Journal of Construction Engineering and Management

Laser scanning technology (LST) is a contactless measurement method with recognized advantages, and it has changed the way smart construction (SC) is measured. However, existing literature lacks a comprehensive summary of the problems of applying LST in SC, hindering its widespread diffusion. This study reviews 264 papers by using bibliometric and scientometric analyses in addressing this issue. The key themes in the applications of LST in SC are identified, and a qualitative discussion of current research issues and challenges are provided. In addition, the changes that LST has brought to SC and the barriers that exist are discussed. Future research directions are explored to help researchers gain insights into the topic. This study provides new ideas for academic researchers and related practitioners by reviewing the literature on the application of LST in SC, promoting the development and application of LST in modern SC.

Immersive technology, a collection of virtual reality, augmented reality, and mixed reality, has been applied to many aspects of the construction industry. To evaluate immersive technology–related experiments, many evaluation approaches have been proposed, which can be categorized as quantitative-based and qualitative-based. With the advancement of the neuroscience discipline, there is an emerging trend in deploying biometric sensors to evaluate physiological responses when participants are exposed to virtual stimuli in an immersive environment, which can be categorized as biometric-based evaluation. This study aims to review state-of-the-art biometric-based evaluations in a variety of immersive technologies (ImTs) in construction. A total of 43 articles published from 2018 to 2024 are included. The systematic review of selected articles produced five research themes: (1) ImT usability evaluation; (2) learning experience and performance; (3) general construction tasks; (4) human–robot collaboration; and (5) hazard identification and risk perceptions. The summarizations revealed that biometric sensors have been increasingly adopted to understand the psychophysiological and cognitive process when exposed to a stimulus in ImT environments without physically exposing workers to danger. This study also summarized limitations and future directions in four aspects, including ImT development, biometric deployment, biometric-based ImT development, and application potentials in the construction industry. The obtained knowledge is expected to benefit the researchers from an overview of the applications of using biometric sensors in immersive environments and promote the integration of biometric and immersive technology in the construction industry.

Target cost contracts (TCCs) with risk/reward-sharing incentivizing arrangements are often used to promote performances in integrated project delivery (IPD) projects. However, setting the target cost can be challenging due to the diverse interests of team members and many uncertain cost influencing factors inherent in such projects. According to prospect theory and goal-setting theory, neither overly lenient nor unattainably high target costs would drive exceptional performance. This study proposes that the relationship between target cost and cost performance is an inverted asymmetrical V-shape, indicating that cost performance improves with more challenging targets up to a point, beyond which unreasonably challenging targets would render negative effect. To mitigate the risk of setting unreasonable targets, establishing cost targets within a zone that spans between the at-risk threshold and the shared-reward threshold can be an option. This zone is identified as neutral. Despite reducing the risk of unreasonable target costs, the incentivizing power of this neutral zone approach diminishes sharply once the cost exceeds the at-risk threshold. Strategies are proposed to augment the incentivizing power of neutral zone–based TCC for two types of agents: myopic and forward-looking. Complementing neutral zone with subgoaling strategy can significantly improve cost performance for myopic agents. Furthermore, the prospect of repeated business can incentivize the forward-looking agents to achieve the shared-reward threshold. This novel method is instrumental in establishing target costs at the early stages of IPD projects.

Extensive research has demonstrated the significance of project governance in enhancing project performance. However, previous studies have not dealt with the problem of governance mechanism design for engineering consulting (EC) with intangible outputs. Researchers have overlooked corporate governance and the coupling of project and corporate governance in improving project performance. This study identifies effective governance mechanisms for enhancing EC project performance through the fuzzy set qualitative comparative analysis (fsQCA) of survey data collected from Chinese EC professionals. It reveals multiple pathways to achieving high performance in EC projects, including: (1) relational governance matched with governance of project management (GoPM); (2) relational governance; and (3) a combination of contractual governance, relational governance, and GoPM. This study contributes to the body of knowledge on EC project governance with intangible outputs in three ways. First, this paper incorporates corporate governance into the framework of EC project governance, demonstrating that GoPM is the core element for enhancing EC project performance. Second, the improvement in EC project performance stems from the synergistic effect of project and corporate governance mechanisms. Moreover, the relational governance mechanism plays a more crucial role than the contractual governance mechanism in enhancing EC project performance.

Material price fluctuations pose significant challenges for executing construction projects and adhering to budgetary estimates. Existing research studies focused on forecasting construction material prices rather than quantifying and gauging overall project cost risks related to price volatilities, and they relied on traditional time-series forecasting methods that are incapable of offering full probabilistic distributions of price fluctuations and of providing a comprehensive assessment of risk uncertainties associated with material price fluctuations. This paper addresses these gaps by developing an integrated framework to quantify and gauge project risks due to construction material price volatilities. The framework’s validity and practicality were demonstrated using real-world projects with various characteristics and different market conditions, including an 11-month bridge replacement project and a 25-month major roadway project. Historical Producer Price Index (PPI) values were collected for four construction materials: steel reinforcement, asphalt, aggregate, and concrete. Three probabilistic deep-learning models—deep autoregressive models, probabilistic feed-forward neural networks, and transformers—were developed to forecast PPI probabilistic distributions. The performance of the developed models was evaluated using probabilistic metrics, and the top-performing models were identified for each material and were compared with a baseline artificial neural network model and a Bayesian prophet model. Finally, stochastic risk models were developed to integrate the predicted distributions into the price escalation clauses of standard construction contracts (i.e., FIDIC) to model risk uncertainties and plot stochastic risk profiles. The findings provided valuable insights about patterns and fluctuations in prices across various construction materials, market volatilities, extreme events, and different types of clauses, including “any-increase escalation clauses” and “threshold escalation clauses.” This study contributes to the growing body of knowledge on construction material price escalation by offering a comprehensive approach that provides project parties with data-driven insights that inform strategies to mitigate financial setbacks resulting from price fluctuations and volatilities in their projects.

Abstract

Psychological distress is a key challenge in the construction industry and suicide rates in the sector are 12 times higher than deaths from workplace accidents. Yet, few evidence-based interventions have been developed to improve construction workers’ mental health—and none focus on the key issue of social group connection. To address this gap, this paper introduces and evaluates a new prevention-based wellbeing training program developed specifically for construction workers—Connections for Work and Health (CWH). The program is informed by a social identity approach to health that focuses on the importance of social group connectedness for mental health and wellbeing within at-risk groups. The feasibility of CWH among Australian construction workers ($N=69$) was evaluated in a quasi-experimental study that included a waitlist control and assessment at three timepoints (preintervention, postintervention, and follow-up). This included evaluation of (1) perceptions of program impact, (2) effects on mental health (psychological distress and life satisfaction), and (3) effects on social group outcomes (social support, multiple group membership). Participant feedback indicated positive perceptions of the intervention including increased knowledge and improved social connections. Efficacy results indicate that CWH participants reported marginally significant reductions in distress relative to the waitlist control group. There were also significant increases in life satisfaction in the experimental group but no significant changes in social support and multiple group membership. Overall, results provide preliminary evidence that CWH—and broader efforts to encourage social group connection—have the capacity to reduce the negative mental health consequences of social isolation and loneliness in the construction sector, although further testing with larger and diverse samples is required.

Practical Applications

This study introduces Connections for Work and Health (CWH), a novel group training program designed to enhance mental health among construction workers by fostering social connections. The construction industry faces an alarming mental health crisis, with suicide rates 12 times higher than workplace accident deaths. Traditional interventions have largely overlooked the role of social connectedness, which is crucial for mental health. CWH aims to fill this gap by highlighting the importance of social group connections and supporting construction workers to manage and grow their group memberships and identities. In a trial involving 69 Australian construction workers, CWH demonstrated promising results. Participants gave positive feedback on the intervention—reporting increased knowledge and improved social connections in the workplace. Importantly, participation in CWH was associated with reduced psychological distress. These findings suggest that strengthening group bonds can be beneficial for mental health in this high-risk sector. For industry leaders, this study highlights the value of cultivating strong work team identities. By focusing on shared interests and goals, managers can foster a supportive environment that enhances both work group cohesion and individual wellbeing. Integrating CWH with existing mental health programs may provide a comprehensive approach to addressing the sector’s urgent mental health needs.

Abstract

Scheduling repetitive construction projects (RCPs) is a challenging task due to the nature of the activities involved. It requires careful consideration of both flexibility and computational performance. This paper develops a versatile RCP scheduling framework applicable to multiple construction scenarios, providing greater flexibility than existing models. The framework incorporates various scheduling features for repetitive activities, such as soft logic, multiskilled crews, multimode execution, crew transfers, and continuous or noncontinuous execution. It also offers optional optimization objectives, such as minimizing the overall project duration, total cost, crew interruption time, and number of employed crews. Planners can combine the features of repetitive activities and choose one or more objectives to meet their needs and preferences. The proposed framework is based on constraint programming, which balances computational efficiency and solution quality while remaining user-friendly. The practicality and effectiveness of the framework are verified through three case studies involving five real-life projects. The results demonstrate that the proposed framework can produce RCP schedules with shorter duration, lower costs, or reduced resource utilization compared with those generated by existing models.

Practical Applications

Efficient scheduling is of great importance for the successful implementation of RCPs. However, it is also a highly challenging task, given that different types of RCPs correspond to different construction scenarios. This paper presents a novel RCP scheduling framework that facilitates the simulation of diverse construction scenarios by incorporating flexibility in the modeling of activities, crews, and objective functions. The framework incorporates multicrew operations for individual activities and facilitates alterations in the construction sequence of units. Moreover, the framework integrates multiskilled crews, offers a variety of execution modes, and supports both intermittent work and strict continuity, as required by the project. Additionally, it provides several objectives, including project duration, project cost, work continuity, total number of crews, or multiples of them. The framework is formulated using the constraint programming technique, which offers the advantages of easy construction, convenient use, and highly efficient solving. Finally, three case studies based on five real-life RCPs are conducted to verify the practicability and validity of the proposed framework. The results demonstrate that the framework outperforms existing models in terms of time, cost, and resource optimization.

Infrastructure projects are characterized by inherent complexities that often lead to their poor performance. Notwithstanding challenges posed by various risks and their interactions, the additional non-linear and dynamic interdependence-induced complexities make infrastructure projects susceptible to systemic risks—probable component disruption that can lead to cascade (system-level) disruptions. The study of teams/resource interdependence-induced systemic risks in an environment of interacting risks is scarce in the literature. In addition, several previous studies demonstrated that current risk interactions and systemic risk analysis models are impractical due to their complexity and limited theoretical application domains. In this respect, the current study fills this knowledge gap by developing a data-driven risk interactions and systemic risk management approach. This approach is formulated in three stages: (1) quantifying risk interactions and teams/resources interdependence; (2) building machine learning model (ML) models to predict project performance based on the quantified characteristics; and (3) devising relevant mitigation strategies. The study also includes a practical demonstration application of the approach to present a step-by-step demonstration for each stage—thus guiding practitioners to proactively safeguard against risk interactions and systemic risks. The current work contributes to the body of knowledge by laying out the foundations of investigating the compound phenomenon of risk interactions and systemic risks as well as by presenting an effective approach to achieve that endeavor. Overall, the current study introduces a reliable and practical approach to enhance the performance of infrastructure projects through interacting risks- and systemic risk-informed management strategies.

Acoustic-based construction site monitoring approaches have attracted recent interest due to their advantages compared to other methods. Previous relevant studies have many limitations, including narrowly focusing on sounds related to a specific/limited application without offering comprehensive monitoring capabilities of various construction site-related activities; tackling the software-side (or computational aspects) with limited work on hardware IoT-enabled embedded devices that could be used for real-time data collection, analysis, and edge computation; and lacking cloud-computing and visualization capabilities needed to improve data accessibility, storage, interpretation, and communication. This paper addresses these research gaps by developing a real-time intelligent IoT-enabled embedded acoustic-based sensing system for construction site monitoring by integrating machine listening techniques based on deep learning algorithms, edge computing based on Wi–Fi and bluetooth low energy (BLE)-enabled embedded systems, and cloud computing based on Amazon Web Services EC2. This study designed an automated monitoring system that uses convolutional recurrent neural networks to interpret construction site audio data with an accuracy of 89.13% across 14 classes of various audio related to different construction site aspects categorized into equipment and work activities, weather/environmental conditions, possible hazards, and workforce-related. The paper also developed a smartphone application to facilitate immediate and targeted alerts to relevant stakeholders. Finally, the proposed approach was tested in various construction workshops and environments. This paper’s contributions are reflected by offering an unprecedented technological workflow/architecture that integrates software and hardware innovative advancements in audio-based monitoring systems of construction jobsites across various types of sounds. The paper also adds to the body of knowledge by developing an integrated system of real-time IoT-enabled acoustic capabilities, utilizing modern machine listening techniques powered by cloud and edge computing to improve current construction-site surveillance systems. This paper has the promise to change the way construction sites are monitored and managed, thereby contributing to enhanced safety and efficiency in the construction industry.

This paper explores transformative strategies in urban pavement management by integrating automated technologies and climate-adaptive innovations, specifically under the challenging conditions posed by climate change (CC). The research focuses on implementing advanced asphalt binders coupled with automated construction processes. We employ a dual approach, using machine learning (ML) algorithms and predictive analytics to optimize the environmental impact assessments, particularly targeting ${\mathrm{CO}}_2$ emissions throughout the pavement life cycle. Our findings reveal that incorporating climate-resilient innovations can significantly decrease maintenance frequencies by approximately 20% and extend the pavement lifespan by up to 15 years, aligning closely with climate projections from 2023 to 2060. A detailed life cycle cost analysis (LCCA) suggests potential fiscal savings of up to $500 million in national highway maintenance over the next four decades. Moreover, our automated predictive model boasts accuracy with a coefficient of determination (${\mathrm{R}}^2$) of 0.85, enhancing the precision and timeliness of maintenance interventions. This paper underscores the imperative of merging automated technologies with climate-adaptive innovations to bolster the sustainability and resilience of urban infrastructures, thereby advancing economically and environmentally sustainable urban development practices. This aligns with the Sustainable Development Goals, emphasizing the urgent need for sustainable cities and communities.

Upper management serves as the originator of safety culture within construction firms. Although the role of upper management is crucial to construction site safety, its specific actions in promoting a superior safety culture are under-researched and need further examination. This study uses a mixed research methodology to identify and rank key actions that upper management can take to enhance organizational safety culture. Specifically, a Delphi method involving 21 experts and a subsequent survey methodology of 113 construction professionals were utilized. Accordingly, 17 key actions were identified and grouped into three categories: leadership; resources and funding; and communication. The findings indicate that the most crucial action upper management can take is demonstrating its commitment to safety through concrete actions. The research also emphasizes the importance of upper management collaborating with and empowering frontline supervisors as safety champions. Building a robust construction firm safety culture and project climate is essential for ensuring the well-being of workers and the success of any project. This cannot be achieved without a clearly defined list of desirable safety actions. Few studies, if any, have focused on the desirable safety actions of upper management. As a result, this study contributes valuable insights to the field, providing practical guidance for the industry and deepening our understanding of how upper management can effectively foster a positive firm safety culture and project safety climate as well as assess their safety contribution.

Abstract

Work-related musculoskeletal disorders (WMSDs) are a significant health issue among construction workers, with prevalence influenced by factors such as personal demographics, exposure to work risk factors, and working conditions. This study addresses a research gap by comparing WMSD prevalence between Kuwait and Denmark; two countries with contrasting working conditions. Data were collected from 117 workers in Kuwait and 47 in Denmark using the Nordic Musculoskeletal Questionnaire (NMQ). Results showed that 78.72% of Danish workers reported discomfort in at least one body part compared to 52.14% in Kuwait, despite Denmark’s comparatively better working conditions. Additionally, absenteeism due to WMSDs was higher in Denmark (29.79%) than in Kuwait (9.40%). This paradoxical finding led to further analysis using logistic regression that indicated country was a significant predictor of WMSD reporting ($\mathrm{OR}=3.38$, $\mathrm{p}<0.05$), with Danish workers being substantially more likely to report WMSDs than their Kuwaiti counterparts. This suggested potential underreporting in Kuwait, prompting an investigation into organizational, economic, and cultural factors that may influence reporting behaviors. Specifically, Kuwait’s high power distance and uncertainty avoidance may contribute to miscommunication and underreporting, while Denmark’s individualistic culture encourages transparency. This study makes two primary contributions to the construction engineering and management body of knowledge by: (1) providing the first cross cultural analysis of WMSD prevalence between Gulf Cooperation Council and Nordic construction sectors, and (2) demonstrating that country factors—likely cultural in nature—are stronger predictors of WMSD reporting than individual worker personal demographics. For Kuwait, this implies a need for improved reporting systems, greater worker empowerment, and enhanced working conditions, while Denmark would benefit from a focus on strengthening preventive measures. Future research should further explore the role of cultural influences on WMSD reporting. This study underscores the importance of culturally informed approaches in developing effective workplace health and safety strategies.

Practical Applications

This research reveals important insights about how country-specific characteristics affect the reporting of work-related musculoskeletal disorders (WMSDs) in construction projects. By comparing construction workers in Kuwait and Denmark, we found that despite better working conditions in Denmark, Danish workers reported more WMSDs than their Kuwaiti counterparts. This unexpected finding highlights that workplace culture significantly influences whether workers report health issues. For construction managers and safety professionals, these findings suggest: (1) Traditional health and safety metrics may underestimate WMSD prevalence in cultures where workers are hesitant to report issues. (2) Anonymous reporting systems could encourage more accurate WMSD reporting in high power-distance cultures. (3) Worker empowerment programs and supportive leadership are crucial for creating an environment where health concerns can be openly discussed. (4) Safety training programs should be culturally adapted rather than using a one-size-fits-all approach. (5) Regular ergonomic assessments should be combined with efforts to understand and address cultural, organizational, and economic barriers to reporting. These insights are particularly relevant for international construction companies operating across different cultural contexts and for organizations employing multicultural workforces.

In the realm of construction safety, disparities in risk perception among workers and frontline managers impede risk communication and undermine risk management endeavors. Building upon previous research, this study zeroes in on a pivotal aspect of risk perception: risk analysis. We executed a behavioral experiment to validate the presence of discrepancies in risk analysis between workers and managers. Event-related potential (ERP) experiments were undertaken to delve into the neural underpinnings of these discrepancies. The results revealed that workers displayed a pronounced bias, extended reaction times, and diminished accuracy rates in both probability and damage judgments, in comparison with managers. Furthermore, the ERP experiment findings suggested notable differences in brain information processing regarding risk analysis between the two groups. In the probability judgment task, workers exhibited higher average amplitudes of N100 and N130, but lower P100 amplitudes than managers. During the damage judgment task, workers showed greater N130 amplitudes and reduced P100 and late positive potential (LPP) amplitudes compared with managers. These results indicated that managers allocated more attentional resources and maintained a broader attention scope during the early attention stage, whereas in the subsequent cognitive stage, they experienced stronger emotional responses and employed more cognitive resources than workers. Moreover, a risk analysis distinction model was developed to discern between the worker and manager cohorts. Employing ERP technology in this investigation enhances our comprehension of the neural mechanisms contributing to risk analysis differences and broadens the scope of related research. This study uncovers the underlying cognitive neuroscientific reasons for the observed differences in risk analysis between workers and managers. The results provide essential references for the scientific development of safety training programs by focusing on three key areas: attention allocation, emotional arousal, and distribution of cognitive resources. Additionally, it furnishes recommendations for the establishment of improved risk communication strategies between managers and workers.

Collaborative contracts are considered a means to address poor communication, adversarial relationships, and unsatisfactory project management arising from traditional contracts. However, the governance mechanisms of collaborative contracts have been unproven. This study investigates the impacts of relational and formal governance on information sharing and project management performance in collaborative contracts. We employ a mixed-method approach, in which the results obtained from structural equation modeling in a survey study are cross-validated by the qualitative findings from a focus group study. The results reveal the mediating role of information sharing in the influencing mechanisms of relational and formal governance on project management performance. The focus group study complements a multilevel framework to cultivate mutual trust (relational governance) for enhancing project management. The findings of this study not only fill existing knowledge gaps in understanding the underlying governance mechanisms of collaborative contracts, but also extend the comprehension of the interplay between relational and formal governance, emphasizing the crucial role of mutual trust in collaborative contracts. Furthermore, this study holds practical implications by highlighting potential strategies for enhancing project management performance by leveraging governance mechanisms and cultivating mutual trust across multiple levels.

Near misses occur much more frequently than accidents, often by factors of hundreds or thousands, and they typically share common causes with accidents. It is believed that eliminating the causes of near misses can make a significant contribution toward accident prevention. However, existing studies on causal factor analysis have mainly focused on accidents, with little attention paid to near misses. To address this gap, this study aims to explore causal factors of near misses and accidents in urban railway construction using a complex network approach. A two-layer urban railway construction safety risk network (URCSRN) was established based on the chain relationships in near misses and accidents, and its topological features were analyzed and revealed. Besides, the network robustness assessment was conducted through random and deliberate attacks. Results showed that both the accident layer network and the near-miss layer network in the URCSRN were scale-free networks. A positive degree correlation existed between the accident layer network and the near-miss layer network. A total of 11 critical factors leading to near misses and accidents were identified and found to exhibit spatial-temporal and worker typer-related characteristics. This study is beneficial for revealing the same contributing factors of near misses and accidents and the occurrence patterns of these factors among diverse worker types, in different construction phases and areas. It can provide practice guidance for safety managers to take safety measures to prevent similar near misses and potential accidents. Also, this study offers empirical evidence to support the common cause hypothesis and improves accident causation theory. Using a multilayer network to examine near misses and accidents simultaneously provides a new perspective for construction incident analysis.

Large-size hydraulic manipulators (LHMs) are widely used in construction areas, but the traditional on-site human–machine interfaces have poor performance problems in efficiency, safety, and usability due to dangers caused by complex obstacles and machine’s constraints. In this study, a uniform constraint velocity polytope (CVP) is introduced to represent the complex constraint information for complying with the machine’s limitations and avoiding collision with the obstacles. The models of the machine and surrounding obstacles are established to calculate the CVP in real-time with a safety margin. The CVP and commanded tool-center-point velocity are incorporated into a visual annotation and displayed in a newly designed augmented reality-based human–machine interface, so that the operator can observe the safe velocity region intuitively and improve the operational efficiency and safety level. The experiment and simulation tests verify the effectiveness of the proposed human–machine interface in improving operation efficiency, safety level, and subjective feeling.

Conventional value engineering (VE) workshops face challenges in brainstorming effective ideas due to heavy reliance on personal expertise and the difficulty in fully considering downstream factors. In contrast, design for manufacturing and assembly (DfMA) emphasizes the proactive consideration of downstream issues through established guidelines. This paper proposes a systematic framework for integrating DfMA to facilitate VE workshops for construction projects. It starts with a comprehensive literature review to achieve the cross-sectoral learning of DfMA in the construction industry, resulting in the generalization of six construction-tailored DfMA principles. A DfMA guideline matrix (DfMA-GM) is developed by clarifying guidelines along two dimensions, offering a structured approach for their utilization in construction projects. Integrating the matrix into the VE process leads to the proposal of the DfMA-GM-supported VE workshop. The workshop acquires and utilizes the guidelines to facilitate idea generation, transforming the creativity phase into a guideline-driven process. The framework undergoes thorough validation, including application illustration, qualitative evaluation, and quantitative comparison. The findings reveal that the framework of integrating DfMA into VE workshops not only offers a rational and feasible strategy for construction projects but also enhances the efficiency and effectiveness of the idea generation with broad implications.

Abstract

In a crisis, drastic changes in the working environment require strong leadership to supervise the team of facility management professionals (FMPs) managing facilities to improve their job performance and job satisfaction, as well as reduce the turnover rate. The critical period of the COVID-19 pandemic, which was characterized by lockdowns and a largely unvaccinated population, was used as the context to study a crisis. This research investigated the forms of crisis management leadership (CML) that engender job satisfaction in FMPs during a crisis and explored the effects on FMPs’ perceived self-efficacy, job performance, and job satisfaction in a crisis context. Using an online survey, 102 sets of completed questionnaires were received from FMPs who managed facilities in Singapore during the critical period of the COVID-19 pandemic. partial least squares structural equation modeling (PLS-SEM) was conducted to explore the relationship between CML, FMPs’ perceived self-efficacy, job performance, and job satisfaction. The study identified 10 leadership competencies that are essential for CML and demonstrated CML’s positive impact on FMPs’ perceived self-efficacy, job performance, and job satisfaction during crises. Notably, FMPs’ perceived self-efficacy was found to mediate the relationship between CML and job satisfaction in crisis situations. The primary contributions that this research makes to the body of knowledge include identifying specific leadership competencies applicable in crises and enriching the literature on the interplay between CML and job satisfaction by examining the mediating effect of perceived self-efficacy. Furthermore, the study offers criteria for selecting suitable crisis leaders and suggests strategies to enhance FMPs’ job outcomes in crisis contexts.

Practical Applications

In a crisis, drastic changes in the working environment require suitable leadership to supervise the team of FMPs to improve their job satisfaction. This study identified 10 leadership competencies that are associated with FMPs’ job satisfaction. These competencies are visibility, providing sufficient resources and support, a sense of urgency, frequent communication with the team, organized response to unexpected changes, clear information sharing, personal resilience, objectivity in perceiving others, creative problem-solving to prevent operational damage, and transparent communication. Amongst them, being objective in perceiving others was observed to have the strongest correlation with FMPs’ job satisfaction; a leader’s visibility to reduce FMPs’ anxiety hold the strongest correlation; and maintained personal resilience positively correlates with organizational justice during the pandemic. We found that organizations can improve employee’s perceived self-efficacy so that they can work at a high level of satisfaction when they face significant psychological pressure and health threats in a crisis. Organizations may do this by providing opportunities for mastery of their work through training, offering feedback, and mentoring, as well as providing crisis management leaders who have the 10 competencies identified in our study.

The construction industry is undergoing a transformative shift with the integration of advanced technologies such as teleoperation, which holds the potential to significantly enhance operational practices and workforce dynamics. This research delves into the adoption of equipment automation technologies within the construction industry, focusing on the critical role of teleoperation. By identifying the key benefits and barriers associated with the adoption of teleoperation, the study underscores its necessity for advancing industry practices. Additionally, it provides insights into the diverse factors that influence technology acceptance and integration. Employing a mixed methodology approach, including semistructured interviews with industry experts and a comprehensive survey of 220 construction professionals, the study identifies key factors influencing the adoption of teleoperation and other equipment automation technologies. The analysis reveals significant organizational characteristics such as company size, sector, and project type that affect technology adoption strategies. Additionally, the study highlights the demographics and gender-specific differences in perceptions of adopting teleoperation, with women expressing greater concerns about job security and safety, while men focus on operational efficiency and performance. Despite the evident benefits of teleoperation, including enhanced worker safety and improved efficiency, significant barriers persist, such as high costs, technological readiness, and fears of labor replacement. The findings suggest that teleoperation has the potential to diversify the workforce by making construction roles more accessible to underrepresented groups. The study concludes with practical recommendations for stakeholders, including developing inclusive teleoperation systems, fostering industrywide collaboration, and advancing diversity and inclusion to encourage widespread adoption and create a safer, more efficient, and inclusive construction environment.

Serious injuries and fatalities (SIFs) continue to plague the construction industry. The preponderance of evidence suggests that preventing SIFs requires the identification, assessment, and control of hazardous energy. In this study, we isolated and measured the impact of energy-based safety training on the quality of prejob safety briefs and the presence of direct controls during subsequent work. We conducted a standardized training intervention in both English and Spanish and tested it via a multiple baseline experiment on 10 construction crews working in the US and Canada. Dependent variables were measured using a prejob safety brief quality scoring rubric and the High-Energy Control Assessment (HECA) protocol. The training caused immediate and significant improvements in the quality of prejob safety briefs and a measurable but smaller effect on the HECA score. Whereas prejob safety meeting scores and effect sizes were consistent, HECA was highly variable across the work crews both before and after the training. This suggests that, although short-term impacts on the quality of safety planning may occur over a short time frame, the impacts on the control of hazardous energy may require comparatively more time and data to achieve conclusive results. Methodologically, this study demonstrates an experimental protocol for isolating and attributing the impact of a safety intervention over short periods. Such a protocol may be used in practice to draw casual inferences, and is a step toward the ability to objectively measure the return on safety investment.

Abstract

Crane operations are common in the construction industry when handling bulky and heavy materials. This study investigated the risk perception of prospective workers on typical risk scenarios regarding crane operations to identify their degree and cognitive dimensions of risk perception and knowledge of the respective situations. The risk perception of 189 university students of engineering-related program majors was evaluated using an online survey featuring 10 crane operation risk scenarios presented via animation videos and a pairwise comparison approach. The results revealed a commendable ability among prospective workers to assess the crane operation risk scenarios. They notably identified unsafe loading and improper rigging as the scenarios posing the highest risks. Furthermore, the analysis uncovered two fundamental dimensions shaping their risk perception: subjective misoperation and hazard nature. These insights are invaluable for designing training programs to minimize crane-related accidents among novice workers. The primary contributions of this study are to provide empirical evidence about prospective workers’ degree and cognitive dimensions of risk perception and knowledge of the crane operation risk scenarios. The findings reveal large gaps in the safety education and training provided to engineering management professionals. The large gaps underscore the urgent need to enhance educational programs and training initiatives to equip future construction managers with the knowledge and skills necessary for effective risk assessment and mitigation. By addressing these gaps, construction accidents can be reduced, and a safe working environment can be promoted within the construction industry.

Practical Applications

First, the findings can inform safety educators and trainers about specific misconceptions or gaps in risk perception among prospective workers. This information enables the creation of tailored virtual reality (VR)-based training programs, enhancing the effectiveness of safety education for crane operations. Second, construction companies can refine their risk assessment methodologies by understanding the cognitive dimensions shaping risk perception. This understanding ensures that the probability of human error and the nature of hazards are adequately considered in safety planning. Third, construction safety managers and officers can use insights from this study to improve communication with prospective workers regarding crane operation risks. Emphasizing scenarios that are perceived as lower risk but are actually high risk can help correct underestimations and promote an accurate understanding of workplace hazards. Fourth, based on the differences in risk perception between genders and academic majors, two targeted strategies for enhancing safety training can be proposed. Future safety training programs could incorporate gender-sensitive educational materials that address unique concerns or risk perceptions identified during the research. For instance, training for female workers might emphasize the risks of crane standing or supporting conditions due to the female perceiving these two scenarios as less risky compared with their counterparts.

Offsite construction (OSC) and building information modeling (BIM) integration offer significant benefits but also present challenges requiring structured guidelines. Currently, there is a lack of a multilevel integration framework to address these challenges. This study develops a framework focused on integration challenges, using literature reviews, surveys, case studies, and validation through a focus group. Findings reveal that challenges vary across the project life cycle and maturity levels, with collaboration among stakeholders being crucial to mitigating these challenges. The framework aims to enhance the integration process by identifying and addressing challenges related to maturity levels and the project life cycle, ultimately improving the efficiency and effectiveness of OSC and BIM integration practices. By providing stakeholders with the essential tools to address complexities, the framework enhances integration effectiveness across the entire project life cycle. The emphasize on stakeholder collaboration underscores the importance of collective efforts in overcoming integration challenges, contributing to the success of construction projects. This study’s limitations include its focus on New Zealand construction projects, a sample size of 116 participants, and the relatively low levels of BIM and OSC experience among respondents. Further research is needed to validate the framework with larger and more diverse samples, and additional case studies are recommended to broaden the findings.