Predicting project performance through neural networks
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Description
Successful project delivery of construction projects depends on many factors. With regard to the construction of a facility, selecting a competent contractor for the job is paramount. As such, various approaches have been advanced to facilitate tender award decisions. Essentially, this type of decision involves the prediction of a bidderÕs performance based on information available at the tender stage. A neural network based prediction model was developed and presented in this paper. Project data for the study were obtained from the Hong Kong Housing Department. Information from the tender reports was used as input variables and performance records of the successful bidder during construction were used as output variables. It was found that the networks for the prediction of performance scores for Works gave the highest hit rate. In addition, the two most sensitive input variables toward such prediction are ‘‘Difference between Estimate’’ and ‘‘Difference between the next closest bid’’. Both input variables are price related, thus suggesting the importance of tender sufficiency for the assurance of quality production.
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ID Code: | 29150 | ||
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Item Type: | Contribution to Journal (Journal Article) | ||
Refereed: | Yes | ||
ORCID iD: |
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Measurements or Duration: | 9 pages | ||
Keywords: | Bid Evaluators, Performance Scores, Prediciton by Neural Networks | ||
DOI: | 10.1016/j.ijproman.2005.08.001 | ||
ISSN: | 0263-7863 | ||
Pure ID: | 33903009 | ||
Divisions: | Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering Past > Schools > School of Urban Development |
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Copyright Owner: | Consult author(s) regarding copyright matters | ||
Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||
Deposited On: | 08 Dec 2009 02:48 | ||
Last Modified: | 10 May 2024 11:50 |
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