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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Alain Symphorien Ndongo1,2, Destin Gemetone Etou1,2, Westinevy Benarez Ndzessou1,3 and Christian Armand Anicet Tathy1,4
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DOI:10.17265/2162-5298/2025.05.004
1. Laboratory of Energetic Mechanics and Engineering (LMEI), National Polytechnic School, Marien Ngouabi University, Brazzaville BP 69, Congo 2. National Superior Polytechnic School (ENSP), University Marien Ngouabi, Brazzaville BP 69, Congo 3. Higher Institute of Architecture, Urban Planning, Building and Public Works (ISAUBTP), Dénis Sassou Nguesso University, Brazzaville BP 69, Congo 4. Higher Normal School (ENS), University Marien Ngouabi, Brazzaville BP 69, Congo
In an environment where demand for housing is growing and the supply from public authorities is virtually non-existent, several mechanisms for housing production are emerging in the formal, semi-informal and informal construction sectors. The project owner wonders how much it costs to construct a building to an acceptable standard. Cost forecasting in general faces a number of difficulties, including a lack of available information during the preliminary phase of the project. As such, estimation becomes a crucial task involving great responsibility, which can lead to either more convincing results or chaotic situations. This study proposes a quick and effective method for estimating the cost of a single-storey F4 residential building. The modelling is done using multiple linear regression based on a statistical approach applied to twenty (20) projects that have already been completed. The project data are collected from design offices in the city of Brazzaville. The method expresses the cost of an F4 construction by certain project tasks, representing five (5) variables, three (3) of which are related to structural work and two (2) to finishing work, which are easy to determine. This approach, known as MECSO (Cost Estimation Model by Sub-structure), gives good results in all statistical tests carried out with reasonable confidence intervals. This method is very practical for engineering professionals working on the evaluation and control of construction costs.
Model, evaluation, estimation, cost, construction, F4.
Journal of Environmental Science and Engineering A 14 (2025) 245-255
141635794493951/pdf/Introducing-the-Adequate-Housing-
Index-AHI-A-New-Approach-to-Estimate-the-Adequate-Housing-Deficit-within-and-across-Emerging-Economies.
pdf.
[2] Habitat for Humanity. n.d. “What Is Affordable Housing?” www.habitat.org/emea/about/what-we-do/affordable-housing.
[3] ACRC. 2024. www.african-cities.org/wp-content/uploads/
2024/07/ACRC_Working-Paper-18_July-2024.pdf.
[4] World Bank. 2015. “Stocktaking of the Housing Sector in Sub-Saharan Africa: Challenges and Opportunities” https://www.worldbank.org/content/dam/Worldbank/document/Africa/Report/stocktaking-of-the-housing-sector-in-sub-saharan-africa-full-report.pdf.
[5] World Bank. 2015. “Stocktaking of the Housing Sector in Sub-Saharan Africa: Summary Report.” www.worldbank.
org/content/dam/Worldbank/document/Africa/Report/stocktaking-of-the-housing-sector-in-sub-saharan-africa-summary-report.pdf.
[6] Cadre Strategique de Developpement (CSD). 2022. “National Development Plan (PND) of the Republic of Congo for the 2022-2026 Financial Years.” https://gouvernement.cg/wp-content/uploads/2022/07/CSD-PND-2022-2026.pdf.
[7] National Institute of Statistics (INS). 2023. Fifth General Population and Housing Census (RGPH-5): Preliminary Results. Brazzaville: INS. (in French)
[8] Destin Gemetone Etou. 2021. “The Dysfunctions of Construction Project Management in Developing Countries: The Case of the Republic of Congo.” American Journal of Engineering Research (AJER) 10 (12): 202-7.
[9] Louzolo-Kimbembe, P. February 2005. “Contribution to Methods of Controlling Construction Costs in Developing Countries: Cost Estimation and Optimisation in a Non-time-bound Context.” Ph.D. thesis, Ecole Nationale Supérieure de Yaoundé (Cameroon).
[10] Manjia, M. B. March 2011. “A Model for Forecasting Construction Costs in Developing Countries: The Case of Cameroon. From Multiple Linear Regression to Artificial Neural Networks.” Ph.D. thesis, Ecole Nationale Supérieure de Yaoundé (Cameroon).
[11] Louzolo-Kimbembe, P., and Pettang, C. 2006. “Contribution to the Amelioration of the Estimation Method of Construction Cost’s Mastering in Developing Countries.” International Journal on Architectural Sciences 7 (1): 14-25.