Tangzhenhao Li , Jianxin You , Emel Aktas , Yongxin Dong , Miying Yang
{"title":"建筑企业数字化转型项目的风险评估:一个增强的FMEA模型","authors":"Tangzhenhao Li , Jianxin You , Emel Aktas , Yongxin Dong , Miying Yang","doi":"10.1016/j.eswa.2025.126991","DOIUrl":null,"url":null,"abstract":"<div><div>The digital transformation of the construction industry is crucial for advancing global digital economies, but it involves significant risks that require a standardized and robust assessment methodology. This paper presents an enhanced Failure Mode and Effect Analysis (FMEA) model that integrates the Multiple Attribute Border Approximation Area Comparison (MABAC) method with Grey Relational Analysis (GRA). Unlike previous approaches, this integration aligns grey relational changes with border approximation vector components, capturing both positive and negative correlations between modes. This enhances the prioritization process by distinguishing failure modes that may amplify or mitigate each other’s impact, leading to more precise risk assessments and mitigation strategies. The model also employs interval numbers instead of crisp numbers to reduce information loss from decision-making ambiguities caused by heterogeneous expert evaluations. Applied in a real-life case study, the improved model effectively accommodates biases and hesitations in expert decision-making, enhancing the accuracy and reliability of risk assessments in digital transformation projects. The findings highlight the model’s potential as a comprehensive and reliable framework for identifying, prioritizing, and mitigating risks in the digital transformation of the construction industry.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"274 ","pages":"Article 126991"},"PeriodicalIF":7.5000,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Risk assessment for digital transformation projects in construction Enterprises: An enhanced FMEA model\",\"authors\":\"Tangzhenhao Li , Jianxin You , Emel Aktas , Yongxin Dong , Miying Yang\",\"doi\":\"10.1016/j.eswa.2025.126991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The digital transformation of the construction industry is crucial for advancing global digital economies, but it involves significant risks that require a standardized and robust assessment methodology. This paper presents an enhanced Failure Mode and Effect Analysis (FMEA) model that integrates the Multiple Attribute Border Approximation Area Comparison (MABAC) method with Grey Relational Analysis (GRA). Unlike previous approaches, this integration aligns grey relational changes with border approximation vector components, capturing both positive and negative correlations between modes. This enhances the prioritization process by distinguishing failure modes that may amplify or mitigate each other’s impact, leading to more precise risk assessments and mitigation strategies. The model also employs interval numbers instead of crisp numbers to reduce information loss from decision-making ambiguities caused by heterogeneous expert evaluations. Applied in a real-life case study, the improved model effectively accommodates biases and hesitations in expert decision-making, enhancing the accuracy and reliability of risk assessments in digital transformation projects. The findings highlight the model’s potential as a comprehensive and reliable framework for identifying, prioritizing, and mitigating risks in the digital transformation of the construction industry.</div></div>\",\"PeriodicalId\":50461,\"journal\":{\"name\":\"Expert Systems with Applications\",\"volume\":\"274 \",\"pages\":\"Article 126991\"},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2025-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert Systems with Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S095741742500613X\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/22 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S095741742500613X","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Risk assessment for digital transformation projects in construction Enterprises: An enhanced FMEA model
The digital transformation of the construction industry is crucial for advancing global digital economies, but it involves significant risks that require a standardized and robust assessment methodology. This paper presents an enhanced Failure Mode and Effect Analysis (FMEA) model that integrates the Multiple Attribute Border Approximation Area Comparison (MABAC) method with Grey Relational Analysis (GRA). Unlike previous approaches, this integration aligns grey relational changes with border approximation vector components, capturing both positive and negative correlations between modes. This enhances the prioritization process by distinguishing failure modes that may amplify or mitigate each other’s impact, leading to more precise risk assessments and mitigation strategies. The model also employs interval numbers instead of crisp numbers to reduce information loss from decision-making ambiguities caused by heterogeneous expert evaluations. Applied in a real-life case study, the improved model effectively accommodates biases and hesitations in expert decision-making, enhancing the accuracy and reliability of risk assessments in digital transformation projects. The findings highlight the model’s potential as a comprehensive and reliable framework for identifying, prioritizing, and mitigating risks in the digital transformation of the construction industry.
期刊介绍:
Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.