Journal of Construction Engineering and Management

Given the dynamic and complex nature of a construction jobsite, workers’ safety is significantly connected to both their ability to efficiently scan their surrounding environment and their ability to anticipate and identify potentially hazardous sources in a timely manner. However, existing studies have failed to consider the spatial-temporal characteristics of high-risk construction hazards as well as the limited training available for enhancing workers’ hazard anticipation. Accordingly, this study (1) examines the impact of dynamic hazards’ spatiotemporal characteristics on construction workers’ hazard identification and anticipation performance, and (2) proposes and illustrates a new methodological approach that harnesses cue perception timing to assemble a coherent cognitive model of situational awareness. To achieve these objectives, this study combines subjective survey measurements with such technologies as 360° video panoramas and wearable psychophysiological sensors to examine 30 construction workers’ hazard search strategies, timely hazard identification performance, and spatial attentional distribution. The results of this study demonstrate that workers’ hazard anticipation abilities are differentially influenced by both spatial and temporal characteristics of dynamic hazards: (1) most workers failed to distribute their spatial attention across the 360° construction environment and missed hazards outside their field of view (behind or overhead), highlighting the importance of attentional orienting; (2) most workers failed to identify emerging hazard cues that would enable anticipating latent hazards; and (3) many workers failed to develop a correct situational awareness framework because they had improper cue-perception timing. The findings of this study highlight the importance of considering the unique spatiotemporal characteristics of dynamic hazards to properly predict workers’ true hazard anticipation abilities. Furthermore, the findings of this study are expected to provide valuable insight into developing effective safety training strategies to enhance workers’ situational awareness.

Although digitalization has become a prospect that is counted on for many problems in the construction industry, there have been limited attempts at exploring decision-making processes in construction firms concerning the integration of digital technologies and impacts beyond the projects. In this research, the system dynamics (SD) approach was proposed to investigate digitalization as a strategic decision considering the inherent relationships between project company and business levels. The SD model was conceptualized, formulated, and tested by conducting a demonstrative case study within a modular construction company. Conforming to the strategic priorities of the case company, business process engineering principles were adopted to model the existing practices and assess the impacts of implementing digital technologies such as building information modeling (BIM), enterprise resource planning (ERP), and radio frequency identification (RFID) at different maturity levels. The simulation tests revealed that the impacts of technologies are influenced by the internal dynamics of projects and company competencies as well as external uncertainties. The SD model has the potential to improve strategic decision-making by anticipating the causalities and feedback between the decisions and consequences of technology integration. The findings and model development steps proposed in this paper can be used by other companies that aim to make process improvements with digital technologies as well as researchers exploring the implications of digitalization in construction considering competencies and uncertainties.

Collaboration in design decision-making is a critical factor in enhancing the quality of built environments. However, several factors, such as the lack of clarity in the negotiation process, the diverse disciplinary backgrounds of stakeholders, and conformity bias, pose significant challenges, rendering the collaboration in built environment design time-consuming. To overcome these challenges and improve the efficiency of collaborative design, a novel solution that introduces a consensus model enhanced by virtual reality (VR) is proposed in this paper. The proposed model implements a structured decision-making process to foster fact-based discussions and minimize conflicts arising from personal biases. It ensures equal influence among all stakeholders, prevents the dominance of any single viewpoint, and offers personalized recommendations to guide stakeholders toward group consensus while respecting their initial preferences. The study leverages VR techniques to enhance communication and comprehension during design negotiations. The VR collaboration platform provides a robust visualization and user-friendly interface, empowering stakeholders to understand the decision-making process better and iteratively refine their preferences for optimal user satisfaction. By integrating VR, the burden traditionally placed on a moderator in group decision-making (GDM) is reduced, resulting in a more streamlined and efficient collaborative process. Additionally, stakeholders can conveniently communicate their preferences remotely through cloud services within the immersive VR collaboration environment, further enhancing the overall design collaboration experience. To the best knowledge of the authors, this study is the first attempt to combine a consensus model with VR to create a comprehensive solution that supports stakeholders in achieving consensus design solutions in the early design stage. This study contributes to the advancement of knowledge in the field of design collaboration by exploring the potential benefits of a VR-enhanced consensus model for GDM.

Abstract

Maintaining the interorganizational relationship is a vital goal in the construction industry, and how to promote relational behavior in the project has received widespread attention. A contract is one of the commonly used control mechanisms in project management. Due to the contradictory conclusions of existing research, there is a lack of explicit guidance and detailed elaboration on how a contract impacts relational behavior. According to regulatory focus theory, this paper examines how different dimensions of contractual complexity affect motivation for different relational behaviors. This research decomposes contractual complexity as control, coordination, and adaptation from a functional perspective, classes regulatory focus into prevention focus and promotion focus and differentiates relational behavior as flexibility, information exchange, and solidarity. By conducting a questionnaire survey, the results reveal that the paths of three contractual functions on relational behavior and the mediating roles of prevention and promotion focus differ. Specifically, contractual control directly affects three dimensions of relational behavior, contractual coordination increases information exchange by triggering a prevention focus, and contractual adaptation enhances flexibility, information exchange, and solidarity by evoking a promotion focus and also directly enhances solidarity. These findings explain the motivation of behaviors in interorganizational relationships from the perspective of social psychology and offer new insights into how to cultivate relational behavior and the linkage between contractual and relational governance in construction projects.

Practical Applications

This study is helpful for construction practitioners in developing a nuanced understanding of interorganizational cooperation from the view of ex ante contract design and social psychology. Project managers need to allocate their resources properly, focus on different aspects of contract design and shape different regulatory focuses to foster specific relational behavior. First, drawing up a detailed contract is costly, and construction practitioners can choose what to focus on when resources and efforts are limited. On the premise that the contract is adequate to reduce the possibility of opportunism, practitioners should spend time and effort infusing flexibility into a contract by affording guidance on uncertain matters. Second, when executing a construction project, if contractual complexity has been established, it is also possible to promote relational behavior by adjusting the regulatory focus of the parties. Project managers should pay attention to the psychological state of both parties in the construction project, since situational triggers can evoke changes in the psychological state of the parties, which in turn affects the motivation for behavior.

Considering the benefits of using robots in the manufacturing and automobile sectors, robots are currently being developed for the construction industry; however, the rate of adopting robots in this industry is still in its nascent stage. As robots are introduced to project sites, safety, productivity, ease of use, level of robot autonomy, etc. become important parameters for wide-scale adoption; however, research that analyzes the point of view of construction industry stakeholders on adopting robots, to our best knowledge, is still limited. Identifying the expectations and perceptions of different stakeholders about robotic technology is crucial to ensuring the effective utilization the human–robot teams on project sites. This research aimed to study and compare stakeholders’ perceptions, levels of trust, and comfort levels in using different robotic technologies on their project sites. Based on these perceptions, this research developed a decision-making framework that will guide industry stakeholders in understanding what steps need to be followed while deciding to robotize a particular task. The research used a questionnaire to collect relevant data from various construction industry stakeholders. The results suggest that these stakeholders have a positive attitude toward the adoption of robots, with drones and layout robots receiving the most favorable response. The top factors that drive robot adoption include a robot’s ability to save time by reducing rework and the ability to help in monitoring and quality control. However, factors such as high costs and lack of a skilled workforce were identified as barriers to robot adoption. This research contributes to the body of knowledge concerning how different stakeholders in the construction industry perceive the utilization of robots in the construction sector.

Sharing of risks and rewards is considered to be one of the key benefits and principles of integrated project delivery (IPD). Despite its importance, risk–reward strategies are not implemented widely in IPD construction projects due to the lack of a well-defined basis for establishing adequate allocation plans. This paper fills this knowledge gap. This research followed a multistep methodology. First, the authors calculated the risk control valuations of all potential combinations of coalitions for IPD stakeholders. This was performed using interrelated steps of risk identification and quantification, risk assignment based on associated contractual analysis, establishment of a coordination network, and Monte Carlo simulation. Second, the authors adopted cooperative game theoretic solutions—including Shapely, Owen, and Myerson partition-graph restricted game values—to allocate risk–reward shares for three IPD relational structures. Third, for each IPD relational structure, the authors evaluated the stability and associated negotiation power of coalitions for the IPD stakeholders using the propensity-to-disrupt ratio. Ultimately, the outcomes of this study show that having a multiparty agreement, in which all stakeholders—the owner, designer, contractor, and subcontractor—have open communication channels, creates the most balanced coalition. In this case, all stakeholders have equal willingness to cooperate in the project. Furthermore, as the engagement of the subcontractor in the IPD coalition decreases, the liability and contribution of the contractor increase in terms of project risk control. The latter emphasizes the importance of the technical capabilities of the contractor in the case of restricted subcontractor’s engagement in the project. This research contributes to the body of knowledge by offering a basis for negotiation among various IPD stakeholders in terms of the degree of the subcontractor’s engagement on the one hand and the proportionate share of each stakeholder on the other hand.

The concept of intelligent building is emerging in the contemporary built environment. Intelligent buildings aim to leverage digital technologies and information throughout the building’s life cycle (design, construction, and operation phases) to improve the building’s performance and value. In recent years, academic scholars and industry practitioners have made efforts to articulate the intelligent building concept and identify its components. However, there is still no commonly accepted definition for the term intelligent (or smart) building. Furthermore, the term is used interchangeably with similar terms such as sustainable building and high-performance building. The primary gaps in research are the lack of a holistic and clearly defined list of intelligent building components. This gap limits building stakeholders’ abilities to decide which technologies to implement in their buildings, prove its capabilities and advantages, and improve its performance. In response to the identified gaps, this research conceptualizes intelligent building in comparison with the concept of sustainable building. We identified the key components that each concept entails and conducted a comparative analysis of the identified components. The findings of this research include a categorization of intelligent building’s definitions which helps to conceptualize intelligent building and distinguish it from other similar concepts. In addition, the research team used the developed ontologies for intelligent and sustainable buildings to provide a fundamental overview of the structure of building evaluation systems and their different approaches for determining evaluation criteria. Overall, this study contributes to the body of knowledge by identifying and classifying components of intelligent buildings, which is a prerequisite for intelligent buildings’ evaluation. It also makes a distinction between the concepts of intelligent building and sustainable building in order to determine their context and applications.

Advancements in sensor technology, artificial intelligence (AI), and augmented reality (AR) have unlocked opportunities across various domains. AR and large language models like GPT have witnessed substantial progress and increasingly are being employed in diverse fields. One such promising application is in operations and maintenance (O&M). O&M tasks often involve complex procedures and sequences that can be challenging to memorize and execute correctly, particularly for novices or in high-stress situations. By combining the advantages of superimposing virtual objects onto the physical world and generating human-like text using GPT, we can revolutionize O&M operations. This study introduces a system that combines AR, optical character recognition (OCR), and the GPT language model to optimize user performance while offering trustworthy interactions and alleviating workload in O&M tasks. This system provides an interactive virtual environment controlled by the Unity game engine, facilitating a seamless interaction between virtual and physical realities. A case study ($N=30$) was conducted to illustrate the findings and answer the research questions. The Multidimensional Measurement of Trust (MDMT) was applied to understand the complexity of trust engagement with such a human-like system. The results indicate that users can complete similarly challenging tasks in less time using our proposed AR and AI system. Moreover, the collected data also suggest a reduction in cognitive load when executing the same operations using the AR and AI system. A divergence of trust was observed concerning capability and ethical dimensions.

The construction industry is vulnerable to heat-related hazards, necessitating identification of high-risk areas and contributing factors. This study introduces a novel framework that integrates microclimate simulations with geometric modeling, focusing on the often-underestimated role of heat radiation in assessing heat-related hazards in construction environments. By analyzing 2 years of meteorological data from a construction site in College Station, Texas, this research uncovers the inadequacies of the heat index (HI), a widely recognized thermal-physiological model in the US construction sector. Compared with the wet bulb globe temperature (WBGT), the HI displayed notable variations. Specifically, out of 1,719 data points labeled as danger by HI, WBGT recategorized them as low risk ($n=62$), moderate risk ($n=\mathrm{1,264}$), high risk ($n=300$), and extreme risk ($n=93$). These discrepancies are predominantly associated with the influence of heat radiation. Furthermore, this study emphasizes the importance of accounting for the spatially varying nature of heat radiation in construction environments, influenced by factors such as adjacent structure height, surface materials, and shading patterns. The research highlights the need for monitoring site-specific heat radiation and its potential impact on workers’ health and safety. Overall, the findings contribute to our understanding of heat-related hazards in construction and offer valuable insights for developing more effective heat-related safety management strategies.

Construction competitive bidding has been studied by many researchers; however, their focus was mainly on certain bidding aspects. Thus, despite their value, existing bidding models have limited applicability for various reasons including the noninclusion of some real-life factors that impact bidding-related decisions. As such, there is a need for identifying a comprehensive list of bidding factors that impact construction bidding–related decisions, studying their associations, and identifying understudied factors to direct future research efforts. This paper fills this knowledge gap. First, the authors conducted a systematic selection of 124 construction bidding–related articles published within the past 40 years. Second, the authors identified a list of 43 bidding factors from the contractor’s perspective and divided them into four groups (project, bidding environment, economy, and company) based on their characteristics and relevance. Thereafter, the authors implemented cluster analysis and social network analysis (SNA) to quantitatively analyze the level of inclusion, co-occurrence, and interconnectivity among the bidding factors and identify the gaps in the literature. Results of cluster analysis revealed that previous studies focused mainly on company-related factors, while economy-related factors were the least studied. Also, SNA outcomes highlighted that experience in similar project and availability and costs of rental labor/equipment/material are the most studied factors in theoretical discussions, while number of competitors and size of the project are the most investigated factors in developed models. Consequently, this paper identified understudied bidding factors, including company reputation level in the market, bidding method, bidding stages, and contractor’s risk attitude. Thus, this paper contributes to the body of knowledge by promoting a comprehensive understanding of bidding-related factors and providing a road map for incorporating critical understudied bidding-related factors. This would minimize redundancies and maximize the effectiveness of future bidding-related research. Ultimately, this should provide better decision-making for all associated stakeholders.

Abstract

Worker shortages and poor performance are perennial problems in the construction industry. The literature suggests that increasing workforce diversity and inclusion is one of the solutions to counter such problems. Because the construction industry is a labor-intensive industry dominated by one particular gender, enhancing workforce diversity and inclusion is imperative. Therefore, this study explores various strategies for fostering gender inclusion in the construction industry. Initially, 29 gender-inclusion attributes were identified for construction workers through a literature review. The opinions on the impact of these attributes on the gender inclusion of female and transgender workers were collected from 76 and 30 respondents, respectively, through a questionnaire survey. Using inferential statistics, the essential, desirable, and context-dependent attributes were established from the identified attributes for female and transgender workers. The essential attributes included workplace safety and career progression for female workers; diversity training and antidiscrimination policies for transgender workers; and inclusion at the top management level and commitment from top management for both groups of workers. The findings will provide practitioners and human resource professionals with a framework to formulate strategies to enhance the inclusion of workers in construction sites. Although the study presented a framework of gender inclusion of workers, it does not differentiate between various levels of workers (unskilled, semiskilled, and skilled), nor does it present the relative weight of the attributes contributing to inclusion.

Practical Applications

Diversity and inclusion practices are gaining traction in the current scenario. This is substantiated globally by socially driven sustainable development goals formulated by the United Nations. Practitioners understand diversity and inclusion benefits in the form of higher performance output of the organization. However, the various strategies and actions required for enhancing workforce inclusion are dispersed across the literature. In other words, there is an absence of a framework that labor-intensive industries like the construction industry can follow and enhance diversity and inclusion. This study provides a framework in the form of a list of essential, desirable, and context-dependent attributes for enhancing diversity and inclusion of women and transgender workers in the industry. Such a classification will provide an aid to practitioners in adopting the most suitable strategies depending on their status quo, goals, and resources. Moreover, the findings of this study will have future implications for the development of an index to quantitatively measure the level of inclusion in the industry.

Schedule management is essential in construction projects to ensure successful completion. However, the dynamic nature of the construction industry introduces variability, leading to uncertainty and challenges in schedule implementation. This paper explores the use of schedule acceleration through overlapping activities as a solution to mitigate the impact of variability on project timelines. Risks associated with overlapping activities can lead to waste and offset anticipated schedule gains. To challenge the assumption that the schedule gain from activity overlapping is directly proportional to the amount of overlapping, a simulation model is developed and implemented in MATLAB where activities are modeled as beta-distributions. The model gradually increases the overlap percentage and evaluates the mean best-case, overall mean, and mean worst-case durations. An isolated overlap consisting of two activities is used to demonstrate the effect of overlapping. With a $1:1$ ratio between durations, it was found that, when using a 90% overlap, the loss in effect varied from 3.2% to 57.5% with an overall mean loss of 34.2%. These results emphasize that even in the most optimistic combination of distributions, the most likely duration still exceeds initial expectations, indicating the influence of variability on the schedule. Thus, the findings highlight the necessity of project managers to consider the impact of variability on overlapping activities, ensuring a more accurate schedule estimation. The study offers practical recommendations for project managers, including a diagram that advocates applying adjustment coefficients based on the degree of overlap and the ratio between the activity’s durations. The diagram can be adopted in future scheduling to adjust durations when applying overlapping to minimize the risk of schedule delays.

Abstract

Construction project management is typically adopted in modern civil landscapes. Owing to the significant global increase in infrastructure investments, it is crucial to analyze the success and timely completion of such public projects, among which the pavement construction project is a representative example. The aim of this study is to identify the critical success factors (CSFs) that enable the success of pavement construction. Additionally, a CSF framework is developed in this study that can be used by project management teams to monitor and control the progress of pavement construction projects effectively. To the best of our knowledge, this is the first study that acquires all pavement management-related factors to develop a framework. To ensure that all pavement management-related factors were identified and considered, the authors of this study conducted an exhaustive preliminary literature review until 2022. Based on an extensive literature review, 61 multidisciplinary factors are developed and validated in a Delphi study. A questionnaire is developed, and pilot tested through interviews. A total of 27 experts were recruited to participate in two rounds of the Delphi study, which included factors related to operations, contractor expertise, logistics, human resources, communication, finances, and bureaucracy. Reliability tests, correlations, and validations are performed, and weighted averages are obtained. The reliability and accuracy of the factors are successfully defined and tested. The findings of the study suggest focusing on the following functional areas to complete a pavement construction project successfully: (1) financial factors; (2) bureaucracy- and governance-related factors; and (3) communication-related factors. According to the experts interviewed in the Delphi study, these factors contribute the most significantly to the success of the project.

Practical Applications

This study focused on addressing the research gap in analyzing pavement construction projects from the angle of CSFs. These factors were first developed using literature, validated through a Delphi study of two rounds across panelists. The findings of the Delphi enabled the researchers to identify what factors are more relevant than others when compared to general construction and enabled the research to establish a preliminary framework on a pavement project’s lifecycle and stages during the entire project tenure. The findings of this study can help project managers and engineers to uniquely approach a pavement construction project and give it its due importance. From an academic perspective, this study has opened the doors to further testing of the proposed framework and the CSF that it has developed with respect to pavement construction. The outcome of this paper would help pavement construction professionals and researchers in the areas of project planning, resource allocation, risk mitigation, project execution, quality assurance, stakeholder communication, and continuous improvement.

Construction projects are known for their dynamic and everchanging nature, characterized by frequent adjustments and temporary durations. Consequently, workers must be aware of evolving hazards and promptly share safety-related knowledge and information with colleagues. Despite extensive prior research conducted on knowledge-sharing behavior within the construction industry, there is a lack of studies focusing on the factors that affect the safety knowledge-sharing behaviors (SKSB) of construction field workers (CFWs) who work in the most hazardous frontline positions at construction sites. Therefore, this study aims to identify the major factors influencing SKSB among CFWs and examine their relationships. To achieve this, the study adopts the theory of reasoned action as the theoretical framework supplemented by a comprehensive literature review that identifies four influential factors. A questionnaire survey involving 252 CFWs from 16 construction sites in South Korea was conducted, and the responses of 146 participants were analyzed using social network analysis and structural equation modeling. By advancing research on SKSB of CFWs and group-level construction safety management, the findings can improve safety communication among CFWs.

Crane-lift planning is critical but challenging to ensure construction safety and efficiency for the installation of heavy components. It engages a group decision-making process that involves various stakeholders to exchange knowledge of crane capabilities, site characteristics, and operational feasibility. However, conventional planning methods based on drawings, animations, and standalone virtual prototypes are inefficient in enabling collaborative decision-making due to rigid visualization and inflexible interactions among different stakeholders. This paper aims to develop a collaborative heavy lift planning (Co-HeLP) system that engages crane suppliers, site managers, and crane operators in an immersive and shared environment for crane layout optimization and lifting simulation. Specifically, the system incorporates a multiuser networking unit to enable stakeholders to design crane-lift layouts concurrently and synchronize changes in real time for facilitating information-sharing and collaborative planning. In addition, a cross-platform virtual reality (VR) unit is developed to provide stakeholders with role-tailored interactions of crane allocation and first-person operation. Automatic feasibility checking is also formulated to assist stakeholders in appraising jib reach limits and loading capacities more efficiently. The system is demonstrated using a real-life modular building project that involves the installation of multiple bulky modules. To evaluate the system, two groups of industry practitioners from crane suppliers and main contractors conducted heavy lift planning using Co-HeLP, where their responses were collected using questionnaire-based surveys and interviews. Results show that the system is rated highly on automatability ($0.77/1$), collectiveness ($0.81/1$), and applicability ($0.85/1$), with the advantages of full-scale visualization and multirole interactions. This paper opens up new possibilities for stakeholders to jointly manage crane-lift constraints and build consensus on layout plans through a mutually interactive and role-independent shared environment. More broadly, the paper derives a generic multiuser VR mechanism to address fragmented coordination and inefficient knowledge transfer, thereby facilitating collective planning and management in construction.

An essential process in earthworks is projecting effective routes for material allocation. In highway construction, haul road planning is a challenge for practitioners once there are few consolidated methodologies to rationally select existing haul routes or construct new ones. Some authors indicated geographic information system (GIS)-based methods for routing through least-cost algorithms. However, most proposed methodologies overlook the logistics related to allocations, not considering supply–demand relations in their criteria. Consequently, through a case study in Brazil, we present an earthwork optimization system that integrated established mathematical programming techniques for allocation and a GIS-based algorithm for haul road construction. In summary, we formulated a model capable of selecting different routes based on their impact on earthworks logistics cost. Thus, we built several paths between source and demand points utilizing two methods. First, based on recent literature, we used a GIS-based least-cost algorithm using the measuring attractiveness by a categorical-based evaluation technique (MACBETH) as a multicriteria support system incorporating multiple economic and environmental parameters. Second, we built routes based on Euclidian distance between the same source and demand points, analyzing if the savings in operational costs would payoff additional expenses of choosing a shorter route. After applying our methodology to the case study, we observed that the proposed procedure presented a lower budget in a reasonable processing time compared with the original project. Therefore, we inferred that the strategy of proposing path alternatives can be significantly efficient when applied to highways. Based on the results, we also found opportunities for improvement of our GIS step once it generated long paths when the distance between source and demand was short.

Accurate project duration estimation is crucial for effective scheduling, budgeting, resource allocation, and overall construction management. Leveraging historical data from completed projects is an effective strategy to achieve this. In heavy industrial projects, where scaffolding activities can span from thousands to millions of hours, refining the estimation of scaffolding time is vital during the planning phase. This study undertook the analysis of data from a completed heavy industrial scaffolding project, aiming to propose a methodology and models for predicting future projects durations. The proposed methodology not only aids in improved duration but also contributes to cost estimation, scheduling, and project delivery of similar future endeavors. Commencing with data cleaning and categorizing the data based on activity types, the scatter plots of person-hours versus task weight within each category revealed a linear relationship. Consequently, linear models for each category were developed. Statistical factors such as data size, coefficient of determination, and mean absolute error were then utilized to calculate a score for each model, guiding the model selection process which substituted low score models with a parent category with a higher score. The data analysis and modeling were performed five times to ensure robustness and consistency in the results. On average, the initial models yielded a project duration estimate of only 0.36% higher than the actual duration, while the selected models increased this deviation to 4.14%. The scoring and selection process enhances estimation accuracy while maintaining proximity to actual project durations. This research makes three significant contributions: (1) introducing a categorical linear regression approach for scaffolding activity duration prediction, (2) presenting a novel normalization and scoring method that scores models based on statistical factors, and (3) implementing a practical model selection process to substitute weaker models with stronger ones, ultimately strengthening the reliability of activity and project duration predictions.

Industrialized construction (IC) has been adopted worldwide for its potential benefits, and prefabricated construction (PC) has traditionally been considered the primary method for promoting and implementing IC. However, IC is not equivalent to PC, especially in the field of concrete buildings. Certain major Chinese companies have amassed valuable experience in on-site industrialized construction (OIC), providing new inspiration and direction for the implementation of IC. Nevertheless, OIC-related research has received very limited attention. Therefore, to deeply explore and decipher the key characteristics of OIC, this study adopts a case study method to review and analyze the OIC systems developed by four large construction and real estate companies in China. After analyzing findings from four cases, the eight key characteristics of OIC were identified: temporary factory, prefabrication, integration, standardization, modularization, mechanization, digitization and intelligence, and interspersed construction. Subsequently, compared with PC, in-depth analysis and discussion were conducted on each characteristic of OIC. Additionally, the study explored the relationship between IC, PC, OIC, and traditional cast-in-situ construction (TCC), incorporating both PC and OIC into the framework of IC. The main contribution is that the key characteristics of OIC reflect a series of strategies for achieving industrialization on construction sites, and thereby aid decision-makers in balancing the “prefabrication and cast-in-situ” or “off-site and on-site” trade-off. Furthermore, these findings enhance the understanding of OIC within both the industry and academia, enrich the theoretical knowledge body of IC, and provide valuable insights and alternative paths for countries and regions to implement IC.