The study investigated the influence of project management practice on performance of building projects in Kenya. Despite devolution in management of building project, their performance is yet to be satisfactory. The objective was to examine the influence of project planning, resource scheduling, and monitoring and evaluation on performance of building construction projects in Kenya. From a sample of 151 respondents, 130 usable instruments were obtained. The majority of respondents 37 (28.5%) were relatively young professionals aged between 25 and 34 years. Quantity surveyors 25(16.6%) Architects 24 (15.9%) , contractors represented 28 (18.5%), clerks of works 25 (16.6%), project managers 27 (17.9%), while structural engineers were 16 (10.6%). In respect of project planning, descriptive results indicated moderate adoption of scope definition and resource allocation practice, and significant gaps in use of building information management and data analytics, work breakdown structure and risk management. Regarding schedule management, results show milestone setting and continuous monitoring are partially implemented, while advanced tools such as Microsoft Project and AI-driven scheduling are not widely adopted. In respect of monitoring and control, results show that while basic monitoring practices such as monitoring for delays and cost overruns, are relatively common, there is limited uptake of advanced monitoring tools such as mobile apps, drones, AI, and Earned Value Management. Data on project performance indicate moderate achievements in stakeholder satisfaction, regulatory compliance, occupational safety, and alignment with strategic goals. The correlation matrix shows that all three independent variables are positively and significantly correlated. A correlation of r = 0.642, p < 0.01, suggesting a strong positive relationship between Project Planning and performance of building projects. The results for Schedule Management (r = 0.613, p < 0.01) indicates that better scheduling techniques could improve performance of building projects. Correlation results for Project Monitoring & Control (r = 0.695, p < 0.01) show the strongest positive relationship, suggesting that a robust monitoring framework had the greatest influence on project performance. Multiple regression results revealed R = 0.782, indicating a strong combined relationship between the independent variables and project performance. The R2 = 0.611 implies that 61.1% of the variation in project performance can be explained by project planning, schedule management, and monitoring & control. The remaining 38.9% is attributed to other factors not captured in this model. The ANOVA show the model is statistically significant (F = 39.75, p < 0.001), suggesting that project planning, schedule management, and project monitoring and control had a positive and statistically significant effect on project performance. Specifically, the standardized coefficient of β = 0.316 (p < 0.001) for project planning indicates that strong planning practices significantly enhanced performance. Schedule management coefficient of β = 0.298 (p = 0.001), confirmed that well-executed scheduling processes contribute to project success. Project monitoring and control’s highest standardized coefficient at β = 0.376 (p < 0.001), suggests it is the most influential factor among the three. These findings provide empirical evidence that effective implementation of key project management practices has a substantial impact on the performance of county government construction projects. The influence of all variables on performance is positive, with project monitoring and control being the strongest predictor, followed closely by planning and then schedule management. The findings suggest that robust monitoring frameworks, strategic planning, and realistic scheduling are foundational to delivering infrastructure projects on time, within budget, and according to quality expectations, within devolved governments in Kenya.
Gangla et al. (Fri,) studied this question.