Abstract:
The rise in technology in the various sectors of the industry has caught the
attention of organizations. Among the numerous developments, big data (BD)
has also become a great field of study. Despite the increasing global emphasis on
big data analytics (BDA) in optimizing supply chain operations, there remains a
significant gap in understanding the specific barriers to its adoption in
developing economies, particularly in Sri Lanka. While previous research has
emphasized the performance benefits of BDA, limited empirical work addresses
the challenges that hinder its implementation. This study addresses that gap by
empirically investigating the technological, organizational, and environmental
barriers to BDA adoption in the Sri Lankan manufacturing sector. This study
follows a quantitative approach to explore the barriers and adoption level of
BDA in supply chain operations within the manufacturing sector in Sri Lanka.
Using the Technology–Organization–Environment (TOE) framework and an
ordered probit regression model, we analyze data from 164 supply chain
professionals across multiple Sri Lankan manufacturing sector sub-sectors.
According to the findings of this study, the hypotheses, data quality,
technological infrastructure, data security, organizational culture, financial
constraints, talent management, regulatory support, and competitive pressure
have been accepted. Theoretically, this research extends the TOE framework by
validating its applicability in an underexplored context. It provides actionable
insights for policymakers and practitioners aiming to foster data-driven
transformation in emerging markets.
