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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.

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.

The focus of this work is on the client-designer interface where decisions have significant impact over the lifecycle of the project. Therefore, the briefing stage is examined in the context of clients’ needs which is divided into project-based strategy and broader clients’ strategy. The purpose of this paper is to address the pitfalls in the briefing process which has been attributed to the shortcomings in the client-designer communication interfaces. This will be achieved by developing an automated brief generation framework. The research examines the efficiency of standard approaches to modelling and design, and the benefits that these methodologies have offered to the computer industry. The work reviews the similarities between the two industries and argues in support of the potential benefits in adopting a standard methodology in the construction industry. The structure upon which the framework is developed is based on system analysis and design methodology (SSADM) which has proven to be an effective platform used within the software development industry.

SSADM is an established methodology within the software development industry. The paper will demonstrate that due to fundamental similarities between the construction and software development industries, SSADM is likely to offer a viable platform upon which an automated enhanced brief generation model is developed for use in the construction industry. The construction design and construction process will be mapped on SSADM high-level definition before focusing and honing on the design phase. The methodology for the development of the framework will be based on the rationalist approach of generating knowledge through reasoning leading to model-building.

A model that is based on SSADM is proposed for the design development phase of construction projects. In order to shape the project strategy, the model considers the combined role of clients’ requirements with organisation strategy and environmental factors. The paper has shown that it is feasible to increase the automation of the briefing process and enhanced the briefing output. The model here does not diminish the importance of direct communication between the client and the design team. It provides a more structured way of doing so, while taking advantage of vast array of data and technology in order to improve the brief outcome.

From practical perspective, the proposed framework is in its formative stage, thus requiring incremental refinement through several case studies. This is particularly true about the AI components of the system which typically rely on extensive data representing the real-case scenarios. Therefore, the work invites further research into the examination of various parts as well as the overall system.

There are several ways by which construction projects are procured. There may be fluctuation in their rate of usage, but while there is no indication of any procurement option fading, new ones such as PPP and PFI are periodically introduced. The existence of this diversity is indicative of the fact that the industry tends to respond to problems rather than attempting to instigate a measured solution supported by theoretical underpinning. Subsequently, there have been suggestions of a communication and information discourse between actors and within processes involved in project lifecycle. This project is aimed at addressing the gap in the client-designer communication. The automated approach to brief generation will lead to better briefs while reducing ambiguities as well as the overhead associated with brief generation.

The quality of project brief has a significant impact on decisions at the design stage. In turn, these decisions will influence all phases of construction project lifecycle. The briefing session and requirement analysis of a construction project can be very difficult for inexperienced clients particularly for complex projects. Therefore, there is potential for the process of client-requirement-analysis to be optimised. The work promises to improve the quality of the briefing process, thus helping clients to realise their intended objectives and minimise resource waste.

The work builds on the commonalities of the construction and software development industries and takes advantage of the advancements in the latter. In doing so, project quality is defined quantitatively which is used to develop project strategy in a three-dimensional space. The development of the model was also contingent upon enhancement of artificial neural network structure.

Construction cash flow models developed in previous researches demonstrated that cash flow profiles vary for differing procurement methods. However, the issue of whether contractors are satisfied or dissatisfied with payment terms impacting cash flows in differing procurement methods is yet to be investigated. This is the concern of this study. The study identified from literature, payment terms potentially thought to impact construction cash flow. Using a 6‐point Likert‐type scale, a questionnaire survey was administered to UK construction contractors in order to assess their level of satisfaction with identified payment terms influencing construction cash flow. Responses from the survey, which focused on traditional and design and build procurement methods were analysed using mean response analysis and one‐way analysis of variance. Results showed that while contractors were satisfied with most of the contractual factors investigated under both procurement systems, they were dissatisfied with two of the factors, namely, time lag between entitlement to receive and actually receiving cash payment and percentage of contract sum retained. This dissatisfaction calls for action to consider devising alternative means of dealing with retention and delay payments.

Significant risk factors inherent in construction cost flow forecast were identified in this study. The aim of this paper is to develop regression models to assess the impacts of the identified risks on the baseline forecast at the in‐progress stage of construction.

Two stages were involved in data collection. The first was a structured questionnaire survey administered on 370 UK contractors to identify significant risk factors inherent in cost flow forecast. The second stage was the collection of forecast and actual cost flow data from 55 case study projects. Variations between these pair of data sets were measured at 30 per cent, 50 per cent, 70 per cent and 100 per cent completion periods. Respondents were then requested to score on a Likert type scale, the extent of occurrence of the significant risk factors in the case study projects. This pair of data sets were used in regression modelling.

Significant risk factors were identified from the questionnaire survey analysis as: changes to initial design, variation to works, production target slippage, delay in agreeing variation/dayworks and delay in settling claims among others. Using the identified significant risk factors and the periodic variability measurements, multiple linear regression models were developed. The models were promising in that they helped to establish the fact that the phenomenon under consideration could be modelled. They also provided some insights in explaining the observed variability between the baseline cost flow forecast and actual cost flow based on risk impacts.

The developed models showed a promising level of accuracy but also indicated that the phenomenon under consideration is not strictly linear and may need to explore some other form of modelling.

The developed models provide invaluable information to the construction contractors regarding the likely impacts of significant risk variables on cost flow baseline forecast at different stages of construction so that a pro active risk response can be put in place.

This study makes an original contribution of providing a modelling insight into the phenomenon of how risks inherent in construction could impact the baseline cost flow forecast at different stages of construction. The information is invaluable in making pro active risk response.