Development of a decision support system (DSS) for the contractors decision to bid: regression analysis and neural network solutions

Jamshid Parvar, David J Lowe, David Lowe (Editor), Margaret Emsley (Editor)

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Abstract

The decision whether to bid or not for a project is extremely important to contractors; besides the issues of resource allocation, the preparation of a bona fide tender commits the organisation to considerable expenditure, which is only recovered if the bid is successful. There is, therefore, a potential financial benefit to be realised through the adoption of an effective and systematic approach to the decision to bid process. Artificial neural network and regression techniques are used to produce a rational and optimal model for the bid/no-bid decision process. While the regression model is ultimately rejected, the selected back-propagation network, comprising 21 input nodes, 3 hidden layers and 4 output nodes is used to support a DSS for the decision to bid process. The results obtained demonstrate that the model functions effectively in predicting the decision process.
Original languageEnglish
Title of host publicationProceedings of the First International Symposium on Commercial Management. The University of Manchester
EditorsDavid Lowe, Margaret Emsley
Place of PublicationManchester
PublisherUniversity of Manchester
Pages122-135
Number of pages14
ISBN (Print)0-9547918-1-1
Publication statusPublished - 7 Apr 2005
EventThe First International Symposium on Commercial Management - The University of Manchester
Duration: 7 Apr 20057 Apr 2005

Conference

ConferenceThe First International Symposium on Commercial Management
CityThe University of Manchester
Period7/04/057/04/05

Keywords

  • Bidding, construction, decision support system, decision to bid, neural networks

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