Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia

Abstract

All across the world, the construction industry is a very crucial sector for development. Cost prediction is the process of forecasting the cost of construction projects at an early stage. An effective estimation technique is necessary to reduce the effort, time, and cost. Therefore, the study aims to develop a mathematical model to predict the cost of Ethiopian Roads Authority road projects in the case of Ethiopia. The data were collected from primary and secondary sources. The method of data analysis for the study was multiple regression analysis, and it was done using SP SS and Microsoft Excel. The data were obtained from a road document review and a questionnaire survey of 62 respondents and 15 interviewers who are working in ERA. The major cost-influential factors were found to be: inflation rate, bridges, culverts, project length, width, type and scope, contract duration, and location. As a result, a multiple regression model was developed using nine significant parameters taken from 18 completed road projects. The multiple regression analysis result revealed that the model can perform at a success rate of 83.8%. The MAPE of the model was ±16.44%. The conclusion and recommendations are likely to support and reduce ineffective estimation trends.

Impact Statement

Road construction projects play a vital role in the development of infrastructure, ensuring safe and efficient transportation for communities. However, cost overruns and lack cost estimation tools in road projects have been a persistent challenge, leading to budget constraints and delays. To address this issue, we propose the development of a mathematical model that can accurately predict the cost of road projects. This innovative solution aims to enhance cost estimation accuracy, optimize resource allocation and foster responsible financial planning.

Keywords:

• Cost prediction
• project cost
• regression model
• road projects
• Roads Authority
• Mathematical Model

Reviewing Editor:

• Sanjay Kumar Shukla, Edith Cowan University, Australia

Subjects:

• History of Engineering & Technology
• Civil Engineering History
• Engineering Management
• Civil, Environmental and Geotechnical Engineering
• Engineering Economics

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Sisay Birhanu Belete

Sisay Birhanu Belete is a lecturer at Assosa College of Engineering, Assosa University, P.O. Box 18, Assosa, Ethiopia. He received his MSc degree in Construction Engineering and Management from the University of Gondar, Ethiopia. His research interest includes Regression Modeling, Cost Prediction and Project Management

Meseret Getnet Meharie

Meseret Getnet Meharie, PhD, is a senior lecturer at Adama Science and Technology University, Adama, Ethiopia. He is an Assistant professor at Adama Science and Technology University, Adama, Ethiopia. His research interest includes Cost Estimation of Construction Projects, Maintenance management, Fuzzy AHP and Machine learning algorithm in predicting the cost of highway projects.

Girmay Getawa Ayalew

Girmay Getawa Ayalew is currently a lecturer at Woldia Institute of Technology, Woldia University, P.O. Box 400, Woldia, Ethiopia. He is former lecturer at Gondar Institute of Technology, University of Gondar, P.O. Box 196, Gondar, Ethiopia. He received his MSc degree in Construction Engineering and Management from the University of Gondar, Ethiopia. His research interest includes Fuzzy AHP, Performance Management and Maintenance management.