Authors :
Isaya Soga Gangla; George kinoti Kingo'riah; Dr. Josiah Nyangaresi Nyagwachi
Volume/Issue :
Volume 10 - 2025, Issue 9 - September
Google Scholar :
https://tinyurl.com/yup3zyyn
Scribd :
https://tinyurl.com/3mj8zdh4
DOI :
https://doi.org/10.38124/ijisrt/25sep449
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Abstract :
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.
References :
- Acebes, F., Pajares, J., Galán, J. M., & López-Paredes, A. (2024). Critical Path Method in construction projects: A simulation approach. Automation in Construction, 48, 1-12.
- Adebayo, A., & Ncube, M. (2021). Challenges of Infrastructure Development in Africa: A Comparative Analysis. African Journal of Project Management, 5(1), 45–62.
- Aghimien, D., Aigbavboa, C., Oke, A., Thwala, W. D., & Khalfan, M. (2021). Digitalization in the construction industry: Examining the drivers and barriers. Journal of Construction Innovation, 21(4), 675–694. https://doi.org/10.1108/JCI-10-2020-0184
- Akintola, A. (2020). Project management methodologies and practices in Africa: Challenges and solutions. African Journal of Project Management, 5(1), 45-62.
- Alila, P. O., & Njoka, J. M. (2021). Decentralization and Its Effects on Local Governance in Kenya. Journal of African Studies, 12(4), 225–238.
- Alila, P., & Njoka, J. (2021). Public infrastructure project delivery and sustainability in Kenya. Kenya Institute for Public Policy Research and Analysis Report.
- Anyangu, S. P., & Ouma, M. A. (2020). Project Management Practices in Kenyan Counties: A Case of Road Construction Projects. International Journal of Project Management, 12(3), 74–85.
- Badiru, A. B. (2020). Project management methodologies: Theory and practice in developing countries. Global Project Management Review, 15(2), 102-115.
- Bertalanffy, L. (1968). General System Theory: Foundations, Development, Applications. George Braziller.
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.