Journal of Management in Engineering

Increasing rates of depression, anxiety, and suicide in the construction industry have drawn the attention of researchers to consider mental health as an integral part of health and safety. However, prior research has focused mainly on determining the sources of work stress, with a paucity of studies related to measures to improve mental health. This study aims to fill this gap by evaluating the mix of measures within an integrated approach that can be adopted to promote good mental health. Surveys were collected from 62 construction experts based in 4 countries. The data were analyzed using descriptive statistics, structural equation modeling (SEM), and a post-survey interview. SEM showed that secondary intervention measures such as those focused on healthy coping and individual resilience do not necessarily mitigate mental health stressors; it also signals the importance of including primary intervention measures in a workplace mental health intervention. These findings highlight intervention measures that could be implemented to create a psychologically healthy workplace. These measures can guide policy-making to boost job satisfaction, mental health, safety, and performance. Furthermore, these results provide a compass for building construction organizations to determine which measures are yet to be implemented in their workplaces and need to be explored.

Safe operation of cranes is essential in the construction industry to ensure continuous gains in productivity and control potential hazards to workers on construction sites. In this research, which was based on human-machine-environment (HME) system thinking, a structured crane-related accident database was developed to identify and prioritize the safety concerns of construction crane operators. In order to technically investigate risk factors from accident reports, an approach was proposed in this work integrating factor clustering and prioritization. Accordingly, the research methodology was designed to first collect crane-related accident cases and determine database variables, including accident types, contributing operational factors, and accident consequences. Second, an advanced multiple correspondence analysis (MCA) method coupled with the fuzzy logic was applied to distribute the variables into different clusters and visualize their associations. Third, once the variables were well clustered, failure mode and effect analysis (FMEA) was adopted to investigate the multiscaled structure of clustering and explore the priorities of failure modes based on current legislation, regulations, and industrial codes of practice. In summary, the proposed approach integrating clustering analysis and prioritization analysis contributes to determining essential safety concerns and their potential impacts during crane operation, generating implications for construction crane safety management and eliciting detailed managerial implementation strategies for prevention measures for crane accidents in the construction industry.

Organizations must be adept at managing the adoption of change initiatives. However, it is argued that more than half of change adoption efforts fail to reach their objectives. This study modeled the relationships between six change management strategies and three identified levels of change adoption outcomes (unsuccessful, moderately successful, and very successful). A total of 633 cases of organizational change adoption were collected from architecture, engineering, and construction (AEC) firms across the US and Canada, of which almost half of the cases represent the adoption of digital technologies. Multinomial logistic regression analyses showed that at least five change management strategies must be used effectively in combination to avoid failed change adoption outcomes. Very successful adoption cases have used two strategies (change agents and realistic timeframe) in a highly effective manner. This study contributes to the body of knowledge of management in engineering by defining three levels of change adoption outcomes and identifying the most effective change management strategies among the different levels.

Rapidly developing technologies, fast evolving business needs, and increasing competition have forced construction companies to respond to changing conditions much faster in their projects. Agile project management, which was originally developed by software engineers, takes advantage of collaborative, integrated, and productive teams composed of project participants guided by principles of trust, transparent processes, and open information sharing. It is a project management approach based on delivering project requirements incrementally through short iterations by a small, self-organized, and cross-functional team. This study aims to investigate the implementation of the agile hybrid approach in construction. In this context, a conceptual model composed of 6 constructs (drivers, barriers, enablers, inputs, process improvements, and project benefits) and 42 corresponding indicators was proposed. A questionnaire survey was designed and administered to construction professionals. The validity of the interrelations among the constructs was tested using structural equation modeling (SEM). The findings revealed a need for project performance improvement as the main driver; a lack of awareness of agile methods and practices as the major barrier; commitment and organizational learning via short feedback loops as the main enabler; an autonomous, self-organized, and multidisciplinary team as the most critical input; better response to changes as the major improvement; and enhanced project performance as the key project benefit. This research proposes an interactive agile integration framework for the construction industry that can be used to reveal primary differences in implementation across countries through the collection and analysis of data from another country. Construction companies can benefit from the recommended strategies to determine their short- and long-term strategies and incorporate agility into their project management practices.

Determining a reasonable construction time (RCT) is crucial in project planning and schedule management. Construction projects are exposed to the external environment, including rainfall, extreme temperatures, snowfall, and high wind speed, and the RCT should be evaluated considering these risks. The risks can be reflected by activity duration using nonworking days (NWDs). However, current construction planning and scheduling practices are ineffective for dealing with of NWD characteristics because working days (WDs) and NWDs are mixed in most schedule performance data used for schedule development. Activity durations estimated using historical performance data may not appropriately reflect the activity characteristics (work type, region, and work timing), leading to an unreasonable construction time for a project. Here, we propose an activity duration segmentation method (ADSM) for determining the RCT. The ADSM can evaluate the combined effects of weather factors according to work type and determine the operation rate, which depends on start date, work type, region, and activity duration. This leads to the separation of WDs and NWDs for determining the RCT. Case-based and comparative analyses were conducted to validate the proposed method. The mean absolute percentage error (MAPE), used to validate the ADSM, was 5.79%. The results of the present study show that NWDs can be determined by considering the characteristics of the various activities (e.g., sensitivities toward environmental conditions, start date) and the environmental conditions of the project (weather conditions at the project location, working hour patterns). The ADSM suggests an integrated framework for combining activity characteristics and project environmental conditions when determining NWDs of each activity. The ADSM can be used by project owners for determining the RCT or the contract time, which varies according to activity characteristics. Also, a construction scheduler can assess to what extent the construction schedule will be influenced by NWDs.

The visibility of material status information is vital to effective decision-making and improving supply chain performance. Information technologies (IT) have been developed to improve visibility through information sharing in the supply chain. However, effective use of shared information for actionable decision-making requires enablers to achieve performance gains. Despite investment in visibility, knowledge about enablers that improve effective information use for the supply chain is largely missing from the construction body of knowledge. This research identified and defined 32 enablers that support effective use of information shared using IT on industrial projects during detailed design, procurement, and construction. These enablers were identified and defined with the aid of a panel of industry experts using structured workshops and qualitative content analysis. Their definition identifies essential capabilities necessary to benefit from investments in improved visibility. Further investigation via survey was conducted to evaluate the enablers’ ability to impact projects and their frequency of competent execution on projects. The analysis of the survey responses to the enablers’ ability to impact projects validated criticality 23 of the 32 enablers used for the survey. The analysis of the frequency of competent execution responses shows that 27 of 32 enablers are competently executed less than frequently on projects, suggesting structural limits to investments in visibility. This study advances our understanding of necessary investment in capabilities or specific enablers that leverage concomitant investments in IT. As such, the study provides specific guidance to practitioners in the industrial construction supply chain and provides an expanded basis for future measurement and study by academia.

As-built building information modeling (BIM) currently is regarded as a tool with the potential to manage buildings efficiently in the operation and maintenance phases. However, as-built BIM modeling is a labor-intensive process that requires considerable cost and time in modeling existing buildings. Although active research on scan-to-BIM automation has addressed this issue, previous studies modeled only major objects such as walls, floors, and ceilings, consequently requiring modeling other objects in indoor spaces. In addition, there was a limitation in modeling objects located in the occluded areas of scanned point clouds. Therefore, this study extracted various indoor objects from a point cloud based on deep-learning, and compensated for incomplete object information from occluded point clouds for automating the process of scan-to-BIM. The number of object classes extracted from the semantic segmentation of a deep learning network was increased to 13, and spatial relationships between objects were defined to improve the accuracy of bounding boxes extracted from point clouds. Furthermore, a parametric algorithm was developed to match the bounding boxes and objects in a BIM library to generate BIM models automatically. In a case study involving an office room, the accuracy of the bounding boxes of some object classes improved by as much as 53.33%. The study verified the feasibility of the proposed method of scan-to-BIM automation for the three-dimensional (3D) reality capture of existing buildings.

Project employees suffer increasing pressures brought by uncertainty, complexity, and temporality, especially in the architecture, engineering, and construction (AEC) industry. Complicated by both need-related factors and stress-related factors, a variable-centered approach to test the main effects of stressors on employee well-being cannot detect distinct configurations that may lead to the same outcome. Combining self-determination theory (SDT) and conservation of resources theory (COR), our study investigated the configural impacts of job stressors and psychological needs on employee well-being in Chinese AEC projects. By collecting 265 questionnaires from 27 Chinese AEC projects, we conducted a fuzzy-set qualitative comparative analysis (fsQCA), and found that (1) the combination of SDT and COR provides multiple equifinal configurations sufficient to produce high or low employee well-being, and SDT is more salient than COR for the interpretation of well-being in AEC projects; (2) counterintuitively, role overload and role conflict can be contributive to employee well-being when certain psychological needs are satisfied; role ambiguity needs to be avoided for its salient threats to well-being; and (3) need for relatedness is particularly salient in all configurations for employee well-being in Chinese culture. We also found evidence for causal asymmetry for high and low well-being. Our person-centered approach yielded more theoretically consistent results than a variable-centered approach. Theoretical and practical implications were discussed.

The COVID pandemic has given rise to the necessity of social distancing regulations, which has brought the importance of workspace management on the construction site to an unprecedented level. Understanding and visualizing the interaction and tradeoff among space, time, and workforce is critical for construction managers to schedule and deliver projects on time. Therefore, the objectives of this research are to investigate how the critical path method (CPM) and Takt-time planning methods utilize space, time, and workforce differently, develop a tool to visualize the space–time–workforce interactions, and investigate the space–time–workforce tradeoff based on different managers’ preferences. This research selected a high-rise office building project and collected 889 sets of productivity data of five specialty trades. The research built a simulation model to investigate productivity and project performance under 267 scenarios of different combinations of the three resources. A dynamic tool was then developed to visualize workspace, time, and workforce interactions. Finally, a Choquet integral–based evaluation and decision tool was developed. The simulation results show that the Takt-time planning method can reduce up to 80% of workspace overlap compared with the actual production plan with less than 20% of duration extension. The contributions to the body of knowledge are (1) creating a visual framework for managers to understand the interaction and tradeoff among space, time, and workforce quickly and accurately, and (2) developing an innovative Choquet integral approach for managers to evaluate planning strategies according to project preferences. The framework and analysis method can be adapted to other construction projects to assist managers to visualize and optimize the space–time–workforce tradeoff under uncertain project drivers.

The construction industry is notorious for poor work–life balance (WLB) due to its strong culture of long working hours, nonstandard work schedules, and variable work duration. Extant construction literature highlights that the poor WLB in the industry is a work stressor that leads to a low level of organizational commitment (OC), which is a strong predictor of employee turnover and productivity. However, little attention has been paid to understanding how WLB affects OC, which could hinder construction organizations from developing targeted measures to improve OC. This study addressed this gap by using the A Shortened Stress Evaluation Tool (ASSET) model grounded in occupational stress theory to depict the underlying mechanisms of how WLB affects OC through the mediation effect psychological well-being [i.e., positive emotions (PE) and sense of purpose (SP)]. The ASSET questionnaire was used to measure the constructs via an online questionnaire survey administered to construction professionals around the globe registered with the Association for Project Management, the Chartered Institute of Building, and the Project Management Institute. A total of 255 valid responses were analyzed using structural equation modeling (SEM). Contrary to previous research, this study found that WLB does not have a direct impact on OC. Instead, it affects OC through the mediation effects of SP and PE. These results indicate that construction firms could benefit from enhancing SP and PE to yield greater organizational commitment rather than emphasizing enhanced WLB per se. This could be done by increasing employee participation in setting goals and objectives, clarifying the meaning and purpose of work, working to align work goals and objectives with employees’ sense of meaning and purpose, and generating a greater frequency of experienced positive emotions by creating work environments that satisfy the psychological needs of autonomy, competence, and relatedness.

Project-based firms (PBFs) have to sense and seize new project opportunities by dynamically adapting and reconfiguring resources and activities to survive in the fast and highly competitive business environment. Yet, it is inconclusive on how project experience alters the way of responding to the vibrant environment. Grounded on the dynamic capabilities theory, this study aims to examine how consulting firms with different project experience configures dynamic capabilities to be competitive. To do so, this study first reviews the literature on dynamic capabilities applied to project management, followed by a questionnaire survey and case studies to better comprehend how PBFs with varying project experience use their dynamic capabilities. Fuzzy-set qualitative comparative analysis (fsQCA) was employed to analyze the questionnaire-survey data. Drawing on dynamic capabilities theory, the dynamic capabilities of PBFs are conceptualized as a four dimension framework, comprising project opportunity sensing, external integrating, internal coordinating, and project-based learning. The empirical results show that PBFs with richer experience would less rely on project opportunity sensing but still have to commit to external integrating, internal coordinating, and project-based learning. This study contributes to the body of knowledge of applying the dynamic capabilities concept to project management to understand how PBFs position themselves in the fast-changing environment.

The rising price to build transport infrastructure poses a challenge to governments. Our paper analyzes a period between 2005 and 2017, during which the price of highway construction increased by 68% on average across our 40 analyzed states. We consider six potential explanations for this increase: (1) labor compensation; (2) material input prices; (3) demand for higher quality roadways; (4) market concentration; (5) urban vs. rural roadway mileage; and (6) relative spending on maintenance and rehabilitation. After testing for possible heteroskedasticity, serial correlation, and endogeneity, this paper uses fixed-effects and random-effects models to evaluate the impact of these six factors on highway construction price growth. The results show that highway construction prices are largely influenced by changes in labor and material input prices as well as shifts in demand for higher quality roadways. The analysis suggests the presence of Baumol’s cost disease, a phenomenon in which labor compensation growth outpaces productivity growth, leading to price increases. This finding implies that the price to deliver highway infrastructure will continue to rise in accordance with increases in labor compensation unless significant productivity gains are achieved in the future. The results of this work provide new evidence to explain the rising prices to build highway infrastructure.

The initiative of project managers gives organizations competitive advantages. This study investigated the role of personal resources (i.e., psychological capital) in driving such behavior. We considered the intervening mechanism of the influence of psychological capital on initiative behavior by treating work engagement as a mediator, and treating job resources (i.e., decision authority) as a reinforcing variable in this relationship. Hypotheses are proposed integrating the literature of psychological capital and the job demands–resources theory. Using a 1-month time-lag questionnaire design, data were collected from 150 project managers responsible for construction projects. It was found that psychological capital has a positive influence on project initiative behavior, and work engagement mediates this influence. Decision authority reinforces the direct influence of psychological capital on work engagement and its indirect influence on project initiative behavior. This research contributes to that on antecedents and formation mechanisms of project initiative behavior and brings new insight to the job demands–resources theory by confirming the reinforcing interaction between psychological capital and decision authority.

An inspection is a crucial construction process that ensures that building works and workers comply with prescribed codes, standards, and building progress. The traditional inspection is characterized by physical effort and onerous paperwork. The emergence of e-inspection 1.0 has meant the adoption of computerized means to ease the paperwork burden, although physical onsite presence has remained mandatory. However, the COVID-19 pandemic has made the dispatch of inspectors difficult and has prompted governments worldwide to explore alternative inspection approaches that harness the latest information antitamper and traceability technologies, such as blockchain. In this paper, we refer to these approaches as “e-inspection 2.0.” This research reports the urgent need for e-inspection 2.0 to guarantee construction quality, compliance, and progress amid pandemic conditions. Using the design science research method, it then proposes a blockchain-based solution to address authenticity and traceability concerns and facilitate e-inspection 2.0. The system is validated through a case study of a modular construction project in the Hong Kong–Pearl River Delta construction nexus. We find that rigorous technological solutions can render e-inspection 2.0 reliable. However, existing regulations are far from amenable to such inspections. Therefore, we call for an extension of the pandemic e-inspection 2.0 expediency to common practice in a post-pandemic era through the development of robust technological instruments and the amendment of inspection regulations.

As one of the emerging digital technologies, building information modeling (BIM) has been increasingly used in the architecture, engineering, and construction (AEC) industry of many countries. One of the core benefits associated with BIM is facilitating collaboration among project teams, thereby improving information sharing and project performance by providing BIM-based construction networks (BbCNs). Nevertheless, it is still challenging to ensure an effective collaboration process in BIM-enabled projects. Several studies have investigated the factors that influence collaboration in BIM-enabled projects; however, most of these studies focus on technical matters of BIM, while the perspectives of socio-organization and processes have received less attention and are still in the conceptual stage, especially for the role of people management. Thus, an exploratory study was proposed to explore how key factors influence the professionals’ willingness to collaborate in BIM-enabled projects. A total of 10 hypotheses were established based on literature review and expert verification. Following that, a questionnaire survey was administered in China to solicit the opinions of 273 BIM professionals for data collection. The hypotheses were then examined on the basis of the predictive capacity of regression analysis (binary logistic regression), with the findings validated using neural network analysis (multilayer perceptron). It was found that seven independent variables have a statistically significant influence on professionals’ willingness to collaborate in BIM-enabled projects, namely, professional knowledge, skill, training, investment, BIM tools, BIM ownership, and standards and regulations. Among them, the variable of professional knowledge was ranked as the most influential factor. While extending the existing knowledge of literature, the findings of this study also deliver insights for stakeholders by enhancing their understanding of the BIM collaboration process and its influence factors.

According to the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) guidelines, people spend about 80%–90% of their time indoors. One of the most important factors that directly affect occupant comfort is the thermal environment. In light of this, this study aimed to evaluate the viability of the proposed electroencephalography (EEG)–based circumplex model of affect for identifying interindividual differences in occupants’ emotional states in a variety of thermal environments. A total of 30 participants were involved in the predicted mean vote (PMV)–based experimental scenarios, in which an EEG-based physiological data set was gathered in real time. First, a questionnaire survey on individual perceptions of thermal comfort (i.e., thermal sensation and satisfaction) was evaluated. Second, a $k$-means clustering method was used to build the EEG-based circumplex model of affect for thermal environment, in which representative affective states in each quadrant were interpreted: (1) Quadrant 1, Happy, (2) Quadrant 2, Nervous, (3) Quadrant 3, Bored, and (4) Quadrant 4, Relaxed. Third, the results of a questionnaire survey (a subjective assessment) were interpreted similarly to those of the EEG-based circumplex model of affect for thermal environment (an objective assessment) proposed in this study. This study breaks new ground in the use of a biometric research technique in the domain of thermal environmental management in engineering. In terms of practical contribution, it is expected that applying the proposed model to forecast thermal sensation and satisfaction will aid in providing occupant-tailored automated building services that are responsive to their emotional preferences in a variety of thermal environments.

This paper explores the factors that influence male and female engineers’ intent to leave. An online questionnaire was completed by 183 female engineers and 229 male engineers. Factor analysis and structural equation modeling were used to develop models of intent to leave for male and female engineers. This study contributes to current knowledge by identifying the specific influence and inclusion factors that increase intent to leave for female engineers, and how these differ from male engineers. The findings show that an increase in access to career opportunities reduces intent to leave for both male and female engineers. This is the only similarity between the two models. Expanding the inclusion measure beyond social inclusion (belonging) to also assess how well individuals are supported to be their authentic selves, identified that for female engineers only, support to bring their authentic selves to work and developing influential relationships decreases intent to leave. For male engineers, pursuing their ideas against the odds reduces intent to leave, while being on the lookout for ways to improve one’s life and situation increases intent to leave. Therefore, organizations should ensure men and women have equal access to roles that help them upskill, are able to be their authentic selves, and can develop relationships with people of influence in the organization.

Contextual information is a crucial delimitation that needs to be considered. A review of the literature suggests the need to develop a context-based decision-making framework (DMF) to improve the quality of the decision-making process. However, retrieving the right information within a specific decision-making context is not an easy task and requires a comprehensive study. To address this need, this study focuses on developing an epistemic context-based DMF. The contextualization was carried out by thoroughly investigating the three epistemic context dimensions related to infrastructure project planning and selection processes in Indonesia. This study adopts a mixed-method approach consisting of contextual information, contextual analysis, contextual synthesis, and contextual validation. All findings were used to develop the DMF, which was validated in a realistic setting. This study is meaningful because the developed DMF can advance the project investment evaluation process by bridging the gap between infrastructure assessment constraints and epistemic context awareness. The retrieval of relevant information within a context is considered useful to configure the required setting needed in the development of a DMF, thus enhancing the relevancy and usability of the proposed DMF.

The rapid development of subway projects in China presents significant safety risks to those involved. Building on the previous empirical research that identified and classified the safety risks of these projects, the aim of this paper is to assess the safety risk management performance in Chinese subway construction projects from a multistakeholder perspective. Questionnaire surveys and semistructured interviews were conducted with three hundred and ninety-nine and eight construction professionals, respectively, who worked on subway construction projects in southeast China. The results indicate that the top five areas of safety risk management performance are related to construction plan development, management of high-risk construction works, hazard identification and communication, government-related factors, and client-related factors. In contrast, the bottom five areas of safety risk management performance are related to engineering consultant-related factors, the site’s natural environment and weather conditions, regular tests, machine calibration and maintenance, site construction schedule, and construction preparedness. The relationship between this safety risk management performance and the perceived importance of each risk factor is also reported, identifying priority areas for improvements on these projects. These findings contribute new conceptual insights to the paucity of research on the safety risk management performance of Chinese subway construction projects from a multistakeholder perspective. The results also provide new practical insights for policymakers and project managers to help them develop more effective and focused strategies to further improve the safety performance of these major projects.

Although emphasis has been placed on three-dimensional (3D) printing technology that can alleviate increasing demand and low-productivity issues in public housing developments, limited research has been conducted to examine perceptions surrounding this technology in the context of public housing projects in the built environment industry. Hence, this study aims to investigate the perceptions of practitioners working in the industry concerning the drivers, challenges, and strategies for 3D printing technology, together with the status quo of its implementation. To achieve these goals, nine drivers, eight challenges, and seven strategies were identified through a comprehensive literature review, followed by a structured questionnaire survey administered to industry practitioners. Based on the survey analyses, the top three drivers, challenges, and strategies were identified, and the differences in perceptions according to respondents and their organizational characteristics were explored. Moreover, postinterviews were carried out with several industry professionals to further substantiate the analyses results. The results serve as a starting point for the industry to reap the benefits from additive manufacturing technology throughout the project life cycle. This study contributes to the body of knowledge relating to the adoption of 3D printing technology in the industry, improving productivity in public housing projects and moving toward more sustainable and cleaner delivery processes in the built environment industry.