Journal of Construction Engineering and Management

Long-term transportation policies require government officials to predict the cost of public road construction during the conceptual planning phase. However, early cost prediction is often inaccurate because public officials are not familiar with cost engineering practices, and moreover, have limited time and insufficient information for estimating the possible range of the cost distribution. This study develops a conceptual cost prediction model by combining rough set theory, case-based reasoning, and genetic algorithms to better predict costs in the conceptual planning phase. Rough set theory and qualitative in-depth interviews are integrated to select the proper input attributes for the cost prediction model. Case-based reasoning is then applied to predict road construction costs by considering users’ difficulties in the conceptual policy planning phase. A genetic algorithm is also used to assist the rough set model and case-based reasoning model to obtain optimal solutions. The result of the analysis shows that the proposed conceptual cost prediction model is reliable and robust compared to the existing cost prediction model.

Activity delays are a common issue in the construction industry and can increase project schedules and costs. Recent research efforts have focused on the quantitative evaluation of delay impacts. The literature suggests that the construction industry is in need of additional research to systematically relate the causes of delays to their impacts. To overcome this limitation, this paper analyzes delay causes in activities that were not completed as scheduled. The paper contributes to a methodology to examine the qualitative (delay causes) and quantitative (time performance) dimensions of the delay issue. The paper proposes two indicators, as follows: (1) reason for noncompliance (RNC) as an indicator that characterizes scheduling failures, and (2) delay index (DI) as a time-performance indicator that describes the impacts of delay on critical and noncritical activities. The paper presents two building projects as case studies, with planning and subcontractors as the primary RNCs that have the greatest impact on time performance. Planning was the most harmful delay cause on time performance.

Construction defects can exert significant impacts on project performance. These defects are typically traced back to their initiating root causes, formulated as infectious decisions, practices, or circumstances. The root causes often act as pathogens that propagate to spread numerous other risky conditions, thereby making projects prone to defects. Accordingly, it is essential to quantify the pathogenic capacity held by each root cause to determine the scope of potential risk associated with its existence. Although several studies have striven to identify project pathogens, research on determining the most pathogenic causes to develop further defect management efforts is lacking. To address this deficiency, the aim of this study was to develop a methodology that captures the complex mechanisms of defect generation and quantifies their pathogenic capacities in accordance to their position within the network of sequential events leading to defects. Specifically, the study uses a social network analysis (SNA) approach as a platform to formulate the interrelationships of defect causes, and review SNA metrics to develop a formal mathematical expression of pathogenicity, forming a new project pathogens network (PPN) methodology. Application to four residential projects in Dubai confirmed that PPN has great potential for revealing the pathogenic capacities held by the infectious conditions resulting in construction defects. This paper contributes to knowledge in the area of construction engineering and management by proposing a methodology that is deliberated to providing both mathematical and visualization analyses needed to address the complex mechanisms of defect generation, which thus enables project practitioners and academics to better understand the vulnerability of a construction-project system to pathogenic conditions.

Contractors rely significantly on quotations from subcontractors to price a tender. However, much of the research carried out in the United Kingdom (UK) on construction-tendering has been done from the perspective of the relationship between the contractor and client. This paper addresses that gap by identifying and examining the major barriers to effective pricing of tenders by subcontractors and the business environment of their commercial relationships with contractors. A questionnaire study involving 94 subcontractors and semistructured interviews with five of them was conducted in 2011. The primary barriers to providing better cost-certainty and quality of response in quotations to contractors relate to quality of documents, bidding time, competition, resource levels, information and communication technology, unethical behavior by the contractor, uneven collaborative relationships, input specificity, level of relationship that exists, and the time to assimilate and provide the output response. Contractors and clients should help address the barriers. For contractors, this can enhance competitiveness, profitability, and supply-chain relationships. For clients, this can lead to better project outcomes because subcontractors form a major part of the organizational structure of projects. Addressing the concerns expressed by subcontractors may also require a collaborative approach, perhaps in conjunction with an industry-wide investigation and plan of action.

Residential buildings are one of the major consumers of energy. The majority of the housing stock consists of existing homes, and a large number of these homes are energy inefficient. Retrofitting existing homes to make them energy efficient can contribute immensely to energy savings. Buildings in the United States consume 72% of electricity and 40% of all energy, and residential buildings account for over half of these percentages. Existing buildings consume more than 70% of the electricity consumed by the buildings. With more than 130 million existing homes, energy retrofitting of existing homes is a critical area. Literature has identified that a key impediment to home energy retrofits (HER) is the lack of information or the lack of information in a format that the homeowners can understand and use to make retrofit decisions. Homeowners traditionally depend on experts in the field of energy efficiency, such as energy auditors and trade contractors, for information. There are, however, several problems with such information, including comprehensiveness, inaccuracy, cost, and perception of bias. The proposed work contributes toward understanding and solving the information barriers in the adoption of energy retrofits in existing homes. Its primary contribution lies in developing an information model for the energy retrofit decision process that can serve as a basis for the future development of a fully functional intelligent decision support system (IDSS). The IDSS will integrate quantitative information with expert knowledge in an interactive computer-based decision tool to assist the user. It will analyze the current situation of a home through queries to the user, and based on the quantitative information and expert knowledge in the system, provide customized and prioritized information needed for decision making by the user. The paper describes and categorizes various types of information needed for a retrofit decision, proposes a decision-making process model for HER, and developes a framework for organizing and integrating the quantitative information with the expert knowledge in an expert system-based IDSS. The quantitative information was gathered from published sources and from a U.S. Department of Energy’s cost database, and the expert knowledge was obtained by interviewing and job shadowing energy auditors and contractors. Finally, an example was provided to demonstrate the functioning of the proposed system. The example assists the user in identifying and prioritizing retrofit measures and provides expert advice on installation of selected measures.

Real-time simulation is powerful in forecasting the completion probability of long-term projects with repetitive tasks but fails to consider the time-varying uncertainty of inputs caused by construction process variabilities. In this paper, an improved method is introduced for predicting the time-varying probability of project completion of ongoing underground cavern group projects using Bayesian updating techniques. Within a tailor-made hierarchical simulation model, the Bayesian approach is adopted to constantly update duration distributions of unfinished project activities according to onsite data. The probability of project completion can therefore be increasingly refined during the process. The methodology is further explained in a case study where its feasibility and advantage over traditional approaches are verified. The success may also be replicated in addressing other similar time-varying uncertainty issues inherently present in almost all construction projects.

Incentives are widely used in construction procurement to motivate the contractor to make cost-reduction efforts. How to choose the right incentive intensity is a critical decision in construction procurement. In this regard, the principal-agent theory has been highly influential in theory and practice alike. However, this research argues that this theoretical model may lead to a biased decision. To demonstrate this point, this research draws on its modeling technique to analyze a standard pain-gain sharing arrangement in construction contracts, finding that taking no account of contract breakup hazards will result in underuse of incentives. When the outturn cost also depends on the contractor’s effort, high-powered incentives can better tap into the contractor’s efficiency improvement potential. The additional profit resulting from efficiency savings can serve as a buffer for downside cost shocks with the effect of reducing the likelihood of contract breakup. This benefit will make it desirable to use incentives more intensively than what is suggested by the principal-agent theory.

The learning curve theory is implemented for the assessment and prediction of performance in repetitive and complex construction operations. The purpose of this study is to explore the applicability of learning curve concepts for the fabrication of floating caissons, a construction activity that has not been adequately explored in the published literature. Although standard statistics and simulation methods have been used, a direct comparison of the produced results, along with their emerging inferences, is attempted for the first time. In addition, simulation modeling is used to predict future performance within the learning curve paradigm. An extended version of an existing simulation platform (CaissonSim) is used to execute the computations. A straight-line model is applied to quantify the improvements in productivity and the dynamically changing learning rates. A comparative analysis of the results has shown that both the statistical and simulation-based approaches have yielded satisfactory results, although the level of accuracy and variability is differentiated. Thus, it is suggested that the synergetic implementation of both methods of analysis is more beneficial because, when combined, they provide a robust analytical framework.

Relational contracting (RC) is based on the recognition of mutual benefits and win–win scenarios that are achieved through more cooperative relationships among the contracting parties in a project. Although RC principles are less difficult to apply in private-sector projects, it has not been established whether public-sector projects can enjoy the full benefits of RC. This study aims to investigate the effective RC practices that are found in China’s public construction projects. The specific objectives are to (1) evaluate project performance levels in terms of cost, time, quality, and client satisfaction; (2) investigate the extent to which RC practices were adopted; and (3) identify the RC practices that lead to better performance. Because of the large geographical area of China, the surveys conducted were confined to Beijing and Hong Kong only. A structured questionnaire was designed to collect qualitative data. The results show that (1) public construction projects achieved significant success in quality performance and client satisfaction, but not in budget and schedule performance; and (2) RC practices were adopted to varying extents in public projects. The findings contribute to knowledge by identifying the specific RC practices that could boost project performance significantly. Another contribution to knowledge is the discovery that the relational contract theory is applicable to public projects notwithstanding the need to keep relations at arm’s length. A framework to manage public projects using the RC approach is recommended for adoption in Hong Kong and other countries that adopt project management style along the Project Management Institute’s framework. A different framework is recommended for adoption in Beijing and places that have a centrally planned and controlled economic system so as to help public projects achieve better project performance.

The concern for occupational health and safety in construction work is reflected in the many preventive measures taken. However, examples of the systematic assessment of project alternatives aimed at minimizing occupational hazards are rare. This paper proposes a measure of occupational safety [occupational risk index (ORI)] that is based solely on the project design and resulting construction process, and is a function of the activities carried out and their specific occupational risk (probability and consequences of occurrence). The ORI can thus be used as an indicator to feed multicriteria decision-analysis tools. The proposal is illustrated with a simple example in which two alternatives (one precast and the other constructed in situ) are prioritized in terms of occupational safety, and certain aspects related to redesign are briefly addressed. With the ORI, occupational safety goes from having a passive influence (application to projects that have already been designed) to an active one (influence on the design concept itself) in the design stage of construction projects. The research is based on an analysis of the applicable legislation and interviews with experts.

Stochastic time-cost trade-off has been a popular object of investigation in past decades because there are uncertain factors that can be considered when determining the appropriate trade-off between project completion time and cost. Previous studies, however, have implemented a double loop procedure, which performs optimization in the outer loop and simulation in the inner loop. The double loop procedure is ponderous because it requires an unacceptably long computation time (taking hours or days), even for a small to medium project. The present study proposes an integrated system that converts the double loop to single loops,thereby dramatically reducing computation time. This is done by incorporating a support vector regression model to obtain a decision function, which will be used to replace the time-consuming Monte Carlo simulation to evaluate the objective function values for individual solutions. With the objective function values, a multiobjective particle swarm optimization algorithm is developed to search for the Pareto front composed of nondominated solutions. It has been empirically shown that the proposed system significantly outperforms the conventional double loop procedure because the former can consistently generate a better Pareto front (with a larger hyperarea ratio) hundreds of times faster by using much less computation time. The Student’s $t$ test is performed to validate the superiority of the proposed system. The contribution of the proposed system is multifold. First, improved computational efficiency is essential for the widespread acceptance of the stochastic time-cost trade-off analysis in practical applications. Second, with less computation time spent in simulation, efforts can be focused on the search for much better nondominated solutions. Third, the proposed system can incorporate the risk attitudes of the decision makers into the analysis by allowing them to specify the probability that they can tolerate for project duration (cost) to exceed a certain limit.

Drawing upon relational contract (RC) theory and network embeddedness theory, this study investigates how relational transactions (i.e., RC norms and network strategies) affect relationship quality and outcomes of public construction projects. The results of a questionnaire survey of 104 public projects in Singapore show that relationship quality and relational transactions have a positive impact on public project outcomes (i.e., time, cost, quality performance, and client satisfaction). The empirical results show that effective information sharing gives rise to better relationship quality, and good relationships further enhance time performance, quality performance, and client satisfaction. The findings show that adoption of these RC norms affects outcomes in the following ways: (1) propriety of means contributes significantly to cost performance, (2) flexibility and contractual solidarity have a significant impact on time performance, and (3) harmonization within the social matrix and propriety of means allow for a significantly higher level of satisfaction. This study contributes to the body of knowledge by empirically showing that good relationship quality can contribute to better outcomes in public construction projects. It also identifies RC norms that have a positive effect on public project outcomes and relationship quality. Recommendations of relational transaction practices that could improve public project outcomes are offered.

To improve the accuracy of early forecasting the final cost at completion of an ongoing construction project, a new regression-based nonlinear cost estimate at completion (CEAC) methodology is proposed that integrates a growth model with earned schedule (ES) concepts. The methodology provides CEAC computations for project early-stage and middle-stage completion. To this end, this paper establishes three primary objectives, as follows: (1) develop a new formula based on integration of the ES method and four candidate growth models (logistic, Gompertz, Bass, and Weibull), (2) validate the new methodology through its application to nine past projects, and (3) select the equation with the best-performing growth model through testing their statistical validity and comparing the accuracy of their CEAC estimates. Based on statistical validity analysis of the four growth models and comparison of CEAC errors, the CEAC formula based on the Gompertz model is better-fitting and generates more accurate final-cost estimates than those computed by using the other three models and the index-based method. The proposed methodology is a theoretical contribution towards the combination of earned-value metrics with regression-based studies. It also brings practical implications associated with usage of a viable and accurate forecasting technique that considers the schedule impact as a determinant factor of cost behavior.

Despite their negative impact on the construction industry, cost overruns have become an almost natural part of building and infrastructure projects. This paper examines the phenomenon as a worldwide problem, identifies its root causes, ranks them (on a local basis), and analyses them. Root-cause analysis is not merely an arbitrary expression; rather, it is a systematic, formal, well-structured methodology, used as part of the total quality-management approach. The expand–focus principles and techniques were applied in this research for assembling an initial, as wide as possible, inclusive list (pool) of 146 potential causes gathered from the international professional literature as well as from prominent local experts. Through two cycles of expand–focus, they were filtered and merged into merely 15 independent universal root causes. These were further investigated through a cross-sectional survey among 200 local construction practitioners who ranked the 15 universal root causes according to their conceived local importance and influence on cost overruns. The survey revealed that, locally, Cause number 1 is premature tender documents; Cause number 2 is too many changes in owners’ requirements or definitions; and Cause number 3 is tender-winning prices are unrealistically low (suicide tendering). The unique value of this paper to the global community of construction engineering and management is twofold: (1) It identified 15 universal root causes of cost overruns, which provide a good starting point for any local investigation, and (2) offers a well-structured methodology for ranking these 15 universal root causes in accordance with the local circumstances, thereby pinpointing the vital few that may prevent locally a substantial part of the problem.

Incentive/disincentive clauses (I/D) are designed to award payments to contractors if they complete work ahead of schedule and to deduct payments if they exceed the completion time. A previously unanswered question is, “Did the costs of the actual work zone impacts that were avoided justify the incentives paid?” This paper answers that question affirmatively based on an evaluation of 20 I/D projects in Missouri from 2008 to 2011. Road user costs (RUC) were used to quantify work zone impacts and included travel delays, vehicle operating costs, and crash costs. Conditions during construction were compared to after construction. Delay costs and crash costs were computed using published data. For every dollar paid in incentives, approximately 5.3 dollars of RUC savings resulted from the use of I/D. Also, I/D projects had a higher on-time completion percentage and a higher number of bids per call than average projects. However, I/D projects resulted in 4.52% higher deviation from programmed costs and possibly more changes made after the award.