Abstracts – Browse Results

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 10 results ...

Abdelgawad, M and Fayek, A R (2012) Comprehensive Hybrid Framework for Risk Analysis in the Construction Industry Using Combined Failure Mode and Effect Analysis, Fault Trees, Event Trees, and Fuzzy Logic. Journal of Construction Engineering and Management, 138(05), 642–51.

Avetisyan, H G, Miller-Hooks, E and Melanta, S (2012) Decision Models to Support Greenhouse Gas Emissions Reduction from Transportation Construction Projects. Journal of Construction Engineering and Management, 138(05), 631–41.

Bröchner, J and Olofsson, T (2012) Construction Productivity Measures for Innovation Projects. Journal of Construction Engineering and Management, 138(05), 670–7.

Kim, J and Philips, P (2012) Determinants of Quits and Dismissals on a Long-Lasting Unionized Industrial Construction Project. Journal of Construction Engineering and Management, 138(05), 661–9.

Lopez, R and Love, P E D (2012) Design Error Costs in Construction Projects. Journal of Construction Engineering and Management, 138(05), 585–93.

Love, P E D, Niedzweicki, M, Bullen, P A and Edwards, D J (2012) Achieving the Green Building Council of Australia’s World Leadership Rating in an Office Building in Perth. Journal of Construction Engineering and Management, 138(05), 652–60.

Puddicombe, M S (2012) Novelty and Technical Complexity: Critical Constructs in Capital Projects. Journal of Construction Engineering and Management, 138(05), 613–20.

Sunindijo, R Y and Zou, P X W (2012) Political Skill for Developing Construction Safety Climate. Journal of Construction Engineering and Management, 138(05), 605–12.

Teizer, J, Venugopal, M, Teizer, W and Felkl, J (2012) Nanotechnology and Its Impact on Construction: Bridging the Gap between Researchers and Industry Professionals. Journal of Construction Engineering and Management, 138(05), 594–604.

Tserng, H P, Liao, H, Jaselskis, E J, Tsai, L K and Chen, P (2012) Predicting Construction Contractor Default with Barrier Option Model. Journal of Construction Engineering and Management, 138(05), 621–30.

  • Type: Journal Article
  • Keywords: Construction industry; Financial factors; Risk management; Predictions; Construction industry; Credit risk; Default prediction; Barrier option model; Financial ratio model;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000465
  • Abstract:
    This is the first study to apply the barrier option model to predict defaults of construction contractors and to assert that the path-dependent characteristic of the model is very suitable for describing the behavior of contractor default. Different from existing contractor-default prediction models, this research uses a much larger contractor sample in empirical analyses to alleviate sample-selection biases, and employs a Receiver Operating Characteristics (ROC) curve to assess the model performance. Empirical results of this study show that the proposed model outperforms traditional financial ratio models in differentiating the risk of defaulted and nondefaulted construction contractors. Additionally, the barrier option model has markedly better discriminatory power than when applied to non–construction-related industries. The results of this paper support the postulation that the barrier option model has significant advantages for the construction industry.