Holt, G D (1997) Classifying construction contractors: A case study using cluster analysis. Building Research & Information, 25(6), pp. 374-382. ISSN 0961-3218
Abstract
It is widely accepted in construction management literature that superlative contractor selection criteria are: contractor ability to complete a project on time, within budgeted cost and to expected quality standards. Hence, contractor evaluation and selection models with the ability to highlight these attributes (i.e. help the selection decision) should be fully exploited. To date, such models have evolved based predominantly on multi-attribute analysis, case-based reasoning, and discriminant analysis, but there is scope for investigation of alternative strategies including: fuzzy set theory; neural networks; regression techniques; and cluster analysis. This paper concentrates on the latter by applying cluster analysis to real-life contractor selection data. Results indicate that the technique will simultaneously classify large numbers of contractors while identifying the most significant discriminating criteria among them. These characteristics offer potential for rationalization of contractor evaluation, classification and selection.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | classification; cluster analysis; construction contractors; prequalification; selection models; tender evaluation |
| Index terms: | neural network, strategy, fuzzy set theory, discriminant analysis, contractor selection, case-based reasoning, case study, quality standard, construction contractor, multi-attribute analysis, cluster analysis, tender evaluation, investigation |
| Subjects: | practitioner, data collection methods, artificial intelligence, data analysis and analytics, tendering, management, quality assurance, statistical analysis, decision-making and optimization, cognitive psychology, decision analysis |
| Topics: | Risk Management, Roles and Professions, Procurement, Business Strategy, Research Practice, Digital Applications, Quality Management |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here