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.

中文翻译：

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探索采用人工智能构建弹性供应链背后的动机：系统文献综述和未来研究议程

 目的

该研究旨在综合现有知识，提出通过人工智能（AI）技术构建弹性供应链（SC）的研究框架。它还确定了现有的文献空白，并为未来的研究议程铺平了道路。

设计/方法论/途径

我们进行了系统的文献综述，以识别来自 Scopus 和 Web of Science 数据库的同行评审文章。然后，采用描述性分析和主题分析方法对2012年至2023年间发表的精选文章进行分析，以挖掘研究空白并提供新的研究方向。

 发现

描述性和主题分析揭示了人工智能在供应链弹性（SCR）方面的作用文献的整体发展。根据主题分析的结果，制定了动机、应用、能力和结果（MACO）框架并提出了建议。还从理论、背景和方法论（TCM）方面提出了几个未来的研究方向。

 实际影响

该研究为 SCR 领域中人工智能技术的集成提供了全新的视角。开发的MACO框架可以作为供应链管理（SCM）专业人员的实用工具，让他们对人工智能在各个功能领域的应用有细致入微的了解，以简化运营、最大限度地减少浪费并优化资源利用，从而帮助他们进行战略规划。

 原创性/价值

这项研究通过发现差距、提供研究方向并为未来研究方向提出建议，为有关人工智能在构建 SCR 中的作用的文献做出了贡献。