Original Research

A model for using knowledge management systems to improve decision-making within the South African energy sector

Masehlabane J. Mamogobo, Agnieta B. Pretorius, Stevens P. Mamorobela
South African Journal of Information Management | Vol 28, No 1 | a2073 | DOI: https://doi.org/10.4102/sajim.v28i1.2073 | © 2026 Masehlabane J. Mamogobo, Agnieta B. Pretorius, Stevens P. Mamorobela | This work is licensed under CC Attribution 4.0
Submitted: 14 August 2025 | Published: 22 January 2026

About the author(s)

Masehlabane J. Mamogobo, Department of Informatics, Faculty of Information and Communication Technology, Tshwane University of Technology, Pretoria, South Africa
Agnieta B. Pretorius, Department of Informatics, Faculty of Information and Communication Technology, Tshwane University of Technology, Pretoria, South Africa
Stevens P. Mamorobela, Department of Information Systems, School of Computing, University of South Africa, Johannesburg, South Africa

Abstract

Background: Organisations in the energy sector play a vital role in ensuring the stability of the national energy supply. Effective knowledge-driven decision-making is of paramount importance to deliver stable energy in the sector. However, many organisations in the energy sector continue to experience low uptake and limited integration of Knowledge Management Systems (KMSs) into operational processes, despite their recognised benefits in supporting evidence-based decision-making and preserving organisational knowledge.
Objectives: This research aimed to develop a model for the use of KMSs to improve decision-making within the South African energy sector.
Method: This study employed a quantitative research approach, utilising closed-ended questionnaires, to collect data from 150 respondents within an organisation in the South African energy sector, aiming to determine the technological, organisational and environmental factors that influence the use of KMSs. The collected data were then analysed using IBM Statistical Package for Social Sciences (SPSS).
Results: The results indicate that self-efficacy, usefulness, motivational culture, performance expectancy and policies and standards are the strongest predictors of behavioural intention to use the KMSs within the South African energy sector. The correlation results further confirmed significant positive associations between perceived usefulness, organisational support and the intention to adopt the system.
Conclusion: The developed model highlights the importance of addressing individual confidence, organisational culture and clear governance models to promote effective KMS usage. The model serves as a guide for the implementation and integration of KMSs to improve knowledge-enabled decision-making in the operational processes of organisations in the South African energy sector.
Contribution: This study contributes an empirically validated model for supporting KMS usage in the energy sector. The model can inform policy development, training programmes and system design to strengthen knowledge management practices in similar organisational contexts.


Keywords

Knowledge Management Systems; decision-making; UTAUT; TOE; energy sector.

JEL Codes

D83: Search • Learning • Information and Knowledge • Communication • Belief • Unawareness

Sustainable Development Goal

Goal 4: Quality education

Metrics

Total abstract views: 201
Total article views: 131


Crossref Citations

No related citations found.