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

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Author Info
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.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Construction Management & Economics.

Volume (Year): 23 (2005)
Issue (Month): 7 (September)
Pages: 673-684
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Handle: RePEc:taf:conmgt:v:23:y:2005:i:7:p:673-684

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Related research
Keywords: Contractor pre-qualification; neural networks; principal component analysis;

References listed on IDEAS
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  1. Patrick Sik-Wah Fong, Sonia Kit-Yung Choi, 2000. "Final contractor selection using the analytical hierarchy process," Construction Management & Economics, Taylor and Francis Journals, vol. 18(5), pages 547-557, July. [Downloadable!] (restricted)
  2. K. C. Lam, Tiesong Hu, S. Thomas Ng, Martin Skitmore, S. O. Cheung, 2001. "A fuzzy neural network approach for contractor prequalification," Construction Management & Economics, Taylor and Francis Journals, vol. 19(2), pages 175-188, March. [Downloadable!] (restricted)
  3. Zedan Hatush, Martin Skitmore, 1997. "Assessment and evaluation of contractor data against client goals using PERT approach," Construction Management & Economics, Taylor and Francis Journals, vol. 15(4), pages 327-340, July. [Downloadable!] (restricted)
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