Predicting financial distress of contractors in the construction industry using ensemble learning
作者：
Highlights：
• This study proposes financial distress prediction models based on ensemble learning.
• The models provide two- and three-year ahead prediction of financial distress.
• Performance was evaluated for contractors in South Korea from 2007 to 2012.
• The models contribute to provide a financial early warning in the construction industry.
• This model can help stakeholders to avoid damage due to financial crisis during a project.
摘要
•This study proposes financial distress prediction models based on ensemble learning.•The models provide two- and three-year ahead prediction of financial distress.•Performance was evaluated for contractors in South Korea from 2007 to 2012.•The models contribute to provide a financial early warning in the construction industry.•This model can help stakeholders to avoid damage due to financial crisis during a project.
论文关键词：Financial distress,Financial crisis,Prediction,Ensemble learning,Contractors
论文评审过程：Received 21 January 2018, Revised 21 May 2018, Accepted 22 May 2018, Available online 26 May 2018, Version of Record 29 May 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.05.026
