Journal of Management in Engineering

Contracts can serve three functions—Control, Coordination, and Adaptation—to mitigate different risks. This multifunctional perspective based on the development of contract theory has been introduced in construction industries to analyze how general conditions of contracts deal with risks. However, the particular conditions of contracts present specific requirements closely related to projects, which can generate additional risks for both parties. To fill in the gap, this study analyzes nine particular conditions from nine projects with good performance respectively based on the Fédération Internationale Des Ingénieurs-Conseils (FIDIC) 1999 Silver Book and explores what aspects good particular conditions focus more on to avert risks when modifying the general conditions. We built machine learning–based classification models to conduct a content analysis of complete contracts (containing both general conditions and particular conditions) to measure the functions of contracts. The optimal model was proved to be acceptable and then used for efficiently coding more particular conditions of the FIDIC 1999 Silver Book. The results indicate that good particular conditions roughly follow the functional distribution of general conditions and no significant difference is found in functional distribution between a whole complete contract and its underlying general conditions. It also suggests minor revisions should be made to the Adaptation function, and particular conditions should concentrate more on explicitly illustrating both parties’ obligations and tasks prudently to mitigate potential risks. These findings can practically assist contract managers to analyze particular conditions and identify the potential risks.

Abstract

Real project experiences show that project actual risk cost is usually higher than expected. A significant reason for that overrun could be that the overall expected risk cost ($E{R}_c$) is often calculated using only the deterministic expected value method (EV), i.e., the sum of the products of probability times the cost for each risk event. This article analyzes the reliability of the so-calculated $E{R}_c$ value by comparing the $E{R}_c$ to results obtained with the Monte Carlo simulation, using thousands of random analytical models and models from 271 real projects. This article addresses the theoretical basis of the EV method and the influence of the number of risk events, their correlation, and their statistical distribution. It proves that common project risk models do not meet the premises required to use the EV method and that this method, when used alone, often results in an underestimation of the $E{R}_c$; project risk cost could actually be up to three times higher. This article proposes the application of an enlargement factor to the deterministic $E{R}_c$ to improve its level of certainty, and provides a formula obtained with multivariate regression analysis to calculate it.

Practical Applications

Project cost overrun is a fact in project management and a risk assessment is usually conducted to prevent it. The total expected cost of the risk events identified is used as a contingency sum to cover for risks that occur, and many companies calculate it as the sum of the products of probability times the cost for each risk event. This contingency sum affects project profitability and, if it is wrongly calculated, the related decision-making process could also be wrong. This article proves that this calculation method increases the chances of an unacceptable overrun in common projects and risk scenarios because it yields just an average that will overrun 50% of the time, and real values could easily be even three times higher. This simplified method should not be used for this purpose in common projects and risk scenarios. A more sophisticated method, such as the Monte Carlo simulation, could be used instead, but many companies do not have the knowledge and skills they require. For that reason, this article proposes the application of an enlargement factor to that sum to improve its level of certainty and provides a formula to calculate it.

Construction logistics centers (CLCs) are gaining increasing interest among academics and practitioners as an alternative method for managing material deliveries in congested urban centers with increasing environmental challenges. Because of their novelty and limited implementation, there is a lack of studies that address CLCs’ environmental impact, particularly concerning materials transportation in the construction phase. Thus, this paper aims to evaluate the contribution of CLCs to emissions from materials transportation. It compares emissions from material transportation in a residential project that consists of 111 condos in the greater region of Paris following a standard design widely used and replicated by the industrial partner when CLCs are used and when they are not. In this comparison, we use actual data collected from a finished project where a CLC was used and historical data from previous projects with identical architectural and engineering designs. In both scenarios, the assessment process included collecting material quantities, trades information, suppliers, and vehicle characteristics to generate the number of deliveries and compute the traveled distances. That information is then used to assess the environmental impact using COPERT, a software that assesses vehicles’ emissions in Europe. The study shows that using CLCs, while all other factors remain the same, can reduce 9%, 12%, 10%, 18%, 19%, and 9% of carbon dioxide (${\mathrm{CO}}_2$), Particulate matter 2.5 (PM 2.5), Particulate matter (PM 10), carbon monoxide (CO), nitrogen oxides (${\mathrm{NO}}_x$), and volatile organic compound (VOC) emissions, respectively. However, (1) the dependence on assumptions and historical data to assess the conventional construction emissions, (2) the limited number of traders who transported their materials through the CLC, and (3) the reliance on only one completed project to evaluate the CLC’s environmental performance make the results inconclusive and suggest further investigation. This work advances knowledge concerning construction transportation’s environmental performance and provides management researchers and practitioners with an approach to examine the environmental potentials of deliveries’ consolidation.

Given the dynamic and complex nature of a construction site, the ability to recognize hazards in a surrounding environment is highly associated with worker safety. While many studies have examined the hazard identification skills of workers, researchers have not yet explored how the dynamic nature of hazards impacts workers’ hazard anticipation, hazard identification, and cognitive perception of hazards within dynamic construction scenarios. This study investigates (1) whether hazard characteristics (i.e., static versus dynamic) impact workers’ hazard identification performance; and (2) how two cognitive steps (i.e., attention and perception) influence hazard identification performance for these dynamic hazards. Employing state-of-the-art 360° video panoramas, this study performed an empirical investigation experiment to assess 30 construction workers’ hazard identification skills and corresponding attention and perception behaviors. The results of this study indicate that worker’s hazard identification abilities are affected by the static and/or dynamic nature of hazards: Generally, workers better anticipate dynamic hazards thanks to target and context anticipatory cues. In addition, a major discriminator between workers with higher hazard identification skills and those with lower hazard identification skills for dynamic hazards manifested in their continuous awareness of hazardous situations and proper prediction of emerging or potential hazards. Beyond identifying these factors, this study discusses multiple reasons underpinning attentional failures and misperception. The study highlights the importance of applying an integrated personalized training program to address cognitive failures and hazard anticipation skills to improve occupational safety in the construction industry.

Public–private partnerships (PPPs) have been accused of importing practices and norms from the private sector that could conflict with core public values (e.g., accountability, transparency, responsiveness, responsibility, and quality). Some scholars believe that PPP renegotiations can enhance public values through ex post adaptation, interference, and monitoring, while others emphasize that PPP renegotiations incentivize opportunistic behaviors on the part of governments and other stakeholders. Focusing on China’s PPPs, this study investigates how the renegotiation of PPP projects impacts public values in infrastructure service delivery through a Delphi survey. Two rounds of Delphi survey questionnaires were conducted with 14 PPP experts in China. The result shows that, in general, renegotiations can safeguard or even strengthen public values in PPPs, although sometimes at the expense of managerial values. Government-led renegotiations are more likely to increase public values than contractor-led renegotiations. This study contributes to the extant literature on PPPs by shifting research concerns from managerial values to public values, and from ex ante planning to ex post renegotiation. Practitioners can derive benefits from renegotiations by paying attention to their positive impact on public values.

A system dynamics (SD) model was developed to identify the best road strategies for network-level maintenance and rehabilitation, considering technical, environmental, and economic grounds. This SD model uses triangulated research methods and data [e.g., interviews, policy analyses, and the VIZIR Pavement Distress Assessment Method (VPDAM)] to determine and allocate maintenance budgets in specific environmental and operational conditions. The system is tested via a case study at the Tunisian Radès Road Port (RRP). Baseline analyses of the simulation show the networked effects of key factors, including increased greenhouse gas (GHG) emissions, rehabilitation deficits, and climate change with reduced average pavement life. The SD model is calibrated and validated using data from RRP rehabilitation operations from 2020 until 2040. The model is coupled with an optimization module that recommends three optimal pavement solutions for the RRP and three pavement management systems (PMS) policies for improved sustainability. The model is based on sound technical principles, enhancing road function, sustainability, and cost savings. These findings contribute to the literature in PMS, SD modeling, sustainable development, and engineering management.

Managing effective apprentice programs is central to addressing the challenges posed by an aging workforce and skill shortages in the construction industry. However, the appeal of construction apprentice programs has declined among the youth. Research showed that young workers could face higher occupational health and safety (OHS) risks in the construction industry, which could be perceived as barriers to attracting and retaining them in construction apprentice programs. Curtailing OHS risks is therefore imperative to sustaining apprentice programs. However, there is limited evidence on vulnerable trades, predominant incident mechanisms, and injury types concerning OHS risk for apprentices. Workers’ compensation data related to construction apprentices between 2008 and 2019 (12 years), were empirically analyzed. Despite the overconcern, the incident proportion of 7% for construction apprentices was lower than their representation of 11% in the workforce. Thirteen fatalities have occurred for the period, and predominant mechanisms were vehicle incidents, electrocution, and fall from a height. Additionally, a range of musculoskeletal diseases due to muscular stress was responsible for permanent incapacities among apprentices. Apprentices who trained as carpenters, electricians, plumbers, bricklayers, and structural steel workers were more vulnerable to fatalities and permanent incapacities. The findings offer practical insights for a focused and optimized OHS management scheme for regaining and improving the appeal of construction apprentice programs. Although the findings and the insights drawn thereof are specific to Australia, these may also apply to other countries where construction apprentice programs are similar.

Informal learning plays a major role in how knowledge, experience, and skills in off-site construction penetrate on-site and off-site processes. Although prior research has indicated that informal learning relies heavily on team members’ embeddedness in advice networks, how and when advice network embeddedness affects the effectiveness of informal learning remain largely unexplored. Drawing on the opportunity–motivation–ability framework, a theoretical model was developed to examine the link between intra- and interteam advice network embeddedness (bonding and bridging) and team members’ informal learning effectiveness in off-site construction projects settings, as well as the joint moderating effect of knowledge acquisition motivation and absorptive capacity. The data analysis was based on survey responses from 263 individuals from 14 teams in 5 off-site construction projects using a mixed approach of social network analysis and hierarchical regression analysis. The results indicate that both bonding and bridging are positively related to team members’ informal learning effectiveness in acquiring off-site construction knowledge. This main effect is positively moderated by controlled motivation and absorptive capacity. The interaction between bonding and bridging is found to positively affect the effectiveness of informal learning. However, autonomous motivation did not significantly moderate the relationship between bridging and informal learning effectiveness. The three-way interaction model effectively explains the effectiveness of informal learning. Knowledge acquisition motivation and absorptive capacity play substitutable and complementary roles in moderating the main effect of bonding and bridging, respectively. This study underlines the need for interteam and interdisciplinary knowledge interaction and improved absorptive capacity if off-site construction knowledge acquisition is to increase, dynamics which may not be as significant in construction using mature technologies. This study enriches the body of knowledge of informal learning effectiveness in project teams from a network embeddedness lens, thereby providing managerial implications for improving team members’ knowledge, experience, and skills to adapt to the modern method of construction.

Given the potential high-stress work environments in civil engineering and construction, many industry stakeholders are recognizing employee well-being as a critical component of improved safety compliance and productivity. Employee resilience is an important protective factor for mental health that can assist employees as they navigate workplace stressors. Accurately measuring resilience in university students can help educators understand how to better equip future civil engineering and construction professionals with tools they need to handle the high demands of practice. The Resilience at University (RAU) scale has been developed for students in higher education; however, validation has yet to occur within a graduate student sample and in the United States. To help address this shortcoming, validation of the RAU scale was conducted using confirmatory factor analysis (CFA) with a sample of graduate civil engineering and building construction students from the United States. Analysis identified a 15-item multidimensional measure of resilience comprising five factors: managing stress, maintaining perspective, building networks, staying healthy, and finding your calling. The results indicate evidence of discriminant validity for the RAU with a graduate student population. This research is a first step toward understanding resilience measurement in graduate students with implications for educators who want to support the well-being of future industry professionals in civil engineering, construction, and academia.

What is a successful public–private partnership (P3)? The existing literature has continued to explore critical success factors (CSFs), key performance indicators (KPIs), and P3 drivers that are linked to P3 performance and outcomes, but some fundamental variations remain in the use of such factors and metrics to assess P3s. Studies have characterized CSFs as the “ingredients” necessary for P3 success and KPIs as the “metrics” to evaluate P3 outcomes or performance. As work in the area has progressed, the literature has evolved to consider CSFs and KPIs more holistically by broadening the factors considered to encompass social, political, economic, and financial categories. These areas in the literature are rather distinct, yet CSFs and KPIs sometimes serve as substitutes for one another, because the definition of and classification between CSFs and KPIs lack clarity. To address this issue, this work characterizes and synthesizes the literature on CSFs and KPIs to identify how to employ these factors and metrics to assess various aspects of P3 performance in transportation projects. CSFs identified were grouped into six categories such as project planning and environment and lifecycle perspectives, while KPIs were combined into four categories such as project delivery and socioeconomic. This work updates prior literature reviews, which is an important contribution because papers addressing CSFs and KPIs in P3s have increased in the last several years. Additionally, the distinction between CSFs and KPIs is clarified, and knowledge gaps such as the relationships between CSFs and future areas of research are presented.

The decision-making situations of the construction workforce have been drastically altered since the outbreak of the Coronavirus 2019 (COVID-19) pandemic. The new situation, where decision-makers strive to promptly respond to the unprecedented crisis to sustain essential construction operations without compromising the safety and health of workers, implies the presence of an availability heuristic. An availability heuristic has the potential to bring unconscious, systematic errors to the decision-making process. This study creates a decision-making experiment to empirically examine the presence of an availability heuristic and the effectiveness of a corresponding mitigation strategy in construction workforce decision-making under COVID-19 uncertainties. The experiment was conducted among students in the construction program from April 2021 to May 2021. Results show that students tend to support the management improvement ideas that fall into their most familiar fields. Providing information on other options against the option with the easiest recalled instances has been proven effective in terms of reducing the presence of the heuristic. Moreover, the results show that the presence of the heuristic is robust and unspecific to the level of education and years of work experience. The primary contributions of this research are (1) identifying the presence of the availability heuristic in construction workforce decision-making under COVID-19 uncertainties, (2) testing the effectiveness of a mitigation strategy against the availability heuristic, (3) bridging the rational decision-making with actual choices, (4) introducing the approach of decision-making experiments for future studies in construction engineering and management (CEM), and (5) suggesting an integrated perspective taking advantage of both positivism and constructivism for CEM decision-making. It is anticipated that policy makers can benefit from this study by enhancing the understanding of construction workforce decision-making amid a pandemic. This enhanced understanding can help to design effective strategies to promote the normal operation of the essential construction industry and ensure the safety and health of approximately 7.6 million employees in the construction industry during the COVID-19 pandemic and similar crises in the future.

Building effective and resilient emergency response networks (ERNs) is essential for the rapid recovery of interrupted infrastructure during extreme events. Aiming at providing critical benchmarking and implementable strategies for improving ERN resilience, this study proposed a novel framework to systematically quantify ERN resilience through an enhanced metanetwork analysis (MNA)–based approach. This framework first applied the MNA approach to conceptualize the complex emergency response as three-stage “agent-task-resource-knowledge” (A-T-R-K) metanetworks, representing connections among stakeholders, response tasks, emergency resources, and professional knowledge. Then, suitable metanetwork measures (i.e., natural connectivity, average speed, overall task completion, and the integrative metric of task resource and knowledge needs and task resource and knowledge waste) generated accordingly were used to quantify ERN resilience capacities—robustness, rapidity, resourcefulness, and redundancy. This proposed framework was validated through a case study of the emergency response to the Manchester Arena attack in the United Kingdom. The dynamic change of ERN resilience over time as well as possible causes within the case scenario were analyzed. Additionally, resilience improvement strategies and the advantages of the MNA approach are discussed. Overall, this enhanced MNA-based framework promotes an understanding of emergency response performance through systematically conceptualizing the complex ERN structure and dynamically quantifying ERN resilience capacities. Lessons learned from historical disasters provide decision-makers with implementable support to advance their collaboration and knowledge sharing and optimize resources and tasks for enhancing resilience in future infrastructure operation and emergency response activities.

Complex by nature, infrastructure megaprojects rarely meet stakeholders’ expectations. A key characteristic of such complexity is the interdependence among different project stakeholders (e.g., contractors) where disruption of one contractor’s work may instigate (system-level) systemic risks, resulting in poor key performance indicators (KPIs) of the whole project. Attributed to the lack of appropriate analysis and quantification tools, managing the systemic risks resulting from such interdependence remains challenging. The current study fills this knowledge gap through proactive systemic risk management (i.e., early identification, analysis, mitigation, and continuous monitoring). The study enhanced and operationalized a previously developed conceptual framework, in which interdependence was quantified through employing complex network theoretic measures. Specifically, the current study correlated contractor interdependence to project KPIs in order to assess associated project systemic risks. Subsequently, a metaheuristic optimization technique was employed to reorganize the project’s schedule—effectively managing interdependence-induced risks. To demonstrate the utility of the developed methodology, a power infrastructure project was considered. Finally, the study provides valuable insights to improve the performance of complex infrastructure projects through proactive systemic risk management, ultimately enhancing the overall project’s hyper resilience (i.e., to interdependence-induced disruptions).

There is extensive literature on top managers committing wrongdoing, but few studies examine white-collar wrongdoing. Drawing on the experiences of a professional service firm, we examine why and how engineering consultants normalize wrongdoing. Leveraging bounded rationality theory, we find that organizational myopia promotes inadequate administrative systems that hold consultants prisoner to their rules and procedures, leading to normalized wrongdoing. Our theoretical contributions are threefold: (1) we contribute to the literature on wrongdoing, presenting the relation between organizational myopia and normalized wrongdoing, (2) we contribute to the administrative systems literature, showing their link with poor project performance, and (3) we show how administrative systems and normalized wrongdoing play a role in project scope creep. We introduce an iceberg model to show that the failed project (the tip of the iceberg) is due to organizational myopia and inefficient administrative systems that need to be addressed before starting any project.

Collusive bidding is regarded as one of the most socially harmful, anticompetitive, and illegal practices in the construction sector. Bid-rigging, which is a form of collusion, refers to the process in which several bidders illegally form a consortium to fix the winner of the bid. Bid-rigging, also referred to as collusive tendering, occurs when two or more competitors agree they will not compete genuinely with each other for tenders, allowing one of the cartel members to win the tender. Bid-rigging results in economic harm to the owner that is seeking the bids, and to the public. An analysis of economic harm due to bid-rigging is intended to demonstrate that the realized price in bid-rigging is an overestimate of the price that bids would have fetched in the absence of collusion. However, in civil antitrust litigation concerning bid-rigging, proof of injury-in-fact and damages have often been the most troublesome elements. Thus, simulating competitive bidding is essential in bid-rigging damages estimation, because the amount of overcharge suffered requires an estimate of what the winning bids would have been if true competitive bidding had occurred. However, simulation models for forecasting the damages due to bid-rigging, especially in design–bid–build (DBB) contracts in the construction management literature, are very scarce. In this paper, a statistical simulation model is proposed for predicting the damage due to bid-rigging in DBB contracts, based on decision-making theory. This empirical study suggests that, for projects with rigged bids, the model simulates competitive bids that are close to the actual competitive bidding environment. The model is validated with an actual bid-rigging case collected from the Korean construction industry. The empirical evidence collected in this study on the possible damages due to bid-rigging provides valuable insight into the challenges faced by the construction industry. The study’s result expands upon competitive bidding theory by developing a process to simulate what the optimal bidding strategy would be in the absence of collusion, to predict the damage due to bid-rigging in DBB construction contracts.

The construction industry is stressful and concerns for workers’ psychological well-being (PWB) are on the rise with the high prevalence of mental health problems. However, there is currently no clear framework or system in the mainstream construction literature to guide management practices such as allocating resources, optimizing work systems, and supporting worker well-being. In this study, a state-of-the-art review was conducted on PWB constructs and the associated theoretical perspectives. This review of theories and dimensions aims to provide a more complete account of the factors associated with PWB and provide more systemic guidance for organizations. Drawing on a three-dimensional taxonomy of PWB in social science literature, this study identified five themes of PWB antecedents in the construction community: motivational, relational, working environment, personal attributes, and social cognitive. Findings in this study could contribute to both PWB theory development and management practices. Theoretically, this review introduced more clarity to PWB theories in the construction literature, linking different dimensions of PWB constructs with their antecedents. This also allows for identifying future research avenues to expand the boundaries of the existing body of knowledge. Practically, management practices are offered to support management, policy makers, and decision makers to optimize and improve health and well-being strategies in the construction industry.

Digital fabrication is growing in adoption within the architecture, engineering, and construction industry. Because digital fabrication often requires a systematic rethinking of the design process, research emphasizes new understanding is needed for digital systems across multiple areas, including technical development, technological systems, organizational contexts, contractual provisions, and business models. Despite the importance of a system view, the current body of knowledge does not yet provide a consistent identification nor a comprehensive evaluation of factors and their complex interdependencies with one another. To fill this knowledge gap, this work categorizes and identifies the industry needs and perceived benefits under five areas. Next, the authors conducted a questionnaire survey, which received effective responses from 114 industry stakeholders. The authors analyzed the responses using Rao–Scott chi-squared tests of independence to identify 70 pairs of correlated categories. This work further investigates the variables’ correlations using heat map visualization. Two variable-correlation mappings are presented as follows: (1) a multiaspect mapping of 292 variable correlations under 10 categories of the industry needs of fabrication information and aspects in design modeling, review, and documentation; and (2) a single-aspect mapping of 26 correlations regarding the industry needs for various benefits of digital systems to adopt digital fabrication. Thereby, this work proposes seven strategy propositions to achieve the benefits of digital systems when adopting digital fabrication in design. The consistent identification of the needs and their interdependencies constitute an integral part of knowledge in construction management.

Abstract

This paper presents a framework for the semiautomated development of textual requirements for the building construction industry, a domain in which quality of textual requirements has a direct bearing on the avoidance of unnecessary project losses and failures. The proposed framework is novel in three respects. First, it employs a combination of natural language processing (NLP) and template matching to restrict the range of ways in which textual requirements can be stated. Second, knowledge-based models work hand-in-hand with the NLP and templates to help designers fill in the details of a model that might be missing. Third, we envision the proposed approach being part of a multidomain semantic modeling and reasoning framework that includes the building construction domain and its connections to processes for project management and governance. To demonstrate the potential of the proposed approach to the practical development and construction of building systems, we developed a prototype software tool—the framework for linking ontology objects and textual requirements (FLOOR)—and procedures for the validation of individual textual requirements and groups of textual requirements related to construction tasks.

Practical Applications

This paper presents a new methodology and a prototype software framework for the semiautomated development and validation of textual requirements for the building construction industry. The work is novel in three respects: (1) it combines a natural language processing tool with a sentence-and-template matching technique to limit the ways in which textual requirements can be stated; (2) it employs a multidomain semantic modeling and reasoning framework to provide coverage in the range of textual requirements that can be handled; and (3) it employs a multidomain semantic modeling and reasoning framework that can work with individual requirements and groups of textual requirements. During the early phases of project development, these three factors work together to improve the quality of textual requirements, which in turn leads to improved levels of communication in construction management and avoidance of unnecessary project delays and failures.

Curtain wall construction has become increasingly popular. Activities on the critical path, engineered materials with long lead times, and involvement of various stakeholders such as architects, façade consultants, structural engineers, general contractors, and subcontractors are the key features of curtain wall construction. Therefore, to successfully construct a curtain wall, integrated coordination based on a common understanding among them is critical because misunderstandings and conflicts caused by differences in perception among different participants can hinder effective collaboration and communication. The purpose of this study is to identify the major problems in curtain wall construction and investigate whether there exist perception differences regarding the problems among the stakeholders executing the curtain wall construction. Based on a thorough literature review and content analysis with the qualitative data collected from interviews with industry experts, 40 problems related to curtain wall construction were identified. A total of 116 responses were collected from the survey developed to address these problems. Based on the results of a descriptive statistical analysis, it is observed that actual measurement after frame construction and quality and design changes caused by the lowest bid are the two major issues of curtain wall construction. In addition, for the 20 major problems identified from the descriptive statistical analysis, analysis of variance tests were conducted to determine whether there existed differences in the perception of each stakeholder on these issues. A total of 14 out of the 20 problems showed statistically significant perception differences regarding the problems of curtain wall construction. These perception differences were particularly noticeable for the subcontractor and architecture supervisor. Two main contributions of this study, identification of major problems in curtain wall construction and verification of the perception differences between stakeholders with respect to the problems, should help practitioners establish plans to improve the construction process and justify creating more efficient circumstances for curtain wall construction.

There are many studies that focus on Prevention through Design (PtD) for construction workers and developing formalized PtD processes for construction projects. However, few studies have aimed at developing a formalized PtD process for mechanical/electrical/plumbing (MEP) worker safety. A formal process for implementing PtD for MEP worker safety is badly needed because MEP work onsite and during operation and maintenance (O&M) can lead to injury and death. To address this knowledge gap, our research team aimed to create a formalized PtD process for MEP safety and developed case studies that detail how the process can be implemented in the field. The formalized process and case studies would then be used in an implementation guide created specifically for the industry. This project was completed through expert interviews, six case studies, and ongoing discussion and review by an Industry Advisory Council. Using these methods, the team identified factors for implementation success and developed a formalized PtD process specific to the MEP worker context. The process consists of five phases: (1) hazard identification, (2) risk assessment, (3) design review, (4) implementation, and (5) learning. We anticipate that this study will contribute to the field of PtD research through creating one of the first formalized PtD processes for MEP construction and O&M worker safety, and through a cross-case analysis of the six PtD cases that indicated not only the importance of stakeholder engagement and cross-disciplinary dialogue, but that effective PtD implementation can occur even outside of a collaborative project delivery context at any point during design and construction.