{"title":"Life Cycle Sustainability Assessment Integrated Data‐Driven Methodological Framework for Sustainable Supplier Selection","authors":"Ankit Kumrawat, Seema Unnikrishnan","doi":"10.1002/bse.4356","DOIUrl":null,"url":null,"abstract":"With the growing importance of sustainable supply chain management, businesses are actively looking for sustainable suppliers that consider all sustainability dimensions. This study aims to demonstrate a data‐driven methodological framework for sustainable supplier selection (SSS). The research proposes a three‐stage, data‐driven approach for SSS. The first stage involves using the life cycle sustainability assessment (LCSA) methodology. The second stage involves determining the weights of each category by using criteria importance through inter‐criteria correlation (CRITIC). Finally, the multi‐attributive border approximation area comparison (MABAC) method is utilized to assess the performance of different suppliers and identify the most sustainable supplier. This study emphasizes relying on a data‐driven approach rather than solely depending on experts' opinions and judgments. Moreover, this study demonstrates the significance of research methodology with prioritization considering industry‐specific relevant categories. This proposed framework will assist professionals and decision‐makers in making informed decisions regarding sustainable suppliers.","PeriodicalId":9518,"journal":{"name":"Business Strategy and The Environment","volume":"121 1","pages":""},"PeriodicalIF":12.5000,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Business Strategy and The Environment","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1002/bse.4356","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
With the growing importance of sustainable supply chain management, businesses are actively looking for sustainable suppliers that consider all sustainability dimensions. This study aims to demonstrate a data‐driven methodological framework for sustainable supplier selection (SSS). The research proposes a three‐stage, data‐driven approach for SSS. The first stage involves using the life cycle sustainability assessment (LCSA) methodology. The second stage involves determining the weights of each category by using criteria importance through inter‐criteria correlation (CRITIC). Finally, the multi‐attributive border approximation area comparison (MABAC) method is utilized to assess the performance of different suppliers and identify the most sustainable supplier. This study emphasizes relying on a data‐driven approach rather than solely depending on experts' opinions and judgments. Moreover, this study demonstrates the significance of research methodology with prioritization considering industry‐specific relevant categories. This proposed framework will assist professionals and decision‐makers in making informed decisions regarding sustainable suppliers.
期刊介绍:
Business Strategy and the Environment (BSE) is a leading academic journal focused on business strategies for improving the natural environment. It publishes peer-reviewed research on various topics such as systems and standards, environmental performance, disclosure, eco-innovation, corporate environmental management tools, organizations and management, supply chains, circular economy, governance, green finance, industry sectors, and responses to climate change and other contemporary environmental issues. The journal aims to provide original contributions that enhance the understanding of sustainability in business. Its target audience includes academics, practitioners, business managers, and consultants. However, BSE does not accept papers on corporate social responsibility (CSR), as this topic is covered by its sibling journal Corporate Social Responsibility and Environmental Management. The journal is indexed in several databases and collections such as ABI/INFORM Collection, Agricultural & Environmental Science Database, BIOBASE, Emerald Management Reviews, GeoArchive, Environment Index, GEOBASE, INSPEC, Technology Collection, and Web of Science.