Journal of Construction Engineering and Management

The shortage of labor in the construction industry is quickly becoming a global phenomenon. To encourage more people to begin careers in construction, work patterns that promote both more leisure and accident rate reduction need to be put in place. This study used logistic regression to analyze 7,497 accident cases that have occurred in the Hong Kong construction industry. Principally, it was found that human factor–related accidents and work patterns are interrelated for both millennials and nonmillennials. Therefore, an adjustment in work patterns may lead to a reduction in accident rates, which could encourage more people, both young and old, to choose a career in the construction industry.

The development of a model to clarify the relationships among innovation activity ($INVACT$), collaboration level ($CL$), and technological capacity ($TC$) should contribute to better innovation management in construction companies. The main purpose of this study was to elucidate the relationships among $CL$, $TC$, and $INVACT$ in construction companies. For the purpose four regression models were developed to clarify the moderating/mediating effects of $TC$ on $INVACT$ and $CL$ in construction companies by using a moderated/mediated regression analysis. A questionnaire was used to collect data from 116 construction companies. The empirical results show that $CL$ has a significant impact on $INVACT$ which is mediated by $TC$. In contrast, the moderating effect of $CL$ with $TC$ on $INVACT$ is considerably weak. In construction companies, $CL$ has an indirect effect on $INVACT$. The proposed model serves as a starting point for better innovation-management models in construction companies. The primary contributions of this research are the development of a new moderator/mediation model for innovation management in construction, so a new theoretical framework and an emphasis that, in the construction industry, there is a strong need for new ways of thinking about innovation management.

Highway infrastructure is critical to the sustainable development of a country. Nonetheless, these capital-intensive projects, especially in build-operate-transfer (BOT) contracts, are prone to the risk of material price fluctuations during the construction phase, which may lead to project cost overruns. To surmount the effects of downside exposures, construction companies seek innovative risk management tools. The main intention of the present study is to show how the construction industry can take advantage of well-developed financial derivatives. In particular, a new methodology is presented for hedging the material price risk using the Bermudan collar option, the applicability of which is shown via a worked example. It was found that these over-the-counter (OTC) options are appropriate risk management instruments, which conforms to the characteristics of highway construction. It is also concluded that in choosing their hedging strategy, companies should have due regard to the specific size, time frame, and counterparty credit risk.

The paper develops an innovative risk evaluation methodology to address the challenges of multicriteria decision-making problem of project evaluation and selection. The methodology considers the fuzzy analytic network process (FANP) to incorporate the interdependencies of different risk factors, and failure mode and effect analysis (FMEA) to conduct the rating analysis of projects to develop the decision matrix. Finally, evaluation based on the distance from the average solution compares alternative projects and reports the optimal solution. The proposed approach allows project managers to engage in the evaluation process and to use fuzzy linguistic values in the assessment process. A case study from the construction sector is selected to verify the efficacy of the proposed approach over other popular approaches in the literature.

Construction workers are commonly subjected to ergonomic risks. Accurate ergonomic assessment is needed to reduce ergonomic risks. However, the diverse and dynamic nature of construction sites makes it difficult to collect workers posture data for ergonomic assessment without intrusiveness. Therefore, this paper proposed a joint-level vision-based ergonomic assessment tool for construction workers (JVEC) to provide automatic and detailed ergonomic assessments of construction workers based on construction videos. JVEC extracts construction workers’ skeleton data from videos with advanced deep learning methods, then Rapid Entire Body Assessment (REBA) is used to conduct the joint-level ergonomic assessment. This approach was demonstrated and tested with a laboratory experiment and an on-site experiment, which indicated the accuracy of the ergonomic risk scores (70%–96%) and its feasibility for use on construction sites. This research contributes to an accurate and nonintrusive ergonomic assessment method for construction workers. In addition, this research for the first time introduces two-dimensional (2D) video–based three-dimensional (3D) pose estimation algorithms to the construction industry, which may benefit research on construction health, safety, and productivity by providing long-term and accurate behavior data.

Since the 21st century, the international engineering contracting industry has been developing rapidly. A growing number of contractors have entered the international market to engage in various business fields, leading to changing market structures and competition. As a result, international contractors face increasing difficulty in the selection of business areas and international markets to maintain or enhance their competitiveness. This paper aims to evaluate the market concentration and competition intensity of the international engineering contracting market based on the theory of organizational ecology. Using data about the top 50 enterprises that remained on a top 250/225 international construction contractor list from 2004 to 2016, this study proposes and calculates the market concentration index (MCI) and the competitive intensity (CI) of the international engineering contracting industry. Specifically, the MCI for the selected 50 enterprises overall and the 1,250 firm pairs formed by the 50 firms were calculated respectively to assess the concentration levels of the various firms. To assess the competitive intensity of the different business areas, the CI of nine business areas, including general buildings, manufacturing, power, water supply, sewer and waste, petroleum, transportation, hazardous wastes, and telecommunications, were calculated. Subsequently, to predict how the CI of the nine business areas change in the future, various time series models were employed and the potential development trend of the nine areas was obtained. This study provides a reference to understand the market competition of the international engineering contracting industry.

Fall from roof (FFR) has been a perennial problem in the construction industry. It has been one of the leading sources of injuries and accidents in many countries. The objectives of this paper are to (1) investigate the causes of fall from roof; (2) identify control measures to roof safety that are being used in the Singapore construction industry; (3) evaluate these controls based on specific working on roof scenarios; and (4) investigate factors that influence the adoption of these solutions. Eleven semi-structured interviews were conducted with experienced practitioners in the Singapore construction industry. In addition, two focus group discussions were conducted to discuss fall protection solutions for six critical and common working on roof scenarios identified during the interviews. Results suggested that FFR accidents and injuries were caused by a combination of individual and organizational factors. Cost-effectiveness, workers competency, and site constraints are the most critical factors that differentiate solutions to specific roofing scenarios. Despite the existing solutions, it was found that some contractors are reluctant to implement appropriate solutions in their roof work due to (1) cost; (2) time pressure; (3) power imbalance; and (4) on-site constraints. Based on these findings, it was suggested that establishing a roof association would help reduce FFR accidents and injuries by addressing the following issues: (1) design working-on-roof best practices; (2) improve tendering process; and (3) develop and manage a licensing roofing worker program.

Managing complex and dynamic construction projects is challenging because it relies highly on the real-time communication and seamless coordination of numerous things and people that are spatially and temporally distributed at a massive scale. To deal with the associated challenges, various concepts, including the internet of things (IoT), cyber-physical systems (CPS), and smart construction objects (SCOs), have been explored in construction. Amid the increasing overlap and merger of principles among these three pervasive technologies, narrow definitions and isolated development of each field are no longer appropriate. Therefore, this study proposes a deployment framework that integrates IoT, CPS, and SCOs to achieve greater synergy that can expedite their holistic implementation. It adopted a mixed-methods approach with a literature review, technological analyses, case studies, and action research at the core. This deployment framework encompassed the key components of each technology (i.e., the three core properties of SCOs, the bidirectional information flow in CPS, and the extensiveness of devices and networking in IoT) in an interconnected structure while enabling the uniqueness of each technology to be evident. Example application scenarios were described to demonstrate the applicability of the proposed framework in real-life practice. This study contributes to the body of knowledge by presenting a taxonomy that clarifies the similarities and differences between IoT, CPS, and SCOs when applied to the construction industry. The integrated deployment framework can be used to guide further theoretical explorations of the synergistic effects of IoT, CPS, and SCOs, enriched with practical cases to facilitate construction project management.

The practice of subcontracting out construction work has been identified as a contributing factor in poor work health and safety (WHS) performance. Relatively few studies have considered the processes through which safety climates develop within subcontracted workgroups. This study sought to examine the relationship between intragroup communication relating to WHS and the workgroup safety climate. Data were collected from 39 subcontracted workgroups in the Australian construction industry using social network analysis to examine worker-to-worker, supervisor-to-worker, and worker-to-supervisor patterns of WHS-related communication. The relationship between group social network metrics and group safety climate were examined. Network density was a predictor of the workgroup safety climate. Furthermore, a suppressor effect was found such that WHS-related communication between group members and the group supervisor increased the variance in group safety climate explained in a regression model. The results highlight the importance of intragroup communication in creating a shared understanding about the priority placed on WHS within subcontracted construction workgroups. In using subcontracted workgroups as the unit of analysis and linking within-group communication patterns to the workgroup safety climate, the research makes an original contribution to knowledge in empirically demonstrating the safety benefits associated with fostering a dense communication network and encouraging frequent supervisor–worker communication in subcontracted workgroups.

In public–private partnerships (PPPs), aligning the goals of the public sector with those of the private contractor is usually achieved using incentives informed by agency theory. However, the success of the traditional PPP model has been contested, and recently PPPs have started focusing more on collaboration and investment sharing. So far, this development in practice has barely been reflected in the research. This paper seeks to widen the theoretical lenses on PPPs by developing a theoretical framework integrating agency theory, social capital theory, and self-determination theory. The aim is to allow for a better understanding of incentives for goal alignment by including motivational and relational aspects in addition to the transactional view. A multiple case study comprising four Norwegian PPP projects was conducted to empirically apply and further develop the framework. The findings suggest several benefits of social and psychological mechanisms to goal alignment in PPPs, including trust, reciprocity, and intrinsic motivation. Early involvement of contractors combined with risk sharing and relationship building are important factors to this end.

Modular construction projects involve concurrent manufacturing production and construction processes for constructing the main structure and the foundation, on-site installation, and finishing work. Using process-driven project scheduling, it is difficult to analyze how different issues affect the overall project schedule and determine alternative solutions based on what-if scenario analysis (WISA). This paper proposes the classification of modular building construction projects as manufacturing driven, on-site driven, or a combination to improve scheduling strategies based on a schedule-driven approach. The scheduling focus is shifted from the working precedence (manufacturing → transportation → installation) to project scales and constraint changes. A discrete-event simulation model is developed for modular construction projects, and WISA is performed in actual modular construction projects. It is noted that compared with the existing WISA method that obtains construction schedule probabilities for specific tasks sequentially and independently, scheduling-based project classification and reflection of expected events are more effective in examining and determining scheduling alternatives. The proposed scheduling strategies and simulation model can enable project managers to assess several alternative scheduling solutions based on project characteristics.

Public–private partnerships (PPPs) have emerged as a promising alternative to financing infrastructure projects in order to address the infrastructure restoration and rehabilitation challenge. However, in the current practice no unanimous agreement exists on what factors to consider when making capital structure decisions in PPP infrastructure projects. To close this gap, generalized least-squares (GLS) regression analysis was performed on data from 498 projects across 22 countries to identify the capital structure determinants. At the 10% significance level, three project-specific factors (number of sponsors, number of lenders, and contract type) and four country-specific factors (total tax rate, real interest rate, risk premium on lending, and bond market capitalization) were identified as critical. It contributes to the body of knowledge (1) by explaining the financial decision from the lender’s perspective, which complements common capital structure theories that focus on sponsors; and (2) by providing sponsors, lenders, and governments with knowledge on the primary factors that drive decisions, which in turn forms the base for effective negotiation and optimization of the capital structure in PPP infrastructure projects.

The construction industry relies heavily on the use of equipment. Equipment management for a single project is, in itself, challenging, and large contractors who want to achieve long-term success must also manage equipment at an intraorganizational level. While vast amounts of data are collected and updated dynamically to track equipment status within an organization, current practices do not consider these data during the decision-making process. Rather, companies often rely on a single metric, equipment utilization, for evaluating management performance. Inspired by the ability of social network analysis (SNA) to examine the interactions and relationships between objects, a SNA-based method for investigating equipment movement between project sites and equipment shops is proposed. This study proposes a novel performance metric, the direct dispatch index (DDI), which adds a distance weight to the clustering coefficient of SNA, to measure equipment dispatching performance from equipment logistics data. Historical equipment logistics data from the equipment and project management systems of a company in Alberta, Canada, were used to demonstrate the functionality and feasibility of the proposed approach. The methodology was found capable of evaluating the logistical effort associated with equipment dispatch and planning, thereby enhancing equipment management through improved decision-making.

The construction industry is always searching for better ways to manage construction projects and improve productivity while leaving a smaller ecological footprint. To help with this goal, a simulation model was developed in a 3D simulation modeling framework to examine the impact of successful concepts from the manufacturing industry, such as just-in-time (JIT) deliveries, Lean tools, and prefabrication in construction. The model developed was based on a real 6-story wooden building erected in the province of Quebec, Canada. Through a design of experiment, results of the simulation showed the impact of each concept and their interactions on the construction duration, shortages, and labor utilization. They also put into light the quantitative advantages and disadvantages of implementing 0%, 50%, or 100% Lean management methods, keeping between 1 and 4 days of buffer stock on the construction site, having 80% or 100% prefabrication of components, and using 1 or 2 construction teams. As a result, this paper contributes to the work of scholars and practitioners by simulating a real construction project to assess the impact of prefabrication, JIT, and Lean principles with tangible metrics, construction duration, shortages, and labor utilization.

Quality and client satisfaction is a long-established focus of attention in the construction industry due to its significant role in the success or failure of a project, yet few studies have examined the impact of a lack of quality on client satisfaction in the context of public construction projects. This study, therefore, proposes that lack of quality in construction projects has a significant impact on client satisfaction using a partial least squares structural equation modeling (PLS-SEM) technique. A conceptual model was developed for assessment of client satisfaction, and the model consisted of two main latent variables. Through the questionnaire survey, an empirical analysis was carried out to test the conceptual model. Data were collected from 484 construction experts employed in the Pakistani public construction industry. The result of the analysis found that the $R^2$ value of the model was 0.454, which revealed that lack of quality in projects has a significant impact on client satisfaction. Based on the final form of the model, the construction-related factor ($\text{beta}=0.491$) has a greater influence on client satisfaction. The goodness of fit index of the conceptual model was measured to be 0.54, which revealed that the conceptual model has appropriate reliability and validity and fits the data correctly. This study adds to the body of knowledge by offering new insights and contributes toward greater understanding of lack of quality in public projects and its impact on client satisfaction, and use of applied advance statistical method, PLS-SEM, which is previously missing in the literature. The lessons from this study would be helpful for policymakers and decision makers to focus on highlighted issues and problems faced by the public construction industry worldwide.