Empirical Validation and Enhancement of ADiBA: A Framework for Big Data Analytics Implementation

Abstract

The implementation of Big Data Analytics (BDA) in organisations requires a structured approach to ensure alignment with strategic goals and infrastructure readiness. This study presents an enhanced version of the previously published ADiBA (Accelerating Digital Transformation Through Big Data Adoption) framework that aimed at guiding organizations through critical components necessary for successful BDA implementation. The initial framework was developed based on systematic literature review. To validate and refine the framework, a mixed-methods survey was conducted among domain experts using a five-point Likert scale and open-ended questions to assess the relevance of each framework component. Quantitative responses were analysed using the Content Validity Index (CVI), with a threshold of 0.78 adopted as the minimum acceptable I-CVI score for each item. Complementing the quantitative analysis, qualitative feedback from the open-ended survey responses, Focus Group Discussions (FGDs), and in-depth interviews were examined through thematic analysis, revealing key themes related to framework’s clarity and operational aspects. Insights from both analyses informed the refinement of several components. The resulting framework is a validated and empirically-informed guide designed to support effective BDA implementation in organizational contexts.