Financial Mitigation Measures – Journal of Research Innovation and Implications in Education https://www.jriiejournal.com Fri, 02 Oct 2026 16:10:35 +0000 en-US hourly 1 https://wordpress.org/?v=7.1.2 https://www.jriiejournal.com/wp-content/uploads/2019/02/cropped-JRIIE-LOGO-1-32x32.jpg Financial Mitigation Measures – Journal of Research Innovation and Implications in Education https://www.jriiejournal.com 32 32 194867206 Assessment of Price Fluctuations and Delays of Construction Projects in Rwanda: A Case Study of Kigali City https://www.jriiejournal.com/assessment-of-price-fluctuations-and-delays-of-construction-projects-in-rwanda-a-case-study-of-kigali-city/?utm_source=rss&utm_medium=rss&utm_campaign=assessment-of-price-fluctuations-and-delays-of-construction-projects-in-rwanda-a-case-study-of-kigali-city https://www.jriiejournal.com/assessment-of-price-fluctuations-and-delays-of-construction-projects-in-rwanda-a-case-study-of-kigali-city/#respond Fri, 02 Oct 2026 16:08:36 +0000 https://www.jriiejournal.com/?p=13096 Read More Read More

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Uwamahoro Pacifique and Daniel Mburamatare
University of Kigali
https://orcid.org/0009-0007-5645-4246
Email: uwamahoropacifique045@gmail.com

Abstract: This study assessed the impact of price fluctuations on construction project delays in Kigali City, Rwanda. Three dimensions were examined: inflation-induced price fluctuations, construction-resource price fluctuations, and financial mitigation measures. A descriptive survey supplemented by correlational analysis was adopted within a mixed-methods study. The target population comprised 302 construction stakeholders, including project managers, civil engineers, quantity surveyors, and project supervisors, while a sample of 173 was determined using Slovin’s formula. Questionnaires, interviews, and documentary review were used in the dissertation, while the manuscript reports the quantitative strand. Of 155 questionnaires reported as administered, 149 were completed and returned, representing 96.1%. Quantitative data were analysed using descriptive statistics, Pearson correlation, and multiple regression. The combined model explained 83.6% of the variation in construction project delays (R = 0.914, R² = 0.836). Inflation indicators had the strongest significant effect (B = 0.454, t = 12.270, p = 0.000), construction-resource price fluctuations were also significant (B = 0.235, t = 4.468, p = 0.000), and financial mitigation measures produced a statistically significant contribution (B = 0.135, t = 1.776, p = 0.030). The study concluded that price instability materially contributes to delays and that mitigation mechanisms remain important for sustaining construction delivery. It recommends stronger price-adjustment provisions, contingency budgeting, forward purchasing, improved access to project finance, and continuous market monitoring during project implementation.

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