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The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

This study aims to investigate low-carbon footprint travel choices, considering both destination attributes and climate change perceptions, and examine the impacts of nudging (a communication tool to alter individuals’ choices in a predictable way) on tourists’ preferences for carbon mitigation in destinations.

A discrete choice experiment questionnaire was administered to a sample of 958 Hong Kong respondents. Hybrid choice modeling was used to examine the respondents’ preferences for destination attributes and to explain preference heterogeneity using tourists’ climate change perceptions. The respondents’ willingness to pay for the destination attributes was also calculated to measure the monetary value of the attributes.

Destination type, carbon emissions and travel cost had significant effects on tourists’ choices of destination. Nudging increased tourists’ preference for low-carbon footprint choices. Tourists with higher climate change perceptions were more likely than others to select low-carbon destinations with carbon offset projects.

The findings of this study provide an impetus for destination management organizations to support local carbon offset projects, implement policies that mitigate carbon emissions and develop sustainable tourism to fulfill tourists’ demand for low-carbon footprint travel choices. Based on the findings, policymakers could promote sustainable tourism by publishing relevant climate change information on social media.

This study addressed a gap in the literature on tourist travel choice by considering carbon emission-related attributes and climate change perceptions and by confirming the role of nudging in increasing the choice of low-carbon destinations.

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.

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.

The main purpose of this research paper is to generate a holistic bibliometric study of the tourism industry and COVID-19 fields, to further investigate the current interests and trends emerging from scientific collaboration and thematic analysis and to identify research gaps that indicate future research directions.

This study conducts several analyses, which include the co-authorship and social network analysis, co-citation and keyword co-occurrence knowledge structures. The authors generate a knowledge map of the leading articles and link them with previous literature to elucidate the debates and consensus in research on COVID-19 and tourism.

Research interests concentrate in the USA, China, Europe and the Oceania areas, so more cross-continental collaborations are expected among them and with other regions. Popular topics are tourism sustainable transformation, crisis management and multidisciplinary fields like tourism, hospitality, information technology and environmental sciences. This paper also identifies underexplored topics for future investigation on the social, environmental, cultural and governance dimensions of sustainable tourism.

This paper contributes to guiding tourism researchers in identifying and finding publication references and future collaborations. Moreover, the investigation of knowledge structures could be beneficial for scholars hoping to broaden the current understanding of this field and discover potential for future tourism research, especially in the global pandemic and other severe health crises.

This study enriches the existing literature in the fields of tourism and the pandemic and highlights current interests and research trends exploring scientific collaboration, thematic analysis and knowledge mapping.

During the construction process of the China Railway Track System (CRTS) I type filling layer, the nonwoven fabric bags have been used as grouting templates for cement asphalt (CA) emulsified mortar. The porous structure of nonwoven fabrics endowed the templates with breathability and water permeability. The standard requires that the volume expansion rate of CA mortar must be controlled within 1%–3%, which can generate expansion pressure to ensure that the cavities under track slabs are filled fully. However, the expansion pressure caused some of the water to seep out from the periphery of the filling bag, and it would affect the actual mix proportion of CA mortar. The differences in physical and mechanical properties between the CA mortar under track slabs and the CA mortar formed in the laboratory were studied in this paper. The relevant results could provide important methods for the research of filling layer materials for CRTS I type and other types of ballastless tracks in China.

During the inspection of filling layer, the samples of CA mortar from different working conditions and raw materials were taken by uncovering the track slabs and drilling cores. The physical and mechanical properties of CA mortar under the filling layer of the slab were systematically analyzed by testing the electrical flux, compressive strength and density of mortar in different parts of the filling layer.

In this paper, the electric flux, the physical properties and mechanical properties of different parts of CA mortar under the track slab were investigated. The results showed that the density, electric flux and compressive strength of CA mortar were affected by the composition of raw materials for dry powders and different parts of the filling layer. In addition, the electrical flux of CA mortar gradually decreased within 90 days’ age. The electrical flux of samples with the thickness of 54 mm was lower than 500 C. Therefore, the impermeability and durability of CA mortar could be improved by increasing the thickness of filling layer. Besides, the results showed that the compressive strength of CA mortar increased, while the density and electric flux decreased gradually, with the prolongation of hardening time.

During 90 days' age, the electrical flux of the CA mortar gradually decreased with the increase of specimen thickness and the electrical flux of the specimens with the thickness of 54 mm was lower than 500 C. The impermeability and durability of the CA mortar could be improved by increasing the thickness of filling layer. The proposed method can provide reference for the further development and improvement of CRTS I and CRTS II type ballastless track in China.

The construction of cement asphalt (CA) emulsified mortar can obviously disturb the slab status after the fine adjustment. To decrease or eliminate the influence of CA mortar grouting on track slab geometry status, the effects of grouting funnel, slab pressing method, mortar expansion ratio, seepage ratio and grouting area on China Railway Track System Type (CRTS I) track slab geometry status were discussed in this paper.

Combined with engineering practice, this paper studied the expansion law of filling layer mortar, the liquid level height of the filling funnel, the pressure plate device and the amount of exudation water and systematically analyzed the influence of filling layer mortar construction on the state of track slab. Relevant precautions and countermeasures were put forward.

The results showed that the track slab floating values of four corners were different with the CA mortar grouting and the track slab corner near CA mortar grouting hole had the maximum floating values. The anti-floating effect of “7” shaped slab pressing device was more efficient than fixed-joint angle iron, and the slab floating value could be further decreased by increasing the amount of “7” shaped slab pressing devices. After CA mortar grouting, the track slab floating pattern had a close correlation with the expansion rate and water seepage rate of CA mortar over time and the expansion and water seepage rate of the mortar were faster when the temperature was high. Furthermore, the use of strip CA mortar filling under the rail bearing platform on both sides could effectively reduce the float under the track slab, and it could also save mortar consumption and reduce costs.

This study plays an important role in controlling the floating values, CA mortar dosage and the building cost of projects by grouting CA mortar at two flanks of filling space. The research results have guiding significance for the design and construction of China's CRTS I, CRTS II and CRTS III track slab.

Artificial intelligence (AI) and big data analysis may further enhance the automated and smart features of tourism and hospitality services. However, it also poses new challenges to human resource management. This study aims to explore the direct and indirect effects of employees’ AI perception on career resilience and informal learning as well as the mediating effect of career resilience.

This paper proposed a theoretical model of AI perception, career resilience and informal learning with perceived AI as the antecedent variable, career resilience as the mediate variable and informal learning as the endogenous variable. Targeting the employees working with AI, a total of 472 valid data were collected. Data were analyzed using structural equation modeling with AMOS software.

Findings indicated that employees’ perception of AI positively contributes to career resilience and informal learning. Apart from the direct effect on informal learning, career resilience also mediates the relationship between AI perception and informal learning.

Research findings provide both theoretical and practical implications by revealing the impact of AI perception on employees’ career development, leaning activities, explaining how AI transforms the nature of work and career development and shedding lights on human resource management in the tourism and hospitality field.

本文提出了人工智能感知为前因变量、职业弹性为中介变量、非正式学习为内生变量的理论模型。以旅游业AI工作环境中的员工为研究对象, 本课题共收集了472份来自中国的有效数据, 并通过结构方程建模（SEM）来进行相关模型检验。

人工智能和大数据分析可能会使旅游和酒店服务更加自动化和智能化, 但这也对人力资源管理提出了新的挑战。本研究旨在探讨员工对人工智能（AI）的感知对职业弹性和非正式学习的直接和间接影响, 以及职业弹性的中介作用。

研究结果显示, 员工对人工智能的感知对职业弹性和非正式学习有积极影响。除了对非正式学习的直接影响外, 职业弹性在人工智能 (A I) 感知和非正式学习之间起中介作用。

本研究在以下几个方面具有重要的理论和实践意义：解释了人工智能感知对员工职业发展和学习行为的影响, 以及它是如何改变工作性质和员工职业发展的; 研究发现对旅游和酒店行业的人力资源管理具有实践指导意义。

La IA y el análisis de big data pueden potenciar aún más las características automatizadas e inteligentes de los servicios de turismo y hostelería. Sin embargo, también plantea nuevos retos a la gestión de los recursos humanos. Este estudio pretende explorar los efectos directos e indirectos de la percepción de la IA por parte de los empleados sobre la resiliencia profesional y el aprendizaje informal, así como el efecto mediador de la resiliencia profesional.

En este trabajo se propone un modelo teórico de percepción de la IA, resiliencia profesional y aprendizaje informal con la IA percibida como variable antecedente, la resiliencia profesional como variable mediadora y el aprendizaje informal como variable endógena. Dirigidos a los empleados que trabajan con IA, se recogieron un total de 472 datos válidos. Los datos se analizaron mediante un modelo de ecuaciones estructurales (SEM) con el software AMOS.

Los Resultados indicaron que la percepción de la IA por parte de los empleados contribuye positivamente a la resiliencia profesional y al aprendizaje informal. Aparte del efecto directo sobre el aprendizaje informal, la resiliencia profesional también media en la relación entre la percepción de la IA y el aprendizaje informal.

Los Resultados de la investigación proporcionan implicaciones tanto teóricas como prácticas al revelar el impacto de la percepción de la IA en el desarrollo profesional de los empleados, las actividades de aprendizaje, explicar cómo la IA transforma la naturaleza del trabajo y el desarrollo profesional, y arrojar luz sobre la gestión de los recursos humanos en el ámbito del turismo y la hostelería.

With the growing concern of various sectors of society regarding environmental issues and the promotion of sustainable development, green technology innovation is generally considered to be conducive to the long-term development of enterprises. However, because of the existence of agency problems, managers may have shortsighted behaviors. Then how will managers' shortsighted behaviors affect enterprises' green technology innovation?

This paper uses machine learning-based text analysis methods to construct a manager myopia index based on the data from A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2015 to 2020. We examine the impact of manager myopia on green technology innovation in companies.

Our study finds that manager myopia significantly inhibits green technology innovation in companies. However, when multiple large shareholders coexist and the proportion of institutional investors' holdings is high, it can alleviate the inhibitory effect of manager myopia on green innovation. Heterogeneity tests show that the impact of manager myopia on green technology innovation is relatively significant in non-state-owned and manufacturing companies, as well as in the electricity industry. Robustness tests demonstrate that our conclusions remain valid after using propensity score matching to eliminate endogeneity problems.

From the perspective of corporate governance, this paper incorporates managers' shortsightedness, multiple large shareholders and institutional investors' shareholding ratios into the same logical framework, analyzes their internal mechanisms, helps improve corporate governance, enhances green innovation capabilities and has strong implications for the implementation of national innovation-driven development strategies and the achievement of “carbon peak” and “carbon neutrality” targets.

The main purpose of this paper is to explore the impact of digital transformation on enterprises' performance considering financing constraints in the capital market to explore whether digital transformation improves enterprises' performance through the financing constraints channel.

This study, using a panel data set of 14,669 observations of 2,858 non-financial enterprises that issued A shares on the Shanghai and Shenzhen stock exchanges from 2013 to 2019, theoretically and empirically tests the impact and mechanism of digital transformation on enterprise performance.

Digital transformation has a significant positive effect on enterprise performance; this conclusion remains the same after the robustness test and endogeneity problems are dealt with. Financing constraints play a mediation role between digital transformation and enterprise innovation. The effect of digital transformation on enterprise performance varies significantly by size, ownership and industry.

The theoretical contributions of this study not only enrich the literature on the economic benefits and mechanism of digital transformation but also expand the literature on the factors that influence enterprise performance. The practical contribution of this study is the reference that it provides for implementing decisions about enterprise digital transformation and formulating differentiated policies for government digital transformation.