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Using the principal component analysis method as a tool in contractor pre-qualification

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  • K. C. Lam
  • T. S. Hu
  • S. T. Ng

Abstract

Contractor pre-qualification can be regarded as a complicated, two-group, non-linear classification problem. It involves a variety of subjective and uncertain information extracted from various parties such as contractors, pre-qualifiers and project teams. Non-linearity, uncertainty and subjectivity are the three predominant characteristics of the contractor pre-qualification process. This makes the process more of an art than a scientific evaluation. In addition to non-linearity, uncertainty and subjectivity, contractor pre-qualification is further complicated by the large number of contractor pre-qualification criteria (CPC) used in current practice and the multicollinearity existing between contractor attributes. An alternative empirical method using principal component analysis (PCA) is proposed for contractor pre-qualification in this study. The proposed method may alleviate the existing amount of multicollinearity and largely reduce the dimensionality of the pre-qualification data set. The applicability and potential of PCA for contractor pre-qualification has been examined by way of two data sets: (1) 73 pre-qualification cases (37 qualified and 36 disqualified) collected in England and (2) 85 (45 qualified and 40 disqualified) pre-qualification cases relating to 10 public sector projects in Hong Kong. The PCA-based results demonstrated that strong and positive inter-correlations existed between most of the qualifying variables, with the minimum correlation coefficient being 0.121 and the maximum being 0.899, and that qualified and disqualified contractors could be satisfactorily separated.

Suggested Citation

  • K. C. Lam & T. S. Hu & S. T. Ng, 2005. "Using the principal component analysis method as a tool in contractor pre-qualification," Construction Management and Economics, Taylor & Francis Journals, vol. 23(7), pages 673-684.
  • Handle: RePEc:taf:conmgt:v:23:y:2005:i:7:p:673-684
    DOI: 10.1080/01446190500041263
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    References listed on IDEAS

    as
    1. Patrick Sik-Wah Fong & Sonia Kit-Yung Choi, 2000. "Final contractor selection using the analytical hierarchy process," Construction Management and Economics, Taylor & Francis Journals, vol. 18(5), pages 547-557.
    2. Zedan Hatush & Martin Skitmore, 1997. "Evaluating contractor prequalification data: selection criteria and project success factors," Construction Management and Economics, Taylor & Francis Journals, vol. 15(2), pages 129-147.
    3. K. C. Lam & Tiesong Hu & S. Thomas Ng & Martin Skitmore & S. O. Cheung, 2001. "A fuzzy neural network approach for contractor prequalification," Construction Management and Economics, Taylor & Francis Journals, vol. 19(2), pages 175-188.
    4. Zedan Hatush & Martin Skitmore, 1997. "Assessment and evaluation of contractor data against client goals using PERT approach," Construction Management and Economics, Taylor & Francis Journals, vol. 15(4), pages 327-340.
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