Journal of Construction Engineering and Management

For the implementation of building information modeling (BIM), an incompatible development among various aspects of a business can lead to different levels of BIM maturity (BIMM) or even project failure. Therefore, it is important to identify key causal factors of BIMM. This research develops a structural equation model of BIMM through three-step multivariate analysis. It starts with exploratory factor analysis to identify three key BIMM factors, which are further tested with confirmatory factor analysis. The causal relationships among the three factors and BIMM are then proposed and validated with structural equation modeling. This research has both practical and theoretical contributions. Practically, the proposed model can be used by practitioners to initiate and evaluate their BIM implementation. Theoretically, the result provides empirical evidence for the multidimensional nature of BIMM and insights into the causal relationships among the factors. Specifically, the factors of process management and technology management are correlated, and both have significant positive impacts on BIMM through the information management factor. However, compared with technology management, process management is identified as more important for BIMM.

Design-build (DB) is an alternative project delivery system that is distinguished by a DB team acting as the single point of responsibility for a project in which the design and construction phases overlap. There are two main methods used to procure DB services: single-step and two-step procurement. Single-step DB involves a request for proposal (RFP) phase, whereas two-step DB involves both request for qualifications (RFQ) and RFP phases. There is an industry perception that more resources are spent to procure single-step DB projects as compared with two-step DB projects. Therefore, this paper focuses on quantifying the resource expenditures and efficiency impacts of single-step and two-step DB through investigating several procurement and project performance metrics. The paper presents results stemming from 32 completed projects. The results of the analysis show that the total cost to industry to develop single-step proposals is approximately 5% of the total project cost, whereas the cost to develop two-step proposals is approximately 1% of the total project cost. Additionally, the relative procurement duration was 18% of the total project time for single-step DB and 22% of the total project time for two-step DB. Moreover, the percentage of design completed at the RFP and award stages are presented. For single-step DB, 23% of the design was completed at the RFP stage, and 43% at the award stage. For two-step DB, 12% of the design was completed at the RFP stage, and 32% at the award stage. Most importantly, the findings contribute to the DB body of knowledge by quantifying a significant five-fold procurement cost difference between the two DB procurement methods, helping the industry implement procurement policy changes.

The benefits of conducting risk analyses in the planning of construction projects are widely acknowledged. However, the actual implementation of procedures notably differs significantly across industry segments. Even within an organization, different units represent risks differently, depending on their primary function. As a result, a holistic picture of the risk exposure is often hard to describe and even harder to manage. The objective of this paper is to provide a link between strategic planning theory, namely the resource-based view (RBV), and project risk management. The proposed resource-based approach is based on the development of a project causal network which then allows for both data-intensive and conceptual evaluation of the project risks, primarily focusing on cost impacts. The key contribution of this paper is the capacity of the developed framework to integrate with a number of methods already used in project management practices with little to no additional data requirement. These contributions are illustrated using real project data.

This paper examines the extent to which engineers can influence the competitive behavior of bidders in best value or multiattribute construction auctions, in which both the (dollar) bid and technical nonprice criteria are scored according to a scoring rule. From a sample of Spanish construction auctions with a variety of bid scoring rules, it is found that bidders are influenced by the auction rules in significant and predictable ways. The bid score weighting, bid scoring formula, and abnormally low bids criterion are variables likely to influence the competitiveness of bidders in terms of both their aggressive/conservative bidding and concentration/dispersion of bids. Revealing the influence of the bid scoring rules and their magnitude on bidders’ competitive behavior opens the door for the engineer to condition bidder competitive behavior in such a way as to provide the balance needed to achieve the owner’s desired strategic outcomes.

Many people lose their homes around the world every year because of natural disasters, such as earthquakes, tsunamis, and hurricanes. In the aftermath of a natural disaster, the displaced people (DP) have to move to temporary housing (TH) and do not have the ability to choose the settlement dimensions, distributions, neighborhood, or other characteristics of their TH. Additionally, post-disaster settlement construction causes neighborhood changes, environmental degradation, and large-scale public expenditures. This paper presents a new model to support decision makers in choosing site locations for TH. The model is capable of determining the optimal site location based on the integration of economic, social, and environmental aspects into the whole life cycle of these houses. The integrated value model for sustainable assessment (MIVES), a multicriteria decision making (MCDM) model, is used to assess the sustainability of the aforementioned aspects, and MIVES includes the value function concept, which permits indicator homogenization by taking into account the satisfaction of the involved stakeholders.

Decision aids, ranging from rating systems to design software to regulatory standards, guide the design and evaluation of infrastructure projects. To present the information in these decision aids, there must first be some options such as, attributes are or are not presented, and, just as in other domains, these factors are likely to influence decisions in infrastructure development. The authors of this paper seek to better understand how choice structures influence engineering decisions. Prospect theory, which is well established in the behavioral sciences, asserts that people tend to think of possible outcomes relative to their starting point, not the resulting end point. For instance, framing a decision outcome as a loss in value (rather than a gain) can reduce the decision makers’ acceptance of risk and, in turn, lead to more conservative outcomes. To measure framing effects in engineering decisions, this paper uses the Envision rating system for sustainable infrastructure, which aims to help civil engineers achieve the highest feasible sustainability performance in their projects. The hypothesis is that Envision’s framework inadvertently limits the likelihood that engineers will set the highest achievable goals for sustainability. In the current framework, engineers start with zero points and achieve points when design considerations move beyond conventional construction standards. In this modified experimental version, a higher benchmark is set. Engineers are endowed points and can lose them for not maintaining high goals for sustainability. Engineering professionals ($n=65$) used Envision to make tradeoffs about site programming and functionality for a rural redevelopment project. Participants were randomly assigned the standard version ($n=33$) or the experimental version ($n=32$). The experimental group achieved 66% of points compared with the standard group’s 51% ($p<0.01$). These results indicate that a choice posed as a loss rather than a gain significantly improved engineers’ consideration for sustainability achievement. The findings suggest the need for more thoughtfully designed decision aids, with guidance from established behavioral science. This type of interdisciplinary research holds the potential to yield relatively low-cost solutions that support greater sustainability in infrastructure development.

Providing accurate forecasts of construction costs at the conceptual phases of building projects is vital since they form an objective benchmark for the subsequent evaluation of project performance. Previous works adopted a conventional approach in which a restricted set of macro project determinants, which are available in the preplanning phase, was employed towards direct estimation of construction costs. Aiming to reduce the prediction error in conceptual estimates, the current study adopts a novel approach from the domain of forecasting. This multistep ahead (MSA) approach relies on the idea of using several cascaded estimations to predict future values. Accordingly, building element quantities were estimated as the first step. In the second step, estimated quantities were combined with the existing set of inputs to achieve a higher accuracy in construction cost prediction. In order to test the hypotheses of interest, 657 building projects from Germany were analyzed using linear regression and artificial neural network methods. Conclusive evidence suggests that the MSA approach significantly outperforms the prediction accuracy of the conventional practice. To the best of authors’ investigation, the current study is the first to offer such a cascaded estimation approach. Therefore, further empirical evidence is necessary prior to generalizing applicability of the MSA approach in construction cost estimation.

This paper focuses on construction workers’ unsafe behaviors and develops a cognitive model of construction workers’ unsafe behaviors (CM-CWUB). In the construction industry, many accident investigations reveal that workers’ unsafe behaviors are the most frequent and direct causes of on-site accidents, and thus need to be addressed urgently. Based on cognitive and social psychology theories and existing accident causation models, this paper develops a CM-CWUB by adopting a five-stage form, specifically representing the construction workers’ cognitive processes when confronted with potential hazards on construction sites. Using a cognitive perspective can reveal the mechanism of human error and thus can elucidate how unsafe behaviors are produced. The five stages include obtaining information, understanding information, perceiving responses, selecting response, and taking action, with obtaining information and selecting response as the two key stages. Obtaining information elaborates construction workers’ observations and processing of hazard information on sites by themselves, and selecting response adopts the theory of planned behavior to reflect various factors of influence when workers select unsafe behavior. Based on the developed model, cognitive failures that would lead to construction workers’ unsafe behaviors at different cognitive stages are then systematically analyzed.

The construction industry is fraught with waste and inefficiencies resulting in projects often failing to meet owners’ expectations. Integrated project delivery (IPD) is the newest project delivery system (PDS) and changes the traditional roles and relationships of key project stakeholders. Through increased early collaboration, IPD attempts to eliminate waste and deliver the highest-value projects to owners. It is seen as a potential solution to many of the challenges impeding successful project performance. However, a transformational move toward IPD has yet to reach a tipping point, and its use is not prevalent throughout the construction industry. Little research has been done to quantitatively analyze IPD compared with the more commonly used delivery methods. Through substantial collection of quantitative project performance data and univariate statistical analysis, this study fills the gap in PDS research by evaluating the effects of IPD on building construction projects across a wide range of performance metrics from the perspective of general contractors and construction managers. This research demonstrates that IPD/near-IPD outperformed non-IPD projects with respect to performance in communication, change management, and business performance areas. Communication was found superior in terms of the number of requests for information (RFIs) per million dollars; change management in terms of change-order processing time; and business performance in terms of a project’s impact on company image and the potential for return business. A new term called project quarterback rating (PQR), which combines key performance metrics, was used to quantitatively evaluate overall performance. Statistically significant evidence of the overall superior performance of IPD/near-IPD compared with non-IPD projects was found. These results should encourage owners to consider the use of IPD, or IPD principles in conjunction with other delivery methods, in future capital facilities endeavors.

Although the construction industry has shown significant improvements in safety performance over the past 30 years, falls are still a leading cause of fatalities and serious injuries. Previous studies have focused on identifying factors affecting the risk of falls, but remained silent on investigating the evidential relationships among these factors to better prevent fall accidents. This research proposes a Bayesian network (BN) based approach to diagnose the accident risk of working at heights. The proposed approach consists of a conceptual and generic model with a protocol for assessing the risk of falls and a computational module. The generic BN model was developed on the basis of an extensive review and evaluation of causal factors leading to falls. The computational module was developed on the basis of Bayes’ rule for inference to customize model input and job site characteristics. The results of the proposed approach provide probabilities associated with different states of safety risk. Additionally, sensitivity analysis allows practitioners to identify appropriate preventive actions and safety strategies to reduce risk of fall. The proposed approach was verified and tested with a construction operation in a condo-hotel project. This study contributes to the construction safety body of knowledge by providing an effective quantitative risk assessment tool to predict the safety risk of falls from heights. Researchers and practitioners may customize the model to assess and benchmark the fall risk for different operations in the construction industry.

Because of the uncertainties present in geology and construction processes, construction projects in underground cavern groups are typically characterized by high degrees of uncertainty. The real-time safety analysis of underground caverns during construction has been a key technological issue because previous three-dimensional simulations have commonly failed to consider the time-varying changes in construction schedules and geological conditions. Thus, this study couples a construction progress simulation with a real-time dynamic analysis of engineering safety. In this study, a real-time online safety analysis approach based on four-dimensional technology during the construction of underground caverns is introduced, and a dynamic visualization management system of safety information in underground caverns during construction is developed using the OpenGL (Open Graphics Library) Tao Framework and C#, with which integrated management of information related to safety, including geological information, construction progress information, monitoring information, and numerical simulation data, is considered. This study also demonstrates that real-time safety evaluation based on a construction safety information model during the construction of underground caverns is feasible and practical, as shown in a real example in China.

A series of field trials with pipefitters in North America was conducted to explore how their spatial cognition influenced their performance on a scale model assembly task. Participants were provided one of three information formats, traditional, two-dimensional (2D) isometric drawings, 2D isometric drawings supplemented with a 2D visual rendering of a three-dimensional (3D) image of the assembly, and 2D isometric drawings supplemented with a 3D physical model of the assembly. Card rotation and cube comparison tests were administered to measure spatial cognition. This paper’s primary contribution centers around the discovery that individual spatial cognition significantly influenced the pipefitter’s performance, but the format of information can neutralize the effect. Both the information format and spatial cognition significantly influenced performance. When only 2D information was provided, participants with relatively low spatial cognition performed significantly worse than participants with relatively higher spatial cognition. When the 2D isometric drawings were supplemented with 3D information, participants with lower spatial cognition were able to complete the model assembly as efficiently and effectively as participants with higher spatial cognition.

The construction industries of developed countries are faced with an aging workforce and a shortage of recruits. It is common for migrant workers/ethnic minorities (EMs) who are already part of the society to join the construction industry. With increasing involvement of EMs in the construction industry, effective strategies for improving their safety and health are urgently needed. The existing body of knowledge is mainly derived from research conducted in English-speaking countries with Western cultures. Research on safety of migrant/EM construction workers in multidialect Asian countries with Eastern cultures has been lacking. This study aimed to identify various strategies for improving the safety and health of EM construction workers from the Asian perspective. Twenty-two face-to-face semistructured interviews were performed with safety professionals in Hong Kong followed by two rounds of Delphi survey with 18 safety experts to verify the interview findings and rank the relative importance of the strategies. The study unveiled 14 strategies for improving the safety performance of EM workers. The three most important ones identified were (1) to provide safety training in EM native languages, (2) that government and industry associations should play an active role in promoting health and safety awareness of EM workers, and (3) to encourage EM workers to learn the local language. This study contributes to filling the research gap by evaluating the strategies for improving safety of migrant/EM construction workers in Asian countries with Eastern cultures in which English is not the first language. Research findings would assist occupational health and safety experts and relevant stakeholders in designing strategies for improving the safety and health of EM workers, which will ultimately improve overall safety performance of the construction industry.

This paper assesses technical efficiency and its determinants in the Spanish construction sector from a comparative perspective for the period 2000 to 2010 by using different parametric approaches in the form of stochastic frontier models. The main results reveal similar (no) influential factors on efficiency. For all models, the determinants found were capital intensity, prefinancial and postfinancial crisis periods, and workers’ skills. There was no difference in terms of sign and statistical significance. Firm age was positively related to efficiency in two of the three models. Firm size was not significant in any model. Finally, the average efficiency values obtained by the models are 55.3, 69.2, and 91.0%, suggesting the possibility of significant improvements in resource management.

Corruption has become an innate feature of Brazil’s construction industry, particularly the procurement of infrastructure projects. Consequently, the Brazilian Federal Police are actively pursuing individuals and companies who are engaged with corruptive practices, particularly overpricing. To address the issue of overpricing in infrastructure projects, this paper describes the current method used by the Brazilian Federal Police and presents a probabilistic approach that is deemed to be a more reliable approach for determining its occurrence. This paper provides legal fraternities in other developing countries facing similar problems with additional support to ensure convictions for overpricing are pursued. Limitations of the current method and future research toward the development of a probabilistic method are identified.