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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.

Although virtual worlds, such as the Metaverse, can disrupt the hospitality sector, few empirical investigations have critically evaluated the scope and scale of this disruption from an industry perspective. This study aims to rectify this knowledge gap by exploring the opportunities and challenges of the Metaverse as seen by hospitality professionals.

This is a Delphi study conducted with UK-based senior hospitality industry practitioners experienced in designing and implementing digital innovations within their organisations.

The Metaverse is most likely to be adopted by hospitality organisations willing and able to take risks, such as large and/or chain-affiliated enterprises. The Metaverse will not replace traditional hospitality services but supplement and enhance them with new layers of service. The main applications are in the context of events and experiences. The Metaverse will also provide the “try before you buy” option, revealing the opportunities to design digital twins of physical businesses. Young and technology-savvy individuals are most likely to first adopt the Metaverse. The key challenges of the adoption are attributed to the technological unpreparedness of hospitality organisations; market immaturity; inflated customer expectations; a skills gap among hospitality employees; and regulatory issues. These challenges require the engagement of various stakeholders to create an operational and monitoring framework for hospitality organisations to embrace the Metaverse.

This study highlights how the Metaverse can disrupt the hospitality industry at the level of strategic planning and business operations.

To the best of the authors’ knowledge, this is one of the first empirical investigations of the potential of the Metaverse from the viewpoint of hospitality industry practitioners.

This study aims to re-examine the growth effects of tourism and role of financial development in this process for countries across the globe for the period 1995–2018.

Considering the asymmetric effect of tourism on economic performance, the author makes use of a recently developed method of moments approach of quantile regression with fixed effects proposed by Machado and Silva (2019).

Model-based on tourist arrival shows a positive effect of tourism on economic performance. Yet, the effect is conditional and shows that relatively low-income economies are benefited more than high-income economies. The results also show that all types of tourism are beneficial for growth, yet business-related tourist arrivals are found to be comparatively more effective than other types of tourism. The evidence also shows that excess tourism does not dampen growth. Finally, the evidence suggests that financial development offers critical absorptive capacity, and tourism-led growth cannot be realised without it.

In contrast to previous studies, the approach effectively deals with non-normality, endogeneity and heterogeneity across issues. Furthermore, this study uniquely tests the role of financial development in channelling tourism-led development.

This paper aims to examine the impact and mechanism of digital development on enterprise labor productivity. In addition, this study empirically analyzes the nonlinear impact of digitalization on labor productivity.

This paper uses a fixed effect model, a mediation effect model and a panel threshold model to test the theoretical hypothesis of this study.

The results demonstrated that digitalization had a promotional effect on labor productivity, with approximately 18% of this effect achieved through transmission and influence on human capital. In addition, the novelty of this study lies in the discovery that digitization has an obvious nonlinear positive effect on corporate labor productivity. The results suggest that companies should increase investment in data-driven innovation capabilities, improve the implementation of digital talent training plans, improve their financing capacity and strengthen corporate internal management, while the government should provide appropriate policy support differently for various enterprises.

This study takes China’s Shanghai and Shenzhen A-share listed companies as the research object, systematically examines the impact and mechanism of digital development on enterprise labor productivity and explores the nonlinear relationship between digitalization and enterprise labor productivity, which is a new angle.

本文旨在探讨数字化发展对企业劳动生产率的影响及其机制。此外, 本研究实证分析了数字化对劳动生产率的非线性影响。

本文采用固定效应模型、中介效应模型和面板门槛模型来检验本研究的理论假设。

结果表明, 数字化对劳动生产率有促进作用, 其中约 18% 是通过对人力资本的传导和影响来实现的。此外, 本文的新颖之处在于发现了数字化对企业劳动生产率具有显著的非线性正效应。结果表明, 企业应加大对数据驱动创新能力的投入, 完善数字化人才培养计划的实施, 提高融资能力, 加强企业内部管理, 政府应针对各类企业提供差异化的政策支持。

本研究以中国沪深A股上市公司为研究对象, 系统考察了数字化发展对企业劳动生产率的影响和机制, 探讨了数字化与企业劳动生产率之间的非线性关系, 这是一个新的研究角度。

The adoption of value management (VM) has been on the rise in the construction industry, especially in the past decade. Identifying the main barriers to VM application for ameliorating poor project outcomes in the construction industry is a critical step to overcoming its implementation. Therefore, this study aims to examine the barriers to the adoption of VM in the Nigerian construction industry (NCI) and identify the critical ones for action by construction stakeholders.

This study used two rounds of Delphi surveys with 15 VM experts to identify the challenges to VM adoption. The Delphi team’s data from the two surveys were analysed using descriptive statistics. The mean-mode approach was used to identify ten major barriers to VM adoption based on the consensus reached during the second round of the Delphi poll. Following that, an interrater agreement analysis and a significant level analysis were performed.

Of the 17 identified barriers hindering VM adoption on construction projects in the NCI, 10 were found to be profound after statistical analyses of the data. The significant barriers include communication gap between the client and other consultants; delay in design preparation because of VM services; the pretext that VM is being practiced in the construction industry; and the wrong perception of VM by construction professionals, among others. The findings of the analysis suggested that the lack of VM adoption in the NCI was because of inadequate knowledge of VM techniques among construction professionals. Therefore, it is advised that VM training be provided for concerned stakeholders to address the lack of VM expertise among Nigerian construction professionals.

This study investigated the barriers to VM adoption on construction projects in the NCI with the opinions of a few construction professionals who can be regarded as VM experts. As against obtaining large survey responses from construction professionals who may not be knowledgeable in the VM process, the limited VM experts’ responses provide a valid basis for drawing inferences and making recommendations to address the paucity of VM applications in the NCI.

Through a Delphi survey, the critical barriers to the adoption of VM were identified, along with recommendations to help construction stakeholders overcome the challenges and enjoy the benefits of VM.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

This study seeks to establish a new framework for categorizing incivility, differentiating between explicit and implicit forms, and to investigate their respective abilities to proliferate and mobilize conversations, along with behavioral outcomes in various social contexts.

Employing computational techniques, this research analyzed 10,145 protest-related threads from the HK Golden Forum, a prominent online discussion board in Hong Kong.

Our analysis revealed divergent effects of explicit and implicit incivility on their diffusion, influences on deliberative discussions, and user participation. Explicit incivility was found to impede deliberative conversations, while implicit incivility tended to provoke more responses. Explicit uncivil expressions encouraged the propagation of incivility but reduced the likelihood of individual involvement. In contrast, implicit incivility had a stronger dampening effect on further uncivil comments and achieved greater thread popularity. The results showed strong associations between uncivil expressions and the contextual norms surrounding social movements.

Theoretically, this research introduced a classification of incivility and underscored the importance of differentiating between implicit and explicit incivility by examining their effects on deliberation and engagement. Although previous studies have extensively covered explicit incivility, this study goes further by analyzing implicit incivility and comparing both forms of uncivil discourse in a less-studied context. Methodologically, the study developed a Cantonese dictionary to differentiate between two types of incivility, providing a practical reference for more nuanced analyses. By revealing how varying movement norms moderate the interplay between deliberative and uncivil expressions, the study drew attention to the highly situational nature of incivility.

Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep learning model for capturing dynamic spatial effects.

A novel deep learning model founded on the transformer architecture, called the spatiotemporal transformer network, is presented. This model has three components: the temporal transformer, spatial transformer and spatiotemporal fusion modules. The dynamic temporal dependencies of each attraction are extracted efficiently by the temporal transformer module. The dynamic spatial correlations between attractions are extracted efficiently by the spatial transformer module. The extracted dynamic temporal and spatial features are fused in a learnable manner in the spatiotemporal fusion module. Convolutional operations are implemented to generate the final forecasts.

The results indicate that the proposed model performs better in forecasting accuracy than some popular benchmark models, demonstrating its significant forecasting performance. Incorporating dynamic spatiotemporal features is an effective strategy for improving forecasting. It can provide an important reference to related studies.

The proposed model leverages high-frequency data to achieve accurate predictions at the micro level by incorporating dynamic spatial effects. Destination managers should fully consider the dynamic spatial effects of attractions when planning and marketing to promote tourism resources.

This study incorporates dynamic spatial effects into tourism demand forecasting models by using a transformer neural network. It advances the development of methodologies in related fields.

纳入动态空间效应在提高旅游需求预测的准确性方面具有相当大的潜力。本研究提出了一种捕捉动态空间效应的创新型深度学习模型。

本研究提出了一种基于变压器架构的新型深度学习模型, 称为时空变压器网络。该模型由三个部分组成：时空转换器、空间转换器和时空融合模块。时空转换器模块可有效提取每个景点的动态时间依赖关系。空间转换器模块可有效提取景点之间的动态空间相关性。提取的动态时间和空间特征在时空融合模块中以可学习的方式进行融合。通过卷积运算生成最终预测结果。

结果表明, 与一些流行的基准模型相比, 所提出的模型在预测准确性方面表现更好, 证明了其显著的预测性能。纳入动态时空特征是改进预测的有效策略。它可为相关研究提供重要参考。

所提出的模型利用高频数据, 通过纳入动态空间效应, 在微观层面上实现了准确预测。旅游目的地管理者在规划和营销推广旅游资源时, 应充分考虑景点的动态空间效应。

本研究通过使用变压器神经网络, 将动态空间效应纳入旅游需求预测模型。它推动了相关领域方法论的发展。

La incorporación de efectos espaciales dinámicos ofrece un considerable potencial para mejorar la precisión de la previsión de la demanda turística. Este estudio propone un modelo innovador de aprendizaje profundo para capturar los efectos espaciales dinámicos.

Se presenta un novedoso modelo de aprendizaje profundo basado en la arquitectura transformadora, denominado red de transformador espaciotemporal. Este modelo tiene tres componentes: el transformador temporal, el transformador espacial y los módulos de fusión espaciotemporal. El módulo transformador temporal extrae de manera eficiente las dependencias temporales dinámicas de cada atracción. El módulo transformador espacial extrae eficientemente las correlaciones espaciales dinámicas entre las atracciones. Las características dinámicas temporales y espaciales extraídas se fusionan de manera que se puede aprender en el módulo de fusión espaciotemporal. Se aplican operaciones convolucionales para generar las previsiones finales.

Los resultados indican que el modelo propuesto obtiene mejores resultados en la precisión de las previsiones que algunos modelos de referencia conocidos, lo que demuestra su importante capacidad de previsión. La incorporación de características espaciotemporales dinámicas supone una estrategia eficaz para mejorar las previsiones. Esto puede proporcionar una referencia importante para estudios afines.

El modelo propuesto aprovecha los datos de alta frecuencia para lograr predicciones precisas a nivel micro incorporando efectos espaciales dinámicos. Los gestores de destinos deberían tener plenamente en cuenta los efectos espaciales dinámicos de las atracciones en la planificación y marketing para la promoción de los recursos turísticos.

Este estudio incorpora efectos espaciales dinámicos a los modelos de previsión de la demanda turística mediante el empleo de una red neuronal transformadora. Supone un avance en el desarrollo de metodologías en campos afines.

The purpose of the present study is to test the effect of financial development and environmental degradation on the control of corruption.

This study used a dynamic approach known as system GMM to analyze annual data from 90 developed and developing countries over 24 years, from 1996 to 2020.

The present study shows a significantly negative relationship between financial development and control of corruption and a significantly positive relationship between environmental degradation and control of corruption. The result suggests that improvement in financial development may reduce control of corruption; however, reduction in environmental degradation may reduce control of corruption. The results are consistent across both developed and developing countries.

The study’s findings have significant implications for financial institutions, governmental policy departments and environmental regulatory agencies. The policy outcomes are closely linked to the economic prosperity of countries. In general, developing countries can implement strategies to promote financial development and environmental regulations, even though they may temporarily tolerate corrupt activities. Conversely, developed nations may have differing implications from developing countries.

This study is different from the past literature as none of the studies have been conducted previously focusing on developed and developing countries’ financial development, environmental degradation and control of corruption.

During metro construction using the shield method, the construction process's complexity, the construction environment's variability, and other factors can easily lead to tunnel construction accidents. This paper aims to explore the interconnections between risk factors and related accident types, as well as the risk chain formed between risk factors, and to analyze the key risk factors and vulnerabilities in shield tunnel construction through empirical data.

Based on the social network analysis theory, the connection of various risk factors in subway shield tunnel construction is explored, and the mechanism of multiple risk factors is studied. Through literature analysis, articles on safety risk factors in metro shield tunnel construction are organized and studied, and the identified safety risk factors can comprehensively reflect the significant risks that need to be concerned in metro shield tunnel construction.

The results show that a small world characterizes the SNA network of safety risk factors for metro shield tunnel construction: The frequency of association between the five risk factors “unsafe behavior,” “site management,” “safety supervision and inspection,” “safety education system” and “safety protection” is higher than that of other factors. Only a few risks, such as “site management,” “safety supervision and inspection,” and “rapid response capability,” directly lead to accidents. In addition, risk factors such as the “safety education system” and “safety protection” will indirectly cause unsafe behaviors of construction personnel.

During construction, the probability of occurrence of risk factors may vary with the construction phase and area and is not considered in this paper. In addition, although this paper identifies, determines and analyzes the risk factors affecting the safety of metro shield tunnel construction, including the importance of each risk factor and the connection between them, more detailed information before and after the accident could not be obtained based on the accident investigation report alone. Therefore, future research can collect the same accident case from more sources to obtain more information.

The theory of accident causation has been improved at the theoretical level. The identified safety risk factors can comprehensively reflect the significant risks that need to be paid attention to in metro shield tunnel construction. From a practical point of view, the results of the study provide a basis for the rational control of the risk factors in the construction of subway shield tunnels, which can help guide practitioners to do a good job of risk prevention before the construction of metro shield tunnels and reduce the probability of related accidents.

This study expands the application of social network analysis in the field of subway tunnel construction risk, quantitatively analyzes the key risk factors and vulnerabilities in shield method tunnel construction and proposes policy recommendations for future metro tunnel construction safety management.