Knowledge-driven ANP approach to vendors evaluation for sustainable construction

Zhen Chen, Heng Li, Andrew Ross, Malik M. Khalfan, Stephen C. Kong

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

This paper presents a multicriteria decision-making approach to evaluate contractor candidates in the open competition of construction project procurement by means of a knowledge-framed analytic network process (KANP), which embeds a construction knowledge framework into a formal analytic network process procedure. An applied KANP model named KANP.BID is set up and used in an experimental case study. The paper concludes that the KANP.BID model is a viable and capable tool for selecting the most appropriate tender alternative under criteria of sustainable construction. It is expected that the proposed KANP.BID model can attract interest from both practitioners and researchers in terms of further research and development.

Original languageEnglish
Pages (from-to)928-941
Number of pages14
JournalJournal of Construction Engineering and Management
Volume134
Issue number12
Early online date1 Dec 2008
DOIs
Publication statusPublished - 31 Dec 2008
Externally publishedYes

Fingerprint

Contractors
Decision making
Vendors
Analytic network process
Evaluation
Sustainable construction
Multicriteria decision-making
Process model
Construction project
Procurement

Keywords

  • bids
  • construction management
  • decision making
  • evaluation
  • procurement
  • sustainable development

Cite this

Chen, Zhen ; Li, Heng ; Ross, Andrew ; Khalfan, Malik M. ; Kong, Stephen C. / Knowledge-driven ANP approach to vendors evaluation for sustainable construction. In: Journal of Construction Engineering and Management . 2008 ; Vol. 134, No. 12. pp. 928-941.
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Knowledge-driven ANP approach to vendors evaluation for sustainable construction. / Chen, Zhen; Li, Heng; Ross, Andrew; Khalfan, Malik M.; Kong, Stephen C.

In: Journal of Construction Engineering and Management , Vol. 134, No. 12, 31.12.2008, p. 928-941.

Research output: Contribution to journalArticle

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