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Although social media has been increasingly applied and valued in the construction industry, there has been little evidence revealing the influence mechanism of social media use in the construction context. In this way, this paper aims to explore how different purposes of social media use affect project performance from a project manager's perspective.

Drawing on the mechanism–outcome–performance framework, this paper developed a research model to figure out the mechanism through which work-oriented and socialization-oriented social media use influences construction project performance. The empirical data were collected from a survey of 249 construction project managers, and the structural equation modeling technique was applied to test the proposed model.

Results indicate that both work-oriented and socialization-oriented social media use promote knowledge acquisition and project social capital, which both further positively impact the project performance. Additionally, the negative moderating role of information overload is identified on the relationship between social media use and knowledge acquisition.

This study fulfills the need for an in-depth investigation of social media use on construction project performance, contributing to the project management and social media literature. Furthermore, this study provides recommendations for project managers to advance social media applications in the construction domain.

In today's digital and post-pandemic era, construction teams can span their boundary to obtain important resources and support in computer-mediated ways. However, the benefits of computer-mediated team boundary spanning (TBS) are mostly assumed. Empirical evidence for these benefits is in lack. Thus, this study attempts to investigate the influence of computer-mediated (instant messaging in this study) TBS on construction project performance and the underlying mechanism.

From the multiteam system (MTS) perspective, this study employs the input-process-outcome (IPO) framework and coordination theory to explore the influence of instant messaging-based team boundary spanning (IMTBS) on construction project coordination processes and project performance. A theoretical model is built and validated with a survey involving 206 construction projects.

Results show that IMTBS positively affects knowledge integration and project coordination, but negatively affects project commitment. The positive link between IMTBS and project performance is attributable to knowledge integration and project coordination. Further, project commitment is also found to negatively mediate the relationship between IMTBS and construction project performance.

To the best of the authors’ knowledge, this study is the first to empirically investigate the influence of TBS on construction project performance. As such, this study contributes to the literature on TBS in the construction field. In addition, the findings of this study unveil the double-edged characteristic of IMTBS, which should attract managers' attention. This also indicates that the form of TBS is a significant determinant of its effectiveness, which should attract scholars' attention in the future.

Although social media use at work has made great impact on employee work performance, little is known about the effect of social media use at work on construction employees, especially construction managers. In this way, the purpose of this study aims to investigate the impact of social media use at work on construction managers' work performance based on the enabler-process-intermediate outcome-performance framework.

This study adopts the knowledge seeker's perspective to empirically investigate the mechanism through which social media use at work impacts construction managers' work performance. Questionnaire survey was conducted with 210 construction managers to test the research model proposed in this study. A component-based structural equation modeling technique was employed to analyze the data.

Results show that social media use at work positively influences knowledge acquisition both internally and externally, and knowledge acquisition promotes task self-efficacy and creativity, which in turn improve construction managers' work performance. In addition, the interaction of task self-efficacy and creativity is found to negatively influence work performance.

These findings contribute to a comprehensive understanding about the impact of social media use at work on construction managers' work performance. This research also provides informative insights for practitioners on how to improve work performance.

A lack of reliable and effective communication tools poses major barriers impeding the performance of construction projects consisting of diverse participants. Although some construction project teams (CPTs) begin to apply social media (SM) as an available approach for project management the entire mechanism of SM adoption in this specific context remains understudied. Therefore, this study aims to adopt a CPT's lens to investigate the critical antecedents and associated effects underlying SM adoption in the construction industry.

Based on the technology–organization–environment (TOE) theory, a conceptual model was proposed and tested by empirical data collected from 159 CPTs in China. Structural equation modeling technique was employed for data analysis.

The results demonstrate that all the five extracted TOE-based antecedents including two technological factors (i.e. compatibility and expected cost), one organizational factor (i.e. top management support) and two environmental factors (i.e. project partner collaboration and project fit) are crucial to the adoption of SM in CPTs. Besides, SM acceptance is found to mediate the relationships between organizational and environmental factors and SM use. Moreover, SM use significantly predicts the communication effectiveness of CPTs.

A questionnaire study based on cross-sectional data from China may only unveil the logic of SM adoption in the context of Chinese construction industry within a shorter time interval. It is recommended that future research could develop longitudinal studies among various construction practitioners in different countries to further specify and generalize the current findings.

This paper provides a comprehensive understanding of SM adoption in the construction industry by exploring the preadoption antecedents and postadoption effects from the perspective of project teams. The empirical findings advance the current web-based project management literature and afford new insights for construction practitioners into better managing SM application to reap its full capabilities in projects.

The construction of smart cities holds the potential to drive digital innovation in the construction industry through various means, such as enhancing supply and demand. This study echoes the urgent need for the construction industry to overcome development challenges. Hence, it is necessary to study the extent and ways in which smart city policies promote digital innovation in the construction industry.

This study treats China’s smart city policies as quasi-natural experiments. Using a dataset of Chinese prefecture-level cities from 2007 to 2021 and a difference-in-differences model, the study scrutinizes the impact of smart city policies on digital innovation within the construction industry.

The study reveals a substantial positive influence of smart city policies on digital innovation in the construction industry. In addition, the study explains these results by analysing supply-side and demand-side mechanisms. Moreover, the effect of smart city pilot policies on promoting digital innovation within the construction industry displays noteworthy heterogeneity across cities at different regional and political levels.

By exploring the impact and mechanisms of smart city policies on digital innovation in the construction industry, this research contributes to a more comprehensive and profound comprehension of the role of policies in facilitating the digital transformation of the construction sector. It is a valuable reference for policymakers and industry practitioners aiming to advance digital development.

After the drawbacks in the process management of China PE commercial real estate development project are analyzed, it is necessary to introduce a more integrated and advanced tool to solve them. The paper aims to discuss this issue.

A standard process model was proposed first. Based on the model, a coupled activity dependency model was also built by structural tool design structure matrix (DSM), the detailed matrix involving 119 activities and 322 information dependencies. Next, two large processes coupled blocks were generated by the sequencing algorithm and tearing algorithm. Then, the general simulation framework with rework probability and rework effect was introduced to do empirical research for one of the activities blocks due to the merit of solving rework of DSM.

These results showed that key activities were rearranged, that information interactive scope for them was optimized and that collaborative organization interface was built. And the expected duration after simulation was 131 days at 90 percent percentile, providing the objective basis of process arrangement to some extent and decreasing the risk of prospective yields during fund period.

This paper is a qualitative and quantitative practical research for the process management of PE commercial real estate development projects in China based on a real project which has begun construction in 2014.

The purpose of this study is to automatically generate a construction schedule by extracting data from the BIM (Building Information Modeling) model and combining an ontology constraint rule and a genetic algorithm (GA).

This study developed a feasible multi-phase framework to generate the construction schedule automatically through extracting information from the BIM, utilizing the ontology constraint rule to demonstrate the relationships between all the components and finally using the GA to generate the construction schedule.

To present the functionality of the framework, a prototype case is adopted to show the whole procedure, and the results show that the scheme designed in this study can quickly generate the schedule and ensure that it can satisfy the requirements of logical constraints and time parameter constraints.

A proper utilization of conceptual framework can contribute to the automatic generation of construction schedules and significantly reduce manual errors in the Architectural, Engineering, and Construction (AEC) industry. Moreover, a scheme of BIM-based ontology and GA for construction schedule generation may reduce additional manual work and improve schedule management performance.

The hybrid approach combines the ontology constraint rule and GA proposed in this study, and it is an effective attempt to generate the construction schedule, which provides a direct indicator for the schedule control of the project.

In this study, the data application process of the BIM model is divided into four modules: extraction, processing, optimization, and output. The key technologies including secondary development, ontology theory, and GA are introduced to develop a multi-phase framework for the automatic generation of the construction schedule and to realize the schedule prediction under logical constraints and duration interference.

Despite the documented benefits of voice behavior for projects, little is known about antecedents of voice behavior in the project context, especially construction projects. Against this background, adopting a multi-team system perspective, this study attempts to investigate antecedents of team voice behavior from a contextual view.

This study identifies and examines six factors that influence team voice behavior. Specifically, project urgency, project temporality, and project complexity are identified from the project nature perspective. Satisfaction, trust, and commitment are generated from the relationship quality approach. Then, data from completed construction projects in China was collected to verify the effectiveness of these factors. Besides, the partial least squares structural equation modeling (PLS-SEM) technique was used in this study.

All six factors are found to be significant predictors of promotive team voice behavior. For prohibitive team voice behavior, only project complexity and project commitment make significant effects. Further, the differential effects of these factors on two types of voice behavior are revealed.

This study contributes to the literature on voice behavior in the project context, especially construction projects consisting of multiple teams. Also, this research enriches our knowledge on antecedents of team voice behavior in construction projects and thus affords practical implications to foster voice behavior.

The purpose of this study is to extract the real requirements of the owner (or users) for the construction project in the operation and maintenance stage completely and accurately and carry out the construction based on the requirements, to make the project status and operation and maintenance requirements (RO&M) consistent after delivered.

This study creatively proposes the operation and maintenance functions deployment (OMFD) under RO&M. In addition, the OPAR (naming is made up of the initials of owners, project, analysis and result) model is constructed to fully identify the requirements of both owners and projects. In this study, three typical construction projects are taken as examples to calculate the correlation strength between project characteristics (PC) and operation and maintenance requirements through the Apriori algorithm, and order parameters are obtained from the cost chain.

This study found that there are significant differences in the correlation strength between 11 types of RO&M and PC, in which the “cost of types” (TC) correlation of residential housing and factory buildings is the largest, while the largest correlation demand of commercial buildings is “safety of types” (TS) and “system” (S). Simultaneously, through the calculation of order parameters, the most influential factors on project characteristics are obtained.

This study could effectively help the owner (or users) to check whether the delivered project fully satisfy their real requirements and also extract the key technical points to realize RO&M, which can guide the accurate construction of the same type of projects.

This research establishes OPAR model to accurately identify the requirements of the project in the operation and maintenance stage and establishes the association rules between the requirements and the construction scheme, which is helpful for the project to construct under the expected requirements.

The purpose of this paper is to mine information on the construction process of previous projects to develop a construction plan that meets both quality requirements and schedule constraints.

This paper uses a failure mode and effect analysis to evaluate the construction quality of 311 apartments in Shanghai. The authors also evaluate construction-scheduling control using the earned value management technique and implement an artificial neural network to correlate the results. The authors then develop a quality risk and schedule correlation model based on Big Data. The model can predict the relationship between the planned schedule and the project quality risk using multiple variables such as the number of layers, the schedule performance index and budget costs.

The methodology offers an innovative approach for assessment on the relationship between quality risk and project schedule. The authors have also built a multiple regression analysis model for comparative purposes with the model. The results show that the proposed model can better describe the relationship. The model can provide a quantitative quality risk value that changes with the planned schedule, as well as help project managers to understand the relationship between quality risk and project scheduling more accurately.

The research approach only focuses on quality risk under the impact of scheduling. Future efforts might focus on developing a model that connects failure models with project schedules and costs in order to improve the effort of quality management.

The model based on Big Data in this paper is developed using real projects and reflects the relationship between project quality risk and scheduling in real environments. The created application provides support for project managers to develop and adjust quality plans and schedules, thereby reducing deviations in quality and scheduling objectives.

The authors make full use of historical project data from the perspective of both quality and schedule management, and provide a novel method to intelligently and objectively analyze the relationship between quality risk and scheduling.