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Predictors of Project Success at the South African Selected Energy State-Owned Enterprise

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dc.contributor.advisor Sebola. M. P. (Chief Editor)
dc.contributor.advisor Molokwane, T. S. (Quest Editor)
dc.contributor.author Mnisi, M. L.
dc.contributor.author Maleka, M. J.
dc.date 2022
dc.date.accessioned 2023-04-10T08:05:12Z
dc.date.available 2023-04-10T08:05:12Z
dc.date.issued 2022-09-14
dc.identifier.citation Mnisi, M. L. and M. J. Maleka (2022) Predictors of Project Success at the South African Selected Energy State-Owned Enterprise. Proceedings of the International Conference on Public Administration and Development Alternatives. 165-174.<http://hdl.handle.net/11602/2424>.
dc.identifier.isbn 9780992197193 (Print)
dc.identifier.isbn 9780992197186 (e-book)
dc.identifier.uri http://hdl.handle.net/11602/2424
dc.description Journal articles of The 7th Annual International Conference on Public Administration and Development Alternatives, 14 - 16 September 2022 en_ZA
dc.description.abstract The study aimed to identify which predictor predicts project success the highest at the selected South African Energy state-owned enterprises (SOE). This study is motivated by the highest failure rates of timeously implementing projects in time by SOEs in the South African context. The literature reviewed revealed many predictors of project success, but the common ones entail the governance committee, project manager, governance structures and project team. Hence in this study, the focus was on them. This study was quantitative and deductive, with a positivist paradigm influenced it. There were 130 employees involved in the projects at the business unit, and a census was used as a sampling strategy. Only 82 responded by completing a close-ended questionnaire which was distributed via SurveyMonkey. The response rate was 63.07%. Statistical techniques like Kurtosis and Skewness were used to determine if the data were normally distributed. Normality and other statistical techniques were calculated in Statistical Package for Social Science (SPSS) version 27. Through exploratory factor analysis (EFA), these factors were extracted: governance committee, project manager; governance structures and processes; project team and project success. For all the predictors and the target variable (i.e. project success), Cronbach's alphas ranged from 0.7 to 0.83. The data showed that 65.9% of the respondents were males and the Pearson correlation results showed that predictors positively correlated with the target variable. The regression results showed that project team was the highest predictor (β = 0.62, t = 5.15, p <0.01) and the second-highest predictor was project manager (β = 4.70, t = 4.70, p <0.01). The R-squared (r2) was 0.58, suggesting that the regression model only predicted 58% of project success at the selected energy SOE. Other predictors were not significant predictors of project success. The results imply that the business unit at the energy SOE should foster a teamwork culture and capitate and support project managers to enhance project success. en_ZA
dc.format.extent 1 online resource (9 pages)
dc.language.iso en en_ZA
dc.relation.requires PDF
dc.subject Governance committee en_ZA
dc.subject Project manager en_ZA
dc.subject Governance structures and processes en_ZA
dc.subject Project team and project success en_ZA
dc.title Predictors of Project Success at the South African Selected Energy State-Owned Enterprise en_ZA
dc.type Article en_ZA


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