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Huang, W, Tserng, H P, Jaselskis, E J and Lee, S (2014) Dynamic Threshold Cash Flow–Based Structural Model for Contractor Financial Prequalification. Journal of Construction Engineering and Management, 140(10).

  • Type: Journal Article
  • Keywords: Contracts; Risk management; Financial factors; Construction management; Contractor financial prequalification; Credit risk; Dynamic threshold; Cash flow structural model; Receiver operating characteristic curve; Quantitative methods;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000902
  • Abstract:
    It is important for project owners to select only those construction contractors who are uniquely qualified to perform the work because this leads to the greatest chance for achieving project success. Owners typically screen contractors by using the following key criteria: financial stability, technical ability, management capability, health and safety, and reputation. This study focuses primarily on the construction contractor’s financial stability during the prequalification phase and employs a dynamic threshold cash flow based structural model (DCFM) to assess the credit quality score for each construction contractor. This model differs from the existing credit model because it only requires accounting statement information; thus, it is applicable to both publicly listed and private construction contractors. Moreover, only a small portion of companies are rated in the construction industry; this model is especially useful for owners to assess the credit quality of unrated construction companies. The Standard & Poor’s issuer credit rating is used as the benchmark to evaluate the model’s discrimination ability to differentiate financially qualified contractors from unqualified contractors. Additionally, the validation indicator area under curve (AUC) is utilized to demonstrate whether the DCFM can identify different credit grade firms according to the model’s credit quality scores. The AUC results of the first three years of this model are 0.861, 0.833, and 0.819, indicating that this model achieves excellent discriminatory ability and is useful for assessing the credit risk of construction contractors.

Kim, H, Orr, K, Shen, Z, Moon, H, Ju, K and Choi, W (2014) Highway Alignment Construction Comparison Using Object-Oriented 3D Visualization Modeling. Journal of Construction Engineering and Management, 140(10).

Kim, T, Lim, H, Cho, H and Kang, K (2014) Automated Lifting System Integrated with Construction Hoists for Table Formwork in Tall Buildings. Journal of Construction Engineering and Management, 140(10).

Liu, J, Shahi, A, Haas, C T, Goodrum, P and Caldas, C H (2014) Validation Methodologies and Their Impact in Construction Productivity Research. Journal of Construction Engineering and Management, 140(10).

Su, X, Li, S, Yuan, C, Cai, H and Kamat, V R (2014) Enhanced Boundary Condition–Based Approach for Construction Location Sensing Using RFID and RTK GPS. Journal of Construction Engineering and Management, 140(10).