Exploring the motivations behind artificial intelligence adoption for building resilient supply chains: a systematic literature review and future research agenda
IF 7.4 3区 管理学Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
{"title":"Exploring the motivations behind artificial intelligence adoption for building resilient supply chains: a systematic literature review and future research agenda","authors":"Laxmi Pandit Vishwakarma, Rajesh Kr Singh, Ruchi Mishra, Mani Venkatesh","doi":"10.1108/jeim-11-2023-0606","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>The study aims to synthesize existing knowledge and proposes a research framework for building a resilient supply chain (SC) through artificial intelligence (AI) technology. It also identifies existing literature gaps and paves the way for a future research agenda.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>A systematic literature review has been carried out to identify the peer-reviewed articles from Scopus and Web of Science databases. Then, the selected articles published between 2012 and 2023 are analyzed using descriptive and thematic analysis methods to unearth research gaps and offer new research directions.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>Descriptive and thematic analysis reveals the overall development of literature on the role of AI for supply chain resilience (SCR). Based on the findings of the thematic analysis, the motivation, application, capability and outcome (MACO) framework has been developed and propositions have been proposed. Several future research directions have also been suggested in terms of theory, context and methodology (TCM).</p><!--/ Abstract__block -->\n<h3>Practical implications</h3>\n<p>The study provides a fresh perspective on the integration of AI technology within the realm of SCR. The developed MACO framework serves as a practical tool for supply chain management (SCM) professionals, offering a nuanced understanding of AI's applications across various functional areas to streamline operations, minimize waste and optimize resource utilization, thereby helping them in strategic planning.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>This study contributes to the literature on the role of AI for building SCR by uncovering gaps, offering research directions and developing propositions for future research directions.</p><!--/ Abstract__block -->","PeriodicalId":47889,"journal":{"name":"Journal of Enterprise Information Management","volume":"494 1","pages":""},"PeriodicalIF":7.4000,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Enterprise Information Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/jeim-11-2023-0606","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
The study aims to synthesize existing knowledge and proposes a research framework for building a resilient supply chain (SC) through artificial intelligence (AI) technology. It also identifies existing literature gaps and paves the way for a future research agenda.
Design/methodology/approach
A systematic literature review has been carried out to identify the peer-reviewed articles from Scopus and Web of Science databases. Then, the selected articles published between 2012 and 2023 are analyzed using descriptive and thematic analysis methods to unearth research gaps and offer new research directions.
Findings
Descriptive and thematic analysis reveals the overall development of literature on the role of AI for supply chain resilience (SCR). Based on the findings of the thematic analysis, the motivation, application, capability and outcome (MACO) framework has been developed and propositions have been proposed. Several future research directions have also been suggested in terms of theory, context and methodology (TCM).
Practical implications
The study provides a fresh perspective on the integration of AI technology within the realm of SCR. The developed MACO framework serves as a practical tool for supply chain management (SCM) professionals, offering a nuanced understanding of AI's applications across various functional areas to streamline operations, minimize waste and optimize resource utilization, thereby helping them in strategic planning.
Originality/value
This study contributes to the literature on the role of AI for building SCR by uncovering gaps, offering research directions and developing propositions for future research directions.
期刊介绍：
The Journal of Enterprise Information Management (JEIM) is a significant contributor to the normative literature, offering both conceptual and practical insights supported by innovative discoveries that enrich the existing body of knowledge.
Within its pages, JEIM presents research findings sourced from globally renowned experts. These contributions encompass scholarly examinations of cutting-edge theories and practices originating from leading research institutions. Additionally, the journal features inputs from senior business executives and consultants, who share their insights gleaned from specific enterprise case studies. Through these reports, readers benefit from a comparative analysis of different environmental contexts, facilitating valuable learning experiences.
JEIM's distinctive blend of theoretical analysis and practical application fosters comprehensive discussions on commercial discoveries. This approach enhances the audience's comprehension of contemporary, applied, and rigorous information management practices, which extend across entire enterprises and their intricate supply chains.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
