Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study
Identifikátory výsledku
Kód výsledku v 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>
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Barriers, Drivers, and Social Considerations for AI Adoption in Supply Chain Management: A Tertiary Study
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
50204 - Business and management
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Logistics
ISSN
2305-6290
e-ISSN
2305-6290
Svazek periodika
6
Číslo periodika v rámci svazku
3
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
22
Strana od-do
63
Kód UT WoS článku
000857076800001
EID výsledku v databázi Scopus
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