IMES LOGIC MODEL AND THE PERFORMANCE OF ROAD PROJECT IN KENYA

Olympia Muhanga Musonye, Dr. Peter Ngatia, Prof. Patrick Karanja Ngugi

Abstract


This study sought to establish the relationship between IMES logic model and the performance of road projects in Kenya through hypothesis testing and at the same time establish the moderating effect of Project Risks on the relationship between IMES logic model and performance of road projects in Kenya. The unit of analysis was the road construction projects implemented by National Government Road Agencies (KURA, KeRRA, and KeNHA) in Kenya, while the unit of observation was the project managers involved in the implementation of these road construction projects. The population for the research was 188 projects initiated and completed between the year 2015 and 2022 by the three agencies. The overall sample size for this study was determined using a formula by Fisher’s exact formula, which obtained 126 respondents. This study employed stratified random and purposive sampling method to select the study sample. Primary data was used and was collected using a semi-structured questionnaire. Samples of the questionnaire were pilot tested with 18 respondents to test for reliability and validity. The data was analyzed using the Statistical Package for Social Sciences (SPSS). The qualitative data collected was analyzed using thematic analysis and presented in text form. Quantitative data was analyzed using descriptive statistics and presented in tables and figures. The study concluded that evaluation logic model positively and significantly influences performance of road projects in Kenya. In addition, the study concluded that project risks have significant moderating effect on the relationship between integrated monitoring and evaluation systems and performance of road projects in Kenya. Based on the findings, the study recommends that the management of road projects in Kenya should integrate real-time data monitoring and feedback mechanisms within the logic model framework. By embedding continuous performance tracking into the evaluation process, project managers can make timely and informed decisions, promptly address emerging challenges, and align implementation strategies with desired outcomes. In addition, the study recommends that the management of road projects in Kenya should embed proactive risk management protocols within the M&E framework. This involves identifying potential risks early in the project lifecycle and continuously assessing their likelihood and impact through the M&E system.

 

Key Words: IMES Logic Model, Project Risks, Performance of Road Project

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References


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