Adoption of Artificial Intelligence in Supply Chain Risk Management: An Indian Perspective

Adoption of Artificial Intelligence in Supply Chain Risk Management: An Indian Perspective

Souma Kanti Paul, Sadia Riaz, Suchismita Das
Copyright: © 2022 |Pages: 18
DOI: 10.4018/JGIM.307569
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Abstract

The study aims to examine factors that influence the adoption-diffusion process of Artificial Intelligence (AI) in Supply Chain Risk Management (SCRM) across manufacturing, wholesale trade, retail trade, and transportation industries in India. As part of this study, eleven constructs that influence the adoption-diffusion stages of AI in SCRM were identified and examined. A survey was conducted to collect data from supply chain executives, risk professionals, and AI consultants across the manufacturing, wholesale trade, retail trade, and transportation industries in India. Partial least squares structural equation modeling (PLS-SEM) was used to study the data. Results show that these factors have varying degrees of influence and direction on the three stages of adoption of AI in SCRM. The study will enable the leadership team in the organizations to build a roadmap for the adoption, implementation, and routinization of AI in SCRM.
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2. Background

AI will change the decision-making process in an organization and how it interacts with other stakeholders and third parties (Haenlein & Kaplan 2019). It has also been argued that in organizations, thinking tasks will increasingly be taken over by AI systems (Huang et al., 2019) due to the promise of fast, accurate, repeatable, and human-like intelligence. AI is evolving, and accordingly, the scope, definition, applications, and usability of AI is under constant change. As per the Artificial Intelligence Index Report 2021, published by Stanford University, business establishments were most likely to identify AI techniques as those covering areas like deep learning, natural language processing, computer vision, and other machine learning techniques (Zhang et al., 2021).

With regards to SCRM, Gurtu and Johny (2021) have highlighted that the definition of SCRM is still evolving and there is no standard definition. Researchers have proposed multiple definitions over a period (Sudeep & Srikanta, 2014; Sodhi et al., 2012). Primarily, SCRM comprises four fundamental constructs, namely, (i) supply chain risk sources, (ii) risk consequences, (iii) risk drivers, and (iv) risk mitigation (Jüttner et al., 2010).

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