Journal of Construction Engineering and Management

Understanding and assessing the value of building systems to stakeholders and the impacts of decision making on this value has become a national imperative. However, there is still a lack of understanding and formalized modeling of what different stakeholders value (e.g., energy conservation, safety, economic growth) in buildings and how to valuate (i.e., quantify the worth) buildings based on these values. This paper proposes an axiology-based valuation modeling approach. Axiology is a theory of value (worth) that explores questions such as what are the objects that we value and how to measure their value. The paper focuses on presenting an axiology-based mathematical value quantification and aggregation model for quantifying the worth of a building object based on object properties and stakeholder values. The proposed model is theoretically grounded in formal axiology. It builds on two key notions in Hartman’s formal axiology. First, object valuation depends on its properties. Second, valuation has systemic, extrinsic, and intrinsic dimensions. The model was validated through predictive validation, which measures the correlation between actual stakeholder rankings of valuated objects and model-predicted rankings. The results of the validation show that there is a very strong and significant positive correlation between the two types of rankings, which indicates that the proposed valuation model is valid. The proposed model contributes to the body of knowledge by offering a way to assess the value of building objects based on stakeholder values; it could facilitate value-sensitive decision making by embodying stakeholder values in project planning and design toward better synergy between human values and the built environment.

The occurrence of accidents at construction sites has negative effects on labor productivity. Conversely, the implementation of good safety management practices (SMPs) can increase productivity. Thus, to enhance productivity, it is essential to assess the implementation levels of safety practices and analyze their effects on productivity. This study aims to develop novel models for assessing the implementation levels of SMPs and for the prediction of labor productivity in multistory building projects. Data regarding safety management practices, projects’ start dates, and projects’ completion dates were collected from 39 multistory building projects across Melbourne, Australia. The quantitative data were analyzed and a scoring tool to measure, plan, and monitor the safety practices influencing the productivity of construction projects was developed. Further, linear and logistic regression models were developed to predict labor productivity when a score of SMPs is determined. By integrating the models and the scoring tool, a user-friendly instrument for assessing the impact of SMPs on the productivity performance of a building project was developed. This study contributes to the body of knowledge by providing tool and models that aid construction project managers to make appropriate decisions regarding the implementation levels of the safety practices influencing building projects’ productivity.

Highway project delivery is a disruption-prone process in which resilience is essential to project success, because different project stages experience disruptions and struggle to reach desired project outcomes. A process to assess resilience in project delivery is necessary to be able to evaluate how a project may respond to disruptive events during the planning, design, and construction phases. Many practices in the literature can aid highway project delivery resilience through resistance, recovery, and adaptation. Through the use of survey data and principal component analysis (PCA), this large group of resilience practices was reduced to seven key resilience criteria for each stage of resilience. These resilience criteria form the basis for future resilience assessment of the project delivery process. The findings of this research add to the body of knowledge by providing a means to incorporate resilience assessment into highway project delivery, which eventually can improve the resiliency of completed infrastructure.

Contractors are often simultaneously subject to capital shortages and resource scarcities in construction projects, forcing them to rely on loans to offset cash deficits during project execution. However, few studies have proposed exact or heuristic methods to deal with the financed-based and resource-constrained project scheduling problem (FBRCPSP). This study aims at developing flexible heuristics for the FBRCPSP. To address the FBRCPSP, a mathematical model is first constructed to maximize a project’s profit considering financing costs, then modified serial schedule scheme (MSSGS) and modified parallel schedule scheme (MPSGS) heuristics are designed to gain a feasible project schedule and its financial plan while complying with feasibilities of the precedence relationship, resource constraints, and credit limits concurrently. Moreover, the proposed heuristics, implemented as part of a genetic algorithm (heuristics-based GA) can be applied to solve the optimization model of the FBRCPSP. In two case studies, the results showed that the heuristics-based GA adequately explored the feasible solution space so that it could obtain the best solutions near those from the integer programming (IP) technique (By optimization software CPLEX version 12.8) and outperformed the previous precedence-preserving GA in terms of solution quality and computational time. Finally, the developed heuristics can devise or update schedules and the corresponding cash flow and resource-demand profiles, helping practitioners achieve expected profits and implement project control.

The study focuses on evaluating the factors contributing to the success of external stakeholder management (SM) at the project planning stage from the perspective of developing countries. Questionnaire survey data was collected from project management practitioners in Ghana and analyzed using mean scoring, factor analysis, and fuzzy synthetic evaluation. The analysis revealed that the involvement of external stakeholders in decision-making is of topmost rank ($\mathrm{mean}=4.717$) and effective communication with external stakeholders makes the highest individual contribution ($\mathrm{weighting}=1.000$). In descending order of contribution based on index values, the seven activity groups established are involving stakeholders and ensuring mutual trust (4.666), effective communication with stakeholders (4.633), sustaining relationships with stakeholders (4.373), preliminary planning (4.006), analyzing project and stakeholder information (3.719), assessing stakeholder attributes and needs (3.675), and developing and applying effective strategies (3.610). Following, an evaluative process model (EPM), which is essentially a practice framework, was developed and demonstrated using the relative weightings of activities. The expert validation results showed that the EPM is comprehensive, objective, reliable, and appropriate for the purpose. The findings contribute to advancing stakeholder theory in construction management research in the context of developing countries. Practitioners can effectively apply, evaluate, compare, and improve the contributing activities in external SM process to inform about needed managerial decisions in projects. The findings will guide practitioners to be more externally oriented, resolve external stakeholder issues proactively, manage project more ethically and sustainably, and improve project success.

Detailed planning, sequencing, and scheduling for the installation of multiple pipe systems are greatly needed to efficiently complete a piping project with both reduced cost and duration. Conventional manual scheduling tools cannot produce optimized and robust installation schedules due to insufficient planning of the installation sequence in generating an appropriate installation schedule. This paper proposes a new approach for automating pipe installation sequence and schedule optimization using 4D building information modeling (BIM). BIM technology is used to automatically capture valuable information from 3D models to assist time-based 4D modeling. Matching rules based on the category of pipe system components are developed to automate the pairing and integration between the 3D BIM models and installation activities. Constraint analysis by sequential rules is formulated and developed to generate favorable sequence and coordination between pipe systems, and conventional simulated annealing (SA) is adapted to optimize the generated practical schedules for installation based on a formulated objective function. An illustrative example is presented to validate the developed approach, and the result shows that the proposed approach can generate a constraint-free installation sequence and an optimal schedule. Compared with conventional methods, the developed approach results in 96%–97% saving in time and enhances accuracy of generating an installation schedule.

This paper presents the findings from a study of the breakdown of project success criteria. An exploration of the evolution of studies on the success of engineering projects over decades was the basis for a project success definition proposal. Using a comprehensive literature review of success criteria for engineering projects, a list of 133 different success criteria was identified. Those criteria were analyzed to develop an integrated framework of project success criteria, describing its hierarchical decomposition. Such a breakdown structure could serve as a starting point when setting project success criteria for a specific project, because the importance of criteria will be context dependent. Practitioners or stakeholders could discuss and tailor it based on specific features of engineering projects or specific needs and interests. Generally, criteria have evolved from simple work-related factors to focusing more on the complex benefits of the projects. Such an evolving success definition has implications for further studies of project success and might contribute toward a long-term vision in which all projects will be delivered successfully.

This paper devised, implemented, and benchmarked a novel framework, named CLOI, that can generate accurate individual labelled point clusters of the most important shapes of existing industrial facilities with minimal manual effort in a generic point-level format. CLOI employs a combination of deep learning and geometric methods to segment the points into classes and individual instances. The current geometric digital twin generation from point cloud data in commercial software is a tedious, manual process. Experiments with our CLOI framework revealed that the method reliably can segment complex and incomplete point clouds of industrial facilities, yielding 82% class segmentation accuracy. Compared with the current state of practice, the proposed framework can realize estimated time-savings of 30% on average. CLOI is the first framework of its kind to have achieved geometric digital twinning for the most important objects of industrial factories. It provides the foundation for further research on the generation of semantically enriched digital twins of the built environment.

Economic changes impact the construction industry and the associated stakeholders involved in construction projects. Construction companies are not immune to economic downturns, as evidenced by the sharp decline and long recovery period associated with the Great Recession of 2007–2009. Therefore, construction companies and construction industry stakeholders need to infuse specific economic strategies into their business operations. To determine effective strategies for construction companies to consider for weathering the risks associated with economic downturns, a Delphi study methodology was employed. Three rounds were conducted with qualified construction economic and financial experts representing financial officers, certified public accountants, and sureties to collect and confirm the existence and effectiveness of economic strategies employed by construction firms during economic downturns and recessions. From the Delphi study, 40 strategies were confirmed as highly or moderately effective methods based on the consensus criteria established from the Delphi study across six categories (1) organizational and project management, (2) direct-cost, (3) overhead, (4) financial, (5) preconstruction and marketing, and (6) efficiency strategies. This study contributes to the body of knowledge by providing a roadmap of economic, managerial, and financial strategies that can be implemented by construction companies to improve their financial health during different economic cycles.

Change orders are documents that describe a specific contract amendment to the original scope of work. Historical change orders are invaluable information sources that can provide practical and proven solutions for developing new change orders from similar cases. However, current change order management systems are not efficient in searching for and finding the most related and similar change orders due to inherent weaknesses in current archiving and search processes, such as keyword-based or reason code–based search. This study proposes and develops a natural language processing (NLP)–driven model that can significantly improve the accuracy and reliability of searching cases by restructuring how each change order’s information is stored and retrieved in change order management systems. The NLP-driven model proposed in this study can automatically detect change reasons and altered work items through text representation pattern analysis and training. The proposed model applies semantic frames to define essential semantic components and determines syntactic features for text representation pattern analysis. The model also utilizes a conditional random field (CRF) classifier, which can consider contexts in sequential texts at the model training stage. The proposed model can significantly improve the accuracy and relevancy of the search process to find the most similar cases by allowing context-driven classification, archiving, and retrieval of change orders.

Construction incentivization (CI) is a collective term that covers the range of incentive schemes that are commonly used in construction projects. Typically, either a carrot or a stick is used as the motivator for the contracting parties to commit to the attainment of certain quantitative outcome targets in regard to costs, scheduling, quality, and safety terms. The working of most CI is thus based on extrinsic motivation. It is proposed that CIs can also engender intrinsic motivation that is more enduring for performance enhancement. This study advocates that the use of CI can be extended beyond the conventional use for project performance improvement. Restoring fairness perception and bridging the equity gap (EG) are also necessary for CI planning. In this study, the equity gap in construction contracting means the disparities and asymmetry between contractual parties in terms of information, risks, power, and expected return. This study advocates that the equity gap is a minefield of opportunism, a source of dispute, and a barrier against collaboration. Thus, addressing the equity gap would provide intrinsic motivation for project performance. This study pioneers the use of CI to bridge the equity gap in construction contracting. A conceptual framework is proposed based on equity theory to analyze the functions of CI at bridging EGs and enhancing project performance. Using the data collected from 142 senior project professionals and partial least-squares structural equation modeling (PLS-SEM) analysis, the validity of the conceptual framework is statistically supported. Equitable contracting has long been recognized as one of the pillars of collaborative working. Moreover, one-sided contracts are commonly used. Prospect theory suggests that the perception of unfairness induces opportunism practices. This study addresses a practical issue of enabling the ex post alleviation of an equity gap created ex ante. It is proposed that CI can be used as a flexible tool to address the equity gap and thereby raise the intrinsic motivation to perform.

Getting a better understanding of the policy effectiveness and efficiency is a promising topic for encouraging the green-building initiative in the architecture, engineering, and construction industry. This study introduces a framework for assessing and improving the green-building policies concerning the effectiveness with “structural consistency” of policy instruments and the efficiency with “behavioral coherence” of interagency collaborative networks and examined it with China’s green-building policies from 2002 to 2019. This framework, using content mining and social network analysis, not merely provides a comprehensive approach for assessing policy performance of green-building initiative, but also contributes to integrating, comparing, and benchmarking the sustainability-transition studies from various industries and countries. The empirical evidence from China brings novel understandings to the policy-makers of emerging markets for the structural deficiencies in information services, international collaboration, and tax incentives, the three-stage roadmap of the green-building initiative, and the importance of policy agenda. This study contributes not only to the green-building literature by offering a systematic and referential framework for assessing policy performance but also to the architecture, engineering, and construction (AEC) community by guiding the improvement of green-building policies in emerging markets.

Retaining employees is a challenge in the construction industry. The purpose of this study is to understand how employees’ career outlook affects their turnover intention in the construction industry as it can have a significant impact on long-term construction project management. Using the time-lagged two-wave data collected from construction industry employees in Lahore, Pakistan, during Covid-19, we tested the impact of negative career shocks caused by unexpected events and human factors on employees’ intention to stay or leave through the underlying mechanism of career satisfaction. We also tested the moderating role of career adaptability to buffer the negative effects of career shocks on career satisfaction. The results revealed that career satisfaction mediates the relationship between career shocks and turnover intention. A slope analysis disclosed the moderating role of career adaptability, illustrating that an employee’s career satisfaction would be enhanced with a higher level of adaptability toward career shocks. We discussed both theoretical and practical implications for construction employees’ career outlook specifically and managing employee turnover for the construction industry broadly.

Public and private organizations are distinct in terms of ownership structure and stakeholders because they approach project management processes and structures differently. Thus, it is likely that they operate project oversight structures such as a project management office (PMO) differently and focus on a diverse set of functions. This study is dedicated to investigating PMO functions in these two cohorts of organizations to highlight their functional contrast through a quantitative survey in the Australian construction industry. The sample includes PMO units in high-performing organizations delivering successful projects in the construction industry. A literature review was conducted to identify possible functions followed by an empirical survey to solicit expert comments on the importance of each function. The results of an independent-samples $t$-test revealed a significant difference in the importance of three functions including (1) benchmarking best practices, (2) project management compliance, and (3) project governance, which indicate a distinction between the underpinning role that PMOs play in the public and private sectors. Following this test, the relative importance index (RII) was calculated to compare the importance level of functions and rank them across two sets of public and private organizations. The unique value that this work contributes to the construction engineering and management global community includes (1) exploring similarities and differences of PMO practice in the public and private sectors and (2) revealing the most important PMO functions in high-performing organizations, which can be applied to enhance the chance of PMO success. The findings address a research gap in the literature and contribute to the extant body of knowledge on how to configure effective PMOs in the construction context.

The psychological contract of safety (PCS) can be understood as the beliefs of employees regarding the reciprocal safety obligations between themselves and their supervisors. Although research has established that PCS is critical to safety management in construction sites, there is limited evidence on how PCS affects construction workers’ safety behavior, including compliance and participation. Building upon the psychological contract theory and social exchange theory, this study investigates the mediating mechanisms that link PCS to safety compliance and safety participation, that is, felt safety responsibility and safety-specific trust in supervisors. Overall, 389 valid data points from multiple sources comprising construction workers and their supervisors from 15 construction projects were collected. The results reveal that felt safety responsibility and safety-specific trust in supervisors partially mediate the relationships between PCS and both safety compliance and safety participation. The findings extend the safety behavior literature by clarifying the two distinct PCS processes toward safety behavior. Interventions should target improving employees’ perception of PCS to support their engagement in safety behavior.

This study examined the determinants of COVID-19-related safety behavior (SB) on construction sites in Nigeria. Specifically, the effect of perceived COVID-19 safety risk (PCSR) on SB, the interacting (moderating) effect of firm size (FS) on the relationship between PCSR and SB, and the mechanism through which PCSR leads to SB through the firm’s safety climate (SC) were examined for a sample of 312 construction site workers in Nigeria. The partial least squares structural equation modeling technique was used to analyze the data. The results indicate that PCSR has no significant effect on SB. SC fully mediated the effect of PCSR on SB, while FS moderated the relationship between PCSR and SB, with a stronger effect observed for small firms. It is recommended that a deliberate effort should be made to inculcate a change in the behavior of workers in small firms because of the inverse relationship between PCSR and SB in such firms. This study’s findings contribute to the existing body of knowledge by equipping construction project managers and engineers with much-required information to create a good SC aimed at fostering an acceptable level of SB among construction workers in order to reduce the spread of COVID-19 on construction sites. The study also advances the academic literature on health and safety performance in the construction sector, particularly during pandemics such as COVID-19.

Cranes are one of the most critical and expensive pieces of construction industry equipment requiring intense safety considerations. Lifting crews should attempt to develop an effective lift plan to improve the operation’s safety and reduce the risks of potential accidents. Although various systems are developed to enhance lifting operations’ safety, most cannot evaluate the entire lifting process in an interactive visual environment. This paper contributes to the body of knowledge by presenting a crane simulator system developed in the virtual reality (VR) environment integrated with a database of comprehensive lift studies and a detailed crane path planning system. This interactive system evaluates the lift operation quantitatively in real time in terms of its safety and practicability for the entire operation (entire lift path). The developed system can be employed in practice by crane operators and lift engineers for various objectives, including gaining hands-on experience before the actual operation, enhancing engineered lift planning, increasing workplace awareness, and evaluating and mitigating lift-related risks. The proposed framework is validated through two scenarios in a modular construction project in Alberta, Canada.

Previous studies argued that gender bias has an effect on the retention of female students in male-dominated academic programs. This study examined the prevalence of gender bias in construction education programs from different sources and the impact on students’ self-concept. Participants responded to a quantitative survey measuring gender bias, construction education self-concept, supportiveness of peers, and group identity. Results indicated that 87% of female students experienced gender bias in the previous year, which emanated significantly more often from male peers than from female peers, mentors or advisors, or professors. Gender bias had a direct impact on students’ self-concept, as did group identity. These findings suggest that interventions attempting to curtail gender bias in construction education programs should focus on male peers as their primary target and professors as a secondary target. Strategies to build group identity likely will improve students’ self-concept. This study contributes to the body of knowledge by exploring gender bias in construction degree programs and the impact of these experiences on student’s self-concept, and by providing evidence-based recommendations for fostering the inclusion of women in construction-related academic programs.

The immediate cause of construction accidents is attributed to human error. However, few studies have investigated the relationship between individual internal factors and unsafe behaviors in construction sites. This study aimed to develop and test a model to understand the mechanism of unsafe behaviors based on individual characteristics and the Theory of Planned Behavior (TPB) constructs. To test the hypotheses, structural equation modeling, and hierarchical regression analysis were utilized. A total of 191 workers were evaluated in five construction sites to explore the effects of each internal factor. The findings showed that the TPB constructs fully mediated the relationship between individual background characteristics and unsafe behaviors. Furthermore, the analysis of the moderating effects of the variable of habits showed that the inverse relationship between safety attitude and unsafe behaviors was stronger when there was a high level of safety habits. This study also found that safety attitude and safety habits were the best predictors for the behaviors of the workers. The findings of this study provide deeper insights for both researchers and practitioners by identifying how internal factors influence the behavior to prevent the workers’ unsafe behaviors.

Repeated exposure to hazards in road construction work zones often generates worker habituation to risks associated with those hazards, a key causal factor in workplace accidents. Understanding the developmental process of risk habituation and providing effective intervention are thus critical to preventing fatalities in road construction work zones. To this end, this study investigates the efficacy of virtual reality (VR) as a behavioral intervention tool to mitigate a decline in vigilant behaviors with habituation to workplace hazards. A VR environment that simulates road construction/maintenance tasks was created and used to repeatedly expose participants to struck-by hazards in road construction operations. An accident was simulated upon the emergence of inattentiveness to hazards within the VR environment. The sustained intervention effect was examined using pretest-posttest analyses to compare the frequency and threshold of participants’ vigilant behaviors. The results revealed that the VR environment elicited a reduction in attentiveness associated with risk habituation over a relatively short period of time, and the simulated accidents in the VR environment generated sustained impacts in the mitigating of the effects of habituation on attention over a week’s time interval. The outcomes of this study contribute to the understanding of how workers’ risk habituation can be measured in a VR environment and provide new knowledge regarding how a VR-based behavioral intervention can mitigate the attentional consequences of habituation to repeatedly exposed workplace hazards.

A case study was conducted on 44 residential homes using both traditional house wrap and ZIP System systems to measure the overall airtightness and compare estimated energy usages. The labor, material, and overhead and profit (O&P) costs were analyzed and used to determine the optimal choice for long-term benefits in terms of cost and performance. The impact of insulation installation is considered a key factor in improving the strategy of reducing energy consumption. Improved installation practices can affect the airtightness of common wall assemblies to reduce the building energy performance gaps and provide insight on how to allocate resources better. A framework was developed to analyze operational costs and building energy performance to address how installation quality is a factor in the return of investment in building construction for heating and cooling systems within the thermal envelope. With this methodology, aggressive energy performance goals will be met while balancing the tradeoff between installation techniques and building systems efficiency based on the introduced probabilistic investment return (PIR) metric.

Benchmarking the energy efficiency of buildings is important for optimizing the efficient use of energy and reducing carbon footprint. Healthcare facilities have especially high energy usage, but the historical difficulty of collecting energy data from a relatively large number of healthcare facilities has made it challenging to develop the appropriate benchmarking system. In this paper, we seek to foster the task of benchmarking the energy efficiency of healthcare facilities using three different methods: multiple linear regression (MLR), generalized additive model (GAM), and energy performance index (EPI). The analysis was applied using a unique dataset that contained information on energy consumption and various building features for 22 large-size public hospitals managed by the Shanghai hospital development center (SHDC). Findings suggest that different benchmarking methods yield substantially different energy performance ranking results. Furthermore, a comparative analysis of the three benchmarking methods was conducted in terms of goodness-of-fit, consistency, and robustness. The results show that MLR tends to be the most consistent and robust benchmarking model, while GAM appears to have the best goodness-of-fit. The proposed methodology can assist hospital managers identify potential improvements for more efficient use of energy in healthcare facilities.

Planning lift activities of mobile cranes for a modular project can raise productivity and improve safety. An optimized lift plan is essential for multiple lifts due to high rental cost of heavy lift cranes. However, choosing among a large number of available lift options (e.g., types, configurations, and locations of cranes) to develop multilift plans can be challenging. Despite numerous efforts in this area, there is still room for improvement to enhance the optimality of solutions, which leads to considerable cost reduction. This paper introduces an integrated framework to automatically generate an optimum lift plan based on a predetermined lifting sequence. Dijkstra’s search algorithm is utilized in the current study to select each module’s optimum lift option. This study contributes to the body of knowledge by proposing an enhanced graph-based optimization algorithm for multiple concurrent heavy lift operations. The suggested framework is validated successfully in an actual modular construction project in Alberta, Canada. The results are also compared with the previously developed lift planning algorithms, showing a remarkable reduction in the project’s total cost.

The importance of understanding individuals’ psychology when studying interorganizational trust has been increasingly acknowledged by researchers in the construction industry. However, few studies have purposely examined the individual’s psychological process in trust development between contracting parties. This research investigated how individuals make inferences about the counterparty’s trustworthiness from the party’s cooperative behaviors. A dual-attribution model of trust development was developed based on the attribution theory and the dual-process theory. Seven hypotheses were proposed and tested. Data collected from 310 practitioners through a questionnaire survey were analyzed with hierarchical multiple regression and Sobel Test. The results suggest that the counterparty’s relational behaviors—which are cooperative behaviors outside of contractual enforcement—will trigger individuals’ dispositional attribution, resulting in positive expectations for their counterparty’s trustworthiness. Reduced conflict perception and aroused affection contribute to the attribution process, analytically and intuitively. Both the theoretical model and the empirical evidence will provide support for contracting parties to develop relational trust in construction projects.

Integrated project delivery (IPD) was originally developed to overcome the challenges associated with increased project complexity, high fragmentation levels of the construction industry, and inadequate interoperability among the different stakeholders. Despite its documented benefits on project performance, IPD adoption is still witnessing a slow uptake in the US. Recent research studies have tied such slow adoption—in part—to the lack of contractual understanding and implementation of IPD. This paper addresses this critical research need. To this end, the authors used an interdependent research methodology consisting of (1) selection of IPD agreements; (2) identification of the main contractual IPD issues of concern that may lead to conflicts, claims, and/or disputes between the contracting parties through analysis of seven various IPD case study projects; and (3) reviewing and analyzing the contractual provisions, relevant to the identified IPD issues of concern, under the most pertinent national IPD standard forms of contracts. It is worth noting that in order to assure the scientific rigor of this research, the authors consulted throughout all methodological steps and verified research outcomes with the construction group of a leading legal firm. Results show that the major areas of concern in relation to contractual management of IPD processes include risks and incentives; liabilities and indemnification; suspension and termination; insurance; data sharing; and, dispute resolution. This study contributes to the body of knowledge by providing (1) a comparative analysis showing how these issues have been tackled under leading IPD standard forms of contracts; and (2) contractual guidelines to promote better understanding of effective and efficient IPD practices. As such, this research offers substantial practical implications through furnishing insightful information about causes of disputes in IPD agreements as well as how the most popular IPD contracts in the US handle them, and finally, checklist questions to serve as a reference for the contracting parties in negotiating the terms governing their IPD projects. Ultimately, this research should better support changing the contracting culture to better enable and facilitate broader and wider adoption of IPD practices in the US.

Given the heightened imperatives for supply chain resilience (SCR) in industrialized construction (IC) in Hong Kong, this study modeled the dynamic impact of supply chain vulnerabilities (SCVs) and supply chain capabilities (SCCs) on IC supply chains. The data collected through expert surveys, interviews, and case studies were analyzed using social network analysis (SNA) and system dynamics modeling (SDM) to develop the research models. Onsite assembly was identified as the most vulnerable supply chain phase, and anticipation as the most influential capability. Further, the use of an interoperable smart software package and other suggested strategies were shown to enhance IC’s resilient capabilities. As key practical contributions, these findings provide evidence-based insights for adopting well-focused performance-enhancing measures to achieve SCR in IC. Moreover, this is the first initiative to explore the potential applications of SDM and SNA to assess IC supply chain dynamics, targeting a goal of enhanced resilience. This study, therefore, contributes substantially to the IC and SCR knowledge domains. Findings should also motivate and provide insights for scholars pursuing similar industry-specific improvements in other jurisdictions.