A Meta Classification and Analysis of Contractor Selection and Prequalification

In order to attain the objectives of a construction project all of the resources should be used effectively and efficiently. Therefore, the success of a construction project is directly related to organize the project team and to select the building production process participants accurately who will use these resources. Selection of the contractor, as a main participant of a construction project, is the most important and challenging decision process for a client. The objectives of this paper are (1) to introduce the findings of the literature review about the contractor selection and pre- qualification models and systems studied between 1992 – 2013 (2) to classify academic studies dealing with pre-qualification and selection criteria of contractors using a Meta classification method. In this paper, 133 peer-reviewed academic studies have been analyzed and classified in the domain of contractor selection, contractor pre-qualification and weighting criteria. A meta- classification system is adapted and used in order to present the state of the art of contractor pre-qualification and selection challenge. It is obtained that the statistical models, fuzzy set theory and AHP are the most preferred methods in order to solve contractor selection problem. Moreover, an increment in the studies of contractor selection in the last period is determined. Then, based on the findings of literature review, supporting the available contractor pre-qualification and selection models and systems with rapidly changing information technology applications such as agent-based systems is discussed