Barriers, drivers, and social considerations for AI adoption in supply chain management: a tertiary study
Open accessAbstract
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.
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An organization's preparedness is an important factor in how new IT innovations are adopted and implemented.
“An organization’s preparedness is an important factor in how new IT innovations are adopted and implemented (Alam et al., 2016; Hangl et al., 2022).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Hangl et al., 2022
AI and related technologies have a significant impact on how businesses operate and are structured.
“AI and related technologies, such as machine learning, neural networks, and virtual assistants, have a significant impact on how businesses operate and are structured (Hangl et al., 2022).”
From Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector (2023) · cites this paper as Hangl et al., 2022
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- Authors
- Hangl, J., Behrens, V. J., & Krause, S.
- Affiliations
- Mendel University in Brno (CZ)
- Corresponding author
- Hangl, Johannes
- Venue
- Logistics
- Publisher
- MDPI AG
- Published
- 2022-09-09
- Volume
- 6
- Issue
- 3
- Pages
- 63
- ISSN
- 2305-6290 (ISSN-L)
- OpenAlex
- W4295539664
- Cited by
- 63
- References
- 82
- Citations by year
- 2026: 24 · 2025: 22 · 2024: 9 · 2023: 8
- FWCI
- 5.97
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Logistics (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Econstor (Econstor) (submittedVersion, cc-by)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence adoption, supply chain management, AI adoption barriers, societal impact of AI, human-robot collaboration, change management, Internet of Things, automation and job displacement, workplace learning, return on investment, artificial intelligence algorithms
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