Logo image
Big data management, knowledge management and institutional support as predictors of SME’s competitiveness
Dissertation   Open access

Big data management, knowledge management and institutional support as predictors of SME’s competitiveness

Mashango Philemon Sithole
Doctor of Philosophy (PHD), University of Johannesburg
2025
Handle:
https://hdl.handle.net/10210/521391

Abstract

This study investigates how Big Data Management, Knowledge Management, and Institutional Support function as predictors of SME competitiveness in South Africa, with Innovation Capability acting as a mediating mechanism and Network Integration serving as a moderating factor. In an era of digital disruption, institutional volatility, and resource scarcity, small and medium-sized enterprises (SMEs) in emerging economies face mounting challenges in sustaining competitiveness. Within the South African context, where SMEs are central to employment creation and economic transformation, many firms continue to exhibit limited innovation capacity, weak absorptive potential, and poor integration into institutional and relational ecosystems. Existing scholarship often examines internal capabilities and external enablers in isolation, offering limited insight into their interactional dynamics. As such, in addressing that gap, the study integrates these dimensions to explain how firms convert technological, knowledge-based, and institutional inputs into competitive advantage. The study is anchored in two theories, Dynamic Capabilities Theory (DCT) and Social Exchange Theory (SET). Thus, competitiveness is conceptualised as a multi-dimensional construct arising from the orchestration of internal capabilities and external relational mechanisms. Accordingly, a quantitative explanatory design, informed by a positivist paradigm, was adopted. Data were collected from a purposive and stratified sample of 334 SMEs participating in formal enterprise development programmes across South Africa. The analysis process followed Structural Equation Modelling (SEM), supported by Confirmatory Factor Analysis, was employed to assess reliability, validity, and model fit. The findings reveal that Big Data Management, Knowledge Management, and Institutional Support each exert significant positive effects on Innovation Capability, which emerged as the strongest predictor of SME Competitiveness. Innovation Capability mediates the Knowledge Management-Competitiveness relationship. This highlights the SME’s role as a strategic transformation mechanism that converts learning-based resources into performance outcomes. Moreover, Network Integration exerts both a direct effect on competitiveness and a moderating effect on the Institutional Support-Competitiveness pathway, confirming the contingent value of relational embeddedness. A central contribution of the study is the development and empirical validation of the Capability-Relational Competitiveness (CRC) Framework, which captures how SMEs orchestrate data, knowledge, and institutional resources through innovation and network...
pdf
Sithole MP- Final Thesis (1)3.99 MBDownloadView
Open Access

Metrics

1 Record Views

Details

Logo image