Author:
Semaan Nabil,Salem Michael
Abstract
Purpose
The construction industry today is one of the biggest industries in the world. As projects continue to grow in complexity, project management continues to evolve. Contractor selection is a difficult task that owners and project managers face. Although previously researchers have worked on the subject of contractor selection, a comprehensive decision support system for contractor selection has not yet been developed. Recent reports of major delays and cost overruns in mega projects highlight the need for a model that is able to be flexible and comprehensive becomes evident. The paper aims to discuss these issues.
Design/methodology/approach
The research focuses on obtaining insights from field experts using both quantitative and qualitative methods. Then, a model was developed in the light of the data collected. Accordingly, the model was tested on a case study.
Findings
This paper presents a model for contractor selection that is wholesome in its take on the topic. The model incorporates both managerial and technical aspects of the problem. The model was tested on a case study and it was proven to be feasible in real world applications. The contractor selection decision support system serves the needs of both academics and industry managers, as an integral part of project management.
Originality/value
The model presented in this paper is innovative in its take on the problems. MCDA tools have been uniquely modified in this paper to cater to the needs of the selection problem while accounting for the criteria hierarchy that incorporates aspects that are instrumental for proper evaluation of a contractor’s likelihood of success.
Subject
General Business, Management and Accounting,Building and Construction,Architecture,Civil and Structural Engineering
Reference30 articles.
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2. Causes of delay in large construction projects;International journal of project management,2006
3. Contractor selection: fuzzy-control approach;Canadian Journal of Civil Engineering,2008
4. Risk assessment of competitive procurement;Journal of Construction Engineering and Management,1995
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