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

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F22%3A43922196" target="_blank" >RIV/62156489:43110/22:43922196 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.3390/logistics6030063" target="_blank" >https://doi.org/10.3390/logistics6030063</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/logistics6030063" target="_blank" >10.3390/logistics6030063</a>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50204 - Business and management

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Logistics

ISSN

2305-6290

e-ISSN

2305-6290

Volume of the periodical

6

Issue of the periodical within the volume

3

Country of publishing house

CH - SWITZERLAND

Number of pages

22

Pages from-to

63

UT code for WoS article

000857076800001

EID of the result in the Scopus database

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