A model of construction contractor selection using competitive intelligence (CI)

dc.contributor.authorSafa, Mahdi
dc.contributor.authorShahi, A.
dc.contributor.authorHaas, C. T.
dc.contributor.authorSafa, M.
dc.contributor.authorHipel, K.
dc.contributor.authorMacGillivray, S.
dc.contributor.authorFiander-McCann, D.
dc.date.accessioned2014-08-07T00:49:41Z
dc.description.abstractWhile comprehensive and ongoing competitive intelligence (CI) is employed in a variety of industries to provide valuable input for broad strategic decisions, the construction industry lags behind in adopting this technique. This paper presents a CI model for use in the construction contractor selection process, which is a critical element of construction project management and one that inherently entails risk and risk management. The use of CI for contractor selection is an important development in light of the realization on the part of many companies that the diffuse nature of the information and lack of robust analysis create numerous inconveniences during the decision making process. Based on the application of the CI method for a competitive environment, the proposed model has the potential to improve the process for assessing and selecting contractors. This paper describes the proposed model, including background information, structural details, guidelines for its use and implementation, and key data analysis findings.en
dc.format.extent329-336en
dc.identifier.urihttps://hdl.handle.net/10182/6304
dc.language.isoen
dc.publisherISARC
dc.relationThe original publication is available from - ISARC - http://www.isarc2014.org/en
dc.relation.isPartOf2014 Proceedings of the 31st ISARC, Sydney, Australiaen
dc.rightsCopyright © ISARC2014
dc.sourceThe 31st International Symposium on Automation and Robotics in Construction and Miningen
dc.subjectconstruction managementen
dc.subjectcompetitive intelligenceen
dc.subjectmegaprojecten
dc.subjectcontractor selectionen
dc.subjectrisken
dc.titleA model of construction contractor selection using competitive intelligence (CI)en
dc.typeConference Contribution - published
lu.contributor.unitLincoln University
lu.contributor.unitFaculty of Agribusiness and Commerce
lu.contributor.unitDepartment of Land Management and Systems
lu.identifier.orcid0000-0002-8670-6156
lu.subtypeConference Paperen
pubs.finish-date2014-07-11en
pubs.publication-statusPublisheden
pubs.publisher-urlhttp://www.isarc2014.org/en
pubs.start-date2014-07-09en
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