ABSTRACT
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.
ABSTRACT
In the global supply chains era, firms are more connected, integrated, and interdependent, bringing along a set of benefits and a number of risks. It is clear that the singular COVID-19 epidemic outbreak has led to unparalleled disruptions and considerable challenges for supply chains (SCs). For example, the sluggish economic environment provoked by the COVID-19 has negatively impacted the flow of goods, generating shortages and interruptions through the SCs. At the global level, many markets are enduring the effects of these disruptions. In this challenging context, the firms and their SCs must apply useful and efficient strategies to minimize and adapt their operations during and after these disruptions. In this view, this study aims to propose a novel framework based on Artificial Intelligence, Blockchain, and Big Data Analytics, to bring useful ideas and contribute to overcoming such disruptions. Besides, we propose novel categorizations that can support new insights for scholars and practitioners about the use of cutting-edge technologies during and after severe disruptions. Copyright (C) 2022 The Authors.
ABSTRACT
The spread of the coronavirus has had a major impact on the global economy, highlighting the shortcomings and weaknesses of global supply chains. Major issues such as supply disruptions, shortages of raw materials and spare parts, restricted transport, and ineffective exchange of information between actors within the supply chain have resulted. The empirical evidence of these events is widely discussed in the literature, which has brought out the urgent need to rethink the configuration of customer-supplier relations at an overall level. One technology that is much discussed in the literature and potentially useful in supporting supply chain processes is the blockchain technology. Blockchain has been gaining attraction across different sectors, even if there are still few applications in supply chain management, most at an experimental level. The aim of this paper is to analyse the potential applications of blockchain to support supply chain processes, to fill the gaps highlighted during the Covid pandemic. Through the analysis of the literature, the authors aim to give a preliminary overview on the relationships between Covid-19 impacts and benefits achievable by the application of blockchain technology in the supply chain, for an effective supply chain reconfiguration in a post-covid era. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
ABSTRACT
Purpose: Although the advances in the supply chain resilience (SCR) literature, there is a critical gap concerning this understanding in a high disruption context, such as in the case of the COVID-19. This paper aims to investigate some dimensions (agility, robustness, disruption orientation and resource reconfiguration) of the SCR during this unprecedented disruption in the Brazilian supply chain context. Design/methodology/approach: Supported by the resource-based view, dynamic capabilities and the SCR literature, we developed a model, which in turn was analyzed and validated by partial least squares structural equation modelling. Findings: The results revealed that while resource reconfiguration and supply chain disruption orientation positively affect SCR, we found a non-significant effect of supply chain robustness and agility. Practical implications: The findings suggest that in a considerable disruption scenario, managers with their supply chain operations in emerging economies should prioritize the development of resources to support the disruption orientation and manage the scarce resources adequately by reconfiguring them. Originality/value: Our study is one of the first that reported the dynamics of the SCR dimensions in an emerging economy during the COVID-19. © 2021, Emerald Publishing Limited.
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.