Journal of Construction Engineering and Management

When the National Environmental Policy Act (NEPA) process and the transportation project planning process are not streamlined, the NEPA process may lead to duplication of work and project delays. This paper presents research work in discovering state-suitable integration practices for integrating NEPA into statewide and metropolitan transportation project planning processes for the state of Illinois. The discovery of practices was based on an analytical review of existing integration guidelines and efforts in other states and using a survey of experts from relevant federal, state, and metropolitan planning, regulatory, and resource agencies. Two types of integration practices were identified: process-oriented and collaboration-oriented integration practices. The selected practices were integrated into existing transportation project planning processes and formalized into an integrated process flow with detailed implementation guidance. The integrated process was validated through a second expert survey. The validation results indicate that the integrated process, including its implementation detail and process representation, provides appropriate guidance for integrating NEPA into transportation project planning processes in Illinois. The implementation of the integrated process would improve interagency coordination and communication, enable early identification of potential environmental issues, reduce duplication of effort, and enhance project delivery in terms of time and cost.

Data-driven models using historical project attributes to estimate future construction costs, such as multiple-regression analysis and artificial neural networks are both proven techniques that highway agencies could adopt for conceptual cost estimating. This research found literature using those techniques has been solely focused on estimating model performance with little to no attention to the level of effort required to conduct the conceptual estimate. It is commonly believed using more input data enhances estimate accuracy. However, this paper finds for the highway agency studied that using more input variables than necessary in the conceptual estimate does not improve estimate accuracy. Conceptual estimates using the minimum amount of input data to produce an estimate with a reasonable level of confidence is more cost effective. This paper quantifies the effort expended to undertake conceptual estimates using data from a highway agency and concludes that input variables that have a large influence on the final predicted cost and require a low amount of effort are desired in data-driven conceptual cost-estimating models for the agency studied.

In addressing the need to ensure not only rigor but also relevance (i.e., practical and socially applicable) in research, this paper provides the knowledge required to understand how to intervene in construction and initiate change that satisfies the need to learn and engender process improvement. In addressing the need to ensure relevance for practice, this paper examines how the 6Es collective learning framework (engaging authentic leadership, enacting coaching, engendering a learning climate enacting behaviors, embedding collective learning, and engaging a new culture) can be operationalized. In doing so, the concept of zero vision (i.e., defects and harm) that is aligned with the notion of error prevention (i.e., errors can be and should be prevented) is challenged and an alternative emphasis on error management (i.e., errors happen) is promulgated; the managerial implications of adopting this approach are discussed as well. The paper concludes that if the construction industry is to gain traction in the pursuit of productivity and performance improvements, then greater emphasis needs to be placed on developing a learning culture that is able to transform error events into experiences; Learning from errors that have occurred (error management) can then help to prevent errors in the future.

The construction industry is often criticized for its lack of innovation. Yet, that same industry designs and builds the largest projects of the world—megaprojects. This discrepancy begs the question, whether lack of innovation is a valid description of the construction industry. A megaproject seems ideal to test the construction industry for its innovation potential. For the collection and analysis of data, longitudinal action research, combined with a case study approach, provides the required level of detail and an understanding of interdependencies. The BangNa Expressway in Thailand serves as the focal case; it is the largest bridge in the world. The following aspects are primary contributions to the stock of knowledge: we identify 58 innovations, some are product or construction technology innovations, others are within the technical, management, or contractual organization. This magnitude attests to the ability of the construction industry to innovate on a level not yet identified. The whole project is embedded in a system of interdependent innovations, and strings of incremental innovation lead to very important changes. There are many innovative features on the world level which different champions sponsored. The construction industry, with its bewildering diversity of products and services, provides results on a continuum from repetition to innovation, with megaprojects situated at the innovative end.

Commissioning and start-up (CSU) must be accomplished before a facility can initiate initial operations and begin meeting commercial objectives. Actions necessary for successful CSU are often not well planned or executed, resulting in poor CSU performance. Recognizing this significant shortfall, the purpose of this study is to determine critical activities necessary to increase the likelihood of successful CSU performance on capital projects. Utilizing input from CSU experts, objective data collection, and subsequent data analysis, 16 critical success factors (CSFs) were identified through this research. Further elements developed include CSF’s timing of CSF implementation, support of safety and quality, and current frequency of CSF achievement. The researchers recommend the industry to pay particular attention to these six laggard CSFs: CSU value recognition, adequate funding for CSU, CSU leadership continuity, system milestone acceptance criteria and deliverables, CSU systems engineering during front-end engineering design (FEED), and systems-focus in detailed design. Capital project team members (representing both owners and contractors) and researchers involved in the planning and implementation of facility CSU will benefit from the results.

The present paper reports on the analysis performed over a set of 44 final designs projected in the period 2000 to 2007, and is aimed at performing a quantitative and qualitative analysis on the prevalence of project deficiencies in flat roofs in construction building projects. The methodology is based on the study of a set of control parameters to point out the most frequent deficiencies in flat-roof designs. Out of the total number of sample projects, only eight (18.18% of total number of projects) were categorized as high-quality projects, while 17 (38.63%) and 19 (43.18%) were finally regarded as intermediate and low-quality, respectively. The use of accurate methodologies at former project stages to identify potential failures or construction deficiencies in advance is a successful predictive strategy, which directly enhances infrastructure sustainability. It provided they might prevent between 70 and 80% of the standard pathologies addressed for flat roofs, and might moreover achieve annual saving rates as high as $€10–12/{\mathrm{m}}^2$ during building use.

Modularization involves breaking up a system into discrete chunks, which communicate with each other through standardized interfaces, rules, and specifications. It is a broad concept with various interpretations and meanings across research disciplines. The complexity and scope of a module is not captured sufficiently and clearly in the construction management and engineering literature, and the impact of modularization across project phases has not been fully explored and articulated. Therefore, the main question addressed in this paper relates to the inherent meaning of what is a module in the context of different phases of a building project. In addressing this question, this paper empirically investigates the use of modularity in 15 construction projects situated in Italy, Germany, Brazil, and the United Kingdom. The findings of this research suggest that a design-based and an operations-based perspective of modularity coexist, and that there is the need for an integrated view of modularity across the project lifecycle phases and for collaborative working between designers and site operators. To this aim, a unifying definition of a module in building projects is proposed along with a practical guide to help managers organize project activities for effective modularization. The actual cost analysis of the various modularization strategies provides an interesting avenue for future research. The template proposed also requires wider testing with a wider range of modules.

Construction workers are frequently exposed to excessive physical demands due to repetitive lifting and material handling while performing tasks. Consequently, many construction workers suffer from a significant level of muscle fatigue that may negatively impact a project’s performance. Thus, evaluating the level of muscle fatigue prior to work and implementing appropriate interventions to reduce physical demands will help to prevent adverse effects of workers’ fatigue on construction operations. Even though several research efforts have suggested methodologies to evaluate muscle fatigue, the extent to which workers’ muscle fatigue would affect construction performance has not yet been fully studied. To address this issue, a simulation-based framework is proposed to estimate physical demands and corresponding muscle fatigue, and thus to quantitatively evaluate the impact of muscle fatigue during construction operations. Specifically, physical demands from a planned operation modeled using discrete event simulation (DES) are estimated through biomechanical analyses. Then, the proposed dynamic fatigue models estimate the level of muscle fatigue of each worker as a function of the estimated physical demands. Workers’ strategies to mitigate muscle fatigue, such as taking voluntary rests, are, in turn, modeled in the DES to understand how muscle fatigue affects time and cost performance of the planned operation. As a proof of concept, a case study on masonry work was performed to demonstrate the usefulness of the proposed framework, describing the need for taking into account muscle fatigue for operational planning due to possible excessive physical demands. The results from the case study indicate that excessive physical demands beyond workers’ capabilities result in reduction of time and cost performance. The proposed framework helps to better understand workers’ response to physical demands by adding workers’ capabilities as changing variables into traditional DES approaches, enabling pro-active management of human resources. Ultimately, the framework, which combines conventional interests on optimized operations in terms of time and cost with those of ergonomics, provides opportunities to take into account both workers’ health and work performance in early design stages.

Disruption to continuous workflow is a major cause of cost overruns affecting many construction projects, especially for repetitive construction. The compensatory claims for damages including disruption are different from damages due to delay because of the complex characteristics of disruption per se. To estimate the cumulative damages due to disruptions, all the possible issues of damages caused by interruption of workflow should be considered. Various methods have been proposed in the literature for analyzing the impact on schedules and the damages resulting from disruptions. However, these methods have a limitation because they do not consider the ripple effect of disruptions. This paper proposes a modified method that can reasonably estimate damages caused by disruptions in construction projects, especially for repetitive construction. The proposed method includes the resource continuity and earned value analysis research methodologies to forecast the direct effect of disruptions. In addition, earned value management (EVM) is utilized to demonstrate and forecast the ripple effect of disruptions on construction activities. The original contribution of the paper is summarized as (1) application of EVM to the topic of damage calculations due to changed process sequence and (2) development of a method to assess the ripple effect as well as the direct effect of disruptions on project productivity performance.

In the concrete-dam-construction process under real-world circumstances, concrete-production schedules can rarely be executed as planned due to the occurrence of various and unpredictable production-system faults, which greatly influence the rapid succession, quality, and quantity of concrete placement. Therefore, identifying these faults beforehand and determining the critical faults are essential for construction management to guarantee harmonious and rapid operations during the dam-construction process. Construction-simulation technology has proven to be an effective approach for predicting the concrete-dam-construction process and the performance of project schedules. However, existing simulation models do not currently consider the adverse influence of concrete-production-system faults. This paper is intended to determine the impact of production-system faults on concrete placement duration, monthly placement strength, and mechanical placement strength. An analysis of the fault-response mechanism of the system was carried out and a fault-response model has been proposed. Taking a typical concrete-dam project as a case study, a mathematical model of probability and statistics is proposed to clarify the occurrence law of the faults in the production system. Random numbers subjected to fault-probability distribution have been generated to represent whether the fault occurred or not, and the results were then fed back to the placement-simulation module to determine a reasonable placement scheme. In addition, a sensitivity analysis was carried out and the results prove that three kinds of production-system faults, namely, broken conveyor belts, broken stone grooves, and pipe blockages, significantly impact placement progress and quality. This study’s primary contribution is to provide a useful approach for the elaborate concrete-dam-construction-process simulations as well as a reference for the reasonable management of production systems and preventive measures.

Construction is one of the most hazardous industries. This study analyzes occupational risk and focuses specifically on the question of perception of risk based on a sample of construction workers from three countries (Spain, Peru, and Nicaragua) that, in spite of sharing the same language (Spanish), have different socioeconomic levels. The model used for this study is based on the psychometric paradigm. The results of the survey using a questionnaire indicate that the sample population can be separated into two different clusters, each characterized either by a high or a low perception of risk. The authors then attempted to establish a link between the level of perceived risk and different socio-demographic variables. The outcome is that only the training variable significantly altered the perception of risk. This finding, as well as various other aspects of risk perception from the different nations, are discussed. The conclusions of this study provide interesting guidelines for risk management for the construction industry, such as, for example, the increase of the number of hours of worker safety and health training or that the nationality the workers does not appear to affect worker risk perception.

This paper investigates the adequacy of some nontraditional approaches to produce realistic forecasts of the final costs of building projects and compare them with forecasts produced by three traditional methods, the unit area costs (UAC), client detailed costs (UPA), and contract sums (CS). As a case study, data of the actual final costs and forecasts produced using the three traditional methods for 420 finished public building projects carried out in Turkey were collected. Based on 75% of the collected data (i.e., 316 projects), three cost models based on UAC, UPA, and CS were established. The remaining 25% of the data (104 projects) were used as control data for testing the accuracies of forecasts produced by the different approaches. Cost forecasts using five nontraditional approaches, namely multilayer perceptron (MLP), radial basis function (RBF), grid partitioning algorithm (GPA), reference class forecasting (RCF), and regression analysis (RA) were then produced and compared with the actual final costs of projects of the control data. The forecasts were compared using four standard error measures: root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and overall index of model performance (OI). Results of the analysis have shown that although the efficacy of each method to produce forecasts closer to the actual final costs varied depending on the model used, in general however, RCF and RA seem to produce more accurate and realistic forecasts than the other methods. As such the work described in the paper represents valuable contributions to knowledge and practice, firstly because RCF has not been used or tested before for cost forecasting of building projects. Secondly such comparison among the various methods and approaches used has not been found in published literature. Finally the paper provides guidance as to what approach to use at what stage of the project as well as how realistic the expected forecasts are.

The Chinese construction sector is one of the largest in the world, but the nation’s 31 provinces, autonomous regions, and municipalities (hereafter ‘provinces’ for simplicity) have experienced varying levels of economic development. It is important for stakeholders to truly understand Chinese construction sector efficiency and these disparities. Considering it a more robust approach, this study uses the Färe-Primont data envelopment analysis (DEA) method to estimate construction productivity and efficiency across China from 1995 to 2012. A general finding is that construction productivity in China has experienced incredible growth from a low base in 1995, with eastern China the most productive region and northern China the least. The most productive provinces were Zhejiang, Hunan, and Jiangsu; contradicting conventional wisdom, the least productive were Beijing, Shanghai, and Guangdong. Decomposing the productivity further, it is found that China’s construction industry appears to be more scale-efficient than technically efficient. In other words, the industry is operating at an optimal scale for productivity but relies less on technological advancement. This research provides significant insights for understanding productivity of the world’s largest construction market in a different perspective. The Färe-Primont DEA method appears to be an effective means of probing industry efficiency from different perspectives, and enables development of evidence-based policies targeted at improved construction productivity in particular regions or provinces.

A recent study reported that the construction management market has grown more competitive. In this environment, identifying a company’s competitive position enables a study of competitor strategies and the ability to select the most suitable path to profitability. This study suggests a methodology to analyze topological competiveness based on social relationships between firms modeled according to four subnetworks: Joint contract networks linked directly between firms, public and private networks linked indirectly by owners, and building and civil networks linked indirectly by work type. This study proposes an analytical framework measuring topological competiveness from four perspectives: The network topology among each subnetwork, centralities and structural positions among the firms, cohesive subgroups and strong relations in the subnetwork, and the structural equivalence among firms. Using 2,984 cases of Korean construction management projects from 1997 to 2013, an empirical analysis of topological competiveness validated the methodology to diagnose competitiveness and select the most suitable relationships with competitors to create company growth.

By showing users different stages of building information modeling (BIM) development and offering a roadmap to these stages, BIM maturity models have become useful means of BIM diffusion around the world. Nevertheless, existing models fail to recognize and measure BIM maturity in different units of analysis, including individual projects, companies, or the construction industry as a whole. This research aims to develop a multifunctional BIM maturity model. A reiterative approach is adopted to identify domains, subdomains, and their rubrics, which are organized in a hierarchical structure to form the BIM maturity model. This research is of particular value. It joins the theoretical debate on the “stool” of BIM maturity including technology, process, and protocol, instead of treating BIM as a technology only. The model is also of immediate practical use. It can be used to evaluate BIM maturity in individual projects, companies with a portfolio of projects, or the industry as a whole. Moreover, the different units of BIM maturity analysis are innovatively integrated in a single, vivid presentation.

In construction schedules, a logical relationship between two activities is specified by the relationship type and a fixed lag time. This rigid representation, however, does not consider the situation when two activities have a degree of flexibility in their relationship. Such flexibility, or soft relation, can be very beneficial as it provides a range of overlapping options that can be utilized in situations that require the schedule to be optimally accelerated. This paper thus proposes a formalization of a generic logical relationship (hard or soft) of any type (finish-to-start, etc.) between any two activities. Using the generic representation, modified activity start and finish time computations are presented to accommodate the overlaps associated with soft relations, and are used in a schedule-crashing model. The model determines the optimum combination of activity crashing and overlapping decisions that minimizes project cost without violating the resource constraints. The new activity relationship and crashing model are beneficial to both researchers and practitioners as they facilitate schedule optimization decisions for projects that exercise a good level of overlapping, such as fast-track projects.