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Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.

The purpose of this study is to develop a new hybrid method that combines interpretative structural modeling (ISM) and matrix cross-impact multiplication applied to classification (MICMAC) to investigate the influencing factors of sustainable infrastructure vulnerability (SIV).

(1) Literature review and case study were used to identify the possible influencing factors; (2) a semi-structured interview was conducted to identify representative factors and the interrelationships among influencing factors; (3) ISM was adopted to identify the hierarchical structure of factors; (4) MICMAC was used to analyze the driving power (DRP) and dependence power (DEP) of each factor and (5) Semi-structured interview was used to propose strategies for overcoming SIV.

Results indicate that (1) 18 representative factors related to SIV were identified; (2) the relationship between these factors was divided into a five-layer hierarchical structure. The 18 representative factors were divided into driving factors, dependent factors, linkage factors and independent factors and (3) 12 strategies were presented to address the negative effects of these factors.

The findings illustrate the factors influencing SIV and their hierarchical structures, which can benefit the stakeholders and practitioners of an infrastructure project by encouraging them to take effective countermeasures to deal with related SIVs.

While the potential of human resource practices (HRPs) for promoting performance is widely recognized, even though crucial, employees’ assessment of HRPs remains under-researched, especially in emerging economies. Hence, the purpose of this research is to examine the influence of employee satisfaction with HRPs on job performance through the mediating role of job dedication (JD) and the moderating role of incentive gamification.

The current research adopts a quantitative method. Specifically, using a questionnaire survey, 418 valid responses collected (through purposive sampling) via cross-sectional method from the employees of Nigerian Information and Communication Technology (ICT) firms were used to test the research hypotheses empirically.

The results revealed that satisfaction with HRPs has a positive influence on job performance. Satisfaction with human resource practices has a positive influence on job dedication. Job dedication has a positive influence on job performance. The link between employees’ satisfaction with human resource practices and job performance is mediated by job dedication. The link between satisfaction with human resource practices and job dedication is moderated by incentive gamification, that is, the positive link is stronger when incentive gamification is high. The link between satisfaction with human resource practices and job performance is moderated by incentive gamification, that is, the positive link is stronger when incentive gamification is high.

The current study highlights the importance of employees’ assessments of human resource practices, which may be used to promote employee dedication, which in turn results in improved performance. The findings are helpful to open the black box of the impact of satisfaction with HRPs on job performance. The results also offer important new valuable guidance for practitioners and will aid the management of human resource practice design, audits, and communication.

The normalization of COVID-19 disease prevention has presented a major opportunity for the transformation and upgrade of cultural and tourism products in Taiwan. This paper aims to explore the attractiveness of Taiwanese military dependents’ villages, known as juancun, two studies were conducted to test the path relationships of juancun experiencescape, authenticity, memorability and revisit intention.

This research conducted two studies by using a mixed sampling of snowball sampling and purposive sampling for the questionnaire survey. Based on the 397 valid questionnaires retained in Study 1, a cultural heritage site experiencescape was developed and validated; in Study 2, 393 valid questionnaires were collected, and structural equation modeling was conducted to test hypotheses that were developed drawing on the stimulus–organism–response model and theory of buyer behavior.

It is revealed that cultural heritage site experiencescape include natural and cultural, social, sensory and functional factors and that the experiencescape affects authenticity positively; “existential authenticity–memorability” mediates the relationship of experiencescape and revisit intention, whereas co-creation behavior has the positive moderating effects on the relationship of experiencescape and authenticity.

The research developed an experiencescape scale for cultural heritage sites and described the managerial implications for destination management organizations regarding product development and service design.

COVID-19疫情防控的常态化为台湾的文化和旅游产品升级转型提供了巨大的契机。为了明确台湾眷村的旅游吸引力, 本研究操作两个研究设计以检定眷村体验景观、真实性、难忘性及重游意图之间的路径关系。

本研究操作的两个研究设计皆采用滚雪球抽样和目的性抽样的混合抽样方法进行问卷调查。基于研究设计一回收的397份有效问卷, 发展和验证了眷村文化遗产地体验景观量表; 运用研究设计二回收的393份有效问卷, 操作结构方程模型分析以检定基于刺激-机体-反应理论和买方行为理论发展的假设。

本研究揭示了文化遗产地体验景观包含自然与文化、社会、感官、功能性因素; 体验景观正向影响真实性; “存在主义真实性-难忘性”中介调节体验景观和重游意图的关系; 共创行为正向调节体验景观与真实性的关系。

本研究发展了文化遗产地体验景观量表, 并就产品发展和服务设计为旅游目的地管理组织提供了实务建议。

Esta investigación llevó a cabo dos estudios mediante un muestreo mixto de bola de nieve y muestreo intencionado para la encuesta por cuestionario. A partir de los 397 cuestionarios válidos retenidos en el Estudio 1, se desarrolló y validó el experiencescape del patrimonio cultural; en el Estudio 2, se recogieron 393 cuestionarios válidos y se realizó un modelado de ecuaciones estructurales para probar las hipótesis que se desarrollaron a partir del modelo estímulo-organismo-respuesta y la teoría del comportamiento del comprador.

La normalización de la prevención de la enfermedad COVID-19 ha supuesto una gran oportunidad para la transformación y mejora de los productos culturales y turísticos de Taiwán. Para explorar el atractivo de las aldeas de los familiares de militares en Taiwan, conocidos como juancun, se realizaron dos estudios para probar las relaciones de trayectoria del experiencescape del juancun, la autenticidad, la memorabilidad y la intención de volver a visitarlo.

Se revela que el experiencescape del patrimonio cultural de la aldea militar incluye factores naturales y culturales, sociales, sensoriales y funcionales, y que el experiencescape afecta positivamente a la autenticidad; la “autenticidad existencial-memorabilidad” media en la relación del experiencescape y la intención de volver a visitarlo, mientras que el comportamiento de cocreación tiene los efectos moderadores positivos en la relación del experiencescape y la autenticidad.

La investigación desarrolló una escala de experiencescape para el patrimonio cultural del sitio y describió las implicaciones gerenciales para las organizaciones de gestión de destinos en relación con el desarrollo de productos y el diseño de servicios.

This paper establishes a quality model for automation assembly of range hood impeller based on generalized grey relational degree, it improves the debugging efficiency of the newly developed assembly workstation.

First, spot check the trial production impellers and obtain three indexes that reflect the assembly quality of the impellers. Then, analyze the parameters that affect the assembly quality of the impeller using grey relational analysis (GRA), establish a model for the assembly quality of the range hood impeller based on the generalized grey relational degree and identify the main parameters. After that, analyze the transmission structure of automation assembly workstation, identify the reasons that affect parameters and propose improvement plans. Finally, a trial production is conducted on the automation assembly workstation after adopting the improved plan to verify the quality model of impeller automation assembly.

The research shows that compared to manual assembly, the automation assembly quality of the impeller using GRA model has been improved, shortening the debugging cycle of the newly developed assembly workstation.

The newly developed automation equipment will have some problems in the trial production stage, which often rely on the experience of engineers for debugging. In this paper, the automation assembly quality model of range hood impeller based on GRA is established, which can not only ensure the quality of finished impeller but also shorten the debugging cycle of the equipment. In addition, GRA can be widely used in the commissioning of other automation equipment.

This study has developed a set of impeller automation assembly workstation. The debugging method in the trial production stage is beneficial to shorten the trial production time and improve the economic benefits.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

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.