A comprehensive framework for big data analytics capabilities and competitive advantage in South Africa

Abstract

This study examines the contribution of big data analytics capabilities to gaining competitive advantage in South African businesses. The study is underpinned by the resource-based theory and dynamic capabilities theory and develops and tests a conceptual model that positions big data analytics capabilities as a multidimensional construct comprising tangible, human, and intangible resources. The study also examines the mediating role of dynamic and operational capabilities in linking big data analytics capabilities to improve competitive advantage. An exploratory sequential mixed method design was employed. The qualitative phase employed semi-structured interviews with high-level executives from various industries to determine the contextual challenges and success factors for implementing big data analytics in South Africa. The outcomes of this phase guided the application of a survey instrument in the quantitative phase where feedback was collected from 110 business leaders. The results were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that big data analytics capabilities have a significant positive effect on dynamic capabilities, which in turn have a substantial impact on competitive advantage. However, operational capabilities revealed no impact on competitive advantage. The study also highlights context-specific challenges such as skills shortages, infrastructure constraints, organisational readiness, and regulatory requirements impacting the adoption of big data analytics capabilities in South Africa. This research contributes to practice as well as theory by applying big data analytics capabilities literature to a developing market context, confirming dynamic capabilities as a driver of competitive advantage. The research also provides business leaders with practical insights into how to develop and deploy big data analytics capabilities. The study also offers a conceptually rich framework and proposes directions for further study to improve the understanding of big data analytics in dynamic and constrained environments. In addition, the study recommends that South African businesses invest in developing dynamic capabilities, talent, and data-driven cultures, while policymakers prioritise digital infrastructure, funding incentives, and regulatory frameworks to support adoption. Limitations include the cross-sectional design, reliance on self-reported data, focus on medium-to-large firms, and restriction to the South African context, which limit generalisability but open avenues for longitudinal and cross-sectoral research.