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One of the main challenges facing construction contractors is incorporating future unknown contracts into their annual financial budgets. This paper sets out to review current academic work in this area and to argue that computer‐based simulation techniques are too complex to be adopted in the industry. Therefore, an alternative and a mathematically‐based technique needs to be developed and evaluated.

The paper proposes that, as the pattern of winning construction contracts lacks any seasonality, it may be possible to assume all future work to be starting at one point in time and, by using an average standard value build‐up curve, average duration and the total value work needed, contractors will be able to estimate the total value of contracts needed to achieve a target turnover. Based on the total value of contracts to be won, a proposed mathematical equation is then used to assess the levels of working capital requirements.

The paper evaluates the proposed mathematical model through a series of hypothetical scenarios (developed using a detailed and tested computer‐based simulation model). Results demonstrated the validity and reliability of the models.

The working capital element of the proposed model applies to construction projects where traditional payment mechanisms have been applied (interim payments based on measurements).

The model is very practical in nature and will allow construction companies (particularly large ones) to assess the level of work (in terms of number and values of contracts) they will need to win for them to meet targets for turnover. The model also allows contractors to assess the associated level of funding required.

The mathematical model developed allows contractors to incorporate into their budgets future unknown contracts without the need for computer simulation.

Building information modelling (BIM) implementation is a major change management task, involving diversity of risk areas. The identification of the challenges and barriers is therefore an imperative precondition of this change process. This paper aims to diagnose UK's construction industry to develop a clear understanding about BIM adoption and to form an imperative step of consolidating collective movements towards wider BIM implementation and to provide strategies and recommendations for the UK construction industry for BIM implementation.

Through comprehensive literature review, the paper initially establishes BIM maturity concept, which paves the way for the analysis via qualitative and quantitative methods: interviews are carried out with high profile organisations in Finland to gauge the best practice before combining the results with the analysis of survey questionnaire amongst the major contractors in the UK.

The results are established in the form of the initial phase of a sound BIM implementation guidance at strategic and operational levels. The findings suggest three structured patterns to systematically tackle technology, process and people issues in BIM implementation. These are organisational culture, education and training, and information management. The outcome is expressed as a roadmap for the implementation of BIM in the UK entailing issues that require consideration for organisations to progress on the BIM maturity ladder.

It paves a solid foundation for organisations to make informed decisions in BIM adaptation within the overall organisation structure.

This research consolidates collective movements towards wider implementation of BIM in the UK and forms a base for developing a sound BIM strategy and guidance.

Project duration and cost play a significant role in fulfilling the objectives of both the contractor and the client. This paper builds upon the assumption that, for a given project quality, there exists a relationship between the project duration and the project cost. The behaviour of this relationship is very much influenced by the nature of the project. The paper proposes a general set of potential mathematical expressions for the above relationship and facilitates the identification of the project duration which yields lowest project cost. These are then applied to ‘Harmony’ type housing projects in Hong Kong. Moreover, while demonstrating the difference between the contractor's optimum cost‐time curve and that of the client, the paper suggests that the parties can select one of three options to reach a compromise. To this end, the paper introduces a set of mathematical expressions to represent these compromise‐solutions.

The way in which clients or their consultants undertake to select firms to tender for a given project is a highly complex process and can be very problematic. This is also true for public authorities as, for them, ‘compulsory competitive tendering’ is a relatively new concept. Despite its importance, contractors' prequalification is often based on heuristic techniques combining experience, judgement and intuition of the decision makers. This, primarily, stems from the fact that prequalification is not an exact science. For any project, the right choice of the contractor is one of the most important decisions that the client has to make. Therefore, it is envisaged that the development of an effective decision‐support model for contractor prequalification can yield significant benefits to the client. By implication, such a model can also be of considerable use to contractors: a model of this nature is an effective marketing tool for contractors to enhance their chances of success to obtain new work. To this end, this work offers a decision‐support model that predicts whether or not a contractor should be selected for tendering projects. The focus is on local authorities because, in the absence of a viable universal selection system, there are significant variations in the way they conduct prequalification. The model is based on the use of artificial neural networks (ANN) and uses data relating to 42 local authorities (clients). With the aid of a questionnaire and a scaling system, the prequalification attributes that are considered to be important by clients are identified. The survey indicates significant variations in the level of importance given to different attributes. Statistical methods are adopted to generate additional data representing disqualified instances. Following a preprocessing exercise, the data form the basis of the input and output layers for training the neural‐net model. An independent set of data is subjected to a similar preprocessing for testing the model. Tests reveal that the model has a highly satisfactory predictive accuracy and that the ANN technique is a viable tool for the prediction of success or failure of the contractor to qualify to tender for local authority projects.

This paper addresses the effect of different procurement methods (traditional, design and build and management contracting) on project cash flow. Historical data relating to the periodic cost of 150 construction projects were collected. Four criteria were identified to classify the projects: type of project, size, company and type of procurement. The effect of these criteria on the S‐curves was then examined using ANOVA. Results confirmed that differently procured projects with different sizes produce different patterns. The company and type of project did not significantly affect the shape of the S‐curve. Standard S‐curves were then modelled for the three aforementioned procurement routes. These curves were used to calculate the relevant cash flows using a computer based cash flow forecasting model. A series of simulation tests were conducted to evaluate the extent of variation in cash flow, given different contract conditions. Results revealed that, in some cases, the variation in procurement routes has a significant effect on contract cash flows.

The model and existing practice of the construction supply chain (CSC) in the United Kingdom (UK) and Australia was presented in this chapter. The policies and reports that support the practice of the CSC were examined in both countries. It was discovered from the review of literature that the UK has a more detailed report targeted at improving the CSC than Australia. However, both countries have a common factor affecting their CSC which originates from fragmentation experienced within their supply chain. Construction stakeholders in the UK and Australia believe that collaboration and integration are vital components for improving performance. The majority of the contractors in both countries embrace collaborative working for the sole purpose of risk sharing, access to innovation and response to market efficiency. However, most of the models developed for managing the CSC in the UK are built around building information modelling (BIM). Also, the reviewed studies show that supply chain management practice will be effective following the following principle: shared objectives, trust, reduction in a blame culture, joint working, enhanced communication and information-sharing. Finally, the UK has a more established framework and more CSC models compared to Australia.

Construction projects are well known for their complexity and ambiguity. These projects carry out higher risk than traditional ones because they entail high capital outlays and intricate site conditions. Poor financial management of these projects may lead to bankruptcy; therefore, effective cash flow management is essential. Although the peculiar characteristics of construction projects, the accuracy of cash flow forecasting has been a long lasting problem. The paper aims to discuss these issues.

Many unforeseen factors affect the cash flow forecasting of construction projects. Therefore, the objective of the presented research in this paper is to examine the impact of these factors on contractor's cash flow. A model has been established by integrating analytic hierarchy process and simulation to examine the impact of various factors on cash flow. Data on the selected factors have been collected through questionnaires from various agencies in North America and China.

Results show that the most significant factors are: change of progress payment, payment duration, financial position of the contractor, project delays, and poor planning. It also shows that the effect of cash inflow factors varied approximately from 9.7 to 16.3 percent with a mean value of 12.4 percent.

The implementation of the developed models are limited to few case study projects in testing the models. However, the developed models and framework are sound for future improvement. They are considered as a major step toward a broader cash flow planning.

The developed methodology and models play essential roles in decision-making process.

The developed model is expected to help contractors realistically forecast project cash flow under uncertainty. This may lead to more dependable and professional cash flow management, which might substantially reduce failures in construction business.

The purpose of this paper is to identify critical non-value adding (NVA) building information modeling (BIM) implementation activities in current building project delivery process, develop a BIM implementation readiness (BIMIR) evaluation model, and assess BIMIR statuses in building projects in Singapore.

A questionnaire survey and four post-survey interviews were conducted in Singapore. A fuzzy synthetic evaluation approach was adopted in the model development.

In total, 38 out of 44 NVA BIM implementation activities were deemed critical and used in the proposed model, among which “lack of involvement by contractors to contribute site knowledge” in the design development phase was ranked top. This model was validated in five projects. It was found that most of 73 surveyed building projects were in a low BIMIR status and the assessment results were consistent with current industry practices of BIM implementation in Singapore.

There may be geographical limitation on the identification of the critical NVA BIM implementation activities. However, because BIM mandate spreads globally, the findings can help overseas project teams customize their own NVA activities and evaluation models.

As BIM implementation is mandated in Singapore, BIMIR evaluation helps local project teams identify weak areas of their BIM implementation activities and prioritize resources to enhance those areas.

No tool has been developed for evaluating BIMIR at the project level in the construction industry in Singapore or at large in Asia. Four BIMIR statuses are defined, which are consistent with Singapore’s BIM guidelines and standards.

Building Information Modeling (BIM) is a revolutionary innovation in the construction industry to virtually design and mange projects throughout the building lifecycle. Although Estonia is one of the foremost countries in the Information and Communications Technology (ICT) sector, BIM adoption in the Estonian construction industry is still lagging behind other countries. This paper is part of doctoral research that aims to determine the barriers to BIM adoption and develop a framework for effective implementation of BIM in the Estonian construction industry. The purpose of this paper is to examine the status of BIM adoption, BIM benefits and common barriers to BIM adoption in the construction industry worldwide.

The methodology used in this study is a literature review of journal articles, conference proceedings and published reports from various sources.

This study showed BIM benefits through building lifecycle phases and explored the BIM adoption rate in the construction industry of various countries. Eighteen barriers to BIM adoption were also identified.

The study presented is limited to a literature review – some related literature may have been missed.

The main practical significance of this study is that the findings can be used to inform a further survey to model the barriers to BIM adoption in the Estonian construction industry.

This study offers information on BIM adoption in the construction industry and will form the basis of further research.

Most decision-making problems in construction are complex and difficult to solve, as they involve multiple criteria and multiple decision makers in addition to subjective uncertainties, imprecisions and vagueness surrounding the decision-making process. In many instances, the decision-making process is based on linguistic terms rather than numerical values. Hence, structured fuzzy consensus-reaching processes and fuzzy aggregation methods are instrumental in multi-criteria group decision-making (MCGDM) problems for capturing the point of view of a group of experts. This chapter outlines different fuzzy consensus-reaching processes and fuzzy aggregation methods. It presents the background of the basic theory and formulation of these processes and methods, as well as numerical examples that illustrate their theory and formulation. Application areas of fuzzy consensus reaching and fuzzy aggregation in the construction domain are identified, and an overview of previously developed frameworks for fuzzy consensus reaching and fuzzy aggregation is provided. Finally, areas for future work are presented that highlight emerging trends and the imminent needs of fuzzy consensus reaching and fuzzy aggregation in the construction domain.