Time and Cost Variations on Performance of Infrastructure Development in Kenya: A Case Study of LAPSSET Corridor Development Authority


Authors : Nancy Mukami; Dr. Domeniter Kathula

Volume/Issue : Volume 10 - 2025, Issue 10 - October


Google Scholar : https://tinyurl.com/2wakvjsm

Scribd : https://tinyurl.com/38hmpxvk

DOI : https://doi.org/10.38124/ijisrt/25oct119

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Abstract : Infrastructure development is vital for socio-economic advancement, providing the foundation for economic growth, social progress, and improved quality of life. In Kenya, major projects such as the Standard Gauge Railway (SGR) and the LAPSSET Corridor have become central to the national development agenda. However, these initiatives often face significant challenges, particularly regarding time delays and cost overruns. This study focused on the LAPSSET Corridor Development Authority (LCDA) to examine how the Schedule Performance Index (SPI), and Cost Performance Index (CPI) influence infrastructure development performance. The research aimed to provide actionable recommendations to improve project management practices, enhance stakeholder collaboration, and promote sustainable infrastructure development in Kenya. The findings are intended to guide policymakers and project managers in addressing persistent delays and cost overruns, ensuring more efficient and cost-effective project delivery. Study was grounded in the Resource-Based View, Institutional Theory, and Goal-Setting Theory. The target population consisted of 100 participants, and a census approach was used for sampling. Data were analyzed using SPSS v.28, and inferential statistics were employed to assess the relationships between variables, while ethical guidelines were strictly observed. Results revealed that LCDA performance was significantly and positively correlated with SPI, suggesting that improving schedule performance would enhance overall project outcomes. Similarly, CPI showed a strong positive correlation with performance, indicating the importance of effective cost management. Depending on SPI results, it may be necessary to revisit the schedule baseline or implement adjustments such as expanding teams, reallocating tasks, or designing more flexible future schedules and suggests further research to identify additional factors influencing LCDA performance.

Keywords : LAPSSET Corridor Development Authority, Schedule Performance Index, and Cost Performance Index, Infrastructure Development Performance.

References :

  1. Afzal, F., Yunfei, S., Sajid, M., & Afzal, F. (2020). Integrated priority decision index for risk assessment in chaos: cost overruns in transport projects. Engineering, Construction and Architectural Management, Vol. 27(4), 825-849.
  2. Asiedu, R., & Adaku, E. (2020). Cost overruns of public sector construction projects: a developing country perspective. International Journal of Managing Projects in Business, Vol. 13(1), 66-84.
  3. Awuzie, B., Mcwari, Z., Chigangacha, P., Aigbavboa, C., Haupt, T., & Obi, L. (2024). Analysing outsourced and insourced public infrastructure projects’ performance in a provincial department of public works: a grounded theory approach. Journal of Engineering, Design and Technology, 22(2), 456-479.
  4. Babatunde, S., Ekundayo, D., Udeaja, C., & Abubakar, U. (2022). An investigation into the sustainability practices in PPP infrastructure projects: a case of Nigeria. Smart and Sustainable Built Environment, 11(1), 110-125.
  5. Clayson, D., Thal, J. A., & White III, E. (2018). Cost performance index stability: insights from environmental remediation projects. Journal of Defense Analytics and Logistics, 2 (2), 94-109.
  6. Enns, C., & Bersaglio, B. (. (2020). On the coloniality of "new" mega‐infrastructure projects in East Africa. Antipode, 52(1), 101-123.
  7. Ibrahim, M., Thorpe, D., & Mahmood, M. (2019). Risk factors affecting the ability for earned value management to accurately assess the performance of infrastructure projects in Australia", Construction Innovation, 19(4), 550-569.
  8. Kakar, A., Hasan, A., Jha, K., & Singh, A. (2024). Project cost performance factors in the war-affected and conflict-sensitive Afghan construction industry. Journal of Engineering, Design and Technology,22 (5), 1570-1590.
  9. Kakar, A., Hasan, A., Jha, K., & Singh, A. (2024). Project cost performance factors in the war-affected and conflict-sensitive Afghan construction industry", Journal of Engineering, Design and Technology,22(5), 1570-1590.
  10. Lee, C. (2019). Financing method for real estate and infrastructure development using Markowitz’s portfolio selection model and the Monte Carlo simulation. Engineering, Construction and Architectural Management, 26 (9), 2008-2022.
  11. Ma, G., & Wu, M. (2020). A Big Data and FMEA-based construction quality risk evaluation model considering project schedule for Shanghai apartment projects. International Journal of Quality & Reliability Management, 37 (1), 18-33.
  12. Mahabir, R., & Pun, K. (. (2022). Revitalizing project management office operations in an engineering-service contractor organisation: a key performance indicator-based performance management approach". Business Process Management Journal, 28(4), 936-959.
  13. Mahmud, A., Ogunlana, S., & Hong, W. (2022). Understanding the dynamics of cost overrun triggers in highway infrastructure projects in Nigeria: a systems thinking modelling approach. Journal of Financial Management of Property and Construction, 27 (1), 29-56.
  14. NASEM. (2021). Evaluation and Enhancement of Infrastructure Performance, Washington, DC. : The National Academies Press, .
  15. Oliveros-Romero, J., & Paton-Cole, V. (2023). Infrastructure development: reflections on Sierra Leone infrastructure scheme and the Lungi Bridge project. Journal of Financial Management of Property and Construction, 28(1), 127-144.
  16. Onuoha, F. C., & Agbede, M. O. (2019). Impact of disaggregated public expenditure on the unemployment rate of selected African countries: A panel dynamic analysis. Journal of Economics, Management and Trade, 24(5), 1-14.
  17. Salhab, D., Lindhard, S., & Hamzeh, F. (2024). Schedule compression and emerging waste in construction: an assessment of overlapping activities. Engineering, Construction and Architectural Management, 31 (12), 4920-4941.
  18. Scala, N., Alves, T., Hawkins, D., & Schiavone, V. a. (2024). Application of the maturity model for collaborative scheduling for construction projects", Engineering, Construction and Architectural Management,23(3).
  19. Seidu, S., Owusu-Manu, D.-G., Kukah, A., Adesi, M., Oduro-Ofori, E., & Edwards, D. (2023). An assessment of the implications of disruptive technologies on the performance of energy infrastructure projects in Ghana. International Journal of Energy Sector Management, 17 (5), 887-903.
  20. Sun, M., & Zhang, T. (2023). A real-time production scheduling method for RFID-enabled semiconductor back-end shopfloor environment in industry 4.0", IIMBG Journal of Sustainable Business and Innovation, 1 (1), 39-57.
  21. Teng, T., & Tsinopoulos, C. (2022). Understanding the link between IS capabilities and cost performance in services: the mediating role of supplier integration", Journal of Enterprise Information Management, 35(3), 669-700.
  22. Yang, J.-B., & Lai, T.-H. (2024). Selecting EVM, ESM and EDM(t) for managing construction project schedule", . Engineering, Construction and Architectural Management, 31 (12,), 4988-5006.

Infrastructure development is vital for socio-economic advancement, providing the foundation for economic growth, social progress, and improved quality of life. In Kenya, major projects such as the Standard Gauge Railway (SGR) and the LAPSSET Corridor have become central to the national development agenda. However, these initiatives often face significant challenges, particularly regarding time delays and cost overruns. This study focused on the LAPSSET Corridor Development Authority (LCDA) to examine how the Schedule Performance Index (SPI), and Cost Performance Index (CPI) influence infrastructure development performance. The research aimed to provide actionable recommendations to improve project management practices, enhance stakeholder collaboration, and promote sustainable infrastructure development in Kenya. The findings are intended to guide policymakers and project managers in addressing persistent delays and cost overruns, ensuring more efficient and cost-effective project delivery. Study was grounded in the Resource-Based View, Institutional Theory, and Goal-Setting Theory. The target population consisted of 100 participants, and a census approach was used for sampling. Data were analyzed using SPSS v.28, and inferential statistics were employed to assess the relationships between variables, while ethical guidelines were strictly observed. Results revealed that LCDA performance was significantly and positively correlated with SPI, suggesting that improving schedule performance would enhance overall project outcomes. Similarly, CPI showed a strong positive correlation with performance, indicating the importance of effective cost management. Depending on SPI results, it may be necessary to revisit the schedule baseline or implement adjustments such as expanding teams, reallocating tasks, or designing more flexible future schedules and suggests further research to identify additional factors influencing LCDA performance.

Keywords : LAPSSET Corridor Development Authority, Schedule Performance Index, and Cost Performance Index, Infrastructure Development Performance.

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Paper Submission Last Date
31 - December - 2025

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