Contractor selection is the process of selecting the most appropriate contractor to deliver the project as specified so that the achievement of the best value for money is ensured. Construction clients are becoming more aware of the fact that selection of a contractor based on tender price alone is quite risky and may lead to the failure of the project in terms of time delay and poor quality standards. Evaluation of contractors based on multiple criteria is, therefore, becoming more popular. Contractor selection in a multicriteria environment is, in essence, largely dependent on the uncertainty inherent in the nature of construction projects and subjective judgment of decision makers (DMs). This paper presents a systematic procedure based on fuzzy set theory to evaluate the capability of a contractor to deliver the project as per the owner’s requirements. The notion of Shapley value is used to determine the global value or relative importance of each criterion in accomplishing the overall objective of the decision-making process. The research reported upon forms part of a larger study that aims to develop a fuzzy decision model for construction contractor selection involving investigating multiple criteria selection tendencies of construction clients, relationship among decision criteria, and construction clients’ preferences of criteria in the contractor selection process. An illustration with a bid evaluation exercise is presented to demonstrate the data requirements and the application of the method in selecting the most appropriate contractor for the project under uncertainty. The proposed model is not intended to supplant the work of decision-making teams in the contractor selection process, but rather to help them make quality evaluations of the available candidate contractors. One major advantage of the proposed method is that it makes the selection process more systematic and realistic as the use of fuzzy set theory allows the DMs to express their assessment of contractors’ performance on decision criteria in linguistic terms rather than as crisp values.

The statistical characteristics of cost overruns experienced from contract award in 276 Australian construction and engineering projects were analyzed. The skewness and kurtosis values of the cost overruns are computed to determine if the empirical distribution of the data follows a normal distribution. The Kolmogorov-Smirnov, Anderson-Darling, and chi-squared nonparametric tests are used to determine the goodness of fit of the selected probability distributions. A three-parameter Frechet probability function is found to describe the behavior of cost overruns and provide the best overall distribution fit. The Frechet distribution is then used to calculate the probability of a cost overrun being experienced. The statistical characteristics of contract size and cost overruns were also analyzed. The Cauchy (<A$1 million), Wakeby (A$1 to 10 million, <A$101 million) and four-parameter Burr (A$11 to 50 million) tests were found to provide the best distribution fits and used to calculate cost overrun p...

Low-carbon building design requests an estimation of total embodied carbon as the environmental performance metric for comparison of different design options in early design stages. Due to a lack of consensus on the system boundaries in building life cycle assessment (LCA), the carbon estimation results obtained by the current methods are often disputable. In this regard, this paper proposes a method for estimating building embodied carbon based on digital twin technology and LCA. The proposed method is advantageous over others by providing (1) a cradle-to-cradle LCA and (2) an automated data communication between LCA and building information modelling (BIM) databases. Because data for the processes in the life cycle are collected via digital twin technology in a standard and consistent way, the obtained results will be considered credible. So far, a conceptual framework is developed based on a comprehensive literature review, which consists of three parts. In the first part, formulas for LCA are given. In the second part, a hybrid approach combining semantic web with a relational database for BIM and radio-frequency identification (RFID) integration is described. In the third part, how to design the LCA database and how to link LCA with BIM are described. The conceptual framework proposed is tested for its reasonableness by a small hypothetical case study.

The construction industry has witnessed the failure of many contractors due to varying reasons such as financial problems, poor performance, or accidents arising from the lack of adequate safety consideration at worksites. All these incidents have led to the impression that the current system of awarding the contracts is inefficient in selecting the contractor capable of meeting the demands and challenges of present times and hence needs to be reviewed accordingly. Therefore, in an attempt to investigate the current situation of the Singapore construction industry a questionnaire survey was conducted for accruing the data required to identify the important contractor selection criteria (CSC) and to draw upon construction practitioners’ opinions regarding the importance of those CSC in assessing the capabilities of the candidate contractors during the selection process. The research reported upon forms part of a larger study that aims to develop a computer-interactive multicriteria decision system for contractor selection involving identification of CSC for inclusion in the system, investigation of CSC preferences of construction practitioners, and establishment of weights for those CSC from their perceived importance determined through the questionnaire survey of Singapore construction practitioners. The study highlights that there are statistically significant differences in opinions regarding the degree of importance assigned to some CSC among public clients, private clients, and contractors. Findings from the study may act as an aid in improving the Singapore construction industry by helping construction clients identify multiple CSC apart from cost which should always be considered when assessing the capability of candidate contractors during the selection process, by assisting contractors in improving their attributes in line with clients’ preferences and by facilitating Singapore construction clients and researchers to develop a contractor selection system capable of assessing multiple attributes of the candidate contractors so that the risk of the project failure due to the selection of an inappropriate contractor is minimized.

The design of concession period for build–operate–transfer (BOT) projects is crucial to financial viability and completion risk management. A systematic analysis shows that concession period design involves the design of concession period structure, the determination of the concession period length and incentive schemes. The concession period may have a single‐period structure or a two‐period structure, its length may be fixed or variable, and it may be combined with incentive schemes. Different designs reflect different risk control strategies for completion time overruns. The single‐period concession structure requires the project company to assume completion risk, while the two‐period concession structure could, to some extent, reduce the completion risk exposure to the project company, depending on the incentive schemes. Through Monte Carlo simulation, this paper evaluates the mean net present value (NPV), variance and NPV‐at‐risk of different concession period structures so that both the government and the concessionaires can understand their risk exposure and rewards. The paper then analyses the influence of project characteristics on concession period design to evaluate the feasibility of the design. It is concluded that a well‐designed concession period structure can create a ‘win–win’ solution for both project promoter and the host government.