The Impact of Data Infrastructure, Management, and Technology on Business Analytics Usage in the Sri Lankan Banking Sector.

Abstract

Business analytics has become a powerful tool worldwide for data-driven decision making. However, the banking sector of Sri Lanka is still adapting to advanced analytical tools and is facing several challenges. Additionally, it is rare to find studies from the Sri Lankan context that attempt to identify the relationship between the technological context and business analytics usage (BAU). Thus, this research was conducted to investigate the interplay between BAU and three key technological dimensions in the form of Data-Related Infrastructure Capabilities (DIC), Data Management Challenges (DMC), and Technology Supporting Infrastructure (TSI). To achieve this objective, a quantitative method with a deductive approach is employed. A structured questionnaire with five-point Likert scale items was distributed among a sample of 220 bank employees in Sri Lanka. Structural Equation Modeling (SEM) was employed as the primary analysis technique. The findings reveal that DIC, DMC, and TSI all positively and significantly impact BAU. DMC emerged as the most influential factor, followed by TSI. These insights provide valuable implications for managerial decision-makers in the banking industry, guiding them to implement business analytics tools within their organizations. This study offers the basis for further studies to examine the broader frameworks of technological adoptions in financial institutions in Sri Lanka, in which they can consider technological dimensions as moderators or mediators.