Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid COVID-19? Mixed-data sampling approach

The coronavirus disease (COVID-19) pandemic has already caused enormous damage to the global economy and various industries worldwide, especially the tourism industry. In the post-pandemic era, accurate tourism demand recovery forecasting is a vital requirement for a thriving tourism industry. Therefore, this study mainly focuses on forecasting tourist arrivals from mainland China to Hong Kong. A new direction in tourism demand recovery forecasting employs multi-source heterogeneous data comprising economy-related variables, search query data, and online news data to motivate the tourism destination forecasting system. The experimental results confirm that incorporating multi-source heterogeneous data can substantially strengthen the forecasting accuracy. Specifically, mixed data sampling (MIDAS) models with different data frequencies outperformed the benchmark models.     

上海市入境旅游市场影响因素分析与预测——以德国、法国、英国、美国与泰国客源国为例

入境旅游是衡量一个国家知名度、影响力和旅游发展水平的主要因素,也是赚取外汇和旅游收入的重要路径。上海是外国游客入境重要的目的地,也是中国最大的入境游客中转站。文章分析了德国、法国、英国、美国、泰国五个上海主要入境旅游客源国2004年第一季度至2018年第三季度的数据,运用计量经济学方法建模,并实证分析了上海入境旅游需求的影响因素。研究表明,口碑效应、客源地的收入水平与上海入境旅游需求正相关;上海入境旅游具有较大的季节波动特点,冬夏两季入境游客数量减少;世博会对上海入境旅游拉动作用较大。同时,对德国、法国、泰国三大市场未来十年的旅游季度需求进行了预测,预测发现,德国、法国、泰国三大市场未来十年都有较大增长,特别是泰国市场的年均增长率达到4%。     

Forecasting h(m)otel guest nights in New Zealand

The purpose of this paper is to highlight some time series models which hotel and motel industry practitioners could use to forecast guest nights. Given their considerable practicality, the lodging industry can easily benefit from using these models as forecasts can be obtained at low cost for effective management and planning. Monthly observations are used for estimating the model from 1997(1) to 2006(12). The Holt–Winters and Box–Jenkins ARMA models are able to forecast guest night demand accurately as 99% of the variations in the guest night forecast are associated with variations in actual guest nights in 2007.     

Modelling Australian domestic and international inbound travel: a spatial–temporal approach

In this paper Australian domestic and international inbound travel are modelled by an anisotropic dynamic spatial lag panel Origin-Destination (OD) travel flow model. Spatial OD travel flow models have traditionally been applied in a single cross-sectional context, where the spatial structure is assumed to have reached its long run equilibrium and temporal dynamics are not explicitly considered. On the other hand, spatial effects are rarely accounted for in traditional tourism demand modelling. We attempt to address this dichotomy between spatial modelling and time series modelling in tourism research by using a spatial-temporal model. In particular, tourism behaviour is modelled as travel flows between regions. Temporal dependencies are accounted for via the inclusion of autoregressive components, while spatial autocorrelations are explicitly accounted for at both the origin and the destination. We allow the strength of spatial autocorrelation to exhibit seasonal variations, and we allow for the possibility of asymmetry between capital-city neighbours and non-capital-city neighbours. Significant temporal and spatial dynamics have been uncovered for both domestic and international tourism demand. For example we find strong seasonal temporal autocorrelations, significant trends and significant spatial autocorrelations at both the origin and the destination. Moreover, the spatial patterns are found to be most significant during peak holiday seasons. Understanding these patterns in tourist behaviour has important implications for tourism operators.     

Structural breaks in international tourism demand: Are they caused by crises or disasters?

It is recognised that the tourism industry is vulnerable to some form of crises or disaster. However, despite the attention given to the nature and consequences of tourism crises and disasters, there is a gap in the literature regarding the ex-post detection of these events. In this article, we estimate both the number and date of structural breaks in international tourism arrival series for 25 countries and Madeira Island using the Bai and Perron (1998) structural break test. We compare the date of tourism crises and disasters to the dating of these structural breaks. We observe that tourism crises and disasters are largely consistent with the dates of breaks. Therefore, this method allows us to solve a gap in the tourism industry related to the correct allocation of negative shocks in international tourism arrival demand to crisis or disaster phenomena.     

Off-season tourists and the cultural offer of a mass-tourism destination: The case of Rimini

This paper assesses the potential implications on off-season tourism of enhancing the cultural offer of Rimini, a popular Italian seaside holiday destination hosting about 12 million overnight stays per year. Since more than 9 million of these stays are concentrated in the summer season, in the last 20 years. Rimini has been undergoing a policy of seasonality smoothing, which mainly pivots around business and cultural tourism. This assessment has been carried out through discrete choice experiments submitted to a sample of about 800 tourists who visited Rimini outside the summer months. Since tourism can be viewed as a composite good, which overall utility depends on how the component characteristics are arranged, the choice experiments allow to disentangle the importance and the willingness to pay of tourists for different attributes of the holiday. The choice model incorporates a number of possible changes to actual tourism features (which are also the subject of public debate), including them in hypothetical alternative “holiday packages”. The conditional logit analysis of the choice experiments can highlight any synergy or trade-off between cultural and business tourism. Results suggest that business and leisure tourists share many features related to the use of the territory, while there are important trade-offs between these two groups and cultural tourists. Since business tourists have a higher willingness to extend their stay, a softer budget, and their demand is also complementary to the demand of summer tourists (Brau, Scorcu, & Vici, 2009), from the destination point of view investing in this market segment would be the best option. Although a “second best”, however, cultural tourists share with the local population of Rimini many aspects of the demand of territory (Figini, Castellani, & Vici, 2009). Hence, cultural tourism can play a fundamental role in the intermediate season as a tool for smoothing seasonality, to diversify investments and to give value to the city’s cultural heritage.     

Modeling Tourism Demand

SUMMARY

Most of the existing studies on tourism demand forecasting apply economic models that use mathematical functions, which require many statistical assumptions and limitations. This paper presents a new approach that applies the rough sets theory to form a forecasting model for tourism demand. The objective of this research is to create patterns which are able to distinguish between the classes of arrivals in terms of volume, based upon differences in the characteristics in each arrival. The information about the arrivals was organized in an Information Table where the number of arrivals corresponds to condition attributes, and the classification was defined by a decision attribute that indicated the forecast categorical value of future arrivals. Utilizing Japanese arrivals data in Hong Kong, empirical results showed the induced decision rules could accurately forecast (86.5%) of the test data.     

Factors affecting hotel human resource demand in Taiwan

This study explores the factors affecting hotel human resource (HR) demand and focusing on the organizational, industrial and macroeconomic factors of the hospitality industry. A prediction model was built with eight independent variables and four dummy variables. Secondary data was collected via a governmental statistic database, and regression analysis was performed using the Generalized Least Squares (GLS) method. The results show that the HR demand of international tourist hotels is more likely to be affected by industrial factors and macroeconomic factors, while the HR demand of standard tourist hotels is less complex, and is mainly affected by organizational factors.     

Sustainable development of industrial heritage tourism – A case study of the Industrial Monuments Route in Poland

The main goal of our research was to identify, characterize and discuss the main types of business models that can be found in touristic heritage sites that have been transformed into such from former industrial facilities or were newly created to pass on the heritage values. The research is a continuation of our study that started in 2017 on on Polish touristic sites, that are associated on a touristic route – Industrial Monuments Route of Silesian Voivodeship. This route is located in southern part of Poland and it is the largest industrial route in the country. Our research revealed, organized and complemented the different types of business model transformation that took place in the analysed sites, among them is the post-production organization model which is the most frequently occurring one. This model applies to touristic ventures or cultural institutions that are former production or extraction facilities. Thanks to the transformation of those sites they suite now to fulfil their new touristic function, even if originally they have been designed for other purposes. The use of such transformed business models has also proven itself as an effective and in many cases the only way to preserve and save cultural heritage from degradation.     

中国旅游地理研究：成果应用转化和研究技术革新

旅游的产业属性决定了旅游地理研究的实践性,在服务国家战略和产业实践需求的过程中,中国旅游地理学科呈现出研究领域、方法和应用的新特征。本文围绕旅游规划、旅游资源、旅游大数据和旅游实验方法等进行总结与展望,认为：（1）旅游规划是透视旅游地理研究发展的重要视角,旅游规划的知识域主要包括旅游开发战略与对策、旅游业与旅游企业、乡村旅游与乡村振兴等12个方面;（2）新时代文化和旅游资源普查面临文旅资源保护和整合利用的重大现实需求,为旅游地理研究带来了文旅资源的内涵与分类评价、普查信息集成与应用、普查技术与组织方式等新命题;（3）大数据背景下要求旅游地理探寻新科学问题,重点要关注大数据旅游统计测量模型和指标规则的规范,数据伦理与信息茧房,大数据旅游现象的地理效应和相关空间格局等研究;（4）实验研究方法在认识论层面从描述走向解释预测,在方法论层面从调查走向直接测量,为认识和理解旅游情境下人地关系的核心科学问题提供了“科学化”的研究路径。因此,面对新时代战略要求和旅游业发展趋势,旅游地理学应加强产业实践、研究方法和学科交叉研究,提升学科服务国家战略和社会经济发展的支撑能力。