Enhancing Supply Chain Agility and Performance through Big Data Analytics: The Role of Digitalization and Top Management Support

Purpose: This study aims to examine the relationships between big data analytics capabilities (BAC), supply chain digitalization (SCD), supply chain agility (SCA), and supply chain performance (SCP), while assessing the moderating role of top management support (TMS) in these relationships. It seeks to advance understanding of how digital transformation and leadership support enhance supply chain agility and performance outcomes. Design/methodology/approach: This study applies regression modeling to survey data collected from manufacturing firms. The model examines the direct effects of BAC on SCA and SCP, while assessing the mediating role of SCA and the moderating influence of SCD and TMS. The analysis also explores how these relationships contribute to sustainable supply chain performance outcomes. Findings: The results demonstrate that BAC positively influences SCA, which in turn enhances SCP. SCD amplifies the effect of BAC on SCA, while TMS significantly moderates the relationships between SCD and both BAC-SCA and SCA-SCP. These findings suggest that digital technologies and leadership support jointly drive supply chain agility and performance in dynamic business environments. Originality/value: This study contributes to supply chain management literature by integrating BAC, SCD, and TMS into a comprehensive framework that elucidates their combined effects on agility and performance. It highlights the strategic importance of digital transformation and top management support in fostering agile and high-performing supply chains, offering actionable insights for managers and policymakers.