A Model for Enhancing the Application of Value Management in Construction Projects in Kenya

Abstract

Value Management (VM) has been widely used in the construction industry to facilitate projects for decades in many countries around the globe. The concept began in the US while other nations such as China, Japan, South Africa, and Nigeria have tested its effectiveness through assessing its impacts on costs, quality, and time. A VM application has a low cost with a high benefit process, and thus if well-practiced and integrated into project management at the beginning of projects, it would lead to their successful completion. It also helps in improving the value of the project by ensuring low costs, high quality, and completion within the stipulated time frame. In Kenya, there remains a gap in that very little has been documented about VM application in construction projects. The study sought to evaluate and develop a model to enhance the application of value management in construction projects in Kenya. More specifically, the study sought to; establish the level of application of VM in construction projects, examine the determinants that influence the level of application of VM in construction projects,determine the relationship between the level of application of VM in construction projects in Kenya and its determinants, and formulate a model for enhancing the implementation of VM in construction projects in Kenya. The study sampled registered key built environment consultants in Kenya, who comprise of Engineers, Architects, and Quantity Surveyors. Stratified sampling strategy was employed and data analysis was conducted using Statistical Package for Social Sciences (SPSS). The analysis methods used in this research were descriptive and inferential statistics. Data summaries in terms of frequencies, mean and standard deviations were obtained under descriptive analysis. The inferential analysis comprised of Pearson’s correlation and regression analysis which determined the significant determinants of VM application and were used to establish a predictive model. The study established that the level VM application was moderate (mean=3.15, std dev=1.34). Further descriptive statistics showed that the four determinants had a moderate performance as well; VM knowledge and awareness (mean=3.14, std dev=0.95), Team dynamic factors (mean=2.83, std dev=0.69), Government regulation factors (mean= 3.18, std dev=0.63), and procurement policy factor (mean=3.68, std dev= 0.615). Pearson correlational analysis revealed that the four predictor variables had a statistically significant influence on VM application in construction projects in Kenya. The study made the following recommendations; proper identification of the project teams and promoting communication within the teams, mapping out the procurement processes, and organizing value management training among the employees.