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Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective

Kirti Nayal (Department of Operations and Supply Chain Management, National Institute of Industrial Engineering (NITIE), Mumbai, India)
Rakesh D. Raut (Department of Operations and Supply Chain Management, National Institute of Industrial Engineering (NITIE), Mumbai, India)
Maciel M. Queiroz (Postgraduate Program in Business Administration, Paulista University - UNIP, São Paulo, Brazil) (School of Engineering, Mackenzie Presbyterian University, São Paulo, Brazil)
Vinay Surendra Yadav (Department of Mechanical Engineering, National Institute of Technology Raipur, Raipur, India)
Balkrishna E. Narkhede (Department of Operations and Supply Chain Management, National Institute of Industrial Engineering (NITIE), Mumbai, India)

The International Journal of Logistics Management

ISSN: 0957-4093

Article publication date: 16 June 2021

1009

Abstract

Purpose

This article aims to model the challenges of implementing artificial intelligence and machine earning (AI-ML) for moderating the impacts of COVID-19, considering the agricultural supply chain (ASC) in the Indian context.

Design/methodology/approach

20 critical challenges were modeled based on a comprehensive literature review and consultation with experts. The hybrid approach of “Delphi interpretive structural modeling (ISM)-Fuzzy Matrice d' Impacts Croises Multiplication Applique'e à un Classement (MICMAC) − analytical network process (ANP)” was used.

Findings

The study's outcome indicates that “lack of central and state regulations and rules” and “lack of data security and privacy” are the crucial challenges of AI-ML implementation in the ASC. Furthermore, AI-ML in the ASC is a powerful enabler of accurate prediction to minimize uncertainties.

Research limitations/implications

This study will help stakeholders, policymakers, government and service providers understand and formulate appropriate strategies to enhance AI-ML implementation in ASCs. Also, it provides valuable insights into the COVID-19 impacts from an ASC perspective. Besides, as the study was conducted in India, decision-makers and practitioners from other geographies and economies must extrapolate the results with due care.

Originality/value

This study is one of the first that investigates the potential of AI-ML in the ASC during COVID-19 by employing a hybrid approach using Delphi-ISM-Fuzzy-MICMAC-ANP.

Keywords

Citation

Nayal, K., Raut, R.D., Queiroz, M.M., Yadav, V.S. and Narkhede, B.E. (2021), "Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective", The International Journal of Logistics Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJLM-01-2021-0002

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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