Data analytics capabilities and organisational performance at an emerging economy’s local government assembly: the roles of top-management support and data driven decision making

This study examines the impact of Data Analytics Capability on organisational performance within an emerging economy’s local government assembly, with particular focus on the mediating role of Data-Driven Decision Making and the influence of Top Management Support. Grounded in the Organisational Information Processing Theory and the Upper Echelons Theory, the study adopts a cross-sectional survey explanatory design. Data was collected from 127 employees of the local assembly through structured online questionnaire and analysed using Partial Least Squares Structured Equation Modelling. The results reveal that DAC has no significant direct effect on organisational performance but exerts a strong positive effect on DDDM. In turn, DDDM significantly enhances organisational performance and mediates the relationship between DAC and performance. Additionally, TMS support significantly and directly influences organisational performance, although it does not moderate the DAC-performance relationship. The study concludes that DAC alone do not guarantee improved performance, rather, their value is realized through integration into decision-making processes. To the best of the authors’ knowledge, this study is among the first to provide empirical evidence from an emerging economy’s local government context demonstrating that DDDM is the critical pathway through which DAC translate into performance outcomes, while TMS operates as a direct driver rather than a conditional enhancer. This study contributes theoretically by refining the application of the OIPT and the UET in public sector analytics contexts and offers practical insights that performance improvements depend more on the use of data in decision-making than on the mere possession of analytics infrastructure.