TY - JOUR
T1 - Artificial intelligence (AI) for supply chain collaboration
T2 - implications on information sharing and trust
AU - Weisz, Eric
AU - Herold, David M.
AU - Ostern, Nadine Kathrin
AU - Payne, Ryan
AU - Kummer, Sebastian
N1 - Publisher Copyright:
© 2024, Emerald Publishing Limited.
PY - 2025/1/2
Y1 - 2025/1/2
N2 - Purpose: Managers and scholars alike claim that artificial intelligence (AI) represents a tool to enhance supply chain collaborations; however, existing research is limited in providing frameworks that categorise to what extent companies can apply AI capabilities and support existing collaborations. In response, this paper clarifies the various implications of AI applications on supply chain collaborations, focusing on the core elements of information sharing and trust. A five-stage AI collaboration framework for supply chains is presented, supporting managers to classify the supply chain collaboration stage in a company’s AI journey. Design/methodology/approach: Using existing literature on AI technology and collaboration and its effects of information sharing and trust, we present two frameworks to clarify (a) the interrelationships between information sharing, trust and AI capabilities and (b) develop a model illustrating five AI application stages how AI can be used for supply chain collaborations. Findings: We identify various levels of interdependency between trust and AI capabilities and subsequently divide AI collaboration into five stages, namely complementary AI applications, augmentative AI applications, collaborative AI applications, autonomous AI applications and AI applications replacing existing systems. Originality/value: Similar to the five stages of autonomous driving, the categorisation of AI collaboration along the supply chain into five consecutive stages provides insight into collaborations practices and represents a practical management tool to better understand the utilisation of AI capabilities in a supply chain environment.
AB - Purpose: Managers and scholars alike claim that artificial intelligence (AI) represents a tool to enhance supply chain collaborations; however, existing research is limited in providing frameworks that categorise to what extent companies can apply AI capabilities and support existing collaborations. In response, this paper clarifies the various implications of AI applications on supply chain collaborations, focusing on the core elements of information sharing and trust. A five-stage AI collaboration framework for supply chains is presented, supporting managers to classify the supply chain collaboration stage in a company’s AI journey. Design/methodology/approach: Using existing literature on AI technology and collaboration and its effects of information sharing and trust, we present two frameworks to clarify (a) the interrelationships between information sharing, trust and AI capabilities and (b) develop a model illustrating five AI application stages how AI can be used for supply chain collaborations. Findings: We identify various levels of interdependency between trust and AI capabilities and subsequently divide AI collaboration into five stages, namely complementary AI applications, augmentative AI applications, collaborative AI applications, autonomous AI applications and AI applications replacing existing systems. Originality/value: Similar to the five stages of autonomous driving, the categorisation of AI collaboration along the supply chain into five consecutive stages provides insight into collaborations practices and represents a practical management tool to better understand the utilisation of AI capabilities in a supply chain environment.
KW - Artificial intelligence
KW - Collaboration
KW - Framework
KW - Information sharing
KW - Trust
UR - http://www.scopus.com/inward/record.url?scp=85198847091&partnerID=8YFLogxK
U2 - 10.1108/OIR-02-2024-0083
DO - 10.1108/OIR-02-2024-0083
M3 - Article
AN - SCOPUS:85198847091
SN - 1468-4527
VL - 49
SP - 164
EP - 181
JO - Online Information Review
JF - Online Information Review
IS - 1
ER -