Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia
AbstractAll 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 stu...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/23311916.2023.2297492 |
| _version_ | 1797354070195830784 |
|---|---|
| author | Sisay Birhanu Belete Meseret Getnet Meharie Girmay Getawa Ayalew |
| author_facet | Sisay Birhanu Belete Meseret Getnet Meharie Girmay Getawa Ayalew |
| author_sort | Sisay Birhanu Belete |
| collection | DOAJ |
| description | AbstractAll 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. |
| first_indexed | 2024-03-08T13:39:58Z |
| format | Article |
| id | doaj.art-1cc8889b55f446edbd4f499029f3b6e4 |
| institution | Directory Open Access Journal |
| issn | 2331-1916 |
| language | English |
| last_indexed | 2024-03-08T13:39:58Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Cogent Engineering |
| spelling | doaj.art-1cc8889b55f446edbd4f499029f3b6e42024-01-16T10:40:48ZengTaylor & Francis GroupCogent Engineering2331-19162024-12-0111110.1080/23311916.2023.2297492Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of EthiopiaSisay Birhanu Belete0Meseret Getnet Meharie1Girmay Getawa Ayalew2College of Engineering, Department of Construction Technology and Management, Assosa University, Assosa, EthiopiaSchool of Civil Engineering and Architecture, Department of Civil Engineering, Adama Science and Technology University, Adama, EthiopiaSchool of Civil and Water Resource Engineering, Department of Construction Technology and Management, Institute of Technology, Woldia University, Woldia, EthiopiaAbstractAll 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.https://www.tandfonline.com/doi/10.1080/23311916.2023.2297492Cost predictionproject costregression modelroad projectsRoads AuthorityMathematical Model |
| spellingShingle | Sisay Birhanu Belete Meseret Getnet Meharie Girmay Getawa Ayalew Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia Cogent Engineering Cost prediction project cost regression model road projects Roads Authority Mathematical Model |
| title | Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia |
| title_full | Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia |
| title_fullStr | Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia |
| title_full_unstemmed | Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia |
| title_short | Development of a mathematical model to predict the cost of Ethiopian Roads Authority road projects: the case of Ethiopia |
| title_sort | development of a mathematical model to predict the cost of ethiopian roads authority road projects the case of ethiopia |
| topic | Cost prediction project cost regression model road projects Roads Authority Mathematical Model |
| url | https://www.tandfonline.com/doi/10.1080/23311916.2023.2297492 |
| work_keys_str_mv | AT sisaybirhanubelete developmentofamathematicalmodeltopredictthecostofethiopianroadsauthorityroadprojectsthecaseofethiopia AT meseretgetnetmeharie developmentofamathematicalmodeltopredictthecostofethiopianroadsauthorityroadprojectsthecaseofethiopia AT girmaygetawaayalew developmentofamathematicalmodeltopredictthecostofethiopianroadsauthorityroadprojectsthecaseofethiopia |