Search results

Accessible tourism is evolving as a field of academic research and industry practice, set within a dynamic social context. The field is interdisciplinary, multidisciplinary and transdisciplinary. The purpose of this paper is to examine key concepts and global initiatives that will shape accessible tourism futures.

Three of the authors have extensive academic experience in the area and the fourth author is the Managing Director of the pre-eminent European Network for Accessible Tourism. In taking a limited Delphi approach to canvassing key areas likely to shape accessible tourism futures, the following concepts and policy initiatives were examined: motivations, dreams and aspirations of people with disability; demography; UN Convention on the Rights of Persons with Disabilities; destination competitiveness; universal design (UD); and the UN Sustainable Development Goals for 2030.

A discussion of each of the above areas was placed in context to accessible tourism futures and to contextualise the papers that were selected for the special issue. The latter part of the paper outlines the contribution of each empirical paper to the issue discussing the approach, findings and implications. Stakeholder collaboration was identified as the key common theme of the papers and the factor for developing accessible tourism solutions, recognising the value of the market and capitalising on it. A collaborative approach is required to recognise the complementary nature of the different paradigms; to re-shape and transform the future of the accessible tourism industry. To assist in the development of accessible tourism futures, UD principles should provide a foundation to enhance the future competitiveness of tourism destinations and organisations.

The paper’s examination of the concepts and global policy considerations provides a strong academic and practitioner foundation for considering accessible tourism futures. In doing so, accessible tourism futures are shown to be affected by key concepts related to core tourism considerations and major policy initiatives on accessibility and sustainability. Yet, accessible tourism futures also have the potential to create their own momentum and contribute unique learnings on the diversity of tourism markets that will shape tourism concepts and global policy initiatives in their own right.

This study aims to predict overnight stays in Italy at tourist accommodation facilities through a nonlinear, single factor, stochastic model called CIR#. The contribution of this study is twofold: in terms of forecast accuracy and in terms of parsimony (both from the perspective of the data and the complexity of the modeling), especially when a regular pattern in the time series is disrupted. This study shows that the CIR# not only performs better than the considered baseline models but also has a much lower error than other additional models or approaches reported in the literature.

Typically, tourism demand tends to follow regular trends, such as low and high seasons on a quarterly/monthly level and weekends and holidays on a daily level. The data set consists of nights spent in Italy at tourist accommodation establishments as collected on a monthly basis by Eurostat before and during the COVID-19 pandemic breaking regular patterns.

Traditional tourism demand forecasting models may face challenges when massive amounts of search intensity indices are adopted as tourism demand indicators. In addition, given the importance of accurate forecasts, many studies have proposed novel hybrid models or used various combinations of methods. Thus, although there are clear benefits in adopting more complex approaches, the risk is that of dealing with unwieldy models. To demonstrate how this approach can be fruitfully extended to tourism, the accuracy of the CIR# is tested by using standard metrics such as root mean squared errors, mean absolute errors, mean absolute percentage error or average relative mean squared error.

The CIR# model is notably simpler than other models found in literature and does not rely on black box techniques such as those used in neural network (NN) or data science-based models. The carried analysis suggests that the CIR# model outperforms other reference predictions in terms of statistical significance of the error.

The proposed model stands out for being a viable option to the Holt–Winters (HW) model, particularly when dealing with irregular data.

The proposed model has demonstrated superiority even when compared to other models in the literature, and it can be especially useful for tourism stakeholders when making decisions in the presence of disruptions in data patterns.

The novelty lies in the fact that the proposed model is a valid alternative to the HW, especially when the data are not regular. In addition, compared to many existing models in the literature, the CIR# model is notably simpler and more transparent, avoiding the “black box” nature of NN and data science-based models.

一般来说, 旅游需求往往遵循规律的趋势, 例如季度/月的淡季和旺季, 以及日常的周末和假期。该数据集包括欧盟统计局在打破常规模式的2019冠状病毒病大流行之前和期间每月收集的在意大利旅游住宿设施度过的夜晚。

本研究旨在通过一个名为cir#的非线性单因素随机模型来预测意大利游客住宿设施的过夜住宿情况。这项研究的贡献是双重的:在预测准确性方面和在简洁方面(从数据和建模复杂性的角度来看), 特别是当时间序列中的规则模式被打乱时。我们表明, cir#不仅比考虑的基线模型表现更好, 而且比文献中报告的其他模型或方法具有更低的误差。

当大量搜索强度指标被作为旅游需求指标时, 传统的旅游需求预测模型将面临挑战。此外, 鉴于准确预测的重要性, 许多研究提出了新的混合模型或使用各种方法的组合。因此, 尽管采用更复杂的方法有明显的好处, 但风险在于处理难使用的模型。为了证明这种方法能有效地扩展到旅游业, 使用RMSE、MAE、MAPE或AvgReIMSE等标准指标来测试cir#的准确性。

cir#模型明显比文献中发现的其他模型简单, 并且不依赖于黑盒技术, 例如在神经网络或基于数据科学的模型中使用的技术。所进行的分析表明, cir#模型在误差的统计显著性方面优于其他参考预测。

这个模型作为Holt-Winters模型的一个拟议模型, 特别是在处理不规则数据时。

即使与文献中的其他模型相比, 所提出的模型也显示出优越性, 并且在数据模式中断时对旅游利益相关者做出决策特别有用。

创新之处在于所提出的模型是Holt-Winters模型的有效替代方案, 特别是当数据不规律时。此外, 与文献中的许多现有模型相比, cir#模型明显更简单、更透明, 避免了神经网络和基于数据科学的模型的“黑箱”性质。

Normalmente, la demanda turística tiende a seguir tendencias regulares, como temporadas altas y bajas a nivel trimestral/mensual y fines de semana y festivos a nivel diario. El conjunto de datos consiste en las pernoctaciones en Italia en establecimientos de alojamiento turístico recogidas mensualmente por Eurostat antes y durante la pandemia de COVID-19, rompiendo los patrones regulares.

El presente estudio pretende predecir las pernoctaciones en Italia en establecimientos de alojamiento turístico mediante un modelo estocástico no lineal de un solo factor denominado CIR#. La contribución de este estudio es doble: en términos de precisión de la predicción y en términos de parsimonia (tanto desde la perspectiva de los datos como de la complejidad de la modelización), especialmente cuando un patrón regular en la serie temporal se ve interrumpido. Demostramos que el CIR# no sólo aplica mejor que los modelos de referencia considerados, sino que también tiene un error mucho menor que otros modelos o enfoques adicionales de los que se informa en la literatura.

Los modelos tradicionales de previsión de la demanda turística pueden enfrentarse a desafíos cuando se adoptan cantidades masivas de índices de intensidad de búsqueda como indicadores de la demanda turística. Además, dada la importancia de unas previsiones precisas, muchos estudios han propuesto modelos híbridos novedosos o han utilizado diversas combinaciones de métodos. Así pues, aunque la adopción de enfoques más complejos presenta ventajas evidentes, el riesgo es el de enfrentarse a modelos poco manejables. Para demostrar cómo este enfoque puede extenderse de forma fructífera al turismo, se comprueba la precisión del CIR# utilizando métricas estándar como RMSE, MAE, MAPE o AvgReIMSE.

El modelo CIR# es notablemente más sencillo que otros modelos encontrados en la literatura y no se basa en técnicas de caja negra como las utilizadas en los modelos basados en redes neuronales o en la ciencia de datos. El análisis realizado sugiere que el modelo CIR# supera a otras predicciones de referencia en términos de significación estadística del error.

El modelo propuesto destaca por ser una opción viable al modelo Holt-Winters, sobre todo cuando se trata de datos irregulares.

El modelo propuesto ha demostrado su superioridad incluso cuando se compara con otros modelos de la bibliografía, y puede ser especialmente útil para los agentes del sector turístico a la hora de tomar decisiones cuando se producen alteraciones en los patrones de datos.

La novedad radica en que el modelo propuesto es una alternativa válida al Holt-Winters especialmente cuando los datos no son regulares. Además, en comparación con muchos modelos existentes en la literatura, el modelo CIR# es notablemente más sencillo y transparente, evitando la naturaleza de “caja negra” de los modelos basados en redes neuronales y en ciencia de datos.

The purpose of this paper is to investigate how previous literature has analyzed the role of augmented reality and virtual reality in the field of tourism, distinguishing between studies focused on one technology or the other as both have characteristics that profoundly differentiate them.

This study carries out a critical review to assess and synthesize the literature on augmented reality and virtual reality in tourism. Literature searches are conducted using various keywords, resulting in a selection of 84 articles (19 on augmented reality and 65 on virtual reality) from 39 indexed journals.

The research findings demonstrate an increasing scholarly focus on exploring the application of virtual reality and augmented reality within the realm of tourism. These results highlight a noticeable progression in recent years with respect to different matters, such as methodologies, used theories or considered variables, among others. Based on these results, it is proposed a future research agenda that seeks to establish a cohesive framework and drive the development of both augmented reality and virtual reality research in tourism.

By conducting an individual and comparative review of the literature on the application of augmented reality and virtual reality in tourism, this research helps elucidate the specific lines of research for each technology while providing a better understanding of how each technology can be used to generate effective tourist experiences.

El objetivo de este artículo es investigar cómo la literatura previa ha analizado el papel de la realidad aumentada y la realidad virtual en el ámbito del turismo, distinguiendo entre estudios centrados en una u otra tecnología ya que ambas tienen características que las diferencian profundamente.

Este estudio realiza una revisión crítica para evaluar y sintetizar la literatura sobre realidad aumentada y realidad virtual en turismo. Se realizan búsquedas de literatura utilizando diversas palabras clave, que dan como resultado la selección de 84 artículos (19 sobre realidad aumentada y 65 sobre realidad virtual) procedentes de 39 revistas indexadas.

Los resultados de la investigación demuestran que existe un interés creciente en explorar la aplicación de la realidad virtual y la realidad aumentada en el ámbito del turismo. Asimismo, se pone de manifiesto una notable progresión en los últimos años con respecto a diferentes cuestiones, como las metodologías aplicadas, las teorías empleadas o las variables consideradas, entre otras. A partir de estos resultados, se propone una agenda de investigación futura que pretende establecer un marco cohesionado e impulsar el desarrollo de la investigación en el ámbito tanto de la realidad aumentada como de la realidad virtual en turismo.

Al realizar una revisión individual y comparativa de la literatura sobre la aplicación de la realidad aumentada y la realidad virtual en el turismo, esta investigación ayuda a esclarecer las líneas de investigación específicas de cada tecnología a la vez que proporciona una mejor comprensión de cómo cada tecnología puede ser utilizada para generar experiencias turísticas efectivas.

本文旨在研究以往的文献是如何分析增强现实和虚拟现实在旅游领域的作用的, 并对侧重于其中一种技术或另一种技术的研究加以区分, 因为这两种技术都有深刻区别于其他技术的特点。

本研究通过批判性综述来评估和归纳有关旅游业中增强现实和虚拟现实技术的文献。通过使用各种关键词进行文献检索, 从 39 种索引期刊中筛选出 84 篇文章（19 篇关于增强现实技术, 65 篇关于虚拟现实技术）。

研究结果表明, 学术界越来越重视探索虚拟现实和增强现实在旅游业中的应用。这些结果突显了近年来在方法论、采用的理论或考虑的变量等不同方面的明显进步。在这些成果的基础上, 提出了未来的研究议程, 旨在建立一个具有凝聚力的框架, 推动旅游业中增强现实和虚拟现实研究的发展。

本研究通过对增强现实和虚拟现实技术在旅游业中应用的文献进行单独和比较审查, 有助于阐明每种技术的具体研究方向, 同时让人们更好地了解如何使用每种技术来产生有效的旅游体验。

The purpose of this paper is to analyse factors influencing the propensity to share travel experiences in social media during a trip, across a sample of Millennial and Generation Z consumers in three different countries.

An online survey was sent to consumers between 16 and 30 years in Sweden, UK and India. Structural equation modelling and multigroup analysis was conducted to compare results between countries and generations.

Young travellers’ need for uniqueness (NFU) and opinion leadership (OL) with regard to travel tends to increase their propensity to share travel experiences in social media during a trip. Reflected appraisal of self is strongly related to NFU and OL and may therefore indirectly influence the propensity to share. Some differences were found between generations and countries.

Future research could consider comparisons between travellers from younger and older generations. The hypotheses formulated in this study could be tested in other countries. Further adaptions or extensions of existing NFU scales to fit in the travel and tourism context are suggested.

Millennial and Gen Z consumers will constitute an increasing part of travellers and visitors in the future. Through a better understanding of their behaviour, tourism managers can design strategies to engage them and increase electronic word-of-mouth (eWOM).

This study contributes by addressing the lack of research on “self”-related drivers of eWOM in general social media during the trip, and by providing an international perspective through cross-cultural comparisons.

Analyzing the main determinants that lead a traveler to make a cultural trip is an important issue to understand where the cultural tourism market is going, and where the decision-makers should intervene. This study helps develop a profile of cultural tourism participants, and underscore the changes in this market niche. This information is crucial for the successful marketing and development of cultural tourism in the future.

The authors estimate a binary probabilistic (logit) model to determine the probability of a tourist to travel for cultural reasons, as a function of the traveler's socio-economic characteristic (e.g. age, gender, income or level of studies), of the trip-related characteristics (e.g. distance traveled to destination or mode of transport) and of the characteristics of the province of destination (e.g. weather conditions or existence of cultural sites at destination).

This study’s estimates reveal that middle-aged individuals, with a higher level of studies and with a medium level of income show a higher propensity to travel for cultural reasons. The latter finding evidences that cultural tourism has evolved from a niche market reserved for an elite clientele to a much wider range of people. Additionally, cultural travelers tend to travel statistically much longer distances. They are less prone to visit crowded destinations, prefer visiting destinations with important cultural sites, and are less sensitive to weather conditions. Finally, the authors discover a complementary effect of culture tourism and other activities carried out during the trip such as visiting cities or theme parks; and a substitution effect with “beach-and-sun” tourism.

The information given in this study can be crucial for the successful marketing and development of cultural tourism in the future. A better understanding of the main determinants of being a cultural traveler implies a better and a more efficient implementation of managerial and political measures to attract a kind of tourism characterized by a high spending capacity.

Discovering the main determinants of being a cultural traveler is a topic scarcely treated in the literature. This study has the main originality to include characteristics of the destination (pull factors) to explain the individual's decision to take a cultural trip. Moreover, the authors work at a provincial (NUTS-3) level of analysis, which makes this study original in the field of cultural tourism.

The purpose of this paper is to examine peer-to-peer sharing platform business models, their sources of competitive advantage, and the roles, motivations and behaviors of key actors in their ecosystems.

This paper uses a conceptual approach that is rooted in the service, tourism and hospitality, and strategy literature.

First, this paper defines key types of platform business models in the sharing economy anddescribes their characteristics. In particular, the authors propose the differentiation between sharing platforms of capacity-constrained vs capacity-unconstrained assets and advance five core properties of the former. Second, the authors contrast platform business models with their pipeline business model counterparts to understand the fundamental differences between them. One important conclusion is that platforms cater to vastly more heterogeneous assets and consumer needs and, therefore, require liquidity and analytics for high-quality matching. Third, the authors examine the competitive position of platforms and conclude that their widely taken “winner takes it all” assumption is not valid. Primary network effects are less important once a critical level of liquidity has been reached and may even turn negative if increased listings raise friction in the form of search costs. Once a critical level of liquidity has been reached, a platform’s competitive position depends on stakeholder trust and service provider and user loyalty. Fourth, the authors integrate and synthesize the literature on key platform stakeholders of platform businesses (i.e. users, service providers, and regulators) and their roles and motivations. Finally, directions for further research are advanced.

This paper helps platform owners, service providers and users understand better the implications of sharing platform business models and how to position themselves in such ecosystems.

This paper integrates the extant literature on sharing platforms, takes a novel approach in delineating their key properties and dimensions, and provides insights into the evolving and dynamic forms of sharing platforms including converging business models.