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Predicting the risk of contractor default in Saudi Arabia utilizing artificial neural network (ANN) and genetic algorithm (GA) techniques

Author

Listed:
  • Obaid Saad Al-Sobiei
  • David Arditi
  • Gul Polat

Abstract

The construction project is subject to several risks, one of the most important of which is contractor default because contractor default may increase the final project cost considerably. In the US construction industry, owners commonly shield themselves from the risk of contractor default by transferring this risk to the contractor, who in turn transfers this risk to a surety company. On the other hand, the General Directorate of Military Works (GDMW) of the Kingdom of Saudi Arabia retains the risk of contractor default rather than transferring it to a third party. An artificial neural network (ANN) and a genetic algorithm (GA) are used in this study to predict the risk of contractor default in construction projects undertaken for the Saudi armed forces. Based on this prediction, the Saudi GDMW can make a decision to engage or not to engage the services of a contractor. In case the models are not able to generate reliable predictions (or generate contradictory outcomes), the GDMW will have to augment its budget with contingency funds to be used in the event of contractor default. The outcome of this study is of particular relevance to construction owners because it proposes an approach that can allow them to replace an indiscriminate blanket policy by a policy that is rational, effective, prudent and economical.

Suggested Citation

  • Obaid Saad Al-Sobiei & David Arditi & Gul Polat, 2005. "Predicting the risk of contractor default in Saudi Arabia utilizing artificial neural network (ANN) and genetic algorithm (GA) techniques," Construction Management and Economics, Taylor & Francis Journals, vol. 23(4), pages 423-430.
    • Handle: RePEc:taf:conmgt:v:23:y:2005:i:4:p:423-430
    DOI: 10.1080/01446190500041578
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    Citations

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    Cited by:

    1. Abdelnaser Omran & Mohammed Alnor Abdulbagei & Abdelwahab O. Gebril, 2012. "An Evaluation Of The Critical Success Factors For Construction Projects In Libya," The International Journal of Economic Behavior - IJEB, Faculty of Business and Administration, University of Bucharest, vol. 2(1), pages 17-25, December.
    2. Shea Matthew & Hutchin James W., 2018. "The Importance of Environmental, Social, and Governance Risks to Surety Underwriters," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 12(2), pages 1-14, July.
    3. Jun Wang & Mao Li & Martin Skitmore & Jianli Chen, 2024. "Predicting Construction Company Insolvent Failure: A Scientometric Analysis and Qualitative Review of Research Trends," Sustainability, MDPI, vol. 16(6), pages 1-22, March.

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