Selecting an architecture‐engineering team by using fuzzy set theory

Abstract

Purpose

Selecting the most appropriate architecture‐engineering (AE) team, one of the most significant decisions leading to the successful completion of a construction project, is usually conducted in a multi‐criteria environment, which is mostly dependent on the subjective judgment of decision makers and is influenced by the uncertainty and vagueness of each individual construction project. This paper aims to present an assessment method to evaluate the capability of an AE team with respect to the criteria defined by decision makers.

Design/methodology/approach

In addition to a proposed tender price, the evaluation of potential AE teams should be also based on other criteria such as its financial soundness, experience, expertise, availability, and compatibility of personality. A selection model is developed, in which different decision criteria and its subcriteria, and their combinations are simultaneously taken into account by using the concept of fuzzy set theory. An illustrative example is also provided in the paper to demonstrate the application of the model and its assessment method in selecting the most appropriate AE team for a construction project.

Findings

The study results show that the proposed evaluation model allows decision makers to express their opinions about the performances of AE bidders using more realistic qualitative and linguistic terms and the fuzzy decision making method is an appropriate tool that can assist decision makers to better evaluate AE bidders' qualifications and select the best firm so that the risk to the project failure is minimized.

Research limitations/implications

While the proposed method is a useful tool for selection of the most appropriate AE team for construction projects, it should be simply used as a guide in reviewing the qualifications of different AE candidate firms and the final decision should be made in accordance with the ultimate goal of the project owner.

Originality/value

The model is proven suitable for quantifying imprecise information, reasoning, and making decisions based on vague and incomplete data.

Citation

Nguyen, T.H., Shehab, T. and Gao, Z. (2008), "Selecting an architecture‐engineering team by using fuzzy set theory", Engineering, Construction and Architectural Management, Vol. 15 No. 3, pp. 282-298. https://doi.org/10.1108/09699980810867433