Emergent Technologies for Supply Chain Risk and Disruption Management

Abstract

Primarily, the disruption risks observed in the supply chain network (SCN) of any product are pertinent to external events, demand variability, instability in supply, processing time, and asymmetry in information dissemination. These disruptions lead to uncertainty across the supply chain, causing deleterious impacts on its operation by impacting SCN entities, namely, external suppliers, production units, distribution units, demand zones, and logistics. Managing the disruptive events mentioned above requires the formulation of a robust operational model for risk and disruption management operational model that facilitates an accurate assessment of demand disturbance and coordination of supply chain actors with true information exchange with an innovation adoption and boundary-spanning theoretical perspectives. In addition, a better understanding of disruptive impact renders quick responsiveness and cost optimization. This draws the attention towards real-time information flow among supply chain stakeholders in a secure, immutable, and trustworthy channel that can be established with the intervention of state-of-the-art emerging digital technologies, namely, Internet of Things (IoT), Big Data Analytics (BDA), Blockchain Technology (BT), Artificial Intelligence (AI), and 5G network communication because of their capability to efficiently identify the root cause of disruption and offer data-driven decision-making based on better real-time visibility, control mechanism, and process coordination. Therefore, the study offers an extant view on the aforementioned technological intervention along with a functional process overview describing the integrated strength of individual digital technologies in risk control and mitigation practices. The study covers two different brief analyses, one elaborating the role of blockchain in real-life scenarios through a secondary case study highlighting the role of the emergent technologies in managing supply chain risk and disruption, whereas the other focuses on role of AI in various stages in a supply chain using the data gathered from experts and industry practitioners. Both studies ardently indicated the promiscuous presence of IT tools in practice and pointed out the great potential ahead. The study has several interesting theoretical and practical implications related to supply chain risk and disruption management (SCRM).