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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.

Diverse construction project stakeholders demand “fully‐informed” and well‐balanced decisions that target multiple objectives appropriately. This paper introduces initiatives into the development of a cluster of information and communication technology‐artificial intelligence supported empowerment systems and sub‐systems. Examples presented include conceptual models and/or descriptions of: the framework of an over‐arching management support system (MSS); multi‐agent support for improved collaborative working in: design development and relationally integrated supply chain management; and web‐based quality management.

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.

A Hong Kong‐based study of factors affecting construction industry performance levels confirms that selection methodologies and decisions are critical, both at the upstream formulation of procurement and operational systems themselves as well as the downstream selection of various project participants. Needs are identified for a holistic approach to broader procurement choices that incorporate all procurement sub‐systems, an integration with synergistic operational sub‐systems and more informed and intelligent participant choices. The many interacting variables and potential information overload point to the consequential need for harnessing IT/IS (information technology/information systems) to enable smarter selections at all stages of the construction supply chain. Frameworks and sample modules of the proposed knowledge‐based decision aids are presented in the case of overall procurement system selection and contractor selection.

Rework is an endemic problem in construction projects and has been identified as being a significant factor contributing cost and schedule overruns. Causal ascription is necessary to obtain knowledge about the underlying nature of rework so that appropriate prevention mechanisms can be put in place. The paper aims to discuss these issues.

Using a supervised questionnaire survey and case-study interviews, data from 112 building and engineering projects about the sources and causes of rework in projects were obtained. A multivariate exploration was conducted to examine the underlying relationships between rework variables.

The analysis revealed that there was a significant difference between rework causes for building and civil engineering projects. The set of associations explored in the analyses will be useful to develop a generic causal model to examine the quantitative impact of rework on project performance so that appropriate prevention strategies can be identified and developed.

The limitations include: small data set (112 projects), which include 75 from building and 37 from civil engineering projects.

Meaningful insights into the rework occurrences in construction projects will pave pathways for rational mitigation and effective management measures.

To date there has been limited empirical research that has sought to determine the causal ascription of rework, particularly in Hong Kong.

The “problem” of selecting a contractor has attracted significant academic research endeavour over the last two decades. The principal aim here is to examine that research via published academic outputs for the period circa 1990‐2009.

A sample of published contractor selection (CSn) research is critically appraised. Aspects highlighted include: stated aims and research justification; methodological approaches employed; research tools used; and products of CSn research.

Main research foci are observed as: modelling the CSn process; studying selection criteria; and “interrogation” of existing CSn systems. Foci justifiers are linked mainly to the “importance” and “difficulties” of CSn decision making. Deterministic modelling of CSn is the favoured methodological approach, followed by documentary synthesis then questionnaire surveys. Preferred research tools are found to be system interrogation, rank order analysis and Likert scale/importance indices, with hypothesis testing and “other” methods used less so. Almost two‐thirds of research products are CSn models, with derived or proffered processes, and knowledge relating to CSn criteria, between them representing approximately the remaining third of output.

It is suggested that many of the CSn models exhibit as much complexity as the original “problem” they sought to resolve, while the reliability and longevity of suggested “cocktails” of CSn criteria (in practice), might be questioned. A call for future research products to more closely consider end‐user impact and potential for “take‐up” by industry is made. An empirical follow‐on study to assess (inter alia) practitioner use and “value” of CSn research is proposed.

The paper signals a possible need for greater industrial engagement in the research domain.

The findings are novel to this paper.

Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).

A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India.

Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution.

It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified.

An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.

The purpose of this paper is to develop a framework to optimize time, cost and quality in a multi-mode resource-constrained project scheduling environment.

A case study approach identified the activity execution modes in building construction projects in India to support multi-mode resource-constrained project scheduling. The data required to compute time, cost and quality of each activity are compiled from real construction projects. A binary integer-programming model has been developed to perform multi-objective optimization and identify Pareto optimal solutions. The RR-PARETO3 algorithm was used to identify the best compromise trade-off solutions. The effectiveness of the proposed framework is demonstrated through sample case study projects.

Results show that good compromise solutions are obtained through multi-objective optimization of time, cost and quality.

Case study data sets were collected only from eight building construction projects in India.

It is feasible to adopt multi-objective optimization in practical construction projects using time, cost and quality as the objectives; Pareto surfaces help to quantify relationships among time, cost and quality. It is shown that cost can be reduced by increasing the duration, and quality can be improved only by increasing the cost.

The use of different activity execution modes compiled from multiple projects in optimization is illustrated, and good compromise solutions for the multi-mode resource-constrained project scheduling problems using multi-objective optimization are identified.

The heightened state of flux in the construction industry in general and construction procurement strategies in particular, provides welcome opportunities to inject innovative improvements. While some improvements are generated from within the construction industry itself, these evolve sluggishly along prolonged learning curves. These are compared with lessons to be learnt and examples to be drawn from manufacturing in the development of a marketable product. A product development focus is thus advocated in re‐integrating segregated groups and in empowering and inspiring the innovations that are needed to achieve the dramatic productivity gains now demanded from the construction industry.

One of the possible systems of project delivery is design & build (D&B), which is widely used in many countries. In the Polish public procurement market, the D&B system has been applied for a relatively short time, only since 2004, and despite the possibility, so far public clients have applied the D&B system only occasionally. This paper describes the current status of using the D&B method in the public procurement sector in Poland. Five hundred and fifty eight completed public-sector projects have been subject to analysis. Items analysed include the design/builder method of award, and types and value of contracts. The results provide insights for owners, the advantages and disadvantages of the D&B system, and highlight the need to change the method of selecting the contractor for the D&B system.