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Dr. Pin-Chao Liao
Department of Construction Management, School of Civil Engineering, Tsinghua University, Beijing 100084, China

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0 Data Analytics
0 Neuropsychology
0 Risk Analysis
0 Safety and quality
0 Cognitive / behavior science

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Journal article
Published: 20 August 2021 in International Journal of Environmental Research and Public Health
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Visual cognitive strategies in construction hazard recognition (CHR) signifies prominent value for the development of CHR computer vision techniques and safety training. Nonetheless, most studies are based on either sparse fixations or cross-sectional (accumulative) statistics, which lack consideration of temporality and yielding limited visual pattern information. This research aims to investigate the temporal visual search patterns for CHR and the cognitive strategies they imply. An experimental study was designed to simulate CHR and document participants’ visual behavior. Temporal qualitative comparative analysis (TQCA) was applied to analyze the CHR visual sequences. The results were triangulated based on post-event interviews and show that: (1) In the potential electrical contact hazards, the intersection of the energy-releasing source and wire that reflected their interaction is the cognitively driven visual area that participants tend to prioritize; (2) in the PPE-related hazards, two different visual strategies, i.e., “scene-related” and “norm-guided”, can usually be generalized according to the participants’ visual cognitive logic, corresponding to the bottom-up (experience oriented) and top-down (safety knowledge oriented) cognitive models. This paper extended recognition-by-components (RBC) model and gestalt model as well as providing feasible practical guide for safety trainings and theoretical foundations of computer vision techniques for CHR.

ACS Style

Rui Cheng; Jiaming Wang; Pin-Chao Liao. Temporal Visual Patterns of Construction Hazard Recognition Strategies. International Journal of Environmental Research and Public Health 2021, 18, 8779 .

AMA Style

Rui Cheng, Jiaming Wang, Pin-Chao Liao. Temporal Visual Patterns of Construction Hazard Recognition Strategies. International Journal of Environmental Research and Public Health. 2021; 18 (16):8779.

Chicago/Turabian Style

Rui Cheng; Jiaming Wang; Pin-Chao Liao. 2021. "Temporal Visual Patterns of Construction Hazard Recognition Strategies." International Journal of Environmental Research and Public Health 18, no. 16: 8779.

Journal article
Published: 06 July 2021 in International Journal of Occupational Safety and Ergonomics
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Abstrac Hazard recognition is mainly a visual search and cognitive process. Mental representations of hazards may impact mental states of hazard recognition. We assessed the effects of critical indicators of mental presentations of construction hazards on prefrontal cortex activation, a proxy for the mental states of hazard recognition. Students participated in a hazard inspection experiment, with near-infrared spectroscopy (NIRS) used to record prefrontal cortex activation. The effects of critical indicators of the hazards’ mental representations on prefrontal activation were analyzed. Results demonstrated that site familiarity, risk tolerance, and safety knowledge have significant effects on medial prefrontal activation for hazards at low visual clutter level. High levels of site familiarity and risk tolerance reduced medial prefrontal activation and saved cognitive resources. Theoretically, the findings supplement the knowledge of safety hazards’ mental representations; and practically, the findings guide provision of individual-specific guidance for improving workers’ hazard inspection performance.

ACS Style

Qingwen Zhang; Dan Zhang; Pin-Chao Liao. Leading indicators of mental representation in construction hazard recognition. International Journal of Occupational Safety and Ergonomics 2021, 1 -38.

AMA Style

Qingwen Zhang, Dan Zhang, Pin-Chao Liao. Leading indicators of mental representation in construction hazard recognition. International Journal of Occupational Safety and Ergonomics. 2021; ():1-38.

Chicago/Turabian Style

Qingwen Zhang; Dan Zhang; Pin-Chao Liao. 2021. "Leading indicators of mental representation in construction hazard recognition." International Journal of Occupational Safety and Ergonomics , no. : 1-38.

Journal article
Published: 05 July 2021 in Sustainability
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Many countries have increased the use of renewable energy and strongly promoted offshore wind power (OWP). However, OWP in Asia is in the preliminary stage of development, for which no precedents exist. The literature on wind energy generation has mostly investigated the causes of onshore wind turbine accidents and risk prevention, and more work on the risks associated with domestic OWP is required for energy market development. According to statistics on international wind power accidents, most offshore accidents occur in the construction and operation stages. Therefore, this work investigates risk management in the construction and operations of offshore windfarms in Taiwan. The goal is to help decision-makers to understand better the risks of the industry and so more effectively manage them. In this study, risk factors are identified from organizing data in the literature, and research methods and action strategies are developed. Research and analysis follow the risk management steps in the PMBOK® Guide (A Guide to the Project Management Body of Knowledge). The risk rankings and preventive measures that are based on the results of this study can serve as references for relevant industry personnel in island cities and nearby Asian countries to reduce risk in the management of OWP projects.

ACS Style

Jui-Sheng Chou; Pin-Chao Liao; Chung-Da Yeh. Risk Analysis and Management of Construction and Operations in Offshore Wind Power Project. Sustainability 2021, 13, 7473 .

AMA Style

Jui-Sheng Chou, Pin-Chao Liao, Chung-Da Yeh. Risk Analysis and Management of Construction and Operations in Offshore Wind Power Project. Sustainability. 2021; 13 (13):7473.

Chicago/Turabian Style

Jui-Sheng Chou; Pin-Chao Liao; Chung-Da Yeh. 2021. "Risk Analysis and Management of Construction and Operations in Offshore Wind Power Project." Sustainability 13, no. 13: 7473.

Journal article
Published: 27 May 2021 in International Journal of Environmental Research and Public Health
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The effective improvement of employee behavioral compliance and safety performance is an important subject related to the sustainable development of the construction industry. Based on data from a Chinese company (n = 290), this study used a partial least squares-structural equation model to clarify the relationship among safety participation, job competence, and behavioral compliance. Empirical analysis found that: (1) safety participation had a significant positive impact on employees’ behavioral compliance; and (2) job competence played a partial mediating role between safety participation and behavioral compliance. By selecting two new perspectives of safety participation and job competence, this study derived new factors affecting behavioral compliance, constructed a new theory about safety management, and conducted an in-depth discussion on improving behavioral compliance theoretically. Practically, the research put forward a new decision-making model, deconstructed the mechanism between safety participation and behavioral compliance, and provided new guiding strategies for improving employee behavioral compliance.

ACS Style

Jia-Ming Wang; Pin-Chao Liao; Guan-Biao Yu. The Mediating Role of Job Competence between Safety Participation and Behavioral Compliance. International Journal of Environmental Research and Public Health 2021, 18, 5783 .

AMA Style

Jia-Ming Wang, Pin-Chao Liao, Guan-Biao Yu. The Mediating Role of Job Competence between Safety Participation and Behavioral Compliance. International Journal of Environmental Research and Public Health. 2021; 18 (11):5783.

Chicago/Turabian Style

Jia-Ming Wang; Pin-Chao Liao; Guan-Biao Yu. 2021. "The Mediating Role of Job Competence between Safety Participation and Behavioral Compliance." International Journal of Environmental Research and Public Health 18, no. 11: 5783.

Journal article
Published: 21 May 2021 in International Journal of Environmental Research and Public Health
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Emotions strongly affect occupational safety attention and public health; however, the underlying mechanisms remain unknown. We investigated the mediation mechanisms of emotional valence and arousal on safety attention using real time data. In all, 70 Chinese workers performed 8400 trials of hazard recognition tasks according to a pre-designed experiment. Their emotional and safety attention levels were recorded based on their facial expressions and eye movements, and the mediating mechanics of emotional valence and arousal were examined through a hierarchical regression. The study results show that: (1) emotional valence and arousal significantly and positively affect safety attention; (2) risk tolerance and personality significantly affect emotional valence and arousal but do not significantly affect safety attention; and (3) emotional valence and arousal significantly mediate safety attention levels and personal factors. From a theoretical viewpoint, this study corroborates the mediating role of emotion on occupational safety attention and personal factors by highlighting valence and arousal. Practically, managers can develop more specific training methods tailored to the results that pertain to workers’ higher emotional resilience for better occupational safety performance and health.

ACS Style

Jiaming Wang; Pin-Chao Liao. Re-Thinking the Mediating Role of Emotional Valence and Arousal between Personal Factors and Occupational Safety Attention Levels. International Journal of Environmental Research and Public Health 2021, 18, 5511 .

AMA Style

Jiaming Wang, Pin-Chao Liao. Re-Thinking the Mediating Role of Emotional Valence and Arousal between Personal Factors and Occupational Safety Attention Levels. International Journal of Environmental Research and Public Health. 2021; 18 (11):5511.

Chicago/Turabian Style

Jiaming Wang; Pin-Chao Liao. 2021. "Re-Thinking the Mediating Role of Emotional Valence and Arousal between Personal Factors and Occupational Safety Attention Levels." International Journal of Environmental Research and Public Health 18, no. 11: 5511.

Construction management
Published: 26 February 2021 in KSCE Journal of Civil Engineering
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Understanding the mental representations used for hazard recognition would help the development of inspection strategies for effective safety management. This study is part of ongoing research to identify hazard recognition patterns based on users’ mental representations. Hence, this study explored normative visual patterns for improving hazard recognition performance using a crisp-set qualitative comparative analysis (cs-QCA). Eye-tracking data and visual trajectories were collected using an eye-tracking device in a structural laboratory. A cs-QCA approach was adopted to analyze and summarize normative visual patterns that were used to successfully detect hazards by all participants, namely, potential electrical contact, a large machine with no guardrails, and steel bars dump. The results show that object identification should suffice as the basis for identifying electricity-related hazards, while struck-by hazards should focus on the objects and their pivot points or potential movement trajectories. The experimental design and analytical approach provide new insights into visual analytics in hazard recognition. The research extends and supplements recognition by component theory in the context of construction hazard recognition. The results also provide new and practical references for hazard inspection training, as well as for future development of automated hazard recognition systems.

ACS Style

Heap-Yih Chong; Mingxuan Liang; Pin-Chao Liao. Normative Visual Patterns for Hazard Recognition: A Crisp-Set Qualitative Comparative Analysis Approach. KSCE Journal of Civil Engineering 2021, 25, 1545 -1554.

AMA Style

Heap-Yih Chong, Mingxuan Liang, Pin-Chao Liao. Normative Visual Patterns for Hazard Recognition: A Crisp-Set Qualitative Comparative Analysis Approach. KSCE Journal of Civil Engineering. 2021; 25 (5):1545-1554.

Chicago/Turabian Style

Heap-Yih Chong; Mingxuan Liang; Pin-Chao Liao. 2021. "Normative Visual Patterns for Hazard Recognition: A Crisp-Set Qualitative Comparative Analysis Approach." KSCE Journal of Civil Engineering 25, no. 5: 1545-1554.

Articles
Published: 25 February 2021 in International Journal of Occupational Safety and Ergonomics
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Introduction: Safety assessment helps the development of continuous improvement strategies in construction safety, especially coping with dynamic changes to the on-site environment with uncertainties. This paper proposes a composite safety assessment based on on-site conditions to facilitate improved and proactive construction safety management. Methods: First, based on evident rectification records, we utilized set pair analysis, a grey-rough approach, and a coevolution approach to quantify overall safety performance. Second, we incorporated two safety performance indicators into a composite assessment framework, using rough set theory and fluid dynamics. Finally, the assessment results of the seven completed projects were compared. Results: The coevolution approach had novel advantages in assessing rectification performance and the fluid dynamics approach could enhance the proactive warning ability of the safety assessment. Contribution: Theoretically, the research contributes to new insights into the quantification of construction safety assessment under dynamic on-site conditions. Practically, it also contributes to the active and objective measurement of management performance and promotes the dynamic and stable safety performance evaluation for onsite construction.

ACS Style

Mei Liu; Heap-Yih Chong; Pin-Chao Liao; Linyu Xu. Incorporation of hazard rectification performance for safety assessment. International Journal of Occupational Safety and Ergonomics 2021, 1 -14.

AMA Style

Mei Liu, Heap-Yih Chong, Pin-Chao Liao, Linyu Xu. Incorporation of hazard rectification performance for safety assessment. International Journal of Occupational Safety and Ergonomics. 2021; ():1-14.

Chicago/Turabian Style

Mei Liu; Heap-Yih Chong; Pin-Chao Liao; Linyu Xu. 2021. "Incorporation of hazard rectification performance for safety assessment." International Journal of Occupational Safety and Ergonomics , no. : 1-14.

Construction management
Published: 12 February 2021 in KSCE Journal of Civil Engineering
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Construction safety assessment is a major component of safety management in construction projects. However, thus far, most assessment studies have focused on either cross-sectional or longitudinal performance. This study aims to develop a proactive and preliminary safety assessment method using a fluid dynamics (FD) approach by integrating longitudinal contractor performance with cross-sectional safety conditions. To this end, an FD framework was first developed using three processes: (a) identifying the connections between FD principles and safety analogs, (b) incorporating the Darcy-Weisbach equation into the framework, and (c) modifying FD equations for construction safety assessment. Subsequently, two case studies were investigated, and the results obtained were compared and verified with one existing assessment results. The results indicate that the state of safety at a construction site incorporates both the occurrence of hazards and conservation of energy. Thus, the proposed FD approach can be used to preliminarily assess and predict safety conditions by combining safety-related measures with the dynamic characteristics of construction processes. The approach considers a comprehensive range of indicators and parameters, which enables the comparison of safety performance between projects or assessment periods by independently changing parameters.

ACS Style

Mei Liu; Heap-Yih Chong; Pin-Chao Liao. A Novel Approach Based on Fluid Dynamics for On-Site Safety Assessment. KSCE Journal of Civil Engineering 2021, 25, 1533 -1544.

AMA Style

Mei Liu, Heap-Yih Chong, Pin-Chao Liao. A Novel Approach Based on Fluid Dynamics for On-Site Safety Assessment. KSCE Journal of Civil Engineering. 2021; 25 (5):1533-1544.

Chicago/Turabian Style

Mei Liu; Heap-Yih Chong; Pin-Chao Liao. 2021. "A Novel Approach Based on Fluid Dynamics for On-Site Safety Assessment." KSCE Journal of Civil Engineering 25, no. 5: 1533-1544.

Original paper
Published: 02 February 2021 in Archives of Computational Methods in Engineering
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Neural engineering, an emerging interdisciplinary subject, is aimed at using engineering techniques to investigate the function and manipulate the behavior of the nervous system. The development of technology along with the advancement in Science helps to apply increasing multimodal research into the field of neural engineering, which has promoted the development of neural engineering. In this paper, a bibliometric analysis of 808 articles in Web of Science from 2003 to 2019 was conducted to determine the current status and future trends of multimodal neural engineering study. This paper conducted a five-step bibliometric analysis based on the proposed multimodal neural engineering research framework (NE-MUL). The results showed that in the past 17 years, multimodal research not only made great contributions to the development of neural engineering, but also brought this field a series of new problems (multimodal fusion, recurrent multimodal learning, multimodal convolutional network, etc.) This paper generated a map of existing research findings with their relationship and provided future researchers with meaningful suggestions and assistance.

ACS Style

Jiaming Wang; Rui Cheng; Pin-Chao Liao. Trends of Multimodal Neural Engineering Study: A Bibliometric Review. Archives of Computational Methods in Engineering 2021, 1 -15.

AMA Style

Jiaming Wang, Rui Cheng, Pin-Chao Liao. Trends of Multimodal Neural Engineering Study: A Bibliometric Review. Archives of Computational Methods in Engineering. 2021; ():1-15.

Chicago/Turabian Style

Jiaming Wang; Rui Cheng; Pin-Chao Liao. 2021. "Trends of Multimodal Neural Engineering Study: A Bibliometric Review." Archives of Computational Methods in Engineering , no. : 1-15.

Journal article
Published: 05 January 2021 in Advanced Engineering Informatics
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Hazard warnings derived from hazard associations help in guiding safety inspectors, while detailed descriptions may limit risk perceptions. However, outlining characteristics of hazards may help inspectors to conduct subjective searches for hazards with fewer preset conditions. This study aimed to facilitate safety inspections by determining critical characters of hazards using a character-based network of networks (NoN) with actual construction site data. First, characters were extracted using text analysis and categorized by hierarchical clustering. Then, a character-based NoN was established using network analysis. Critical characters and hazards were generated by considering association strengths and node measures. Finally, the practicability and reliability of associated characters were validated through a case study. Results indicated that (1) “facility/equipment/device,” “setting,” “site/construction site,” and “power distribution/distribution box” were critical characters by evaluation of outdegree, betweenness, closeness, and eigenvector centrality; (2) the hazard warning route from “railing” to “facility/equipment/device” was obtained through associations within and between different layers of the NoN. The case study indicates that the proposed approach based on character associations not only simplifies hazard association routes but also discovers hazards omitted from the hazard network. In practice, the proposed method may assist safety inspectors to focus on critical characters and thereby improve the efficiency of risk identification.

ACS Style

Mei Liu; Linyu Xu; Pin-Chao Liao. Character-based hazard warning mechanics: A network of networks approach. Advanced Engineering Informatics 2021, 47, 101240 .

AMA Style

Mei Liu, Linyu Xu, Pin-Chao Liao. Character-based hazard warning mechanics: A network of networks approach. Advanced Engineering Informatics. 2021; 47 ():101240.

Chicago/Turabian Style

Mei Liu; Linyu Xu; Pin-Chao Liao. 2021. "Character-based hazard warning mechanics: A network of networks approach." Advanced Engineering Informatics 47, no. : 101240.

Journal article
Published: 29 December 2020 in International Journal of Occupational Safety and Ergonomics
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Introduction. Most methods used to develop construction risk responses address the risk-mitigation optimization problem by solving the objective functions. They are passively achieved by satisfying constraint conditions, which are not adequate for efficient construction management. This study aims to provide an active optimization strategy for selecting risk responses. Methods. We combined set pair analysis (SPA) with the technique for order preference by similarity to an ideal solution (TOPSIS) to control the construction risks to an acceptable level instead of excessively to the minimum level. SPA is employed to assess the pre- and post-mitigation risk levels based on the uncertainty theory, and TOPSIS is used to rank safety measures based on their risk-mitigation effects. A case study of concrete pumping for a super high-rise building was used to exemplify how the proposed optimization model assists risk control and validate its reasonability. Conclusion. The developed TOPSIS-SPA-based method figures out the optimal safety-measure combination reducing construction risks economically to an acceptable level with the fewest number of measures. The findings can assist decision-makers in formulating cost-effective risk-control schemes.

ACS Style

Qingwen Zhang; Hongling Guo; Pin-Chao Liao; Dongping Fang; Man Fu. Optimizing safety-measure combinations to address construction risks. International Journal of Occupational Safety and Ergonomics 2020, 1 -17.

AMA Style

Qingwen Zhang, Hongling Guo, Pin-Chao Liao, Dongping Fang, Man Fu. Optimizing safety-measure combinations to address construction risks. International Journal of Occupational Safety and Ergonomics. 2020; ():1-17.

Chicago/Turabian Style

Qingwen Zhang; Hongling Guo; Pin-Chao Liao; Dongping Fang; Man Fu. 2020. "Optimizing safety-measure combinations to address construction risks." International Journal of Occupational Safety and Ergonomics , no. : 1-17.

Journal article
Published: 01 December 2020 in Automation in Construction
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Comprehending the neurophysiological mechanics of hazard recognition (HR) is crucial in image analysis and automated hazard inspection. Although previous studies have used brain–-computer interfaces (BCIs) to reveal brain activity patterns during HR, few have considered construction hazards. In this study, we identified salient prefrontal cortex (PFC) areas that that signify different recognized hazards. We performed an experiment consisting of multiple HR tasks in a laboratory setting and recorded the hemodynamic responses with near-infrared spectroscopy (NIRS). The Fisher score and linear discriminant analysis were used to classify hazardous situations. The results showed that the left PFC was more engaged in HR: specifically, the dorsolateral PFC for electricity and impact-related HR and the ventrolateral PFC for stabbing-related HR. Theoretically, the identified critical areas for hazard differentiation can be regarded as a neuropsychological basis for cognition. Practically, these results demonstrate the potential of NIRS-based BCIs for hazard inspections.

ACS Style

Xiaoshan Zhou; Yinan Hu; Pin-Chao Liao; Dan Zhang. Hazard differentiation embedded in the brain: A near-infrared spectroscopy-based study. Automation in Construction 2020, 122, 103473 .

AMA Style

Xiaoshan Zhou, Yinan Hu, Pin-Chao Liao, Dan Zhang. Hazard differentiation embedded in the brain: A near-infrared spectroscopy-based study. Automation in Construction. 2020; 122 ():103473.

Chicago/Turabian Style

Xiaoshan Zhou; Yinan Hu; Pin-Chao Liao; Dan Zhang. 2020. "Hazard differentiation embedded in the brain: A near-infrared spectroscopy-based study." Automation in Construction 122, no. : 103473.

Journal article
Published: 30 September 2020 in Safety Science
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Hazard recognition has been extensively explored in previous studies. However, deficits have arisen due to the neglect of task-specific effects, information distortion by image-based experimental tasks, and the exclusive use of eye trackers. This study aimed to explore how cognitive patterns vary in simulated construction worksites with different types of hazards using multimodal monitoring. A hazard recognition task was conducted in a hazardous civil laboratory using both an eye tracker and a near-infrared spectrum system to capture pupil responses and cerebral oxyhemoglobin signals. Cognitive responses were analyzed according to hazard type and scene complexity. The results showed that falling hazards induced the most cerebral and pupillary activation. Scene complexity triggers an increase in pupil diameter and impacts cerebral activities by interaction with hazard type. This study also reveals the complementary functions of pupillary responses and neural processes in hazardous simulated worksites and a ceiling effect of cognitive resources. We conclude that construction workplaces with different types of hazards can induce different cognitive demands and should thus be treated individually. This information is potentially useful for practical applications.

ACS Style

Pin-Chao Liao; Xinlu Sun; Dan Zhang. A multimodal study to measure the cognitive demands of hazard recognition in construction workplaces. Safety Science 2020, 133, 105010 .

AMA Style

Pin-Chao Liao, Xinlu Sun, Dan Zhang. A multimodal study to measure the cognitive demands of hazard recognition in construction workplaces. Safety Science. 2020; 133 ():105010.

Chicago/Turabian Style

Pin-Chao Liao; Xinlu Sun; Dan Zhang. 2020. "A multimodal study to measure the cognitive demands of hazard recognition in construction workplaces." Safety Science 133, no. : 105010.

Earlycite article
Published: 20 May 2020 in Engineering, Construction and Architectural Management
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PurposeThis study aims to determine the influences of explanatory factors on the efficacy of the implementation of corporate safety policy (CSP) in international projects from the perspective of international contractors.Design/methodology/approachFour explanatory factors were identified for the implementation of CSP in international projects based on literature review. A questionnaire survey was then conducted among Chinese organizations that have been involved in international projects. In total, 121 valid responses were received from the questionnaire survey and were modeled using logistic regression to examine the impact of each factor on the observed event of interest.FindingsThe factors related to the effectiveness of implementing CSP, including “attitudes toward safety management measures (ASMM),” “operational mechanism for safety regulations (OM),” “safety knowledge management system (SKMS)” and “systematic safety training scheme (STS),” were selected. The results revealed that OM and SKMS were significant predictors (p < 0.05) of the odds of implementation satisfaction of CSP, but ASMM and STS were not. The probability of satisfactory CSP implementation increased as the value of SKMS increased, whereas the probability of unsatisfactory implementation improved as the value of OM increased.Research limitations/implicationsThe questionnaire was distributed to respondents in international contractors headquartered in China. Other types of international organizations can be covered in future research. Furthermore, other factors, such as the local construction environment, should be considered in future studies.Practical implicationsThe results provide new insights on CSP implementation overseas. Effective implementation of CSP contributes to the improvement of the safety performance of contractors. The practical significance of interpreting the influence factors is that the contractors can implement more efficient and targeted approaches and tools in the execution of their CSP. The impact of OM reminds safety managers of the synchronization of CSP as well as its implementation environment and characteristics. The effect of ASMM encourages contractors to adopt Web-based and digital knowledge management systems to improve the implementation efficiency of CSP.Originality/valueThe novelty of this study lies in the selection of factors and their impacts on CSP implementation in international projects. This study has also extended knowledge on normative safety in international projects based on quantitative modeling.

ACS Style

Qing-Wen Zhang; Heap-Yih Chong; Pin-Chao Liao; Yao-Lin Wan. Logistic regression modeling of implementation of corporate safety policy in international infrastructures. Engineering, Construction and Architectural Management 2020, 27, 3031 -3050.

AMA Style

Qing-Wen Zhang, Heap-Yih Chong, Pin-Chao Liao, Yao-Lin Wan. Logistic regression modeling of implementation of corporate safety policy in international infrastructures. Engineering, Construction and Architectural Management. 2020; 27 (10):3031-3050.

Chicago/Turabian Style

Qing-Wen Zhang; Heap-Yih Chong; Pin-Chao Liao; Yao-Lin Wan. 2020. "Logistic regression modeling of implementation of corporate safety policy in international infrastructures." Engineering, Construction and Architectural Management 27, no. 10: 3031-3050.

Journal article
Published: 19 February 2020 in Safety Science
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Human error by workers is the most important causal factor in accidents. This study aims to improve construction safety by controlling critical hazards using dissipative structure theory (DST) applied to an associated network of workplace hazards. To analyze the interaction of hazards leading to human errors, the associated network is established using the cognitive reliability and error analysis method (CREAM) and complex network theory. This network-based approach is applied to the onsite hazard and rectification records of seven construction projects in Qingdao, China. DST is employed to simulate the energy exchange process in the consideration of hazard association and management. Finally, we measure the ability of the proposed model to simplify the propagation of hazards. The results indicate that (1) critical hazards and hazard couplings related to falling mainly derive from sequence errors, insufficient knowledge, missed observations, and inadequate planning; (2) the energy transfer mechanism and key hazard path can be obtained using DST in the process of hazard triggering; and (3) the proposed DST approach has the ability to simplify the hazard associated network regarding the hazard-triggering process. This research contributes to the analysis of hazard propagation leading to human errors from the perspective of energy exchange, and thus assists in the formulation of a proactive safety management plan for controlling and rectifying critical hazards in construction engineering.

ACS Style

Mei Liu; Pingbo Tang; Pin-Chao Liao; Linyu Xu. Propagation mechanics from workplace hazards to human errors with dissipative structure theory. Safety Science 2020, 126, 104661 .

AMA Style

Mei Liu, Pingbo Tang, Pin-Chao Liao, Linyu Xu. Propagation mechanics from workplace hazards to human errors with dissipative structure theory. Safety Science. 2020; 126 ():104661.

Chicago/Turabian Style

Mei Liu; Pingbo Tang; Pin-Chao Liao; Linyu Xu. 2020. "Propagation mechanics from workplace hazards to human errors with dissipative structure theory." Safety Science 126, no. : 104661.

Earlycite article
Published: 05 December 2019 in Engineering, Construction and Architectural Management
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Purpose Human error is among the leading causes of construction-based accidents. Previous studies on the factors affecting human error are rather vague from the perspective of complex and changeable working environments. The purpose of this paper is to develop a dynamic causal model of human errors to improve safety management in the construction industry. A theoretical model is developed and tested through a case study. Design/methodology/approach First, the authors defined the causal relationship between construction and human errors based on the cognitive reliability and error analysis method (CREAM). A dynamic Bayesian network (DBN) was then developed by connecting time-variant causal relationships of human errors. Next, prediction, sensitivity analysis and diagnostic analysis of DBN were applied to demonstrate the function of this model. Finally, a case study of elevator installation was presented to verify the feasibility and applicability of the proposed approach in a construction work environment. Findings The results of the proposed model were closer to those of practice than previous static models, and the features of the systematization and dynamics are more efficient in adapting toward increasingly complex and changeable environments. Originality/value This research integrated CREAM as the theoretical foundation for a novel time-variant causal model of human errors in construction. Practically, this model highlights the hazards that potentially trigger human error occurrences, facilitating the implementation of proactive safety strategy and safety measures in advance.

ACS Style

Zhangming Ma; Heap-Yih Chong; Pin-Chao Liao. Development of a time-variant causal model of human error in construction with dynamic Bayesian network. Engineering, Construction and Architectural Management 2019, 28, 291 -307.

AMA Style

Zhangming Ma, Heap-Yih Chong, Pin-Chao Liao. Development of a time-variant causal model of human error in construction with dynamic Bayesian network. Engineering, Construction and Architectural Management. 2019; 28 (1):291-307.

Chicago/Turabian Style

Zhangming Ma; Heap-Yih Chong; Pin-Chao Liao. 2019. "Development of a time-variant causal model of human error in construction with dynamic Bayesian network." Engineering, Construction and Architectural Management 28, no. 1: 291-307.

Journal article
Published: 18 October 2019 in Advanced Engineering Informatics
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Construction workplace hazard detection requires engineers to analyze scenes manually against many safety rules, which is time-consuming, labor-intensive, and error-prone. Computer vision algorithms are yet to achieve reliable discrimination of anomalous and benign object relations underpinning safety violation detections. Recently developed deep learning-based computer vision algorithms need tens of thousands of images, including labels of the safety rules violated, in order to train deep-learning networks for acquiring spatiotemporal reasoning capacity in complex workplaces. Such training processes need human experts to label images and indicate whether the relationship between the worker, resource, and equipment in the scenes violate spatiotemporal arrangement rules for safe and productive operations. False alarms in those manual labels (labeling no-violation images as having violations) can significantly mislead the machine learning process and result in computer vision models that produce inaccurate hazard detections. Compared with false alarms, another type of mislabels, false negatives (labeling images having violations as “no violations”), seem to have fewer impacts on the reliability of the trained computer vision models. This paper examines a new crowdsourcing approach that achieves above 95% accuracy in labeling images of complex construction scenes having safety-rule violations, with a focus on minimizing false alarms while keeping acceptable rates of false negatives. The development and testing of this new crowdsourcing approach examine two fundamental questions: (1) How to characterize the impacts of a short safety-rule training process on the labeling accuracy of non-professional image annotators? And (2) How to properly aggregate the image labels contributed by ordinary people to filter out false alarms while keeping an acceptable false negative rate? In designing short training sessions for online image annotators, the research team split a large number of safety rules into smaller sets of six. An online image annotator learns six safety rules randomly assigned to him or her, and then labels workplace images as “no violation” or ‘violation” of certain rules among the six learned by him or her. About one hundred and twenty anonymous image annotators participated in the data collection. Finally, a Bayesian-network-based crowd consensus model aggregated these labels from annotators to obtain safety-rule violation labeling results. Experiment results show that the proposed model can achieve close to 0% false alarm rates while keeping the false negative rate below 10%. Such image labeling performance outdoes existing crowdsourcing approaches that use majority votes for aggregating crowdsourced labels. Given these findings, the presented crowdsourcing approach sheds lights on effective construction safety surveillance by integrating human risk recognition capabilities into advanced computer vision.

ACS Style

Yanyu Wang; Pin-Chao Liao; Cheng Zhang; Yi Ren; Xinlu Sun; Pingbo Tang. Crowdsourced reliable labeling of safety-rule violations on images of complex construction scenes for advanced vision-based workplace safety. Advanced Engineering Informatics 2019, 42, 101001 .

AMA Style

Yanyu Wang, Pin-Chao Liao, Cheng Zhang, Yi Ren, Xinlu Sun, Pingbo Tang. Crowdsourced reliable labeling of safety-rule violations on images of complex construction scenes for advanced vision-based workplace safety. Advanced Engineering Informatics. 2019; 42 ():101001.

Chicago/Turabian Style

Yanyu Wang; Pin-Chao Liao; Cheng Zhang; Yi Ren; Xinlu Sun; Pingbo Tang. 2019. "Crowdsourced reliable labeling of safety-rule violations on images of complex construction scenes for advanced vision-based workplace safety." Advanced Engineering Informatics 42, no. : 101001.

Journal article
Published: 26 August 2019 in Safety Science
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Mental representations of hazard recognition are crucial to inspection strategies in construction safety management. However, few studies have investigated scan patterns as the means of mental representation of hazard recognition in the construction industry. This paper aims to explore visual searching strategies through eye-tracking scan patterns for construction safety inspection. An experimental study with 47 participants was designed to identify hazards in a pseudo construction site, and the scanning data were collected with a portable eye-tracking device. Artificial intelligence was then used to quantitatively define areas of interest based on the extracted fixation data of all participants. For two specific hazards, 23 and 29 scanpaths were generated and presented in the form of fixation sequences. Finally, the searching strategies of the participants who successfully recognized hazards were compared to the strategies of those who failed, and their scan patterns were summarized with eyePatterns®. The results show that the successful participants follow similar hazard searching patterns, concentrating on specific hazardous areas rather than unimportant distractors, following a logical and serial search pattern. They tend to observe one sub-area fully before a systematic shift to another one. This paper reports on a conceptual study of hazard searching patterns based on visual scanpaths, contributing to research of the searching strategies of mental representations for hazard recognition as well as providing useful practical implications for hazard inspection strategies in construction projects.

ACS Style

Qingwen Xu; Heap-Yih Chong; Pin-Chao Liao. Exploring eye-tracking searching strategies for construction hazard recognition in a laboratory scene. Safety Science 2019, 120, 824 -832.

AMA Style

Qingwen Xu, Heap-Yih Chong, Pin-Chao Liao. Exploring eye-tracking searching strategies for construction hazard recognition in a laboratory scene. Safety Science. 2019; 120 ():824-832.

Chicago/Turabian Style

Qingwen Xu; Heap-Yih Chong; Pin-Chao Liao. 2019. "Exploring eye-tracking searching strategies for construction hazard recognition in a laboratory scene." Safety Science 120, no. : 824-832.

Journal article
Published: 01 July 2019 in Safety Science
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Hazard recognition (HR) is a critical process for safety management in the complex and dynamic occupational environment. Although previous studies have attempted to quantify hazard recognition ability (HRA), the results are potentially optimistic because of limitations in their experimental settings and/or single data collection channels. This study aims to re-develop a compound HRA index that incorporates microvascular function in the brain. First, the authors identify critical indicators of HR and design an experiment to be conducted in a real scene. Data are then collected through questionnaires (experience and risk tolerance), eye-tracking devices (eye movement), and near-infrared spectroscopy. Finally, discriminant analysis is applied to develop an HRA index. The prediction accuracy of the proposed HRA index is shown to outperform previous approaches. Theoretically, this research signals a new perspective (changes in hemodynamic properties of the prefrontal cortex) in the assessment of HRA. The proposed HRA index can be used for onboard assessment of workers or safety inspectors, reducing human errors and undetected occupational hazards.

ACS Style

Xinlu Sun; Pin-Chao Liao. Re-assessing hazard recognition ability in occupational environment with microvascular function in the brain. Safety Science 2019, 120, 67 -78.

AMA Style

Xinlu Sun, Pin-Chao Liao. Re-assessing hazard recognition ability in occupational environment with microvascular function in the brain. Safety Science. 2019; 120 ():67-78.

Chicago/Turabian Style

Xinlu Sun; Pin-Chao Liao. 2019. "Re-assessing hazard recognition ability in occupational environment with microvascular function in the brain." Safety Science 120, no. : 67-78.

Journal article
Published: 07 June 2019 in Accident Analysis & Prevention
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Safety assessment is crucial for the development of continuous improvement strategies. However, most studies assess construction safety with cross-sectional information and thus management tends to be passive. This study proposes an evidence-based methodology incorporating hazard rectification efficiency for project safety assessment. First, we theoretically introduced hazard rectification efficiency as a proxy for hazard exposure. Later, based on set-pair analysis, we proposed a safety assessment model that incorporates hazard occurrence and rectification efficiency. Subsequently, we collected site investigation records from seven building projects in Qingdao, Shandong. The data were used to develop a safety performance index (SPI) with the proposed model and a default model. The results were compared and discussed according to industrial practices for validation purposes. The proposed model provides conservative indications of project safety performance; more importantly, the index calculated with the model provides advance warning when necessary. In the proposed method, in terms of the SPI, hazard and rectification indicators provide actionable information to address failures and improve safety conditions. This research describes a new perspective (rectification efficiency) for safety assessment, which supplements the current body of knowledge on safety assessment. The proposed index, SPI, promotes the adoption of proactive hazard identification, monitoring, and control in construction.

ACS Style

Mei Liu; Pin-Chao Liao. Integration of hazard rectification efficiency in safety assessment for proactive management. Accident Analysis & Prevention 2019, 129, 299 -308.

AMA Style

Mei Liu, Pin-Chao Liao. Integration of hazard rectification efficiency in safety assessment for proactive management. Accident Analysis & Prevention. 2019; 129 ():299-308.

Chicago/Turabian Style

Mei Liu; Pin-Chao Liao. 2019. "Integration of hazard rectification efficiency in safety assessment for proactive management." Accident Analysis & Prevention 129, no. : 299-308.