Journal of Construction Engineering and Management

Workspace planning is critical for effective construction planning and control, and workspace modeling is an essential part of computer-aided workspace planning. The existing construction four-dimensional (4D) models, which have gained popularity in construction as an effective tool for planning, control, and communication, lack efficient means to capture the dynamic nature of workspaces to avoid potential workspace conflicts in future construction. This paper presents a life-cycle approach to workspace modeling and planning by first investigating the dynamic nature of the workspace requirements of construction activities and then introducing a conceptual framework to format space usages into life-cycle workspace evolution patterns. Specifically, an object-oriented data structure was designed and implemented to incorporate workspace representation into construction product models, and a workspace identification and adjustment method was created to facilitate the creation of construction workspaces. This newly created approach was tested in an implementation case study of a campus garage project with a number of application scenarios and was proven to be effective and convenient for modeling the dynamic workspace evolution associated with typical construction activities.

The construction process is inherently prone to risks. Risk management is an essential and integral part of project management on virtually all construction projects. Risk analysis is one of the core components of risk management that enables professionals to quantify and analyze risks that may pose potential threats to project performance in terms of cost, quality, safety, and time. This research was conducted to identify and analyze risks associated with bridge construction in Pakistan. A questionnaire was conducted to collect data. Risks affecting bridge construction project performance were identified through interviews conducted with engineers and managers involved with various bridge projects. Cost and schedule impacts of project risks were supplemented by conducting a case study using the Monte Carlo simulation. The key findings indicate that financial risks were a major factor that affected cost and schedule objectives. The highest ranked factor identified was unavailability of funds with a relative importance index greater than 85. The results of the Monte Carlo simulation were compared to the actual completion times and costs of activities in the case study. In all cases of this comparison, the actual completion date and costs fell within the predicted distribution of the Monte Carlo simulation, indicating that risk analysis can help project managers to manage cost and schedule risks. Additionally, this study provided risk analysis guidelines, which were unclear. The results of this paper can help engineers, cost control managers, and project managers evaluate particular risks on their projects and avoid delays and cost overruns.

Sewer construction in urban areas often requires nighttime operations to meet project schedules and to reduce possible negative effects of construction work on traffic operations. Although several studies investigated the correlation between daytime and nighttime construction productivity, there is a limited understanding of how shift work may influence productivity in sewer construction projects. This research examined the labor productivity of 10 activities typically performed in both day and night shifts in sewer construction. The research employed Levene’s test and t-tests to analyze the data collected from eight sewer construction projects in Ho Chi Minh City, Vietnam. The results indicated that (1) pavement cutting and timber piling were more productive in daytime operations, whereas steel sheet piling and manhole concreting were more productive in nighttime operations; (2) no statistically significant difference exists in productivity between day and night shifts for the following activities: excavation, form installation, rebar installation, pipe laying, sand filling, and asphalt paving; and (3) the productivity of pavement cutting, excavation, timber piling, steel sheet piling, pipe laying, and asphalt paving was higher in partial road closure than in full road closure methods. These statistical results were verified and validated by the experienced site managers/engineers through eight structured on-site interviews. This research contributes to the construction productivity knowledge by providing empirical results of daytime and nighttime operation productivity in sewer construction. It is expected that practitioners can use these results to focus proper attention and resources for day and night shifts in sewer construction projects.

In recent times, linear project resource leveling based on the linear scheduling method (LSM) has attracted considerable interest owing to the unique advantages of applying the LSM to linear projects. In the research reported in this paper, the linear project resource leveling problem was described as a constraint satisfaction problem based on analyses conducted in previous studies and a two-stage scheduling model for resource leveling of linear projects based on the LSM was proposed. The optimization process was reasonably set so as to fully utilize the rate float of the activity to obtain a more optimal schedule. The constraint programming (CP) technique was used for solving this problem. Based on the proposed scheduling model and algorithm, a two-stage scheduling system for resource leveling of linear projects was developed for automatically establishing a linear schedule for resource leveling. The effectiveness of the proposed model and algorithm was verified for a highway construction project reported previously.

This paper examines sensitivity of the performance of seven project duration forecasting methods in the earned value management (EVM) literature to characteristic patterns of planned value and earned value S-curves. Specifically, this paper aims at identifying relative robustness and early warning capacity of six deterministic methods and one probabilistic method with respect to the nonlinearity of progress curves and the schedule delay patterns. The sensitivity analysis in this paper shows that forecast accuracy and early warning credibility of deterministic methods are very sensitive to the S-curve patterns, especially early in a project. The results also indicate that the probabilistic method (the Kalman filter earned value method) is the only method among the seven alternatives that is robust with respect to the progress curve nonlinearity and the schedule delay patterns. Consequently, this paper would positively contribute to the practice of project schedule control by providing practical guidance for and valuable insights into a sanity test on the forecasts and warning signals from the forecasting methods so that more informed decisions are made and unnecessary control actions triggered by false warning can be effectively prevented.

Most construction safety management processes rely on the hazard recognition capability of workers. Hazards that remain unidentified can potentially result in catastrophic injuries and illnesses. As such, thorough hazard recognition is fundamentally essential to protect the health and well-being of the construction workforce. Despite its importance, recent research indicates that a large proportion of hazards remain unrecognized, exposing workers to unmitigated risks. Surprisingly, safety research has not adequately focused on developing specialized strategies to develop construction worker competency in hazard recognition. This paper reports a two-year research effort with the following objectives: (1) develop a high-fidelity augmented virtual environment [System for Augmented Virtuality Environment Safety (SAVES)] that helps develop workers’ hazard recognition skill through risk-free learning and immediate feedback; (2) embed cognitive retrieval mnemonics to improve long-term retention of cues for construction hazards; (3) evaluate the effectiveness of the strategy as an intervention on active construction crew by using the multiple baseline testing approach. The first two objectives were accomplished through a combined effort from a panel of 14 subject matter experts and five academic researchers. This was followed by field experiments to test the hypothesis that the experience with SAVES improves the proportion of hazards identified by participants during subsequent field operations. The findings revealed that crews, on average, were able to only identify 46% of hazards prior to the introduction of the intervention, but were able to recognize 77% of hazards in the postintervention phase. This study represents the first endeavor to measure the effectiveness of augmented virtuality and serious gaming in developing hazard signal detection skills in construction field settings.

For the overall success of a construction project, it is very important to accurately estimate the construction cost from the early stage. However, the limited information available in the early stage makes the cost estimation challenging. Recently, there has been an increase in the use of case-based reasoning (CBR) to estimate construction cost in the early stage. Based on the hypothesis that similar problems have similar solutions, CBR searches for the most similar cases (e.g., previous projects) for a given problem (e.g., a new project). However, because no previous project is exactly the same as a new project, the solutions applied to the past project may not work for the new project, especially when there are no sufficient cases stored in the case base. To overcome this limitation, some studies have highlighted the importance of revision algorithms to account for the deviation of the new project and the identified similar past projects. These studies, however, were limited in considering the deviation of numerical variables while the majority of variables available in the early stage is more categorical (e.g., structural system or underground condition) than numerical (e.g., gross floor area). Based on this recognition, this paper presents a revision method considering the deviation of categorical and numerical variables using regression analysis. Application to multihousing projects confirmed that the proposed CBR model can increase the accuracy of construction cost estimation. This paper is of relevance to researchers in terms of providing a theoretical basis to incorporate both numerical and categorical variables in revising the CBR model. This paper is also of value to practitioners with regard to providing an accurate cost estimation tool in the early stage of construction projects.

While web-based project management (WBPM) systems have been widely implemented in most construction projects, the current literature lacks any clear consensus on rationalizing such decisions across the industry. In an attempt to understand the factors influencing the implementation of web-based systems and their performance in construction projects, a theoretical structural model has been established, termed the partial least-square structural equation model (PLS-SEM). The effect of six latent variables on the performance of WBPM systems has been analyzed using the empirical data collected from a questionnaire survey of 77 respondents within the construction industry. The results of the data analysis suggest that the implementation of web-based systems (PMB) is rationalized with the two key factors being complexity (PC) and information streamline (IS) in the project. The general perception of increased users’ satisfaction (US) and transparency and accountability (TA) has no strong empirical basis for rationalizing the use of web-based systems across projects. Effective monitoring and control (EMC) during project delivery can only be marginally enhanced by implementing WBPM systems. The key significance of this research is the unfolding of tacit knowledge of these key factors and addressing the limitations reported in previous research in the context of implementation of WBPM systems. Appropriate consideration of these factors would potentially contribute to the development of company procedures or to enhance existing knowledge within the construction industry.

Wheel detachment from plant trailers used on public highways represents a significant health and safety hazard and major financial risk, especially for construction and utility companies that rely on these type of trailers to transport machinery such as miniexcavators or road rollers. This study uncovers the antecedents of plant trailer wheel detachment and suggests pragmatic guidance for mitigating this risk. A case study using elements of action research studies the problem in the field through direct observation and stakeholder interviews. Analysis of resulting qualitative data conceptualizes antecedents on which guidance is formulated. Risks are found to result from a combination of physical failure underpinned by inadequate human interventions and poor risk management. The primary contributions of the study are that it describes entirely novel research on trailer wheel detachment, produces new safety guidance for businesses and practitioners that operate plant trailers, and resultantly contributes to lowering the risks identified.

Limited research has been undertaken to explore how Chinese construction workers’ personality affects their safety behavior. Inappropriate behavior on-site can instigate serious accidents, injuries, or fatality as well as incur significant costs and loss of corporate reputation. To address this dearth within the extant literature, this paper uses Eysenck Personality Questionnaire to examine the complex relationship between the personality of Chinese construction workers (especially, bar benders) and occupational accidents. A significant relationship between personality, unsafe behaviors, and the extent of injury was identified. Using the results generated, a series of practical recommendations are proffered to reinforce behavioral safety training (and reduce accidents on-site), including suggestions for conducting training programs that can be tailored to construction workers with different personality traits.

Early sourcing decisions have a critical impact on the performance of industrial construction projects. However, the industrial construction sector has been relatively understudied, especially the sourcing and supply chain practices typically implemented in early phases of capital projects. This study reports on how engineering-procure-construction (EPC) firms select suppliers in the early stages of the project. Particular focus involves the decisions firms make in sourcing process and the types and roles of supporting information. The paper reports on five case studies with large EPC firms. Data were collected from multiple individuals in each firm with extensive supporting documentation. A cross-case analysis describes similarities and differences between EPCs and helps to compare empirical findings with the broader literature. Findings contradict some areas of the literature, in particular the push for strategic supplier alliances. Other findings confirm the strategic importance of early procurement decisions to project performance and similarity across the types of decision drivers for supplier selection. Practitioners will find the case studies useful examples of current practice to compare with their corporate efforts. Researchers will similarly find details that extend extant literature, proposing new avenues for future research.