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Organizational Adoption of Artificial Intelligence in Supply Chain Risk Management

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Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation (TDIT 2020)

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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.

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Author information

Authors and Affiliations

  1. S P Jain School of Global Management, Mumbai, India

    Souma Kanti Paul & Suchismita Das

  2. S P Jain School of Global Management, Dubai, UAE

    Sadia Riaz

Authors
  1. Souma Kanti Paul
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  2. Sadia Riaz
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  3. Suchismita Das
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Corresponding author

Correspondence to Souma Kanti Paul .

Editor information

Editors and Affiliations

  1. Indian Institute of Management Tiruchira, Tiruchirappalli, India

    Sujeet K. Sharma

  2. Swansea University, Swansea, UK

    Yogesh K. Dwivedi

  3. Indian Institute of Management Nagpur, Nagpur, India

    Bhimaraya Metri

  4. University of Bradford, Bradford, UK

    Nripendra P. Rana

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Paul, S.K., Riaz, S., Das, S. (2020). Organizational Adoption of Artificial Intelligence in Supply Chain Risk Management. In: Sharma, S.K., Dwivedi, Y.K., Metri, B., Rana, N.P. (eds) Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation. TDIT 2020. IFIP Advances in Information and Communication Technology, vol 617. Springer, Cham. https://doi.org/10.1007/978-3-030-64849-7_2

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  • DOI: https://doi.org/10.1007/978-3-030-64849-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64848-0

  • Online ISBN: 978-3-030-64849-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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