Digital Supply Chain Capabilities: Mitigating Disruptions and Leveraging Competitive Advantage Under COVID-19

Researchers and practitioners have highlighted the importance of supply chain analytic capabilities in managing risk while maintaining a competitive advantage (COA). However, the importance of digital supply chain capabilities (DSCCs) in improving resilience, agility, and robustness practices to foster the implementation of sustainable supply chain practices and any resulting COA remains unclear. Based on the dynamic capabilities view, we propose a research model for achieving a COA in contexts of uncertainty, such as the COVID-19 pandemic. A survey of Indian small and medium-sized enterprises in the original equipment manufacturing industry, comprising 310 respondents, was administered. Using structural equation modeling, we examine the proposed model. The findings show a significant positive effect of DSCCs on supply chain resilience and agile practices. The findings also indicate that supply chain resilience, robustness, and agile practices positively affect sustainable supply chain practices. Moreover, sustainable supply chain practices positively influence COA. Furthermore, the study reveals that the effect of DSCCs on sustainable supply chain practices is mediated by supply chain resilience, robustness, and agile practices. Managers concerned with investment in sustainable supply chain practices can obtain a COA through the successful implementation of supply chain resilience, robustness, and agile practices.

Exploring the role of artificial intelligence in managing agricultural supply chain risk to counter the impacts of the COVID-19 pandemic

Purpose In India, artificial intelligence (AI) application in supply chain management (SCM) is still in a stage of infancy. Therefore, this article aims to study the factors affecting artificial intelligence adoption and validate AI's influence on supply chain risk mitigation (SCRM). Design/methodology/approach This study explores the effect of factors based on the technology, organization and environment (TOE) framework and three other factors, including supply chain integration (SCI), information sharing (IS) and process factors (PF) on AI adoption. Data for the survey were collected from 297 respondents from Indian agro-industries, and structural equation modeling (SEM) was used for testing the proposed hypotheses. Findings This study's findings show that process factors, information sharing, and supply chain integration (SCI) play an essential role in influencing AI adoption, and AI positively influences SCRM. The technological, organizational and environmental factors have a nonsignificant negative relation with artificial intelligence. Originality/value This study provides an insight to researchers, academicians, policymakers, innovative project handlers, technology service providers, and managers to better understand the role of AI adoption and the importance of AI in mitigating supply chain risks caused by disruptions like the COVID-19 pandemic.

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

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.