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The outbreak of COVID-19 has introduced critical challenges in the architecture, engineering, and construction (AEC) industry; to address these challenges, building information modelling (BIM) can be applied as a project management tool to help enhance collaboration among stakeholders and improve business performance. Amidst the COVID-19 crisis, there is a greater need to explore and implement effective strategies to promote a wider adoption of BIM. However, increasing the willingness of project participants to adopt BIM through event management has not received much attention. Therefore, based on event system theory and innovation diffusion theory, we developed a model to explore the influence of the COVID-19 crisis on the willingness of AEC participants to adopt BIM. Structural equation modelling was performed to test the hypotheses. The results demonstrate that the intention of the AEC project participants to adopt BIM is directly driven by the COVID-19 event criticality and perceived usefulness of BIM. Moreover, the event criticality and BIM technical features (relative advantage, compatibility, and complexity) can indirectly affect this intention, through the perceived usefulness. However, the impact of event disruption and novelty on the BIM adoption intention is not significant. Several recommendations are provided to improve the BIM adoption intention of AEC participants during and after the pandemic.
Wenshun Wang; Shulei Gao; Lingyun Mi; Jinwen Xing; Ke Shang; Yaning Qiao; Yuting Fu; Guodong Ni; Na Xu. Exploring the adoption of BIM amidst the COVID-19 crisis in China. Building Research & Information 2021, 1 -18.
AMA StyleWenshun Wang, Shulei Gao, Lingyun Mi, Jinwen Xing, Ke Shang, Yaning Qiao, Yuting Fu, Guodong Ni, Na Xu. Exploring the adoption of BIM amidst the COVID-19 crisis in China. Building Research & Information. 2021; ():1-18.
Chicago/Turabian StyleWenshun Wang; Shulei Gao; Lingyun Mi; Jinwen Xing; Ke Shang; Yaning Qiao; Yuting Fu; Guodong Ni; Na Xu. 2021. "Exploring the adoption of BIM amidst the COVID-19 crisis in China." Building Research & Information , no. : 1-18.
Purpose The purpose of this paper is to figure out the paths about transformation of tacit knowledge into explicit knowledge, i.e. tacit knowledge explicating (TKE) in real estate companies, and determine the influencing factors of TKE in Chinese real estate companies to enable enterprises make better use of their knowledge resources. Design/methodology/approach The study adopted an exploratory design method using thematic analysis and grounded theory, and semi-structured interviews were conducted to collect data. The interviewees consisted of employees in different positions, who come from Chinese real estate companies with different ranking ranges and different knowledge management levels. Data collection was divided into two rounds for the identification of transformation paths and influencing factors. Findings This study has shown that 11 paths about TKE divided into solidified organization process and construction of organizational infrastructure go into effect within the real estate companies. Factors influencing TKE in real estate companies concern three main categories: organizational distal factors, contextual proximal factors and individual factors, including 21 subordinates in total. Furthermore, correlation between TKE paths and influencing factors is established. Research limitations/implications Research results may lack generalizability due to the method adopted. Therefore, researchers are encouraged to verify the outcomes of this research. Practical implications This research provides a new idea and solutions for the tacit knowledge management in real estate companies. Originality/value To the best of the authors’ knowledge, this study is the first to systematically identify paths and the influencing factors of TKE in real estate companies, contribute to the incipient but growing understanding of achievement of “tacit to explicit” and enrich the corporate tacit knowledge management literature.
Guodong Ni; Ziyao Zhang; Zhenmin Yuan; Haitao Huang; Na Xu; Yongliang Deng. Transformation paths and influencing factors of tacit knowledge into explicit knowledge in real estate companies: a qualitative study. Engineering, Construction and Architectural Management 2021, ahead-of-p, 1 .
AMA StyleGuodong Ni, Ziyao Zhang, Zhenmin Yuan, Haitao Huang, Na Xu, Yongliang Deng. Transformation paths and influencing factors of tacit knowledge into explicit knowledge in real estate companies: a qualitative study. Engineering, Construction and Architectural Management. 2021; ahead-of-p (ahead-of-p):1.
Chicago/Turabian StyleGuodong Ni; Ziyao Zhang; Zhenmin Yuan; Haitao Huang; Na Xu; Yongliang Deng. 2021. "Transformation paths and influencing factors of tacit knowledge into explicit knowledge in real estate companies: a qualitative study." Engineering, Construction and Architectural Management ahead-of-p, no. ahead-of-p: 1.
The literature and practices of construction safety management have highlighted the importance of domain knowledge. Effectively extracting the domain knowledge elements (DKEs) of construction safety management remains a challenging task. To address this problem, this paper develops a rule-based natural language processing (NLP) approach for extracting DKEs from Chinese text documents in the domain of construction safety management. First, a linguistic pattern of DKEs was constructed according to lexical analysis and syntactic dependency parsing. Then, the extraction rules and workflow paths were established and tested. The results indicated that most DKEs in the domain of construction safety management are composed of specific compound parts of speech (nouns and noun phrases), specific word dependencies (attribution, verb-object, subject-verb, preposition-object, and coordinate relationship), and words of specific lengths (two to six Chinese characters). This work is the first to reveal the Chinese linguistic patterns and linguistic features of DKEs in the domain of construction safety management. The findings of this study can facilitate the establishment and supplementation of domain lexicons and knowledge-based safety management systems and can guide safety training for construction safety management.
Na Xu; Ling Ma; Li Wang; Yongliang Deng; Guodong Ni. Extracting Domain Knowledge Elements of Construction Safety Management: Rule-Based Approach Using Chinese Natural Language Processing. Journal of Management in Engineering 2021, 37, 04021001 .
AMA StyleNa Xu, Ling Ma, Li Wang, Yongliang Deng, Guodong Ni. Extracting Domain Knowledge Elements of Construction Safety Management: Rule-Based Approach Using Chinese Natural Language Processing. Journal of Management in Engineering. 2021; 37 (2):04021001.
Chicago/Turabian StyleNa Xu; Ling Ma; Li Wang; Yongliang Deng; Guodong Ni. 2021. "Extracting Domain Knowledge Elements of Construction Safety Management: Rule-Based Approach Using Chinese Natural Language Processing." Journal of Management in Engineering 37, no. 2: 04021001.
Workplace accidents in construction commonly cause fatal injury and fatality, resulting in economic loss and negative social impact. Analysing accident description reports helps identify typical construction safety risk factors, which then becomes part of the domain knowledge to guide safety management in the future. Currently, such practice relies on domain experts' judgment, which is subjective and time-consuming. This paper developed an improved approach to identify safety risk factors from a volume of construction accident reports using text mining (TM) technology. A TM framework was devised, and a workflow for building a tailored domain lexicon was established. An information entropy weighted term frequency (TF-H) was proposed for term-importance evaluation, and an accumulative TF-H was proposed for threshold division. A case study of metro construction projects in China was conducted. A list of 37 safety risk factors was extracted from 221 metro construction accident reports. The result shows that the proposed TF-H approach performs well to extract important factors from accident reports, solving the impact of different report lengths. Additionally, the obtained risk factors depict critical causes contributing most to metro construction accidents in China. Decision-makers and safety experts can use these factors and their importance degree while identifying safety factors for the project to be constructed.
Na Xu; Ling Ma; Qing Liu; Li Wang; Yongliang Deng. An improved text mining approach to extract safety risk factors from construction accident reports. Safety Science 2021, 138, 105216 .
AMA StyleNa Xu, Ling Ma, Qing Liu, Li Wang, Yongliang Deng. An improved text mining approach to extract safety risk factors from construction accident reports. Safety Science. 2021; 138 ():105216.
Chicago/Turabian StyleNa Xu; Ling Ma; Qing Liu; Li Wang; Yongliang Deng. 2021. "An improved text mining approach to extract safety risk factors from construction accident reports." Safety Science 138, no. : 105216.
Mega construction projects (MCPs) are inherently high-risk and complex. The challenge of safety management for mega construction projects is that safety risk factors constantly change and interact with each other in the long-term construction period. Few of the prior studies have enabled the prediction of the safety state in a dynamic and connected overview, which is a critical characteristic of safety risks in MCPs. Therefore, a hybrid approach for the dynamic simulation of risk factors is proposed. A three-stage procedure review of explicit documents, including accident investigation reports and construction standards, was carried out to identify safety risk factors and the causal relationships among them. Subsequently, the likelihood exposure and consequence (LEC) assessment method was applied to define the changes in risk factors over time. A system dynamics (SD) model was established to integrate the interacting risks and simulate the developing trend of the overall safety risk state. Moreover, a sensitivity analysis was provided to rank risk factors and simulate optimal risk mitigation strategies. Finally, the model was applied to the urban rail transit Line 9 project in China as a case study. The results indicated that the proposed hybrid approach performed satisfactorily under complex interrelated risk factors. Therefore, this study provides a practical framework to simulate and predict the safety state dynamically in a timely process for MCPs, either ahead of a project theoretically or during a project with real data.
Na Xu; Qing Liu; Ling Ma; Yongliang Deng; Hong Chang; Guodong Ni; Zhe Zhou. A Hybrid Approach for Dynamic Simulation of Safety Risks in Mega Construction Projects. Advances in Civil Engineering 2020, 2020, 1 -12.
AMA StyleNa Xu, Qing Liu, Ling Ma, Yongliang Deng, Hong Chang, Guodong Ni, Zhe Zhou. A Hybrid Approach for Dynamic Simulation of Safety Risks in Mega Construction Projects. Advances in Civil Engineering. 2020; 2020 ():1-12.
Chicago/Turabian StyleNa Xu; Qing Liu; Ling Ma; Yongliang Deng; Hong Chang; Guodong Ni; Zhe Zhou. 2020. "A Hybrid Approach for Dynamic Simulation of Safety Risks in Mega Construction Projects." Advances in Civil Engineering 2020, no. : 1-12.
Building Information Modeling (BIM) technology has promoted the development of the architecture, engineering, and construction (AEC) industry, but has encountered many barriers to its application in China. Therefore, identifying the barriers to BIM application and capturing their interactions are essential in order to control and eliminate the determined barriers. From this standpoint, 23 BIM application barriers were identified through a literature review and expert interviews. Furthermore, the interactions among them were determined based on the Delphi method, which was the foundation for establishing the BIM application barrier network (BABN). Then, the software Pajek was employed to construct the network model and reveal its topological characteristics based on complex network theory, including degree, betweenness, eigenvector, clustering coefficient, network diameter, and average path length. As indicated by the results, BABN possesses scale-free network property because its cumulative degree distribution obeys power–law distribution. BABN is also a small-world network, due to its relatively high clustering coefficient as well as small average path length, implying that barrier propagation in BABN is fast. In addition, the results are discussed and recommendations are proposed. This research will help BIM stakeholders to develop coping strategies to control and eliminate BIM application barriers for the sake of driving BIM sustainable development.
Yongliang Deng; Jinyun Li; Qiuting Wu; Shuangshuang Pei; Na Xu; Guodong Ni. Using Network Theory to Explore BIM Application Barriers for BIM Sustainable Development in China. Sustainability 2020, 12, 3190 .
AMA StyleYongliang Deng, Jinyun Li, Qiuting Wu, Shuangshuang Pei, Na Xu, Guodong Ni. Using Network Theory to Explore BIM Application Barriers for BIM Sustainable Development in China. Sustainability. 2020; 12 (8):3190.
Chicago/Turabian StyleYongliang Deng; Jinyun Li; Qiuting Wu; Shuangshuang Pei; Na Xu; Guodong Ni. 2020. "Using Network Theory to Explore BIM Application Barriers for BIM Sustainable Development in China." Sustainability 12, no. 8: 3190.
As a sustainable and cleaner type of facility, prefabricated buildings face more design barriers than traditional non-prefabricated buildings. Identifying and managing these barriers is key to improving the success rate of prefabricated building design. However, direct studies on these design barriers are extremely rare. The present study solved this problem by combining multiple methods, including grounded theory (GT), structured self-intersection matrix (SSIM), analytic network process (ANP), and the linear weighted sum method (LWSM). GT was adopted to identify the barriers to prefabricated building design and then SSIM was used to analyze the interactions among them. The eight design barriers were finally identified and classified into three clusters: technical barriers, economic barriers, and management barriers. A further analysis found that there is dependence and feedback among these clusters. The technical barrier cluster and management barrier cluster experience self-feedback. A network model based on ANP was next established to calculate the weights of the barrier elements and then this model was combined with LWSM to evaluate the overall design barrier strength of a project case. The results showed that architectural individualization has the greatest impact on prefabricated building design, followed by the collaborative issues among multiple units and professional designer issues. The overall design barrier strength of the project case was larger. Therefore, the first suggestion provided to the facility management sector is to establish a library for standard house types to achieve architectural design through multihouse combinations.
Zhenmin Yuan; Guodong Ni; Linxiu Wang; Yaning Qiao; Chengshuang Sun; Na Xu; Wenshun Wang. Research on the Barrier Analysis and Strength Measurement of a Prefabricated Building Design. Sustainability 2020, 12, 2994 .
AMA StyleZhenmin Yuan, Guodong Ni, Linxiu Wang, Yaning Qiao, Chengshuang Sun, Na Xu, Wenshun Wang. Research on the Barrier Analysis and Strength Measurement of a Prefabricated Building Design. Sustainability. 2020; 12 (7):2994.
Chicago/Turabian StyleZhenmin Yuan; Guodong Ni; Linxiu Wang; Yaning Qiao; Chengshuang Sun; Na Xu; Wenshun Wang. 2020. "Research on the Barrier Analysis and Strength Measurement of a Prefabricated Building Design." Sustainability 12, no. 7: 2994.
Researchers and practitioners are focusing greater attention on safety citizenship behavior (SCB), an important factor in preventing injuries and improving workplace safety conditions; however, very little research has been done to study the cognitive mechanisms of employees engaged in this proactive safety behavior. This study aims to explain critical antecedents and cognitive mechanisms of construction workers’ SCBs based on an integrated theoretical framework of the theory of planned behavior (TPB) and norm activation model (NAM). This study was conducted by distributing a questionnaire survey to 719 construction workers in China. The results of structural equation modeling (SEM) indicated that personal norms (PNs), attitudes toward SCB (ATT), subjective norms (SNs), and perceived behavioral control (PBC) have significant positive impacts on the intention of SCB, and the size of direct effects decreases in turn. The study also confirmed the significant indirect effects of SN on behavioral intention by way of ATT, PBC, and PN; ATT, PN, and PBC predicted SCB through the mediating processes of SCB intention. The study demonstrates the applicability and effectiveness of the integrative model in predicting workers’ intentions to adopt SCBs and provides targeted suggestions and strategies for the sustainable development of safety management. These findings have meaningful implications for academic research on SCBs and the industrial practice of safety management.
Qing Liu; Na Xu; Hui Jiang; Shengcheng Wang; Wenshun Wang; Jianping Wang. Psychological Driving Mechanism of Safety Citizenship Behaviors of Construction Workers: Application of the Theory of Planned Behavior and Norm Activation Model. Journal of Construction Engineering and Management 2020, 146, 04020027 .
AMA StyleQing Liu, Na Xu, Hui Jiang, Shengcheng Wang, Wenshun Wang, Jianping Wang. Psychological Driving Mechanism of Safety Citizenship Behaviors of Construction Workers: Application of the Theory of Planned Behavior and Norm Activation Model. Journal of Construction Engineering and Management. 2020; 146 (4):04020027.
Chicago/Turabian StyleQing Liu; Na Xu; Hui Jiang; Shengcheng Wang; Wenshun Wang; Jianping Wang. 2020. "Psychological Driving Mechanism of Safety Citizenship Behaviors of Construction Workers: Application of the Theory of Planned Behavior and Norm Activation Model." Journal of Construction Engineering and Management 146, no. 4: 04020027.
China’s urban rail transit (URT) construction is coming into the stage of rapid development under the guidance of national policies. However, the URT construction projects belong to high-risk projects and construction safety accidents occur frequently. Presently, safety risk management is in continuous development. Unfortunately, due to risk data deficiencies and lack of relationship between participants and safety risk factors, most of the research results cannot be well applied to URT projects. To overcome the limits, this paper has applied the text mining method into safety risk analysis. Through word frequency analysis and cluster analysis, 15 safety risk factors and 3 participants are identified from 156 accident reports. In addition, the accident descriptive model has been established, which is composed of indirect safety risk factors (management defects), direct safety risk factors and participants. In this model, each accident is the standardized description of the corresponding accident information. This is useful for risk data accumulation and analysis. Then the network structure analysis and risk assessment methods are utilized to make clear 63 relationships among participants, management defects and direct safety risk factors. Subsequently, the risk value of each relationship is evaluated. These safety risk information is integrated into the accident descriptive model by using accident points. Finally, ABC analysis which is a popular and effective method used to classify items into specific categories that can be managed and controlled separately is used to analyze the safety risk management’s core process(A), important process(B) and general process(C) in the accident descriptive model. The research results show that the constructor should pay attention to construction coordination, safety specifications, safety measures and personnel education, the supervisor should attach importance to timely communication, the monitoring unit should pay attention to advanced forecast and dynamic control. The main research contributions are as follows: (1) A method of obtaining risk data from unstructured content has been provided; (2) The accident descriptive model could be utilized for risk data continuous accumulation; (3) The emphases of URT construction safety risk management are made clear.
Jie Li; Jianping Wang; Na Xu; Yunpeng Hu; Caiyun Cui. Importance Degree Research of Safety Risk Management Processes of Urban Rail Transit Based on Text Mining Method. Information 2018, 9, 26 .
AMA StyleJie Li, Jianping Wang, Na Xu, Yunpeng Hu, Caiyun Cui. Importance Degree Research of Safety Risk Management Processes of Urban Rail Transit Based on Text Mining Method. Information. 2018; 9 (2):26.
Chicago/Turabian StyleJie Li; Jianping Wang; Na Xu; Yunpeng Hu; Caiyun Cui. 2018. "Importance Degree Research of Safety Risk Management Processes of Urban Rail Transit Based on Text Mining Method." Information 9, no. 2: 26.