Early Highway Construction Cost Estimation: Selection of Key Cost Drivers
Аутори
Simić, NevenaIvanišević, Nenad
Nedeljković, Đorđe
Senić, Aleksandar
Stojadinović, Zoran
Ivanović, Marija
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
Cost estimates in the early stages of project development are essential for making the right deci-sions, but they are a huge challenge and risk for owners and potential contractors due to limited information about the characteristics of the future highway project. While previous studies were mainly focused on achieving the highest possible estimation accuracy, this paper aims to propose cost estimation models that can provide satisfactory accuracy with the least possible effort, and to compare the perspectives of owners and contractors, as the key stakeholders on projects. To de-termine cost drivers (CDs) which have a high influence on highway construction costs and re-quire low effort for their establishment, a questionnaire survey was conducted. Based on the key stakeholders’ perceptions and collected data set, cost estimation models were developed using multiple regression analysis, artificial neural networks, and XGBoost. The results show that rea-sonable cost estimation accuracy c...an be achieved with a relatively low effort for 3 CDs for the owners' perspective and 5 CDs for the contractors' perspective. Additional inclusion of input CDs in models does not necessarily imply an increase in accuracy. Also, the questionnaire results show that owners are more concerned about environmental issues, while contractors are more con-cerned about the possible changes in resource prices (especially after recent high increases caused by COVID-19 and the Russia-Ukraine war). These findings can help owners and potential con-tractors in intelligent decision-making in the early stages of future highway construction projects.
Кључне речи:
cost estimation / cost driver / influence / effort / questionnaire / extreme gradient boosting / artificial neural networks / highway projectsИзвор:
Sustainability, 2023, 15Издавач:
- MDPI
Колекције
Институција/група
GraFarTY - JOUR AU - Simić, Nevena AU - Ivanišević, Nenad AU - Nedeljković, Đorđe AU - Senić, Aleksandar AU - Stojadinović, Zoran AU - Ivanović, Marija PY - 2023 UR - https://grafar.grf.bg.ac.rs/handle/123456789/3224 AB - Cost estimates in the early stages of project development are essential for making the right deci-sions, but they are a huge challenge and risk for owners and potential contractors due to limited information about the characteristics of the future highway project. While previous studies were mainly focused on achieving the highest possible estimation accuracy, this paper aims to propose cost estimation models that can provide satisfactory accuracy with the least possible effort, and to compare the perspectives of owners and contractors, as the key stakeholders on projects. To de-termine cost drivers (CDs) which have a high influence on highway construction costs and re-quire low effort for their establishment, a questionnaire survey was conducted. Based on the key stakeholders’ perceptions and collected data set, cost estimation models were developed using multiple regression analysis, artificial neural networks, and XGBoost. The results show that rea-sonable cost estimation accuracy can be achieved with a relatively low effort for 3 CDs for the owners' perspective and 5 CDs for the contractors' perspective. Additional inclusion of input CDs in models does not necessarily imply an increase in accuracy. Also, the questionnaire results show that owners are more concerned about environmental issues, while contractors are more con-cerned about the possible changes in resource prices (especially after recent high increases caused by COVID-19 and the Russia-Ukraine war). These findings can help owners and potential con-tractors in intelligent decision-making in the early stages of future highway construction projects. PB - MDPI T2 - Sustainability T1 - Early Highway Construction Cost Estimation: Selection of Key Cost Drivers VL - 15 DO - 10.3390/su15065584 ER -
@article{ author = "Simić, Nevena and Ivanišević, Nenad and Nedeljković, Đorđe and Senić, Aleksandar and Stojadinović, Zoran and Ivanović, Marija", year = "2023", abstract = "Cost estimates in the early stages of project development are essential for making the right deci-sions, but they are a huge challenge and risk for owners and potential contractors due to limited information about the characteristics of the future highway project. While previous studies were mainly focused on achieving the highest possible estimation accuracy, this paper aims to propose cost estimation models that can provide satisfactory accuracy with the least possible effort, and to compare the perspectives of owners and contractors, as the key stakeholders on projects. To de-termine cost drivers (CDs) which have a high influence on highway construction costs and re-quire low effort for their establishment, a questionnaire survey was conducted. Based on the key stakeholders’ perceptions and collected data set, cost estimation models were developed using multiple regression analysis, artificial neural networks, and XGBoost. The results show that rea-sonable cost estimation accuracy can be achieved with a relatively low effort for 3 CDs for the owners' perspective and 5 CDs for the contractors' perspective. Additional inclusion of input CDs in models does not necessarily imply an increase in accuracy. Also, the questionnaire results show that owners are more concerned about environmental issues, while contractors are more con-cerned about the possible changes in resource prices (especially after recent high increases caused by COVID-19 and the Russia-Ukraine war). These findings can help owners and potential con-tractors in intelligent decision-making in the early stages of future highway construction projects.", publisher = "MDPI", journal = "Sustainability", title = "Early Highway Construction Cost Estimation: Selection of Key Cost Drivers", volume = "15", doi = "10.3390/su15065584" }
Simić, N., Ivanišević, N., Nedeljković, Đ., Senić, A., Stojadinović, Z.,& Ivanović, M.. (2023). Early Highway Construction Cost Estimation: Selection of Key Cost Drivers. in Sustainability MDPI., 15. https://doi.org/10.3390/su15065584
Simić N, Ivanišević N, Nedeljković Đ, Senić A, Stojadinović Z, Ivanović M. Early Highway Construction Cost Estimation: Selection of Key Cost Drivers. in Sustainability. 2023;15. doi:10.3390/su15065584 .
Simić, Nevena, Ivanišević, Nenad, Nedeljković, Đorđe, Senić, Aleksandar, Stojadinović, Zoran, Ivanović, Marija, "Early Highway Construction Cost Estimation: Selection of Key Cost Drivers" in Sustainability, 15 (2023), https://doi.org/10.3390/su15065584 . .