Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective
International Journal of Logistics Management
; 2021.
Article
in English
| Scopus | ID: covidwho-1281935
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. © 2021, Emerald Publishing Limited.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
International Journal of Logistics Management
Year:
2021
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS