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An interpretive structural modelling (ISM) methodology is used to indicate the relationships between identified drivers to stimulate transition to CE and SOM. Drivers and pair-wise interactions between these drivers are developed by semi-structured interviews with a number of experts from industry and academia.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results show that Information Management and Technology, Governmental Incentive and Management Team Capability drivers are classified as independent factors; Organizational Commitment and Operations Efficiency are categorized as dependent factors. SC Visibility, Data-driven innovation, Demand management and Production Planning, Talent Management and Collaborations between SC partners can be classified as linkage factors. It can be concluded that Governmental Incentive is the most fundamental driver to achieve BDA applications in FSC transition from linearity to CE and SOM. In addition, Operations Efficiency, Collaborations between SC partners and Organizational Commitment are key BDA drivers in FSC for transition to CE and SOM.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title><jats:p>The interactions between these drivers will provide benefits to both industry and academia in prioritizing and understanding these drivers more thoroughly when implementing BDA based on a range of factors. This study will provide valuable insights. The results from this study will help in drawing up regulations to prevent food fraud, implementing laws concerning government incentives, reducing food loss and waste, increasing tracing and traceability, providing training activities to improve knowledge about BDA and focusing more on data analytics.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>The main contribution of the study is to analyze BDA drivers in the context of FSC for transition to CE and SOM. This study is unique in examining these BDA drivers based on FSC. We hope to find sustainable solutions to minimize losses or other negative impacts on these SC.<\/jats:p><\/jats:sec>","DOI":"10.1108\/jeim-12-2020-0521","type":"journal-article","created":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T11:48:44Z","timestamp":1619696924000},"page":"219-242","source":"Crossref","is-referenced-by-count":71,"title":["Drivers of implementing Big Data Analytics in food supply chains for transition to a circular economy and sustainable operations management"],"prefix":"10.1108","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9199-671X","authenticated-orcid":false,"given":"Yigit","family":"Kazancoglu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1356-3203","authenticated-orcid":false,"given":"Melisa","family":"Ozbiltekin Pala","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4630-2464","authenticated-orcid":false,"given":"Muruvvet Deniz","family":"Sezer","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7571-1331","authenticated-orcid":false,"given":"Sunil","family":"Luthra","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1691-0098","authenticated-orcid":false,"given":"Anil","family":"Kumar","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2021,4,29]]},"reference":[{"key":"key2025012304070284600_ref001","first-page":"387","article-title":"Evaluation of key challenges to industry 4.0 in Indian context: a Dematel approach","volume-title":"Advances in Industrial and Production Engineering","year":"2019"},{"key":"key2025012304070284600_ref002","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.ijpe.2015.11.013","article-title":"Data-driven and adaptive leadership contributing to sustainability: global agri-food supply chains connected with emerging 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