Pre-Selection of Construction Consultants based on Attributes of Trust

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A review of construction consultants’ selection identified weaknesses in the process that focused on cost and technical abilities alone. This paper presents a construction consultant pre-selection factor model based on attributes of trust, which attempts to improve consultant selection processes. A review of related literature shows that trust was found to enhance the decision making process. However, there is a knowledge gap in construction management literature as regards what constitute the attributes of trust which can be of benefit to the construction client or its agent in selecting appropriate consultants. In total 37 consultant selection trust attributes thought to potentially influence consultant pre-selection were identified from literature. Based on these attributes, a structured questionnaire survey was designed using a Likert-type scale and administered online to 189 willing construction clients. Survey responses were analysed using principal component analysis. This led to the development of an 8-factor model of consultant pre selection, namely, (1) service quality,(2) collaborative relationships, (3) qualification, (4) organisational trust, (5) personal qualities, (6) ability, (7) experience and (8) respect. The research provides the construction industry clients with a practical 8-factor pre selection model that can be effectively used by the construction clients to improve the consultant selection process.
Original languageEnglish
Title of host publicationUnknown Host Publication
EditorsSimon Smith
Place of PublicationSchool of Construction Management and Engineering, University of Reading, PO Box 219, Reading, RG6 6AW, UK
PublisherAssociation of Researchers in Construction Management
Number of pages10
Publication statusPublished (in print/issue) - 3 Sept 2012
Event28th Annual ARCOM Conference - Edinburgh, UK.
Duration: 3 Sept 2012 → …


Conference28th Annual ARCOM Conference
Period3/09/12 → …

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  • Consultant selection
  • pre-selection
  • principal component analysis
  • trust.


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