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Abd El-Razek, M E, Bassioni, H A and Mobarak, A M (2008) Causes of Delay in Building Construction Projects in Egypt. Journal of Construction Engineering and Management, 134(11), 831–41.

Choi, H and Mahadevan, S (2008) Construction Project Risk Assessment Using Existing Database and Project-Specific Information. Journal of Construction Engineering and Management, 134(11), 894–903.

Eom, C S, Yun, S H and Paek, J H (2008) Subcontractor Evaluation and Management Framework for Strategic Partnering. Journal of Construction Engineering and Management, 134(11), 842–51.

Hu, J, Ren, Z and Shen, L (2008) Impacts of Overseas Management Structures on Project Buyout Management: Case Studies of Chinese International Contractors. Journal of Construction Engineering and Management, 134(11), 864–75.

Kang, Y, O’Brien, W J, Thomas, S and Chapman, R E (2008) Impact of Information Technologies on Performance: Cross Study Comparison. Journal of Construction Engineering and Management, 134(11), 852–63.

Kim, J and Ellis, R D (2008) Permutation-Based Elitist Genetic Algorithm for Optimization of Large-Sized Resource-Constrained Project Scheduling. Journal of Construction Engineering and Management, 134(11), 904–13.

Kong, D, Tiong, R L, Cheah, C Y, Permana, A and Ehrlich, M (2008) Assessment of Credit Risk in Project Finance. Journal of Construction Engineering and Management, 134(11), 876–84.

  • Type: Journal Article
  • Keywords: Risk management; Assessments; Financial management; Construction management;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2008)134:11(876)
  • Abstract:
    In project finance, raising sufficient funds via the debt channel is a key task for all project companies and sponsors. Before furnishing a loan, lenders typically need to ascertain the ability of the project company to service principal payments plus interest. This paper aims to establish a quantitative model to analyze default risks and loan losses in infrastructure projects. Acting as an assessment system, the model will help lenders evaluate their exposure to default risk by monitoring the changes in credit quality of the project company. The model uses a conditional credit rating transition matrix to predict the probability of default and the net present value technique to estimate the maximum default loss. The Hong Kong-Canton highway project is used as a case study to illustrate the techniques and output of the proposed credit risk model. The model can be used to assist lenders and investors in making sound investment decisions, price contracts, and allocate capital. Similarly, it can also help project sponsors evaluate those critical measures that they must control in order to secure favorable loan terms by minimizing the risk of default and improving the bankability of a project.

Schatteman, D, Herroelen, W, Van de Vonder, S and Boone, A (2008) Methodology for Integrated Risk Management and Proactive Scheduling of Construction Projects. Journal of Construction Engineering and Management, 134(11), 885–93.