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Contractor prequalification is a typical multiple criteria decision‐making problem that includes both quantitative and qualitative criteria. The conditions surrounding the prequalification decision are often imprecise, subjective and uncertain; assessments are consequently made using linguistic approximations. Fuzzy set theory is specifically designed to handle qualitative and linguistic data based on approximations and provides a method of representing in numerical form the linguistic approximations used to describe the decision‐maker judgments. However, fuzzy set theory has a weakness in identification of the relative weights of the decision criteria. On the other hand, one of the most accurate and easy methods for identifying the relative weights is the analytic hierarchy process (AHP). This paper seeks to address these issues.

The main objective of this paper is to develop a new integrated decision model composed of fuzzy set theory and analytic hierarchy process (AHP) methodologies approach that takes full advantages of the fuzzy set theory and the AHP. Two fuzzy approaches are considered, namely Chang's extent analysis and Jaskowski aggregated group decision analysis.

Both approaches are applied and validated on actual contractors in the Egyptian construction market. A software tool is developed to automate the calculations and a case study is provided.

This research produced a new integrated decision model composed of fuzzy‐AHP methodology approach that takes full advantages of the fuzzy set theory and AHP for tackling the uncertainty and imprecision of contractor prequalification during the prequalification stage, where the decision‐makers comparison judgments are represented as fuzzy triangular numbers. The default criteria used in this model had been collected through the literature review and experts’ opinion for building projects.

Prequalification of contractors is a very important step in construction project procurement under the contract “Due Process” policy in Nigeria. The purpose of this study, therefore, is to investigate the impact of contractors' prequalification on cost, time and quality performance of construction projects.

Data were collected with the aid of a questionnaire addressed to construction practitioners selected from clients, consultants and contractors' organizations. Also archival data on 77 completed building projects relating to prequalification assessment of contractors and project delivery variables were sourced from consultant quantity surveyors. The data were analysed with the aid of mean score and one‐way analysis of variance (ANOVA).

The results show that contractors' prequalification has significant impact on time and quality performance of construction projects as evidenced by p‐values of 0.039 and 0.030, respectively.

The findings should provide a valuable reference for clients and consultants during contractors' prequalification and contract award.

The outcome of this paper will assist clients and consultants in the construction industry to carry out objective assessment of contractors' potential performance in relation to project goals prior to contract award.

The studies on contractor prequalification focus more on the review of models and algorithms rather than review of the criteria for contractor prequalification. However, the basis of every prequalification model primarily relates to the measurement and judgement of prospective contractors based on a set of decision criteria. This paper aims to address the gap by reviewing academic papers on contractor prequalification criteria.

A desktop search was conducted under the “T/A/K (title/abstract/keyword)” field of the Scopus search engine. A total of 49 papers were initially identified; however, only peer reviewed journals were selected for the study; therefore, a sample of 36 was subsequently used. Further filtering was done in which 26 papers were found valid for further analysis as it was realized that, not all the identified papers presented empirical arguments about the issue of contractor pre-qualification criteria. The selected 26 papers were subjected to content analysis to identify the key contractor pre-qualification criteria.

A total of 41 criteria were identified which were subsequently classified into six main categories, namely, technical considerations, management considerations, financial considerations, reputation considerations, general experience considerations and health, safety and environmental considerations. There was an indication that, the involvement of health, safety and environmental considerations in contractor prequalification proceedings is limited.

The major limitation of this research was the limited number of papers selected for further analysis based on the Scopus search engine. The identified criteria serve as a basis for further empirical studies on contractor prequalification criteria.

The outcome of this study broadens the understanding of practitioners and researchers on the various criteria for contractor prequalification.

By critically reviewing available literature on contractor prequalification, the study sets the tone for further empirical studies on contractor prequalification.

Competent contractors are one of the critical stakeholders to achieve targeted sustainability objectives in green building (GB) projects. Prior to contractor selection, prequalification is an important step, which requires contractors with certain capabilities in addition to traditional features. This study aims to develop a systematic and practical model for prequalification in GB projects using a multi-criteria decision-making (MCDM) approach by adopting the analytical hierarchy process (AHP).

The AHP model with 8 main criteria groups and 25 sub-criteria is structured based on literature review and professional opinions accompanied by a pilot study. Then, interviews with experts, who are experienced in the development and application phases of GB projects in Turkey, are arranged to collect judgements. The agreement levels between different groups of experts are analysed via Pearson's and Spearman's rank correlation coefficient. Model applicability is tested on six hypothetical contractors for practicality.

The results show that i) financial capabilities, ii) legal status and iii) sustainability groups are the top three main criteria, while i) compliance with schedule requirements of the client, ii) current legal status including suits, iii) negative litigation history records, iv) contractor's compliance capacity to client's sustainability checklist for the proposed project and v) sustainability with lower life cycle cost (durability, maintenance, constructability) are the top five sub-criteria.

There is a gap in the literature analysing contractor prequalification phase in GB projects. This study attempts to fill this lack provided with a practical evaluation tool.

Nowadays, engineering, procurement and construction (EPC) contracts are being widely used to perform industrial and infrastructure projects because of several reasons like high speed of implementation. However, these contracts are always accompanied by high risks and uncertainties. Thus, selection of the right EPC contractor has significant importance. This paper aims to present a fuzzy multi-criteria decision-making (MCDM) model for EPC contractor prequalification.

First, the EPC contractor prequalification criteria are defined by using literature review and interviewing experts. Second, the weights of criteria are determined by interviewing experts. Then, each EPC contractor is evaluated in each criterion. Finally, fuzzy weighted average (FWA) approach is employed to select the right contractor among potential EPC contractors.

The proposed model is prepared as an applicable model for clients to select the right EPC contractors among contractors who want to conduct the project.

As a lack of applicable model does exist to assign the prequalification of EPC contractors, this study is one of the first research studies which proposed a fuzzy MCDM model for evaluation of EPC contractors. To cope with the uncertainty of the prequalification problem, fuzzy logic has been used. Using fuzzy sets leads to reaching more reliable results. Also, a real case study is provided to explain the proposed model.

Management capability is one of the major criteria for evaluating construction contractors during prequalification and tender evaluation This paper aims to investigate the impact of contractors' management capability as a prequalification criterion on cost and time performance of selected building projects.

Prequalification assessments of management capability of wining contractors as well as cost data relating to 77 completed building projects executed between 2004 and 2007 are obtained. The data obtained from a questionnaire and archival data are analyzed using one‐way analysis of variance and multiple regression.

The results reveal that contractors' management capability has significant impact on cost and time performance of building projects as evidenced by p‐values of 0.042 and 0.039, respectively.

The research could be of significant benefit at the research implementation stage of public procurement practice especially in relation to the construction industry in Nigeria. Construction practitioners involved in prequalification and tender evaluation should continue to seek relevant information relating to management capability from the candidate contractors during prequalification and tender evaluation.

Models capable of predicting the final cost and duration of building projects are eventually derived based on prequalification assessment of contractors on management capability, proposed contract duration and the initial contract figure. The goodness of fit of the models as defined by the value of R² is found to be 96.2 percent and 90.01 percent for cost and time, respectively; thus signifying high predictive efficacy of the models.

Contractor prequalification involves the establishment of a standard for measuring and assessing the capabilities of potential tenderers. The required standard is based on a set of prequalification criteria (PQC) that is intended to reflect the objectives of the client and the requirements of the project. However, many pre‐qualifiers compile a set of PQC according to their own idiosyncratic perceptions of the importance of individual PQC. As a result, sets of PQC, and hence prequalification standards, vary between prequalifiers. This paper reports on an investigation of the nature of the divergencies of the perceived importance of individual PQC by different groups of prequalifiers via a large‐scale empirical survey conducted in the UK. The results support the conclusion that there are significant systematic differences between groups of prequalifiers, with the individual PQC that contribute most to the differences being the method of procurement, size of project, standard of quality, financial stability, project complexity, claim and contractual dispute and length of time in business.

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.

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.

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.

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.

A quantitative contractor selection technique which embraces the pre‐qualification, evaluation and final selection processes is being developed. The emphasis is on evaluating contractors' performance potential in terms of their ability to achieve time, cost and quality standards. This approach is in contrast to the majority of current selection techniques which tend to prequalify, then discriminate predominantly on the cost component of tenders. The conceptual model is applied to a hypothetical but realistic scenario of a contractor competing for a small industrial contract. This illustrates the mechanics of the new technique, emphasizing that contractor selection should include identifying the contractor with the best performance potential and not merely the lowest bidder.

Contractor selection is carried out in order to choose a competent and capable contractor to do the work. To help in this selection, baselines are established to ensure that the contractors have the required skills, resources, and abilities to execute the project. Contractor selection is a multiple criteria decision making wherein several criteria are required to be evaluated simultaneously. This paper aims to propose a decision‐making model.

The proposed model utilizes superiority and inferiority ranking (SIR) method and it provides six preference structures in order to compare the performance of alternatives' criteria. As such, it can represent discrete or continuous criteria. The preference structures utilize indifference and preference thresholds to capture the characteristics of functions that represent the specified criteria. The model provides two aggregation procedures (simple additive weighting and technique for order preference by similarity to the ideal solution) to generate superiority and inferiority flows.

The proposed model is generic and can be used as a tool to evaluate alternatives in several applications such as value engineering, optimum organization structure, and constructability analysis. It enables its users to define the criteria that are deemed important for evaluation.

The proposed multiple criteria decision making (SIR method) is novel to construction. This ranking method can be utilized as a successful tool in contractor selection problem.