This study aims to examine how the implementation of big data analytics (BDA) influences operational performance and supply chain resilience in China's manufacturing sector. It aims to explain the mechanisms through which BDA contributes to both immediate efficiency gains and long-term adaptability, drawing on the Dynamic Capabilities Theory (DCT).
A mixed-method approach was adopted. Quantitative analysis was conducted using survey data from 304 manufacturing firms, analyzed through structural equation modelling. To complement the statistical findings, two in-depth case studies were carried out to provide contextual insights into how BDA initiatives are implemented and managed in practice.
The results show that BDA implementation significantly enhances operational performance and supply chain resilience. Dynamic capabilities partially mediate the relationship between BDA adoption and supply chain resilience, indicating that BDA not only drives short-term operational improvements but also fosters long-term strategic adaptability. Case study evidence further demonstrates that firms' motivations, process focus, and implementation strategies shape the performance outcomes of BDA adoption.
The study focuses on manufacturing firms in China, which may limit the generalisability of the findings to other sectors or regions. Future research could explore cross-country comparisons and longitudinal designs to capture the evolving role of BDA and dynamic capabilities in global supply chain resilience.
This study advances understanding of BDA by showing that its strategic value extends beyond process efficiency to the development of dynamic capabilities that enhance long-term agility and adaptability. It demonstrates that performance outcomes depend on how BDA is strategically aligned with organisational priorities, while strategic integration drives sustained competitive advantage. The research reframes BDA as a capability enabler rather than a technological tool, emphasizing the need for learning environments, predictive analysis, collaborative practices, and data-driven decision-making to unlock its transformative potential for supply chain resilience and competitiveness.
