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Applying cluster analysis to construction contractor classification
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DOI：10.1016/0360-1323(96)00028-5.png)
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Abstract
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The essential task of prequalifying contractors most often involves a lar ge number of firms, each being represented by many disparate dimensions. Therefore, to effectively perform prequalification normally requires an inordinate amount of resource commitment by the construction owner. The statistical technique of cluster. analysis (CA) could aid this decision process by classifying contractor's into groups of like nature or common characteristics/ability. Further, the technique can identify the most discriminating criteria involved in achieving such classification and, thereby, help avoid subjective rejection of ''good'' firms, when large numbers of contractors are being considered. Example applications of the CA method are presented, in a construction contractor prequalification scenario. Copyright (C) 1996 Elsevier Science Ltd.
Keywords:
SELECTION
CRITERIA
CHOICE
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