Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study

Johannes Hangl (), Viktoria Joy Behrens and Simon Krause
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Johannes Hangl: Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1665/1, 613 00 Brno, Czech Republic
Viktoria Joy Behrens: Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1665/1, 613 00 Brno, Czech Republic
Simon Krause: Faculty of Business and Economics, Mendel University in Brno, Zemědělská 1665/1, 613 00 Brno, Czech Republic

Logistics, 2022, vol. 6, issue 3, 1-22

Abstract: Background: The number of publications in supply chain management (SCM) and artificial intelligence (AI) has risen significantly in the last two decades, and their quality and outcomes vary widely. This study attempts to synthesise the existing literature in this research area and summarise the findings regarding barriers, drivers, and social implications of using AI in SCM. Methods : The methodology used for this meta-study is based on Kitchenham and Charters guidelines, resulting in a selection of 44 literature reviews published between 2000 and 2021. Results : As a summary of the results, the main areas of AI in SCM were algorithms, followed by the Internet of Things (IoT). The main barriers to AI adoption in SCM are change management, existing technical limitations, and the acceptance of humans for these techniques. The main drivers of AI in SCM are saving costs and increasing efficiency in combination with reducing time and resources. The main social factor is human–robot collaboration. As a result, there will be a decreased amount of labour needed in the future, impacting many existing jobs, especially in low-income areas. Conclusions : Therefore, it is essential for organisations that implement new technology to start as early as possible to inform the organisation about the changes and help them successfully implement them. It is also important to mention that constant learning and improvement of the employees are critical for adopting and successfully using new AI tools. Before investing in new technology, a solid Return on Investment calculation (ROI) and monitoring costs and value are critical to transforming the business successfully.

Keywords: supply chain management; SCM; artificial intelligence; AI; SCOR (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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