengyuan Wu , Witold Pedrycz
{"title":"基于达成共识的决策模型,利用社会网络分析评估具有弹性的城市公共卫生安全生态系统","authors":"Zelin Wang , Xiangbin Wang , Weizhong Wang , Muhammet Deveci , Zengyuan Wu , Witold Pedrycz","doi":"10.1016/j.jii.2024.100716","DOIUrl":null,"url":null,"abstract":"<div><div>In 2021, United Nations released the \"Creating Resilient Cities 2030 Project\", which aims to strengthen urban resilience in developing and implementing disaster reduction strategies. Resilient cities are a new type of urban development model that emphasizes the ability of cities to resist natural disasters and social pressures, reduce losses, and allocate resources reasonably to quickly recover from disasters. With the frequent occurrence of public health and safety accidents, the concept of public health safety ecosystem has become increasingly prominent in the field of urban resilience. To effectively manage public health incidents and enhance emergency response capabilities, evaluating the urban public health safety ecosystem is essential. A consensus-based decision-making model that accounts for the social networks among experts to accurately assess urban public health emergency capacity is introduced. To ensure the objectivity of indicator weights, we build up a novel model to calculate the weight of indicators utilizing social network analysis and consensus-reaching process analysis of indicator evaluation value. An illustrative case study on public health emergency capacity in Luoding is presented. This research expands the framework for assessing resilience in urban systems and provides a methodology for improving urban public health and resilience, introducing a novel approach for evaluating the urban public health safety ecosystem through social network analysis.</div></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"42 ","pages":"Article 100716"},"PeriodicalIF":10.4000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Consensus reaching-based decision model for assessing resilient urban public health safety ecosystem with social network analysis\",\"authors\":\"Zelin Wang , Xiangbin Wang , Weizhong Wang , Muhammet Deveci , Zengyuan Wu , Witold Pedrycz\",\"doi\":\"10.1016/j.jii.2024.100716\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In 2021, United Nations released the \\\"Creating Resilient Cities 2030 Project\\\", which aims to strengthen urban resilience in developing and implementing disaster reduction strategies. Resilient cities are a new type of urban development model that emphasizes the ability of cities to resist natural disasters and social pressures, reduce losses, and allocate resources reasonably to quickly recover from disasters. With the frequent occurrence of public health and safety accidents, the concept of public health safety ecosystem has become increasingly prominent in the field of urban resilience. To effectively manage public health incidents and enhance emergency response capabilities, evaluating the urban public health safety ecosystem is essential. A consensus-based decision-making model that accounts for the social networks among experts to accurately assess urban public health emergency capacity is introduced. To ensure the objectivity of indicator weights, we build up a novel model to calculate the weight of indicators utilizing social network analysis and consensus-reaching process analysis of indicator evaluation value. An illustrative case study on public health emergency capacity in Luoding is presented. This research expands the framework for assessing resilience in urban systems and provides a methodology for improving urban public health and resilience, introducing a novel approach for evaluating the urban public health safety ecosystem through social network analysis.</div></div>\",\"PeriodicalId\":55975,\"journal\":{\"name\":\"Journal of Industrial Information Integration\",\"volume\":\"42 \",\"pages\":\"Article 100716\"},\"PeriodicalIF\":10.4000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Industrial Information Integration\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2452414X24001596\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Industrial Information Integration","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452414X24001596","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Consensus reaching-based decision model for assessing resilient urban public health safety ecosystem with social network analysis
In 2021, United Nations released the "Creating Resilient Cities 2030 Project", which aims to strengthen urban resilience in developing and implementing disaster reduction strategies. Resilient cities are a new type of urban development model that emphasizes the ability of cities to resist natural disasters and social pressures, reduce losses, and allocate resources reasonably to quickly recover from disasters. With the frequent occurrence of public health and safety accidents, the concept of public health safety ecosystem has become increasingly prominent in the field of urban resilience. To effectively manage public health incidents and enhance emergency response capabilities, evaluating the urban public health safety ecosystem is essential. A consensus-based decision-making model that accounts for the social networks among experts to accurately assess urban public health emergency capacity is introduced. To ensure the objectivity of indicator weights, we build up a novel model to calculate the weight of indicators utilizing social network analysis and consensus-reaching process analysis of indicator evaluation value. An illustrative case study on public health emergency capacity in Luoding is presented. This research expands the framework for assessing resilience in urban systems and provides a methodology for improving urban public health and resilience, introducing a novel approach for evaluating the urban public health safety ecosystem through social network analysis.
期刊介绍:
The Journal of Industrial Information Integration focuses on the industry's transition towards industrial integration and informatization, covering not only hardware and software but also information integration. It serves as a platform for promoting advances in industrial information integration, addressing challenges, issues, and solutions in an interdisciplinary forum for researchers, practitioners, and policy makers.
The Journal of Industrial Information Integration welcomes papers on foundational, technical, and practical aspects of industrial information integration, emphasizing the complex and cross-disciplinary topics that arise in industrial integration. Techniques from mathematical science, computer science, computer engineering, electrical and electronic engineering, manufacturing engineering, and engineering management are crucial in this context.