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To address this gap, this study examines the factors driving GenAI implementation in an SCM environment and how these factors optimize SCM performance.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>A thorough literature review was followed to identify the drivers. The resultant model from the drivers was validated using a quantitative study based on partial least squares structural equation modeling (PLS-SEM) that used responses from 315 expert respondents from the field of SCM.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The results confirmed the positive effect of performance expectancy, output quality and reliability, organizational innovativeness and management commitment to GenAI usage. Further, they showed that successful GenAI usage improved SCM performance through improved transparency, better decision-making, innovative design, robust development and responsiveness.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title><jats:p>This study reports the potential drivers for the contemporary development of GenAI in SCM and highlights an action plan for GenAI\u2019s optimal performance. The findings suggest that by increasing the rate of GenAI implementation, organizations can continuously improve their strategies and practices for better SCM performance.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>This study establishes the first step toward empirically testing and validating a theoretical model for GenAI implementation and its effect on SCM performance.<\/jats:p><\/jats:sec>","DOI":"10.1108\/imds-08-2024-0773","type":"journal-article","created":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T02:05:46Z","timestamp":1738289146000},"page":"1110-1133","source":"Crossref","is-referenced-by-count":20,"title":["Understanding determinants of GenAI usage and its effect on SCM performance using dynamic capability view"],"prefix":"10.1108","volume":"125","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4922-9212","authenticated-orcid":false,"given":"Hemlata","family":"Gangwar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Shameem","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandeep","family":"Patel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4565-0408","authenticated-orcid":false,"given":"Alex","family":"Koohang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6602-9285","authenticated-orcid":false,"given":"Anuj","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"140","published-online":{"date-parts":[[2025,2,3]]},"reference":[{"issue":"5","key":"key2025022108513203200_ref001","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1080\/08874417.2023.2240744","article-title":"Towards adoption of generative AI in organizational settings","volume":"64","year":"2023","journal-title":"Journal of Computer Information Systems"},{"key":"key2025022108513203200_ref002","doi-asserted-by":"publisher","DOI":"10.1016\/j.techsoc.2023.102403","article-title":"Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: a TOE framework","volume":"75","year":"2023","journal-title":"Technology in Society"},{"key":"key2025022108513203200_ref003","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.chb.2016.11.040","article-title":"The moderating role of trust in business-to-business electronic commerce (B2B EC) adoption","volume":"68","year":"2017","journal-title":"Computers in Human Behavior"},{"issue":"1","key":"key2025022108513203200_ref098","first-page":"2","article-title":"Education in the era of generative artificial intelligence (AI): understanding the potential benefits of ChatGPT in promoting teaching and learning","volume":"7","year":"2023","journal-title":"Journal of AIDS"},{"issue":"8","key":"key2025022108513203200_ref004","doi-asserted-by":"publisher","first-page":"260","DOI":"10.3390\/fi15080260","article-title":"The power of generative ai: a review of requirements, models, input\u2013output formats, evaluation metrics, and challenges","volume":"15","year":"2023","journal-title":"Future Internet"},{"issue":"1","key":"key2025022108513203200_ref102","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1186\/s40537-021-00445-7","article-title":"A survey on artificial intelligence assurance","volume":"8","year":"2021","journal-title":"Journal of Big Data"},{"issue":"2","key":"key2025022108513203200_ref005","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1007\/s10479-021-03956-x","article-title":"Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation","volume":"333","year":"2024","journal-title":"Annals of Operations Research"},{"issue":"2","key":"key2025022108513203200_ref006","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/emr.2023.3272799","article-title":"Accelerating innovation with generative AI: AI-augmented digital prototyping and innovation methods","volume":"51","year":"2023","journal-title":"IEEE Engineering Management Review"},{"issue":"2","key":"key2025022108513203200_ref007","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1111\/jpim.12656","article-title":"Augmenting human innovation teams with artificial intelligence: exploring transformer\u2010based language models","volume":"40","year":"2023","journal-title":"Journal of Product Innovation Management"},{"key":"key2025022108513203200_ref008","doi-asserted-by":"crossref","unstructured":"Brill, T.M., Munoz, L. and Miller, R.J. 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