Journal of Construction Engineering and Management

Intelligent compaction (IC) is an emerging technology that can be applied to improve the compaction of hot mix asphalt (HMA). This study investigated the applicability of IC technology for the quality control (QC) and/or quality assurance (QA) of HMA compaction through a survey, phone interviews, and a review of IC demonstrations conducted in Indiana. The questionnaire survey gathered information about (1) the field usage of IC technology by state DOTs, (2) the benefits of IC technology, and (3) future plans for IC implementation. Only two state DOTs have adopted IC technology for QC, whereas the other 24 respondents have not applied IC technology for either QC or QA. A review of IC demonstrations conducted on US 52 in Indiana was undertaken to explore the possibility of substituting the nonnuclear density value with the ICMV. Multiple regression analysis of the data (predicted variable: nonnuclear density) indicated a ${\mathit{R}}^2$ value of 0.67 with statistically significant p-values for the independent variables [i.e., pass count, temperature, and intelligent compaction measurement values (ICMV)]. The results of this research indicate that IC technology would improve both the compaction coverage and the uniform compaction for HMA QC applications, although no solid evidence is available to date to support the possibility of substituting core density values with ICMVs for QA.

Construction sector productivity is of great importance for the government and policymakers because it determines a nation’s future living standards and creates a competitive business environment. Addressing the factors influencing labor productivity is crucial for improving the productivity performance of the sector. A theoretical structural model is developed to understand the influence of six key factors on construction labor productivity and their links to labor productivity performance on a project. A structural equation modeling technique is used to analyze data collected via a questionnaire survey of 185 respondents consisting of government authorities and construction actors. The final model adapts 29 attributes across six labor productivity factors, namely, management and control, workforce, financial, external, project, and material and equipment. The outcomes of the final structural equation model confirm the significance of management team competency level and workforce quality in enhancing labor productivity. Moreover, client support and efforts by government authorities are found to be significant for labor productivity improvements. Despite the limitations of the study, it is hoped that the research outcomes will significantly contribute to improve the labor productivity performance in the Malaysian construction industry for faster delivery of construction projects with lower cost and higher quality.

Both hazard recognition and safety risk perception are fundamental to effective safety management. When construction hazards remain unrecognized or the associated safety risk remains unperceived, the likelihood of human errors and injuries increases. Unfortunately, recent studies have shown that a large number of construction hazards remain unrecognized in typical workplaces. Likewise, past research has demonstrated that safety risk is widely underestimated in construction. Therefore, to improve safety performance, a proper understanding of factors that influence hazard recognition and safety risk perception is vital. Toward achieving this goal, the objective of the current study is to evaluate the effect of distractions—which are ubiquitous in construction environments—on the hazard recognition performance and safety risk perception of workers. The study goals are accomplished through an experimental effort involving 70 construction workers representing various specialty trades. The workers were randomly assigned to a distracted or undistracted condition, and their hazard recognition performance and safety risk perception levels were measured using construction case images. The study findings revealed that the distracted workers recognized a smaller proportion of hazards compared with undistracted workers. However, there were no significant differences in the level of perceived safety risk between the two groups. A closer examination of the data revealed that the safety risk perception levels for the undistracted workers are positively related to their hazard recognition performance. In other words, when undistracted workers recognize a larger proportion of hazards, they also perceive higher levels of safety risk. However, no such relationship was observed for the distracted workers, suggesting that the perceived risk was unrelated to or not dependent on their hazard recognition performance. The findings suggest that workplace distractions can adversely affect hazard recognition, safety risk perception, and safety performance. Given that constuction workers are already exposed to numerous distractors in typical workplaces, contractors seeking to introduce emerging technologies such as drones, mobile devices, and smart robots must be cognizant of their potential distracting effects. The current study represents the first empirical effort investigating the effect of workplace distraction on construction hazard recognition and safety risk perception.

This paper presents a novel construction project planning model that allows more-efficient and more-realistic planning than current methods. Unlike scheduling methods such as the critical path method (CPM), the proposed model represents spatial entities on the construction site, such as work areas and safety buffers. The model uses Boolean operators to allow the codification of the actual constraints that guide construction projects and to create a single integrated temporal-spatial model. Singularity functions are used for the mathematical definition of the constructs and their relationships, providing a flexible modeling framework. The model is implemented in a real-world case study with input data from building information modeling, demonstrating its feasibility and usefulness.

Fall accidents (FAs) constitute a substantial proportion of construction accidents. While the predominant prevention strategy relies on passive approaches (e.g., guardrails), research on proactive measures is lacking, which may reduce the incidence of FAs in high-risk construction trades. Literature suggests that rebar work is one of the foremost FA-prone construction trades. Since rebar workers spend hours in rebar tying postures with periodic postural transitions, they hypothetically are at risk of posttask loss of balance. While recent research showed that a sitting stool could significantly alleviate physical discomfort during rebar tying, the current study aimed to investigate temporal changes in standing balance (using a force plate) after simulated rebar tying in squatting, stooping, and stool-sitting while the respective postural load during rebar tying was quantified by electromyography and oximeters. Results demonstrated that stool-sitting resulted significantly better posttask standing balance than squatting or stooping, which might be attributed to differential postural loadings. Overall, the findings reported herein underpin the importance of using safety informatics to proactively analyze task-specific fall hazards, to monitor workers’ balance, and to implement proper prevention strategies for workers at risk of falls.

In this paper, a novel framework is presented for estimating, allocating, and managing schedule contingency using the theory of constraints and the earned schedule technique. The main aim of the proposed framework is to present a practical technique to manage schedule contingency in a manner that is easy to use and simple to understand; can overcome the drawbacks of earned value management for the schedule component; can overcome the inaccuracy caused by using critical path method; and takes into account the statistical nature of each activity and merges them to form a single framework. The framework introduces two new measures, buffer performance index and buffer variance, for measuring the expected remaining buffer and the actual remaining buffer on critical and noncritical chains based on the percentage completion for each activity at the end of the reporting period, respectively. To verify the proposed framework, the processes and measures have been applied to three projects, each with different complexities. The results show potential for managing buffers when placed at the project level, without the involvement of complex mathematical models or tedious equations.

Although a few studies have considered financing cost in the construction project, no research has been conducted to select the optimal financing alternatives out of those offered by financial institutions. This study presents a model that minimizes financing cost by considering different financing alternatives and a work schedule with normal activity durations. The proposed model creates a cash flow forecast based on a work schedule generated by the critical path method (CPM). The output includes optimized schedules of financing inflow (borrowed money) and outflow (repayments of principal and interest). The proposed model has advantages compared to models developed in previous studies because the contractor: (1) pays less financing cost, (2) avoids extending the project duration and avoids liquidated damages, (3) provides an optimal financing schedule, and (4) reduces the risk of ending up with a work schedule composed of more critical activities. The model has been tested in three cases and sensitivity analysis has been performed.

Risk management is a key concern in public-private partnership (PPP) projects and the efficient allocation of risk remains problematic. Previous studies on PPP practices have documented the prevalence of inefficiency in risk allocation. Nevertheless, the nature of PPP risk misallocation has not been quantitatively described and verified. This study examines risk allocation in the Chinese water sector as it supports the highest number of PPP projects. Based on the expertise of 32 senior practitioners, statistical analysis is used to contrast where risks ought to lie in order to maximize risk mitigation efficiency with where such risks actually lie. The results confirm that current risk allocation practices are far from ideal, with the implication that current practices play a significant role in project failure. Details within the data provide insight into how practitioners should modify current risk allocation practices to better achieve risk management optimization. The lesson learned from this study can be transferred to projects in other emerging PPP markets.

This study aims to investigate the level of social capital between construction supervisors and workers and how this influences construction workers’ safety behavior. To fulfill these research aims, a structural equation model (SEM) was constructed to explore the relationships among social capital (including the structural, relational, and cognitive dimensions); safety competency; and safety behavior (i.e., safety compliance and safety participation), considering safety competency as a mediation variable. Data on these variables were collected via questionnaires answered by 535 construction workers who participated in 93 completed building projects in China. In regard to safety behavior, only the cognitive dimension, represented by shared language and shared goals, had a significant positive effect on safety behavior. The structural dimension, which includes network ties between supervisors and workers as well as the centralization of supervisors, had a significant negative effect on safety behavior. The relational dimension, characterized by mutual trust and reciprocity norms, had no direct or indirect effect on safety behavior. For the mediation effect, the cognitive dimension had an indirect, positive effect on this variable, considering safety competency as the mediation variable; the structural and the relational dimensions did not indirectly affect safety behavior. This paper provides a theoretical basis for construction supervisors to develop measures to improve workers’ safety behavior from the perspective of relationships between people, and it points out the important role of safety competency in safety behavior. Unlike assumptions, the high level of the network has a negative effect on safety behavior, which should cause supervisors to pay attention to workplace safety management. In general, this study can inform management methods for improving workers’ safety behavior and on-site safety conditions from the perspective of social capital.

The work processes for highway infrastructure projects are undergoing significant transformations because of the advent of digital technologies for project delivery and asset management. Civil integrated management (CIM) encompasses the digital tools and practices that facilitate the collection, organization, and use of accurate project information throughout the facility lifecycle. With the increasing reliance on CIM technologies due to their proven benefits, there is a growing need to formalize a CIM maturity model that helps agencies gauge their CIM utilization activities. Through a survey of state transportation agencies and other CIM experts, this paper develops a quantitative approach to benchmark an agency’s CIM capability. A multistage Bayesian factor analysis technique was used in this study. The study jointly analyzes the information from the relevant literature and the collected data on relative importance and actual implementation levels of 16 attributes related to CIM utilization. Results suggest the existence of three latent factors that adequately indicate the measurements on these attributes related to technology, processes, and organization. Furthermore, results demonstrated an overall CIM maturity score exists at second-order and can adequately summarize the measurements along the first-order latent factors. The empirical validity of the second-order model was demonstrated by applying this framework to the usage data of six U.S. highway agencies to benchmark their CIM maturity. The mathematical framework of this study can help highway agencies develop customized applications for maturity assessment and support decisions for prioritizing CIM investments.

Highway construction has consistently reported relatively high fatality rates largely because of the considerable exposure of workers to live traffic. To address this anomaly, traffic control planners are tasked with making decisions geared toward reducing hazardous situations caused by transiting vehicles and construction equipment. The growing application of technologies to enhance worker safety should be considered during the traffic control planning process. In certain cases, decisions such as choosing among technology options are made using experiential individual knowledge without the application of scientific and systematic decision-making methods. Use of experience-based decision making in this context is largely the result of sparse literature on scientific methods of selecting between alternatives in highway construction work zones. By applying the Choosing by Advantages (CBA) decision-making method, a process that achieves sound and effective decisions, the current study aims to fill the gap in practice by proposing a decision-making framework that could enhance the value-cost selection process of safety technologies in highway construction work zones. A situation that applied work zone intrusion alert technologies (WZIATs) was selected as a case study. Using a focus group session and case projects as an evaluation study process, the proposed framework based on the CBA decision-making process was applied to evaluate three WZIATs. Findings from the current study will benefit safety professionals and practitioners by providing a step-by-step approach to make sound decisions that can enhance the level of safety in highway construction work zones.

Workers involved in asphalt pavement construction are exposed to asphalt fumes. The adverse health effects of asphalt fumes have long been recognized; however, there is still a lack of consistent and systematic approaches to measurement, assessment, and mitigation of asphalt fume exposures. This study reviewed the current status of research and practice on this issue and conducted case studies in 12 pavement construction projects. Literature review suggests that much work needs to be done in (1) health effect identification, (2) development of standard methods for exposure measurement, (3) characterization of harmful components in asphalt fumes, (4) establishment of exposure limits, and (5) quantification of factors that affect exposures. Case studies indicate that short-term exposures to the respirable portions of asphalt fumes can be quite high on some projects, and the high exposures are related to construction factors. The detected chemicals in fume samples appear to be affected by construction materials and construction temperature. From the perspective of construction management, a simple guideline to help field managers and workers to estimate exposure risk and avert risky situations will be beneficial. This study contributes to the body of knowledge in construction management by providing renewed and first-hand information on asphalt fume exposures by workers.

Communities near forests are vulnerable to wildfires. Retrofit measures to reduce the vulnerability of residential buildings to wildfire include improvements that hinder, mitigate, or prevent damage from wildfire heat and embers to building exteriors and within the parcel limits. The objective of this study is to provide a cost model for optimal retrofit planning for residential properties by integrating multiattribute vulnerability rating systems, on-site wildfire vulnerability assessments, property characteristics, and uncertainty in homeowner preferences. Integer programming is used to find the optimal combination of retrofit activities that leads to the minimum vulnerability mitigation cost for 389 residential properties in Santa Fe, New Mexico. A cost model is derived for wildfire retrofit planning for residential properties. Although this study was conducted on a specific study area, the framework introduced in this study presents a planning tool for large-scale retrofit planning for urban or suburban buildings that can be used and adapted for other types of natural hazards and in other communities.