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Safety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.

Based on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.

The research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.

Considering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.

This research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.

This research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

This paper aims to design a novel feature descriptor to improve the performance of feature matching in challenge scenes, such as low texture and wide-baseline scenes. Common descriptors are not suitable for low texture scenes and other challenging scenes mainly owing to encoding only one kind of features. The proposed feature descriptor considers multiple features and their locations, which is more expressive.

A graph neural network–based descriptors enhancement algorithm for feature matching is proposed. In this paper, point and line features are the primary concerns. In the graph, commonly used descriptors for points and lines constitute the nodes and the edges are determined by the geometric relationship between points and lines. After the graph convolution designed for incomplete join graph, enhanced descriptors are obtained.

Experiments are carried out in indoor, outdoor and low texture scenes. The experiments investigate the real-time performance, rotation invariance, scale invariance, viewpoint invariance and noise sensitivity of the descriptors in three types of scenes. The results show that the enhanced descriptors are robust to scene changes and can be used in wide-baseline matching.

A graph structure is designed to represent multiple features in an image. In the process of building graph structure, the geometric relation between multiple features is used to establish the edges. Furthermore, a novel hybrid descriptor for points and lines is obtained using graph convolutional neural network. This enhanced descriptor has the advantages of both point features and line features in feature matching.

This paper aims to prepare third-order nonlinear optical (NLO) organic materials with large nonlinear optimization value, high damage threshold and ultrafast response time.

A series of novel symmetric and asymmetric compounds possessing third-order NLO properties were synthesized using 1,3,5-tribromobenzene as the basis. The photophysical and electrochemical properties, as well as the click reactions, were characterized by means of UV–VIS–NIR absorption spectroscopy and cyclic voltammetry.

The donor–acceptor chromophores were inserted into compound, making the molecule to have a broader absorption in the near-infrared regions and a narrower optical and electrochemical band gap. It also formed an electron-delocalized organic system, which has larger effects on achieving a third-order NLO response. The third-order NLO phenomenon of benzene ring complexes was experimentally studied at 532 nm using Z-scan technology, and some compounds showed the expected NLO properties.

The click products exhibit more NLO phenomena by performing different click combinations to the side groups, opening new perspectives on using the system in a variety of photoelectric applications.

This study aims to expand tourism knowledge by analysing literature review articles published in English Web of Science (WOS) and Chinese China National Knowledge Infrastructure (CNKI) language journals and reviewing their influence, interconnection and trends.

A three-stage method was designed to understand the tourism research progress. Performance analysis identified the publication timeline, high-yielding journals and authors that published tourism literature reviews and frequently cited papers. Science mapping visualisation examined the intrinsic connections between co-authorship and co-institution. Finally, emerging trend analysis explored the topic modelling and evolution through Latent Dirichlet allocation (LDA) and regression.

The key statistics and collaborations relationships of tourism literature reviews were traced. LDA identified 45 and 22 topics, which narrowed the barriers in tourism studies. The regression analysis divided these topics into “hot”, “fresh”, “bell-shaped” and “stable” patterns. These modes represent the progress of tourism studies. The topic “new emerging technologies and the internet” is the focus of tourism literature reviews published in both databases. Future research could pay more attention to the topics in the “hot” and “fresh” patterns. The results enrich the progress of tourism literature reviews and provide a direction for future research.

To the best of the authors’ knowledge, this study is the first literature analysis for tourism literature reviews published in WOS versus CNKI journals. The proposed three-stage systematic method is used for the first time for the literature review and can guide future research.

本研究旨在通过分析英文WOS和中文CNKI语言期刊上发表的文献综述文章, 回顾其影响、相互联系和趋势, 来扩大旅游知识体系。

本研究设计了一个三阶段方法来了解旅游研究进展。绩效分析确定了出版时间线、发表的旅游文献综述的高产期刊和作者以及经常被引用的文章。科学地图可视化审视了合作作者和合作机构之间的内在联系。最后, 新兴趋势分析通过潜在狄利克雷分配和回归探讨了主题建模和演变。

本文追踪了旅游文献综述的关键统计数据和合作情况。潜在狄利克雷分配确定了45个和22个主题, 这缩小了旅游研究中的研究缺口。回归分析将这些主题分为“热门”、“新鲜”、“钟形”和“稳定”模式。这些模式代表了旅游研究的进展。主题“新兴技术和互联网”是不同数据库中发表的旅游文献综述的焦点。未来的研究可以更多地关注“热门”和“新鲜”模式中的主题。研究结果丰富了旅游文献综述的进展, 为今后的研究提供了方向。

这项研究是首次对WOS与CNKI期刊上发表的旅游文献评论进行文献分析。所提出的三阶段系统方法首次用于文献综述, 可以指导未来的研究。

El objetivo de este estudio es ampliar el conocimiento turístico analizando los artículos de revisión documental publicados en revistas, tanto en la versión WOS en inglés cómo en CNKI China, y revisando sus efectos, interconexiones y tendencias.

Se ha diseñado el método de tres etapas para comprender el progreso de la investigación turística. El análisis del desempeño determinó la línea de tiempo de publicación, las revistas de alto rendimiento y los comentarios de la literatura turística publicados por los autores, así como los artículos citados con frecuencia. La visualización de los mapas científicos, examina los vínculos intrínsecos entre los autores colaboradores y las instituciones colaboradoras. Finalmente, el análisis de tendencias emergentes explora el modelado temático y la evolución a través de posibles asignaciones y regresiones de dilick-ray.

Se han analizado las estadísticas clave y las relaciones de cooperación de la revisión de la literatura turística. La asignación potencial de dilich-ray identifica 45 y 22 temas, lo que reduce las barreras en la investigación turística. El análisis de regresión divide estos temas en patrones “populares”, “novedosos”, “en forma de campana” y “estables”. Estos modelos representan el avance de la investigación turística. El tema “tecnologías emergentes e internet” es el foco de la revisión de la literatura turística publicada en diferentes bases de datos. La investigación futura puede centrarse más en temas en modelos “populares” y “novedosos”. Los resultados de la investigación enriquecen el progreso de la revisión de la literatura turística y proporcionan una dirección para futuras investigaciones.

El estudio es el primer análisis documental de los comentarios de la literatura turística publicados en las revistas WOS y CNKI. El método sistemático de tres etapas propuesto se utiliza por primera vez en la revisión documental y puede guiar futuras investigaciones.

This study aims to use event system theory and job demands–resources (JD-R) model to examine the double-edged sword effect of event strength of Beijing Winter Olympics (BWO) on volunteers’ in-role performance and proactive behavior as mediated by work overload and meaningfulness.

The sample included 193 volunteer–leader dyads working at one BWO venue. The authors conducted a multitime and multisource study using Mplus 8 to examine the hypotheses.

Volunteers’ perceived BWO event strength was positively related to work overload, which reduced in-role performance and proactive behavior. Volunteers’ perceived BWO event strength was also positively related to work meaningfulness, which promoted in-role performance and proactive behavior. Perceived organizational support served as a moderator by mitigating the positive relationship between perceived BWO event strength and work overload; however, it did not strengthen the positive relationship between perceived BWO event strength and work meaningfulness.

This study developed a comprehensive model of how BWO event strength affected volunteers’ performance from the perspective of event system theory and the JD-R model, which enriches theoretical application and research in the context of mega sport events.

本研究运用事件系统理论和工作需求-资源(JD-R)模型, 探讨了2022年北京冬奥会（BWO）事件强度通过工作负荷和工作意义感知进而对志愿者角色内绩效和主动性行为的双刃剑效应。

我们在冬奥会场所之一实施了多时点、多来源的收集数据的方式, 最终样本包括193份志愿者-领导配对数据, 并使用Mplus 8来检验我们的假设。

志愿者感知的BWO事件强度与工作负荷呈正相关, 进而会降低他们的角色内绩效和主动性行为。志愿者感知的BWO事件强度与工作意义感也呈正相关, 进而会促进他们的角色内绩效和主动性行为。感知的组织支持通过弱化BWO事件强度与工作负荷之间的正相关关系, 进而调节了志愿者的角色内绩效和主动性行为; 然而, 感知的组织支持并没有强化BWO事件强度与工作意义感之间的正相关关系。

本研究结合事件系统理论和JD-R模型, 发展了一个BWO事件强度对志愿者绩效表现影响的综合模型, 丰富了有关大型体育赛事志愿者的理论应用和研究。

Este estudio utiliza la teoría del sistema de eventos y el modelo de demandas de trabajo-recursos (JD-R) para examinar el efecto de doble filo de la fuerza del evento de los Juegos Olímpicos de Invierno de Pekín (BWO) sobre el rendimiento en el rol y el comportamiento proactivo de los voluntarios, mediado por la sobrecarga laboral y la significatividad del trabajo.

Nuestra muestra incluyó 193 díadas de voluntarios-líderes que trabajaban en una sede de BWO. Realizamos un estudio multitemporal y multifuente utilizando Mplus 8 para examinar nuestras hipótesis.

La intensidad percibida por los voluntarios en los eventos de BWO también se relacionó positivamente con la significación del trabajo, que promovió el rendimiento en el rol y el comportamiento proactivo. Además, el apoyo organizativo percibido sirvió como moderador al mitigar la relación positiva entre la intensidad percibida del evento BWO y la sobrecarga de trabajo; sin embargo, no reforzó la relación positiva entre la intensidad percibida del evento BWO y la significatividad del trabajo.

Este estudio desarrolló un modelo integral de cómo la fuerza del evento BWO afectaba al rendimiento de los voluntarios desde la perspectiva de la teoría del sistema de eventos y el modelo JD-R, lo que enriquece la aplicación teórica y la investigación en el contexto de los megaeventos deportivos.

The purpose of this paper is twofold: first, it explores the influencing factors of the government’s trust decision-making in the private sector; second, it explores how these influencing factors affect the government’s trust decisions.

A theoretical model was established, and a questionnaire survey was conducted among 152 professionals. The collected datas were analyzed by the structural equation modeling (SEM) method.

The study identified four critical factors that influence the government’s decision to trust the private sector in public-private-partnership (PPP) projects. All the four factors have a positively correlated impact on the government’s trust decision-making. The structural equation path analysis shows that the most important factor affecting the government’s trust decision-making is the trustee’s (private sector) trustworthy characteristics, and the path coefficient is 0.92. The path coefficients of risk perception and the trustor’s trust tendency are 0.83 and 0.74, respectively. The influence of the legal system environment on government trust decision-making is moderate, with a path coefficient of 0.68.

This paper contributes to the literature in two aspects. First, the factors influencing decision-making to government trust in the private sector in PPP projects have been identified. Second, a comprehensive view of the mechanism of government trust in the private sector in PPP projects has been theorized by the SEM method.

This paper aims to explore the impact of cycle superposition on bank liquidity risk under different levels of financial openness so that banks can better manage their liquidity risk. Meanwhile, it can also provide some ideas for banks in other emerging economies to better cope with the shocks of the global financial cycle.

Employing the monthly data of 16 commercial banks in China from 2005 to 2021 and based on the time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR) model, the authors first examine whether the cycle superposition can magnify the impact of China's financial cycle on bank liquidity risk. Subsequently, the authors investigate the impact of different levels of financial openness on cycle superposition amplification. Finally, the shock of the financial cycle of the world's major economies on the liquidity risk of Chinese banks is also empirically analyzed.

Cycle superposition can magnify the impact of China's financial cycle on bank liquidity risk. However, there are significant differences under different levels of financial openness. Compared with low financial openness, in the period of high financial openness, the magnifying effect of cycle superposition is strengthened in the short term but obviously weakened in the long run. In addition, the authors' findings also demonstrate that although the United States is the main shock country, the influence of other developed economies, such as Japan and Eurozone countries, cannot be ignored.

Firstly, the cycle superposition index is constructed. Secondly, the authors supplement the literature by providing evidence that the association between cycle superposition and bank liquidity risk also depends on financial openness. Finally, the dominant countries of the global financial cycle have been rejudged.

The purpose of this paper is to find how those uncertainty factors influence transaction costs generated and to identify ways to minimize the transaction costs borne by the construction owner.

The literature indicates that there is no consensus on a standard definition of transaction costs in the construction industry. A detailed literature review of research work on transaction costs in construction is conducted in order to identify the determinants of transaction costs in construction projects. A structural equation model is tested on data collected by means of a survey administered to construction owners.

The findings indicate that the transaction costs borne by the owner can be minimized if the owner minimizes the uncertainties inherent in the construction project by making sure the engineering design is as complete as possible before bids are sought from contractors; harmonious relationships between project participants; fair risk allocation; have experience in similar type projects; and contractor selection practices that routinely detect irregular behavior.

The data used in this research are primarily based on the experiences of public owners and the markets in which they operate; a larger representation of private owners could make the conclusions more general. Another limitation of the study is that it relies on a survey of opinions rather than actual records of costs and other hard data.

No empirical study has ever been conducted of transaction-related issues in the construction industry because of the lack of a common understanding of transaction cost. This paper provides the groundwork for such a study.

This paper attempts to reconcile the many determinants of transaction costs in construction projects under uncertainty considered by different researchers in a multitude of research studies.

Servitization and research and development (R&D) innovation provide new developmental opportunities for transformation in the construction industry. This study aims to explore the transformative impact of servitization and R&D innovation on the value added of the construction industry, offering new insights into industry transformation and growth.

This study utilizes panel data from Chinese listed construction companies from 2014 to 2022 to empirically investigate the relationship among servitization, R&D innovation and value added in the construction industry. The data analysis is augmented by incorporating text mining techniques to rigorously investigate the interplay among servitization, R&D innovation and the value added within the construction industry.

The research findings indicate that the impact of servitization on value added follows a positive U-shaped relationship, while the influence of R&D innovation on value added exhibits an inverted U-shaped relationship. Additionally, innovation investment plays a negative moderating role in the relationship between servitization and value added.

This study reveals a fresh perspective on how construction companies can leverage servitization as a strategic pathway for transformation and competitive advantage. The research also lays a theoretical groundwork for future innovation investment strategies in the construction industry, emphasizing the need for a balanced approach to innovation investments to maximize value added.