Organizational Adoption of Artificial Intelligence in Supply Chain Risk Management
With the growing complexity of global supply chains, geopolitical events, pandemics, and just-in-time processes, organizations can benefit immensely in managing supply chain risks by adopting artificial intelligence (AI). Building upon past research in te
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S P Jain School of Global Management, Mumbai, India [email protected] 2 S P Jain School of Global Management, Dubai, UAE
Abstract. With the growing complexity of global supply chains, geopolitical events, pandemics, and just-in-time processes, organizations can benefit immensely in managing supply chain risks by adopting artificial intelligence (AI). Building upon past research in technology adoption, we study factors influencing the adoption intention of AI in SCRM across organizations in India. Based on a qualitative study, we discuss the applications and uniqueness of AI adoption in the field of supply chain risk management (SCRM) and propose a research model on the adoption, implementation, and routinization intention of AI in SCRM at an organizational level. Secondly, we discuss the implications of the study and the benefits to decision-makers and supply chain planners in devising effective strategies when adopting AI in SCRM. Keywords: Adoption Management
Artificial intelligence Supply Chain Risk
1 Introduction Growing incidences of events like natural disasters, pandemics, just-in-time processes, and global supply chain networks have resulted in increased vulnerability of supply chains to disruptions [1]. A report [2] on the impact of Covid-19 on global Gross Domestic Product (GDP) cites that more than five million companies, including greater than 90% Fortune 1000 companies, had one or multiple tier-2 suppliers in the impacted region in China during the initial months of the pandemic. There has been a growing interest in the application of Artificial Intelligence (AI) in Supply Chain Risk Management (SCRM). However, there has been limited research on the adoption of AI in SCRM at an organizational level across industry verticals in India. The objective of this research is to identify factors that influence the adoption intention, implementation intention, and routinization intention of AI in SCRM at an organizational level in India. The industries considered for this study cover consumer-packaged-goods (CPG), consumer durables, wholesale, logistics, and retail.
© IFIP International Federation for Information Processing 2020 Published by Springer Nature Switzerland AG 2020 S. K. Sharma et al. (Eds.): TDIT 2020, IFIP AICT 617, pp. 10–15, 2020. https://doi.org/10.1007/978-3-030-64849-7_2
Organizational Adoption of AI in SCRM
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2 Literature Review 2.1
Definition of AI
The field of AI has evolved over the past few decades and accordingly, the definition and scope of AI have been continually evolving. Today, Artificial Neural Networks (ANN) and Deep Learning (DL), form the core of applications classified under AI [3]. Accordingly, for this study we consider deep learning techniques that use artificial neural networks as the definition of AI. 2.2
Definition of SCRM
Based on past research, SCRM is defined as the management of supply chain risks through active coordination between all supply chain partners to identify, assess, and respond to risks ensuring disruptions are mitigated leading to business conti
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