Journal of Construction Engineering and Management

An increasing number of construction contractors are actively participating in international markets. One of the most fundamental issues confronting contractors moving offshore is where to do business. Although international market selection is a much studied topic, the market choices made by construction firms have attracted little attention. This paper aims to identify factors that influence international market selection and to develop an international market selection model for construction firms. The market entry choices of 39 large international Chinese contractors across 87 countries were investigated through logistic regression analysis. The results indicate that international contractors prefer to enter countries with large market potential, small culture distance, and, surprisingly, high country risk and high competitive intensity. Moreover, large, experienced contractors are more willing to compete in international markets. Contrary to generally accepted belief, geographic distance is not revealed to have any significant influence on international market selections by Chinese contractors. This paper will be of interest to contractors considering international market selection as part of their global expansion strategy.

Measuring productivity growth in construction has been a classic challenge, largely because reliable output deflators are scarce. This paper reports first results from a Bureau of Labor Statistics research group convened to measure construction productivity better. Results show that labor productivity growth has been positive, and fairly substantial, in all four industries where reliable deflators now exist. Shifts of labor between construction industries reduce productivity growth by 0.4% a year. Regulation is a significant negative effect on productivity, but reduces productivity growth by only 0.1% a year. Undocumented immigrants are important in construction, and often work off the books, but reasonable allowance for their increased presence reduces productivity growth by only 0.1% a year. The influences examined are not sufficient to explain why productivity growth is so much lower in construction than elsewhere. Later work will measure productivity growth in a broader range of industries, including some industries representing contractors. However, this further work requires access to restricted Census microdata, and so will take several years more to complete.

Buffers are used to deal with the detrimental impacts of uncertainty on projects. However, methods for the allocation of buffers often provide single unique solutions, which are inefficient in the multiobjective decision-making environment of construction. This paper discusses a probabilistic-based buffer allocation method (PBAL), which enables the final decision on buffer size to be made by the project planners based on their preferences about project completion time. It investigates the construction projects where each activity starts as early as possible. Accordingly, the decision involves determining the size of time buffer at the end of the project network. The accuracy of the results is subjected to approximation and numerical errors in the mathematical models among others. Most buffer allocation heuristics for projects have approximation errors and simulation-based techniques introduce numerical errors by their iterative sampling calculation approach. PBAL can minimize these errors by supporting important details of modeling the production in activities, and preserving these details when modeling at the project level. The PBAL capability to minimize mathematical modeling errors and its accuracy has been successfully tested using the records from ten construction projects.

The modular building construction method is the industry’s effort for industrialization of building construction. Similar to other types of production, a product information model is required for lifecycle information management of modular buildings. In this research, the mutual hierarchy of typical multistory modular systems is identified and represented in a product architecture model (PAM). This provides the industry with an information model required for industrial design of this type of construction. Since modular construction is neither as heavily project-based as conventional construction methods nor as significantly mass-produced as manufactured products, none of the current information management frameworks in manufacturing and construction industries are necessarily capable of addressing the needs of such projects. In the research reported here, this need is addressed by development of a product PAM for the most conventional modular systems. The PAM represents the hierarchy of modular building components along with their interactions, functionality, and attributes. This paper initially reviews major types of modular systems, and then focuses on the development methodology, validation, architecture, and content of the PAM. This is followed by an explanation of its different uses, including extension of the current construction industry’s information management frameworks and platforms such as building information modeling (BIM) to support modular construction and providing a basis for product-base design of such buildings.

Most construction safety activities focus on managing identified hazards. Hazards that remain unrecognized, and as a result unmanaged, can potentially result in catastrophic and unexpected injuries. Therefore, proper hazard recognition is foundational to the success of any safety program. However, recent research has revealed that a large proportion of construction hazards remain unrecognized in construction projects. To improve hazard recognition performance, employers provide their workers with safety and hazard recognition training. Despite these efforts, desirable levels of hazard recognition have not been achieved, and the anticipated return on investment (ROI) from training has not been attained. Such failures in training efforts are partly because knowledge acquired through training programs is often not transferred or applied in the workplace. Subsequently, training efforts do not alter work practices or behavior once workers return to the field. Other reasons for training failure include improper training delivery and the adoption of low-engagement training methods. To advance theory and practice in hazard recognition, training transfer, and training delivery, the objectives of this study were to (1) identify training transfer elements that maximize the transfer of safety training, (2) evaluate the relative effectiveness of the identified training transfer elements in transferring safety knowledge gained through training programs, and (3) assess the interaction effect between training method (i.e., high-engagement versus low-engagement training) and training transfer levels on hazard recognition performance. The objectives of the study were accomplished by gathering input from construction industry experts through interviews, questionnaire surveys, and the analysis of empirical data gathered from 51 case projects in the United States. The results of the study revealed that training efforts may be undermined if training transfer elements are not synergistically adopted. Specifically, the findings suggest that safety training is necessary, but is not sufficient to maximize training outcomes such as hazard recognition. To maximize safety training outcomes, employers must adopt training transfer elements along with high-engagement training methods. This study represents the first formal attempt to evaluate the role of training transfer elements in the construction context.

In construction cost estimating, bid documents—drawings and specifications—are a primary means to communicate design intent to bidders who then extract cost item quantities. However, uncertainties in conveying information affect the accuracy of quantity takeoffs. Therefore, the goal of this research is to explore types of uncertainties that hamper the quantity takeoff process. This text analyzes bid documents, including architectural, structural, and other plans of real-world school projects with structural steel frames in the Washington, DC metropolitan area. Contributions to the body of knowledge are (1) deriving a classification of five major types from 67 minor uncertainties as collected in the Conflicting/Incomplete/Vague/Incorrect/Lack-of-Work-Assignment (C-I-V-I-L) mnemonic; (2) establishing a framework of information flow between bid participants to explain how uncertainties arise; and (3) extracting contradictions between current contract rules to resolve conflicts in bid documents. This research addresses such uncertainties, which can translate into more accurate cost estimates and time savings when building these designs.

Bid prices vary greatly based on assumptions about uncertain conditions. In steel construction bidding, the contingency amount is typically used as a bid line item to factor in the unexpected—including impact of uncertainty—to the lump-sum bid price. Therefore, the goal of this research is to explore the impacts of uncertainties that contribute to contingency amounts. The costs of uncertainties in bid documents of several real-world school projects have been calculated. Contributions to the body of knowledge are (1) providing illustrative examples of real-world uncertainties from the data set; (2) statistically analyzing the relative occurrence and cost significance to increase estimators’ awareness when they evaluate uncertainties; and (3) comparing the cost significance from the data with officially recommended contingency percentages. This research enables steel estimators to make quantitative-based decisions on contingencies in their estimates should various major types of uncertainties arise without an opportunity to resolve them.

In spite of the strong influence of the construction industry on the national health of the United States’ economy, very little research has specifically aimed at evaluating the key performance parameters and trends (KPPT) of the industry. Due to this knowledge gap, concerns have been constantly raised over lack of accurate measures of KPPT. To circumvent these challenges, this study investigates and models the macroeconomic KPPT of the industry through spatiotemporal clustering modeling. This study specifically aims to analyze the industry in 14 of its subsectors and subsequently, by 51 geographic spatial areas at a 15-year temporal scale. KPPT and their interdependence were firstly examined by utilizing the interpolated comprehensive U.S. economic census data. A hierarchical spatiotemporal clustering analysis was then performed to create predictive models that can reliably determine firm’s profitability as a function of the key parameters. Lastly, the robustness of the predictive models was tested by a cross-validation technique called the predicted error sum of square. This study yields a notable conclusion that three key performance parameters—labor productivity, gross margin, and labor wages—have steadily improved over the study period from 1992 to 2007. This study also reveals that labor productivity is the most critical factor; the states and subsectors with the highest productivity are the most profitable. This study should be of value to decision-makers when plotting a roadmap for future growth and rendering a strategic business decisions.

Improving safety performance is paramount to the success of oil and gas construction projects. Although considerable attention has been paid to developing and using new types of safety performance indicators, contractor safety has traditionally been measured and managed through lagging indicators. Alternatively, risk mitigation measures can be used to predict safety performance as leading indicators. Several research studies have been performed on safety leading indicators; however, no research has empirically validated the predictive validity of candidate indicators. To address this knowledge gap, empirical data were used to measure both potential safety leading and lagging indicators in an effort to test the hypothesis that variability in candidate safety leading indicators predicts variability in lagging indicators of safety performance. A total of 261 contractors were included in the study, with more than 60,000 data points. Using principal factor analysis, model building, and regression, factors with predictive power were identified. The predicted total recordable incident rate (TRIR) and severity rate (SR) provided strong correlation with the actual TRIR and SR, with coefficients of 0.7251 and 0.5338, respectively. The models of predictive TRIR and SR were validated and suggest a good fit when applied to new contractor safety data set. The models can be used as new safety leading indicators that provide warning signs for weakness in contractor safety performance. Consequently, clients can use the results to implement adaptive risk mitigation, reduce incidents, and continuously improve contractor safety performance. This research contributes to the existing body of knowledge by empirically identifying safety leading indicators, testing their efficacy, and validating the resulting models. This research set a foundation for establishing quantitative safety leading indicators in the construction industry in the future for other forms of project outcomes.

Traditional project design and construction delivery is segmental. Researchers and practitioners often cite the separation, or “silo effect,” as a reason for poor project outcomes. In response, new forms of integrated contracts have emerged, fostering more collaborative efforts and a focus on successful project outcomes, instead of individual organizational outcomes. Relational contract theory provides a basis for understanding these new integrated forms of agreement through a set of relational contracting norms. This study operationalizes the relational contracting norms designed to measure project integration. The norms and their dimensions were developed through a rigorous construct mapping methodology and then tested, analyzed, and validated with a survey of owners and owners’ representatives from 314 completed projects using exploratory and confirmatory factor analyses. The study validates the measures and demonstrates the potential that the measures have to illuminate the nature of relational contracting in construction project teams. The validated scales can be used in future research to better understand when and how contracts influence integration and project performance.

A construction project can be accelerated by overlapping critical activities. This paper presents a computational method called exact time–cost tradeoff (ETCT) in concurrency-based scheduling that identifies exact global overlaps between critical activities. It calculates the rework cost slope and amount by integrating the activities’ concurrency attributes, identifies the exact global solution, and computes the probability to complete a project within the project completion time (PCT) and/or the project completion cost (PCC). The study is of value to project schedulers because ETCT identifies the exact global solution (i.e., the set of activities to be overlapped and the exact overlap rates between these activities) expeditiously, and establishes a compressed schedule that satisfies a project’s budget and duration constraints. This is also relevant to researchers in that it clearly defines the computational formula to compute the exact solution in detail and facilitates a comparison of the outcome of a schedule under different project objectives, such as minimizing project completion duration and/or project completion cost. The usability and validity of the computational methods was confirmed by performing two test cases.

Modularization is a well-established method that can improve the efficiency and effectiveness of the construction industry. However, the industry continues to struggle with its implementation, and not all executed modular projects have resulted in successful project performance. This study investigates the combinatorial effects of modularization critical success factors (CSF) on the cost and schedule performances of industrial modular projects and derives a conceptual model of cost and schedule successes using information from actual cases by applying crisp-set qualitative comparative analysis. The findings confirm that CSFs interactively and collectively affect modular industrial project performance. The most commonly involved CSFs for cost and schedule successes are timely design freeze, owner-furnished/long-lead equipment specification, vendor involvement, and management of execution risks. This work contributes to researchers and practitioners in the industrial sector to improve understanding of the recipes (i.e., CSFs or combinations thereof) for successful modular project planning and execution, which will lead to improved modular project performance in the construction industry.

The construction of public schools is a complex endeavor due to the involvement of multiple and diverse parties, funding and budgetary concerns, and statutory limitations imposed by local, state, and federal agencies, all of which serve to increase project risk. Project delivery methods using distinctive procedures to manage the design and construction process have been developed to reduce risk and improve project performance. To increase the probability of successful project outcomes, those responsible for public school construction require conclusive delivery method performance data. Completed in 2014, this two-year study used actual construction documents from 137 southeastern public schools to analyze and determine project delivery method cost, time, quality, and claims performance. The analysis indicated that performance of the Design-Bid-Build (DBB) method was significantly superior across all cost metrics, whereas the Construction Manager at Risk (CM at Risk) method produced higher levels of product and service quality. Essentially, public school administrators were paying a significant premium to obtain perceived improvements in both service and product quality. This research empowers decision-makers and benefits the public by providing evidence of the most efficient and effective means for the construction of new public schools.

Transportation construction projects are often plagued by cost overruns and delays. Applying contingencies and estimating risks at the project level often do not capture the multiple uncertainties in the construction process of large transportation projects. Thus, there is a need for innovative approaches and tools to avoid large construction cost and duration overruns. To counteract such underestimations, a construction model and an uncertainty model are developed. In the construction model, the construction of the four main types of structures in rail lines (tunnels, viaducts, cuts, and embankments) is modeled bottom-up from the single activity to the entire rail line. In the uncertainty model, three sources of uncertainty (variability in the construction process, correlations between the costs of repeated activities, and disruptive events) are modeled jointly at the level of the single activity. In a Monte Carlo simulation environment, these uncertainties are propagated to the total construction cost and duration through the combination of the individual activity costs and durations. The construction and uncertainty models are incorporated in the decision aids for tunneling (DAT), which have been extended beyond tunneling to consider these different structures and uncertainty types. All this was applied in the Portuguese high-speed rail project, in which historical data and expert estimations were used to model the cost and duration uncertainty. This application allowed validation of the model and then illustration of a variety of effects: the three sources of uncertainty produce different cost and duration impacts depending on the type of structure, suggesting structure-specific mitigation measures. Most importantly, their cumulative impact causes significant increases in construction cost and duration of the modeled rail line compared with the deterministic estimates: specifically, 58% in the construction cost of tunnels, and 94% in the construction duration of cuts and embankments. The proposed construction and uncertainty models contribute and advance the body of knowledge: For the first time, variability, correlations, and disruptive events are quantitatively modeled in one simulation environment, and the impact of these uncertainty sources can be assessed jointly and compared. The proposed models also significantly contribute to practice by providing transportation agencies with a modeling tool to tackle cost and duration uncertainty in the construction of rail lines and other linear or networked infrastructure projects.

Since 2013, the Chinese government has attempted to make a transition from user-pay public-private partnership (PPP) to government-pay PPP systems with the aim of facilitating infrastructure investment and government transformation. Whereas the application of government-pay PPP systems can considerably expand the areas where PPPs are suitable, the lengthy procurement time experienced in the implementation of similar systems [e.g., private finance initiative (PFI)] presents a tough challenge to Chinese procuring authorities who are under increasing pressure to get the earmarked PPP projects off the ground swiftly in order to stem the downward pressure in the economy. The first PFI-like project in China, the Anqing Urban Road PPP project, has been successfully tendered in May 2015 with an impressive record on procurement time. Through the scrutiny of this project, it is found that speedy procurement is achieved by leaving some of the major risks ill-defined and vaguely allocated in the tender document. However, this apparent high-risk exposure did not deter investors. This research maintains that the greater risk tolerance revealed among state-owned enterprise (SOE) investors should be attributed to the power structure embedded in China’s administrative system. While leveraging this mechanism can reduce transaction costs, it could hold back the participation of private investors in future Chinese PPP projects.

Academics have been devoting a growing attention to different matters involving public-private partnerships (PPPs), and, as the use of PPPs for delivering infrastructure evolves worldwide, so does the number and type of papers addressing this procurement model. The objective of this paper is to undertake a comprehensive literature review of papers relating to PPPs and private finance initiatives (PFIs), using a bibliometric analysis. More than 600 papers published between 1990 and 2014 were examined. None of the previously existing studies analyzed such a large sample of papers. The research found that PPP studies appear to have a steady momentum toward growth. Engineering journals (and engineering as a research area) have been particularly active in this field. Authors based in Europe and Asia had written almost two-thirds of the papers, with transportation and health sectors at the top of sector-based papers. Most of the existing work is focused on aspects of contract design, risk sharing, and analyzing the contract performance and benefits, and neglects areas such as contract termination and renegotiation. The management of PPPs will be the next big challenge for PPP scholars and professionals.