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Journal of Civil Engineering and Management Volume 20, 2014 - Issue 2
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Original Articles

Prediction of default probability for construction firms using the logit model

H. Ping TserngDepartment of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, TaiwanCorrespondence[email protected]
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,
Po-Cheng ChenDepartment of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, TaiwanView further author information
,
Wen-Haw HuangLong Reign Development Co., 16F-2, No. 76, Sec. 2 Dunhua S. Road, Taipei, TaiwanView further author information
,
Man Cheng LeiDepartment of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, TaiwanView further author information
&
Quang Hung TranDepartment of Civil Engineering, National Taiwan University, No. 1 Roosevelt Rd., Sec. 4, Taipei, TaiwanView further author information
Pages 247-255 | Received 11 Aug 2011, Accepted 11 May 2012, Published online: 24 Apr 2014

Citations (19)

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Hafiz A. Alaka, Lukumon O. Oyedele, Hakeem A. Owolabi, Azeez A. Oyedele, Olugbenga O. Akinade, Muhammad Bilal & Saheed O. Ajayi. (2017) Critical factors for insolvency prediction: towards a theoretical model for the construction industry. International Journal of Construction Management 17:1, pages 25-49.
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Hafiz A. Alaka, Lukumon O. Oyedele, Hakeem A. Owolabi, Saheed O. Ajayi, Muhammad Bilal & Olugbenga O. Akinade. (2016) Methodological approach of construction business failure prediction studies: a review. Construction Management and Economics 34:11, pages 808-842.
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Articles from other publishers (17)

Tomasz Tomczyk, Anna Szymańska & Robert Dankiewicz. (2022) Corporate Bankruptcy, a Spatial and Temporal Perspective – the Case of Poland. Journal of Security and Sustainability Issues 13:1, pages 17-28.
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Jiseok Jeong & Changwan Kim. (2022) Comparison of Machine Learning Approaches for Medium-to-Long-Term Financial Distress Predictions in the Construction Industry. Buildings 12:10, pages 1759.
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Denis Kušter. (2022) Financial ratio indicators as early predictors of business failure: Evidence from Serbia. Anali Ekonomskog fakulteta u Subotici:00, pages 5-5.
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Ana Sousa, Ana Braga & Jorge Cunha. (2022) Impact of macroeconomic indicators on bankruptcy prediction models: Case of the Portuguese construction sector. Quantitative Finance and Economics 6:3, pages 405-432.
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Youjin Jang, Inbae Jeong & Yong K. Cho. (2021) Identifying impact of variables in deep learning models on bankruptcy prediction of construction contractors. Engineering, Construction and Architectural Management 28:10, pages 3282-3298.
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Kuashuai Peng & Guofeng Yan. (2021) A survey on deep learning for financial risk prediction. Quantitative Finance and Economics 5:4, pages 716-737.
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Roman Burekhin. 2021. Risk Assessment and Financial Regulation in Emerging Markets' Banking. Risk Assessment and Financial Regulation in Emerging Markets' Banking 177 187 .
Haifeng Guo, Ke Peng, Xiaolei Xu, Shuai Tao & Zhen Wu. (2020) The Prediction Analysis of Peer-to-Peer Lending Platforms Default Risk Based on Comparative Models. Scientific Programming 2020, pages 1-10.
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Jiabao Jing, Xiaomei Deng, Rashid Maqbool, Yahya Rashid & Saleha Ashfaq. (2020) Default Behaviors of Contractors under Surety Bond in Construction Industry Based on Evolutionary Game Model. Sustainability 12:21, pages 9162.
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Rayan AssaadIslam H. El-adaway. (2020) Enhancing the Knowledge of Construction Business Failure: A Social Network Analysis Approach. Journal of Construction Engineering and Management 146:6.
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Youjin Jang, Inbae Jeong & Yong K. Cho. (2020) Business Failure Prediction of Construction Contractors Using a LSTM RNN with Accounting, Construction Market, and Macroeconomic Variables. Journal of Management in Engineering 36:2.
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Youjin Jang, In-Bae Jeong, Yong K. Cho & Yonghan Ahn. (2019) Predicting Business Failure of Construction Contractors Using Long Short-Term Memory Recurrent Neural Network. Journal of Construction Engineering and Management 145:11.
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Senthil Arasu Balasubramanian, Radhakrishna G.S.Sridevi P.Thamaraiselvan Natarajan. (2019) Modeling corporate financial distress using financial and non-financial variables. International Journal of Law and Management 61:3/4, pages 457-484.
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Hyunchul Choi, Hyojoo Son & Changwan Kim. (2018) Predicting financial distress of contractors in the construction industry using ensemble learning. Expert Systems with Applications 110, pages 1-10.
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Hafiz A. Alaka, Lukumon O. Oyedele, Hakeem A. Owolabi, Muhammad Bilal, Saheed O. Ajayi & Olugbenga O. Akinade. (2018) A framework for big data analytics approach to failure prediction of construction firms. Applied Computing and Informatics 16:1/2, pages 207-222.
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Hafiz A. Alaka, Lukumon O. Oyedele, Hakeem A. Owolabi, Vikas Kumar, Saheed O. Ajayi, Olugbenga O. Akinade & Muhammad Bilal. (2018) Systematic review of bankruptcy prediction models: Towards a framework for tool selection. Expert Systems with Applications 94, pages 164-184.
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Michal Karas & Mária Režňáková. (2017) The Potential of Dynamic Indicator in Development of the Bankruptcy Prediction Models: the Case of Construction Companies. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 65:2, pages 641-652.
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