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引用次数: 0
摘要
目的本研究旨在综合现有知识，并提出通过人工智能（AI）技术构建弹性供应链（SC）的研究框架。设计/方法/途径进行了系统的文献综述，以确定 Scopus 和 Web of Science 数据库中的同行评审文章。然后，采用描述性分析和专题分析方法对 2012 年至 2023 年间发表的所选文章进行分析，以发现研究空白并提供新的研究方向。研究结果描述性分析和专题分析揭示了人工智能在供应链复原力（SCR）方面作用的文献总体发展情况。根据专题分析的结果，制定了动机、应用、能力和结果（MACO）框架，并提出了一些命题。该研究为将人工智能技术融入 SCR 领域提供了一个全新的视角。开发的 MACO 框架可作为供应链管理（SCM）专业人员的实用工具，让他们对人工智能在各个职能领域的应用有细致入微的了解，以简化操作、减少浪费和优化资源利用，从而帮助他们制定战略规划。
Exploring the motivations behind artificial intelligence adoption for building resilient supply chains: a systematic literature review and future research agenda
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.
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