IDEAS home Printed from https://ideas.repec.org/a/taf/conmgt/v22y2004i6p643-653.html
   My bibliography  Save this article

A logistic regression approach to modelling the contractor's decision to bid

Author

Listed:
  • David Lowe
  • Jamshid Parvar

Abstract

Significant factors in the decision to bid process are identified and a pro-forma to elicit a numerical assessment of these factors is developed and validated using the bid/no-bid decision-makers from a UK construction company. Using the pro-forma, data were collected from the collaborating company for historical bid opportunities. Statistical techniques are used to gain a better understanding of the data characteristics and to model the process. Eight variables have a significant relationship with the decision to bid outcome and for which the decision-makers are able to discriminate. Factor analysis is used to identify the underlying dimensions of the pro-forma and to validate functional decomposition of the factors. Finally, two logistic regression models of the decision to bid process are developed. While one model is ultimately rejected, the selected model is capable of classifying the total sample with an overall predictive accuracy rate of 94.8%. The results, therefore, demonstrate that the model functions effectively in predicting the bid/no-bid decision process.

Suggested Citation

  • David Lowe & Jamshid Parvar, 2004. "A logistic regression approach to modelling the contractor's decision to bid," Construction Management and Economics, Taylor & Francis Journals, vol. 22(6), pages 643-653.
    • Handle: RePEc:taf:conmgt:v:22:y:2004:i:6:p:643-653
    DOI: 10.1080/01446190310001649056
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/01446190310001649056
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01446190310001649056?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Prebensen, Nina K. & Xie, Jinghua, 2017. "Efficacy of co-creation and mastering on perceived value and satisfaction in tourists' consumption," Tourism Management, Elsevier, vol. 60(C), pages 166-176.
    2. 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.
    3. Z Hua & S Li & Z Tao, 2006. "A rule-based risk decision-making approach and its application in China's customs inspection decision," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(11), pages 1313-1322, November.
    4. Mohammed Ziaul Hoque & Mohammad Akter Hossan, 2020. "Understanding the Influence of Belief and Belief Revision on Consumers’ Purchase Intention of Liquid Milk," SAGE Open, , vol. 10(2), pages 21582440209, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:conmgt:v:22:y:2004:i:6:p:643-653. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RCME20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.