Factors Influencing the Completion of Renewable Energy Infrastructural Projects: a Case of Kengen Company, Nakuru County

Abstract

This report is tasked with the objective of analyzing the success factors for infrastructural development projects in the renewable energy sector in Kenya, the case of KenGen Company Ltd, Nakuru County. The objectives guiding this research are to establish the level to which capital availability, top management team support, training of project team and technical team competence affect the development and completion of infrastructural projects in the renewable energy sector. The study used descriptive survey design method which encompasses measurement, classification, contrast and interpretation of data. This method is appropriate as it is used in assembling data from a comparatively great number of circumstances at a specific interval. The target population for the study included staff drawn from Management, with a total population of 2831 employees of KenGen Company Ltd. A sample of 340 as obtained by application of Krejcie and Morgan table from the total population of 2831 was interviewed by use of questionnaire to generate response required for the study. The researcher collected data through personally-administered questionnaire method which is suitable as it reaches a large number of subjects who are literate. A pilot study was channeled beforehand the real study was done to ascertain the reliability of the questionnaires in collecting the data and involved 34 respondents picked randomly from the groups to show how closely related a set of items are as a group in order to give logical deduction. To ensure content validity of the instruments, the researcher thoroughly checked with the Supervisor who aided in quantifying the variables to be measured by the instruments and also aided in influencing whether or not the set of articles were precisely representative of the variables under study. A split-half method was used to test for reliability where the items in the instrument were separated obsessed by two sub groups of even and odd numbered items given to a few respondents and the results interrelated. The data collected was scrutinized by use of descriptive statistics where the responses from the questionnaires were tallied, tabulated and analyzed using percentages, frequencies, mean and standard deviation. The data was further analyzed using correlation, analysis. The study revealed that the respondents were homogeneous in how they perceived the research questions and this led to consistency in response. Findings for capital availability revealed measure of central tendency of slightly high mean of 4.088 and standard deviation of 0.953. Findings for top management team support revealed a measure of central tendency of mean of 3.936 and standard deviation of 1.048. For training, measure of central tendency indicated a mean of 3.34 and standard deviation of 1.302. For technical team competency, measure of central tendencies of mean 3.588 and standard deviation of 1.255 was obtained. Pearson correlation analysis was conducted on the data and it was found that the response on how the independent variables affect the dependent variable were correlated with the correlation coefficient of between capital availability against top management support being highest at 0.9809 and capital availability against training of project staff being lowest at 0.6135. The study concluded that all the four independent variables influence significantly the implementation of infrastructural projects in KenGen. Measures need to be put in place to ensure that success of implementation of infrastructural projects in assured through capital availability, top management team support, proper training and technical team competency in order to successfully addressed repeated episodes of project failures as seen in many infrastructure build up. It is recommended that the independent variables mentioned should be strengthened through a collective effort of the project leadership in order to successfully address the problem. The researcher recommended that similar studies be conducted in other energy sectors of the country and other independent variables be studied on too.