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The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention from investors, policy makers and researchers. This study investigates neural networks for composite property price index forecasting from ten major Chinese cities for the period of July 2005–April 2021.

The goal is to build simple and accurate neural network models that contribute to pure technical forecasts of composite property prices. To facilitate the analysis, the authors consider different model settings across algorithms, delays, hidden neurons and data spitting ratios.

The authors arrive at a pretty simple neural network with six delays and three hidden neurons, which generates rather stable performance of average relative root mean square errors across the ten cities below 1% for the training, validation and testing phases.

Results here could be utilized on a standalone basis or combined with fundamental forecasts to help form perspectives of composite property price trends and conduct policy analysis.

The primary objective of this study is to ascertain how Metaverse technologies, primarily virtual reality (VR) and augmented reality (AR), redefine tourism experiences. It aims to delve into the capabilities of these technologies in eliminating conventional physical and economic barriers and enabling virtual exploration of destinations. Additionally, this study seeks to understand how tourism enterprises can leverage Metaverse technologies for operational efficiency and enhance customer satisfaction.

This research uses a two-pronged methodological approach, incorporating bibliometric analysis techniques and a systematic literature review. Bibliometric analysis provides a quantitative assessment of existing literature, identifying key trends, authors and publications in the domain of Metaverse tourism. Concurrently, this systematic literature review qualitatively evaluates the content and context of these studies, focussing on the applications of VR and AR in tourism as well as the managerial and consumer implications therein.

The findings reveal a significant uptick in literature production in the Metaverse tourism domain post-2018, indicating a burgeoning interest in this field. Metaverse facilitates a unique blend of engaging and personalised tourism experiences from the comfort of one’s home. Moreover, tourism enterprises stand to gain from streamlined booking processes and to improve operational efficiency, which in turn augments customer satisfaction.

This research is confined to the analysis of the existing literature and does not involve primary data collection, which could limit the comprehensiveness of the insights. Moreover, the nascent stage of Metaverse technology in tourism presents a challenge in deriving conclusive implications. This study underscores the need for further empirical research to validate the theoretical frameworks discussed and explore the long-term implications of Metaverse technologies in the tourism sector.

Metaverse opens avenues for tourism enterprises to enhance their customer engagement and operational efficiency. It offers a novel platform for immersive and personalised travel experiences, thereby potentially increasing the market reach and customer satisfaction. The streamlined processes facilitated by Metaverse could also lead to cost reduction and increased profitability for tourism enterprises.

The integration of Metaverse technologies could democratise travel experiences, allowing individuals who might be economically or physically constrained to virtually explore global destinations. However, it also raises concerns regarding the digital divide and potential loss of authentic human interactions and cultural exchanges that traditionally characterise tourism.

This study is among the pioneering efforts to quantitatively and qualitatively analyse the burgeoning field of metaverse tourism. By amalgamating bibliometric analysis with a systematic literature review, it unveils the potential of Metaverse technologies in transcending conventional tourism paradigms, presenting a comprehensive understanding of the practical, managerial and consumer-centric implications therein.

本研究采用了双管齐下的方法, 既有文献计量分析技术, 又有系统的文献综述。文献计量分析对现有文献进行定量评估, 确定元旅游领域的主要趋势、作者和出版物。同时, 系统性文献综述对这些作品的内容和背景进行了定性评估, 重点关注虚拟现实（VR）和增强现实（AR）在旅游业中的应用以及对管理和消费者的影响。

本研究的主要目的是确定元宇宙技术（主要是 VR 和 AR）如何重新定义旅游体验。研究旨在深入探讨这些技术在消除传统物理和经济障碍以及实现目的地虚拟探索方面的能力。此外, 本研究还试图了解旅游企业如何利用元数据技术提高运营效率和客户满意度。

研究结果表明, 2018 年后, Metaverse 旅游领域的文献产量大幅上升, 表明人们对这一领域的兴趣日益浓厚。Metaverse 可以让人们在家中就能享受到独特的个性化旅游体验。此外, 旅游企业可从简化预订流程和提高运营效率中获益, 进而提高客户满意度。

本研究仅限于对现有文献的分析, 不涉及原始数据收集, 这可能会限制研究见解的全面性。此外, Metaverse 技术在旅游业中的应用尚处于起步阶段, 这对得出结论性影响提出了挑战。本研究强调有必要开展进一步的实证研究, 以验证所讨论的理论框架, 并探索元数据技术在旅游业中的长期影响。

Metaverse 为旅游企业提高客户参与度和运营效率开辟了道路。它为身临其境的个性化旅游体验提供了一个新颖的平台, 从而有可能提高市场覆盖率和客户满意度。Metaverse 推动的简化流程还可降低旅游企业的成本, 提高其盈利能力。

Metaverse 技术的整合可以使旅游体验平民化, 让经济或身体条件有限的人也能以虚拟方式探索全球旅游目的地。然而, 它也引发了人们对数字鸿沟的担忧, 以及对传统旅游业所特有的真实人际互动和文化交流的潜在损失的担忧。

本研究是定量和定性分析新兴的 Metaverse 旅游领域的开创性研究之一。通过将文献计量学分析与系统的文献综述相结合, 本研究揭示了元数据技术在超越传统旅游范式方面的潜力, 并对其中的实用、管理和以消费者为中心的含义提出了全面的理解。

Esta investigación utiliza un enfoque metodológico doble, que incorpora técnicas de análisis bibliométrico y una revisión sistemática de la literatura. El análisis bibliométrico proporciona una evaluación cuantitativa de la literatura existente, identificando tendencias, autores y publicaciones clave en el ámbito del turismo en el Metaverso. Al mismo tiempo, la revisión sistemática de la literatura evalúa cualitativamente el contenido y el contexto de estos trabajos, centrándose en las aplicaciones de la Realidad Virtual (RV) y la Realidad Aumentada (RA) en el turismo, así como en sus implicaciones para la gestión y el consumidor.

El objetivo principal de este estudio es determinar cómo las tecnologías asociadas al Metaverso, principalmente la RV y la RA, redefinen las experiencias turísticas. Pretende profundizar en las capacidades de estas tecnologías para eliminar las barreras físicas y económicas convencionales y permitir la exploración virtual de los destinos. Además, este estudio pretende entender cómo las empresas turísticas pueden aprovechar las tecnologías relacionadas con el Metaverso para mejorar la eficiencia operativa y la satisfacción del cliente.

Los resultados revelan un aumento significativo en la producción de literatura en el ámbito del turismo en el Metaverso desde el año 2018, lo que indica un creciente interés en este campo. El Metaverso facilita una combinación única de experiencias turísticas atractivas y personalizadas desde la comodidad del hogar. Además, las empresas turísticas se benefician de la agilización de los procesos de reserva y la mejora de la eficiencia operativa, lo que a su vez aumenta la satisfacción del cliente.

La investigación se limita al análisis de la bibliografía existente y no incluye la recopilación de datos primarios, lo que podría limitar la exhaustividad de las conclusiones. Además, el estado incipiente de la tecnología relacionada con el Metaverso en el turismo supone un reto a la hora de extraer implicaciones concluyentes. Este estudio subraya la necesidad de realizar más estudios empíricos para validar los marcos teóricos discutidos y explorar las implicaciones a largo plazo de estas tecnologías en el sector turístico.

El Metaverso abre vías para que las empresas turísticas mejoren su compromiso con el cliente y su eficiencia operativa. Ofrece una plataforma novedosa para experiencias de viaje inmersivas y personalizadas, con lo que aumenta potencialmente el alcance del mercado y la satisfacción del cliente. La racionalización de los procesos facilitados por el Metaverso también podría conducir a la reducción de costes y al aumento de la rentabilidad de las empresas turísticas.

La integración de las tecnologías relacionadas con el Metaverso podría democratizar las experiencias de viaje, permitiendo a personas con limitaciones económicas o físicas explorar virtualmente destinos globales. Sin embargo, también suscita preocupación en relación con la brecha digital y la posible pérdida de interacciones humanas auténticas e intercambios culturales que tradicionalmente caracterizan al turismo.

Este estudio es uno de los pioneros en analizar cuantitativa y cualitativamente el creciente campo del turismo en el Metaverso. Amalgamando el análisis bibliométrico con una revisión sistemática de la literatura, desvela el potencial de las tecnologías relacionadas con el Metaverso para sacar a la luz los paradigmas turísticos convencionales, presentando una comprensión exhaustiva de sus implicaciones prácticas, de gestión y centradas en el consumidor.

This paper aims to establish the causal relationship between destination image and tourist motivation and engagement.

A causal model with seven hypotheses was tested into a sample of 438 domestic tourists in Acapulco (Mexico).

Cognitive destination image is the main antecedent of tourist engagement, exerting an important direct and indirect effect through push and pull motivations. Affective image also exerts a direct effect on tourist engagement and an indirect effect through push and pull motivations. Only pull motivations exert an influence on tourist engagement.

The study is based on domestic tourists at a sun and beach destination.

Destination management organisations should invest in the care, improvement and promotion of tourism resources. Online and offline communication campaigns should be based on tourism resources and experiences.

This paper fulfils three research gaps: destination image is associated with tourist engagement; tourist motivations affect tourist engagement; and destination image is associated with tourist motivations.

This study aims to analyze the entrepreneurial intention (EI) of Colombian researchers using machine learning (ML) techniques, considering their academic activity, contexts and social norms (SN).

Unsupervised classification techniques were applied, including principal component analysis, hierarchical clustering with the Ward method and a logistic model to evaluate the classification. This was done to group researchers according to their characteristics and EI.

The methodology used allowed the identification of three groups of academics with distinct characteristics, of which two showed a high presence of EI. The results indicate that EI is influenced by the connection with the private sector (consulting, intellectual property and applied research) and by the lack of institutional support from universities. Regarding SN, only the preference for entrepreneurial activity over being an employee and the social appreciation of entrepreneurial dedication were identified as predictors of EI.

The use of ML techniques to study the EI of researchers is uncommon. This study highlights the ability of the methodology used to identify differences between two groups of academics with similar characteristics but different levels of EI. One group was identified that, despite rejecting values associated with entrepreneurs, has a high predisposition to develop a career as an entrepreneur. This provides valuable information for designing policies that promote EI among Colombian researchers.

This study aims to explore the use of time series analyses to examine changes in travelers’ preferences in accommodation features by disentangling seasonal, trend and the COVID-19 pandemic’s once-off disruptive effects.

Longitudinal data are retrieved by online traveler reviews (n = 519,200) from the Canary Islands, Spain, over a period of seven years (2015 to 2022). A time series analysis decomposes the seasonal, trend and disruptive effects of six prominent accommodation features (view, terrace, pool, shop, location and room).

Single accommodation features reveal different seasonal patterns. Trend analyses indicate long-term trend effects and short-term disruption effects caused by Covid-19. In contrast, no long-term effect of the pandemic was found.

The findings stress the need to address seasonality at the single accommodation feature level. Beyond targeting specific features at different guest groups, new approaches could allow dynamic price optimization. Real-time insight can be used for the targeted marketing of platform providers and accommodation owners.

A novel application of a time series perspective reveals trends and seasonal changes in travelers’ accommodation feature preferences. The findings help better address travelers’ needs in P2P offerings.

This paper aims to focus on the research progress of intelligent self-healing anti-corrosion coatings in the aviation field in the past few years. The paper provides certain literature review supports and development direction suggestions for future research on intelligent self-healing coatings in aviation.

This mini-review uses a systematic literature review process to provide a comprehensive and up-to-date review of intelligent self-healing anti-corrosion coatings that have been researched and applied in the field of aviation in recent years. In total, 64 articles published in journals in this field in the last few years were analysed in this paper.

The authors conclude that the incorporation of multiple external stimulus-response mechanisms makes the coatings smarter in addition to their original self-healing corrosion protection function. In the future, further research is still needed in the research and development of new coating materials, the synergistic release of multiple self-healing mechanisms, coating preparation technology and corrosion monitoring technology.

To the best of the authors’ knowledge, this is one of the few systematic literature reviews on intelligent self-healing anti-corrosion coatings in aviation. The authors provide a comprehensive overview of the topical issues of such coatings and present their views and opinions by discussing the opportunities and challenges that self-healing coatings will face in future development.

The purpose of this study is to explore the impact of asymmetric trust on construction project management performance in China's construction industry. Moreover, the authors explore the mediating role of two types of knowledge sharing (explicit knowledge sharing and tacit knowledge sharing) in explaining the association between asymmetric trust and project management performance.

A theoretical model based on the research hypotheses proposed in this study was developed and a questionnaire survey was conducted with 271 professionals. The data collected was analyzed by the structural equation modeling (SEM) technique.

The results of this study indicate that there is a significant and negative association between asymmetric trust and project management performance. Moreover, two types of knowledge sharing (explicit knowledge sharing and tacit knowledge sharing) have different degrees of impact on improving project management performance. In addition, tacit knowledge sharing is a mediator between asymmetric trust and project management performance.

The data used in this study is from Chinese scenarios, so the research conclusions and application effects based on this are bound to have certain regional limitations. Besides, there are many factors that affect project management performance improving, and the relationships among them are so complex. The theoretical model proposed in this study may not be fully considered. Therefore, follow-up researchers can consider bringing more suitable variables into their researches, so that the theoretical researches can be more in line with the actual project management practice, and the specific mechanism for improving project management performance can be explained more deeply.

This research's value is as follows: Firstly, this paper contributes to the trust and relational governance literature by expanding the research perspective of mutual trust to asymmetric trust. Specially, this research designs a measurement scale for asymmetric trust and then reveals the impact mechanism of it on project management performance, which will certainly promote research paradigm change of trust. Secondly, this research is beneficial to knowledge sharing literature in the construction management field by expanding the research scope of knowledge sharing from a cross-organizational perspective.

Ukraine hosts thousands of international students for educational tourism, of which more than 18,000 Indian medical students were compelled to escape Ukraine under emergency conditions of war. This paper aims to examine their intention to return to Ukraine to complete their education based on an integrated theory of planned behaviour (TPB) framework with added constructs, i.e. risk perception, career anxiety, rescue and relief memory.

The data were collected from 26 February 2022 to 30 June 2022 in two phases and two modes. It was ensured that the respondents were strictly confined to Indian medical students who had travelled to Ukraine for educational tourism. SPSS 25 and AMOS 23.0 were used to analyse the data. The hypotheses proposed were statistically tested.

The analysis reveals that the extended TPB model resulted in a strong model and the empirical findings corroborate that the students’ attitude, subjective norms, perceived behavioural control and career anxiety significantly and positively influence the students’ revisit intention (RI) while risk perception and rescue and relief memory have a negative influence on the RI.

The study provides timely insights and implications to the Ukrainian tourism industry, particularly educational tourism business and medical institutions under the present turmoil, which can also act as blueprint research for destinations with a similar unstable political background.

The primary value of this research work is that it provides an understanding of the intention of medical students (educational tourists) towards revisiting the war-hit destination of Ukraine.

Artificial intelligence (AI) agents have been increasingly applied in the tourism and hospitality industry. However, AI service failure is inevitable. Thus, AI service recovery merits empirical investigation. This study aims to explore how AI empathic accuracy affects customers’ satisfaction in the context of AI service recovery.

A moderated mediation model was presented to describe the effect of empathic accuracy on customer satisfaction via four scenario-based experiments.

The results reveal the positive impact of AI empathic accuracy on customer satisfaction and the mediating effects of perceived agency and perceived experience. Moreover, anthropomorphism moderates the empathic accuracy effect.

This paper expanded AI service studies by exploring the significance of empathic accuracy in customer recovery satisfaction. The results provide a novel theoretical viewpoint on retaining customers following AI service failure.

人工智能（AI）设备已越来越多地应用于旅游业和酒店业。然而, AI服务失败是不可避免的。因此, AI服务补救值得进一步实证研究。本研究探讨了AI共情准确性如何影响顾客对AI服务补救的满意度。

通过四个基于场景的实验, 提出了一个有调节的中介模型来描述共情准确性对顾客满意度的影响。

结果揭示了AI共情准确性对顾客满意度有积极影响, 感知能动性和感知感受性具有中介效应。此外, 拟人化调节了共情准确性的效应。

本文通过探讨共情准确性在顾客服务补救满意度中的作用, 拓展了AI服务研究。研究结果为AI服务失败后如何留住顾客提供了新的理论视角。

Las agentes de inteligencia artificial (IA) se aplican cada vez más en el sector del turismo y la hostelería. Sin embargo, los fallos de los servicios de IA son inevitables. Por lo tanto, la recuperación de servicios de IA merece una investigación empírica. Esta investigación explora cómo la precisión empática de la IA afecta a la satisfacción de los clientes con la recuperación del servicio de IA.

Se presentó un modelo de mediación moderado para describir el efecto de la precisión empática en la satisfacción del cliente mediante cuatro experimentos basados en escenarios.

Los resultados revelan el impacto positivo de la precisión empática de la IA en la satisfacción del cliente y los efectos mediadores de la agencia percibida y la experiencia percibida. Además, el antropomorfismo modera el efecto de la precisión empática.

Este artículo amplía los estudios sobre los servicios de IA al investigar el papel de la precisión empática en la satisfacción del cliente. Los resultados aportan un punto de vista teórico novedoso sobre la retención de clientes tras el fallo de un servicio de IA.

Users' voluntary forwarding behavior opens a new avenue for companies to promote their brands and products on social networking sites (SNS). However, research on voluntary information disseminators is limited. This paper aims to bring an in-depth understanding of voluntary disseminators by answering the following questions: (1) What is the underlying mechanism by which some users are more enthusiastic to voluntarily forward content of interest? (2) How to identify them? We propose a theoretical model based on the Elaboration-Likelihood Model (ELM) and examine three types of factors that moderate the effect of preference matching on individual forwarding behavior, including personal characteristics, tweet characteristics and sender–receiver relationships.

Via Twitter API, we randomly crawled 1967 Twitter users' data to validate the conceptual framework. Each user’s original tweets and retweeted tweets, profile data such as the number of followers and followees and verification status were obtained. The final corpus contains 163,554 data points composed of 1,634 valid twitterers' retweeting behavior. Tweets produced by these core users' followees were also crawled. These data points constitute an unbalanced panel data and we employ different models — fixed-effects, random-effects and pooled logit models — to test the moderation effects. The robustness test shows consistency among these different models.

Preference matching significantly affects users' forwarding behavior, implying that SNS users are more likely to share contents that align with their preferences. In addition, we find that popular users with lots of followers, heavy SNS users who author tweets or forward other-sourced tweets more frequently and users who tend to produce longer original contents are more enthusiastic to disseminate contents of interest. Furthermore, interaction strength has a positive moderating effect on the relationship between preference matching and individuals' forwarding decisions, suggesting that users are more likely to disseminate content of interest when it comes from strong ties. However, the moderating effect of perceived affinity is significantly negative, indicating that an online community of individuals with many common friends is not an ideal place to engage individuals in sharing information.

This work brings about a deep understanding of users' voluntary forwarding behavior of content of interest. To the best of our knowledge, the current study is the first to examine (1) the underlying mechanism by which some users are more likely to voluntarily forward content of interest; and (2) how to identify these potential voluntary disseminators. By extending the ELM, we examine the moderating effect of tweet characteristics, sender–receiver relationships as well as personal characteristics. Our research findings provide practical guidelines for enterprises and government institutions to choose voluntary endorsers when trying to engage individuals in information dissemination on SNS.