Surviving major disruptions: Building supply chain resilience and visibility through rapid information flow and real-time insights at the “edge”

Disruptive events with damaging consequences afflict supply chains across industries. The survival of the business and its consequent recovery depend on the supply chain's resilience. This exploratory article discusses how technology-driven real-time decision-making in a connected supply chain...

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Bibliographic Details
Main Author: Shantanu Dey
Format: Article
Language:English
Published: Elsevier 2023-04-01
Series:Sustainable Manufacturing and Service Economics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2667344422000081
Description
Summary:Disruptive events with damaging consequences afflict supply chains across industries. The survival of the business and its consequent recovery depend on the supply chain's resilience. This exploratory article discusses how technology-driven real-time decision-making in a connected supply chain achieves intended business outcomes of resilience, agility, and visibility. Based on an Integrative Literature Review and adopting a Design Science Research Methodology (DSRM), we propose a distributed approach for real-time inferencing in edge near the data sources for rapid autonomous decisioning and recovery planning under disruption. We develop a framework for building resilience in the supply chain using real-time distributed information sharing in a collaborative partner ecosystem. Visibility across the supply chain is ensured with a Digital Control Tower by making information available to any connected node for synchronized action. The important contribution of this research is building a real-time decision framework for sustainable resilience-building in resource-constrained organizations unable to invest in big data and enterprise systems. A set of design propositions following the CIMO framework is expected to help scholars and practitioners alike. A research agenda is provided for the researchers to take forward hypothesis formulation and empirical validation on the basis of the propositions. (194 words)
ISSN:2667-3444