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To bid or not to bid: a parametric solution

Author

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  • M. Wanous
  • A. H. Boussabaine
  • J. Lewis

Abstract

One of the most important decisions that has to be made by construction companies/contractors is whether or not to bid for a new project when an invitation has been received. It would be of great help if a structured model could be developed that deals systematically with different bidding situations. A simple parametric solution for the ';bid/no bid' decision is reported in this paper. This solution is based on the findings of six semi-structured interviews and a formal questionnaire through which 38 factors that affect the bid/no bid decision were identified and ranked according to their importance to contractors operating in Syria. Only the most influential factors were considered in the development process. The model was optimized using data about 162 real bidding situations. Then the optimized model was tested using another 20 real projects. It proved 85% accurate in simulating the actual decisions. Although, the proposed model is based on data from the Syrian construction industry it could be modified very easily to suit other countries.

Suggested Citation

  • M. Wanous & A. H. Boussabaine & J. Lewis, 2000. "To bid or not to bid: a parametric solution," Construction Management and Economics, Taylor & Francis Journals, vol. 18(4), pages 457-466.
    • Handle: RePEc:taf:conmgt:v:18:y:2000:i:4:p:457-466
    DOI: 10.1080/01446190050024879
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    References listed on IDEAS

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    1. Lawrence Friedman, 1956. "A Competitive-Bidding Strategy," Operations Research, INFORMS, vol. 4(1), pages 104-112, February.
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    Cited by:

    1. YeEun Jang & JeongWook Son & June-Seong Yi, 2021. "Classifying the Level of Bid Price Volatility Based on Machine Learning with Parameters from Bid Documents as Risk Factors," Sustainability, MDPI, vol. 13(7), pages 1-18, April.
    2. Martin Ekstrom & Hans Bjornsson & Clifford Nass, 2003. "Accounting for rater credibility when evaluating AEC subcontractors," Construction Management and Economics, Taylor & Francis Journals, vol. 21(2), pages 197-208.
    3. Qiao, Yu & Labi, Samuel & Fricker, Jon D., 2021. "Does highway project bundling policy affect bidding competition? Insights from a mixed ordinal logistic model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 228-242.
    4. Ren Tan & Kairong Hong, 2021. "Research on Extreme Dispute Decisions of Large-Scale Engineering Projects from the Perspective of Multidimensional Preferences," Mathematics, MDPI, vol. 9(22), pages 1-24, November.
    5. Fuchigami, Helio Yochihiro & Tuni, Andrea & Barbosa, Luísa Queiroz & Severino, Maico Roris & Rentizelas, Athanasios, 2021. "Supporting Brazilian smallholder farmers decision making in supplying institutional markets," European Journal of Operational Research, Elsevier, vol. 295(1), pages 321-335.
    6. Joe Wong & Eddie Hui, 2006. "Construction project risks: further considerations for constructors' pricing in Hong Kong," Construction Management and Economics, Taylor & Francis Journals, vol. 24(4), pages 425-438.

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