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Contractor selection models have been developed for large scale works with the assumption of the availability of contractor’s information for the clients. However, a similar study of small building works, especially building maintenance and repair works, is almost ignored. In light of the small amount of work, the employment of building consultants for the selection of contractors in small works is often not feasible, and the cost of acquiring the contractor’s information is often prohibitively high. This research uses case studies to show that a contractor selection model for large scale works does not perform well in small works without the advice of the consultant. The high proportion of specification costs in small works contracting deters the detailed design and documentation stage. A wider variation of tender sums is therefore expected and revealed in the case studies. This paper reviews the building procurement mechanism in small building works in Hong Kong and argues that the employment of a property management agent is conducive to the contractor selection process. Accordingly, further investigations are warranted for a contractor selection model for small building works.

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.

Construction projects in Nigeria are generally characterized by cost and time overrun, substandard work, disputes and abandonment; emanating from several factors of which the wrong choice of contractors is a key factor. This study evaluated the criteria adopted by clients and consultants in contractors’ selection in Nigeria. Data were collected with the aid of questionnaire administered on clients and consultants within the Nigerian construction industry. Also prequalification/bid evaluation scores for eighty contractors were collected based on the criteria used in assessing them. The data collected were analysed with the aid of mean score and regression analysis. The result showed that past performance; contractors’ experience; workmanship quality; tender sum; and plant and equipment were the most important criteria for contractors’ prequalification/bid evaluation in Nigeria. A contractors’ selection model was eventually derived based on some of the identified factors. The goodness of fit of the model as defined by the value of r2 was found to be 99%. This therefore implies that only 1% is explained by other independent variables not included in the regression equation; hence the suitability of the model for contractors’ selection in Nigeria.

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.

Procuring best value should be one of the key objectives in public sector construction projects. Best value depends upon sound “selection” strategies which ensure that the outlined project procurement objectives, including client/user demands are met. Examples of “best value” procurement are presented to demonstrate their usefulness and acceptance in principle. Further conceptualizations of various aspects of best value and the “dominance vectors” influencing the ultimate value definitions are developed, in accordance with basic public sector procurement principles. Presents a structured best value based contractor selection framework to optimize realizable value in public sector construction projects.

Benchmarking of best practices has proved useful in the business and manufacturing sectors. However, benchmarking is not established in the construction industry in general and in government organizations in particular. A study of the contractor selection methodologies used by various clients confirms the multiplicity of approaches in practice. This paper aims at identifying some relevant ‘best’ practices and highlighting ‘innovative’ contractor selection approaches that have been used by large public clients. A ‘co‐operative’ and ‘non‐competitive’ conceptual benchmarking model is formulated and presented with a view to encouraging continuous improvement in contractor selection for construction projects.

The ‘lowest‐price wins’ philosophy has been a consistent theme of contractor selection over the years. To comprehensively elucidate this selection preference and compare it with the use of a multi‐criteria selection (MCS) approach in the tenderer evaluation process, this paper investigates MCS tender price selection preferences. That is, project‐specific criteria (PSC) and lowest‐price wins selection practices of UK construction clients, in both building and civil engineering works at in detail via results of the empirical survey. The investigation provides further insight into the evaluation of contractors' attributes (i.e. PSC). Levels of importance assigned (LIA) for each criterion were analysed (i.e. quantitative analysis of the differences in opinions and, variance amongst the respondents) in a multivariate statistical method. Importance attached by construction clients to the ‘lowest‐price wins’ philosophy is also presented. Contrast was made between the MCS approach and the ‘lowest‐price wins’ option amongst the surveyed construction clients. It was found that increased awareness of the use of PSC prevailed amongst the survey construction clients. This indicated that cost has to be tempered with the evaluation of PSC and the attempt of construction clients searching for a new evaluation paradigm (i.e. adoption of MCS approach rather than basing on the lowest‐price wins alone).

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.

This paper describes a multiple‐criteria decision support system (MCDSS) for the selection of the most appropriate contractor. The system can accommodate the unique characteristics of a project in addition to the qualifications and capabilities of those contractors assessed. The system first evaluates the list of contractors by matching their qualifications with specific project conditions. A short list of eligible contractors is thus selected and further the MCDSS compares the current capabilities of the short listed contractors and their plans for the project under consideration, to select the most appropriate contractor. The Delphi method was used to evoke expertise and obtain reliable assessment values for all criteria related to the contractor qualification, while the analytic hierarchy process (AHP) was used to assess the specific project conditions. The system can be easily modified to adopt specific conditions of the proposed project and also to facilitate the decision maker in explaining the reasons for the elimination of excluded contractor.

The selection of the contractor, as a main participant of a construction project, is the most important and challenging decision process for a client. The purpose of this paper is to propose a multi-agent systems (MAS)-based contractor pre-qualification (CP) model for the construction sector in the frame of the tender management system.

The meta-classification and analysis study of the existing literature on CP, contractor selection and criteria weighting issues, which examines the current and important CP criteria, other than price, is introduced structurally. A quantitative survey, which is carried out to estimate initial weightings of the identified criteria, is overviewed. MAS are used to model the pre-qualification process and workflows are shown in Petri nets formalism. A user-friendly prototype program is created in order to simulate the tendering process. In addition, a real case regarding the construction work in Turkey is analyzed.

There is a lack of non-human-driven solutions and automation in CP and in the selection problem. The proposed model simulates the pre-qualification process and provides consistent results.

The meta-classification study consists of only peer-reviewed papers between 1992 and 2013 and the quantitative survey initiates the perspectives of the actors of Turkish construction sector. Only the traditional project delivery method is selected for the proposed model, that is other delivery methods such as design/build, project management, etc., are not considered. Open, selective limited and negotiated tendering processes are examined in the study and the direct supply is not considered in the scope.

The implications will help to provide an objective CP and selection process and to prevent the delays, costs and other troubles, which are caused by the false selection of a contractor.

Automation and simulation in the pre-qualification and the selection of the contractor with a non-human-driven intelligent solution ease the decision processes of clients in terms of cost, time and quality.