Assessing the Role of IT Capability in Enhancing Supply Chain Agility During Macroeconomic Disruptions

Abstract

Today, macroeconomic shocks, such as structural geopolitical split, resource scarcity, global logistics changes and systemic inflation, are all a major threat to enterprise supply chain models. Conventional models of operational management are not enough to shield against these cascading disruptions. The study uses Dynamic Capabilities Theory and Resource Based View (RBV) as the basis for studying and analyzing how well the variable Information Technology (IT) Capability can develop and contribute to the implementation of Supply Chain Agility (SCA) empirically.This study is based on Dynamic Capabilities Theory and Resource Based View (RBV) so as to analyze and evaluate the appropriate role of Information Technology (IT) Capability in developing and driving Supply Chain Agility (SCA) in an empirical way. We break down IT Capability into three elements: IT Infrastructure Flexibility, IT Personnel Expertise, and IT-Supply Chain Integration, and examine how they increase the real-time visibility, collaborative responsiveness and strategic reconfigurability. This paper uses a 12-month empirical data sample from 124 manufacturing and distribution firms in the world across four major industry segments (Automotive Systems, Heavy Machinery, Consumer Electronics, and Medical Supplies) to highlight the significant performance difference between high-capability and low-capability infrastructure networks. We test and validate three research propositions that revolve around Data Visibility Latency Minimization as a mediating variable between the two independent variables, Cross-Functional Strategic Alignment and Data Culture, with the aim of discovering whether this mediating role is indeed present.In order to determine whether Data Visibility Latency Minimization is indeed a structural mediator between the two independent variables, Cross-Functional Strategic Alignment and Data Culture, three research propositions were developed and tested and validated. Last but not least, we set up a rigorous path estimation methodology by applying the Covariance-Based Structural Equation Modeling (CB-SEM) matrix equations to validate the relationships. Finally, a roadmap of action for tech directors and operations executives who want to make their supply chains as robust as possible in the face of structural economic crises is provided in the paper.