Forecasting turning points in tourism growth

Tourism demand exhibits growth cycles, and it is important to forecast turning points in these growth cycles to minimise risks to destination management. This study estimates logistic models of Hong Kong tourism demand, which are then used to generate both short- and long-term forecasts of tourism growth. The performance of the models is evaluated using the quadratic probability score and hit rates. The results show that the ways in which this information is used are crucial to the models’ predictive power. Further, we investigate whether combining probability forecasts can improve predictive accuracy, and find that combination approaches, especially nonlinear combination approaches, are sensitive to the quality of forecasts in the pool. In addition, model screening can improve forecasting performance.     

基于人工神经网络的国际入境旅游需求的定量分析与预测--以日本对香港的国际旅游需求分析为例

旅游需求预测研究研究一直是旅游学研究的一个重要课题。本文尝试用人工神经网络模型的的3层BP模型来仿真模拟国际入境旅游需求，并以日本对香港的国际旅游需求为例进行模型验证。其输入层结点为SP、FR、POP、GDE、AH、MK，旅客量为输出节点，得出3层前馈反向传播神经网络模型。最后将模拟结果与目前常用的几种模型利用相同的数据源进行对比，最后发现人工神经网络模型模拟结果与目前常用的几种模型利用相同的数据源进行模拟的结果进行对比，最后发现人工神经网络模型的模拟结果与实际情况最为逼近。     

Determinants of tourism destination competitiveness in the countries most visited by international tourists: Proposal of a synthetic index

Tourism destination competitiveness is a multidimensional concept that is widely studied in the academic literature, but multiple factors make its measurement a difficult task. In this article, we design a synthetic index to rank the 80 countries that attract the majority of international tourists by level of tourism competitiveness. In order to do this, we use all of the simple variables included in the 2017 Travel & Tourism Competitiveness Index, proposing a new methodology for the construction of this synthetic index, which it solves the problems of aggregation of variables expressed in different measures, arbitrary weighting and duplicity of information; issues that remain unresolved by the TTCI. Likewise, we analyse the most influential dimensions in tourism competitiveness. Air transport infrastructures, cultural resources and ICT readiness are the key dimensions that explain the main disparities.     

Scientific value of econometric tourism demand studies

The objective of this paper was to evaluate the scientific value of econometric tourism demand studies. Based on a questionnaire answered by ourselves we analyzed articles published in Annals of Tourism Research, Journal of Travel Research, Tourism Management, and Tourism Economics during the period 2007 to 2017. The evaluation showed that current scientific practice generally failed to differentiate between substantive (economic) significance and statistical significance, and used these terms interchangeably in many cases. In line with these flaws, most authors avoided discussing the estimation results in terms of their size and their reliability, as well as failing to adequately address the limitations of their studies and to justify the chosen methods.     

Cross-temporal coherent forecasts for Australian tourism

Key to ensuring a successful tourism sector is timely policy making and detailed planning. National policy formulation and strategic planning requires long-term forecasts at an aggregate level, while regional operational decisions require short-term forecasts, relevant to local tourism operators. For aligned decisions at all levels, supporting forecasts must be ‘coherent’, that is they should add up appropriately, across relevant demarcations (e.g., geographical divisions or market segments) and also across time. We propose an approach for generating coherent forecasts across both cross-sections and planning horizons for Australia. This results in significant improvements in forecast accuracy with substantial decision making benefits. Coherent forecasts help break intra- and inter-organisational information and planning silos, in a data driven fashion, blending information from different sources.This article also launches the Annals of Tourism Research Curated Collection on Tourism Demand Forecast, a special selection of research in this field.     

论旅游文化——文化人类学视野

目前,国内旅游文化研究已进入了瓶颈阶段。尽管有近40部与旅游文化相关的著作和教材以及大量学术论文,但人们在各种意义上使用"旅游文化"这一词汇,旅游文化的内涵与外延仍模糊不定。文章在追溯国内外旅游文化研究成果的基础上,从文化的发生层面来界定和框限旅游文化,并在内涵、特性、功能层面上对旅游文化与一般文化进行比较分析,进而指出未来的旅游文化研究可以运用文化人类学传统民族志方法来获取第一手资料。同时,文章旨在反思国内旅游文化研究的概念误区,并尝试以文化人类学视角来廓清旅游文化的外延,将旅游文化视为文化生产与再生产的结果,为旅游文化内涵的明确化、具体化做抛砖引玉的前期思考。     

Spatial-temporal forecasting of tourism demand

This study conducts spatial-temporal forecasting to predict inbound tourism demand in 29 Chinese provincial regions. Eight models are estimated among a-spatial models (autoregressive integrated moving average [ARIMA] model and unobserved component model [UCM]) and spatial-temporal models (dynamic spatial panel models and space-time autoregressive moving average [STARMA] models with different specifications of spatial weighting matrices). An ex-ante forecasting exercise is conducted with these models to compare their one-/two-step-ahead predictions. The results indicate that spatial-temporal forecasting outperforms the a-spatial counterpart in terms of average forecasting error. Auxiliary regression finds the relative error of spatial-temporal forecasting to be lower in regions characterized by a stronger level of local spatial association. Lastly, theoretical and practical implications are provided.This article also launches the Annals of Tourism Research Curated Collection on Tourism Demand Forecasting, a special selection of research in this field.     

Forecasting international city tourism demand for Paris: Accuracy of uni- and multivariate models employing monthly data

The purpose of this study is to compare the predictive accuracy of various uni- and multivariate models in forecasting international city tourism demand for Paris from its five most important foreign source markets (Germany, Italy, Japan, UK and US). In order to achieve this, seven different forecast models are applied: EC-ADLM, classical and Bayesian VAR, TVP, ARMA, and ETS, as well as the naïve-1 model serving as a benchmark. The accuracy of the forecast models is evaluated in terms of the RMSE and the MAE. The results indicate that for the US and UK source markets, univariate models of ARMA(1,1) and ETS are more accurate, but that multivariate models are better predictors for the German and Italian source markets, in particular (Bayesian) VAR. For the Japanese source market, the results vary according to the forecast horizon. Overall, the naïve-1 benchmark is significantly outperformed across nearly all source markets and forecast horizons.     

Forecasting tourist arrivals with machine learning and internet search index

Previous studies have shown that online data, such as search engine queries, is a new source of data that can be used to forecast tourism demand. In this study, we propose a forecasting framework that uses machine learning and internet search indexes to forecast tourist arrivals for popular destinations in China and compared its forecasting performance to the search results generated by Google and Baidu, respectively. This study verifies the Granger causality and co-integration relationship between internet search index and tourist arrivals of Beijing. Our experimental results suggest that compared with benchmark models, the proposed kernel extreme learning machine (KELM) models, which integrate tourist volume series with Baidu Index and Google Index, can improve the forecasting performance significantly in terms of both forecasting accuracy and robustness analysis.     

旅游学科升格的理路探析

由于政府指令性学科专业目录的存在,旅游学科在中国的成长受到外在制度的束缚“,工商管理”一级学科下“旅游管理”二级学科的设置现状,对高等旅游教育和旅游业健康发展极为不利,遂有旅游学科升格之需。文章从“学科”意蕴的探讨入手,审视了学科专业目录规制的内在危机及其在旅游学科发展中的矛盾表现,借用学术性和实践性二维学科评价标准,分析说明了创建旅游管理一级学科的逻辑依据,并引入学科发展的一般逻辑和“好旅游”的基本框架,提出了旅游管理一级学科内部架构设计的三种基本模式。文章的主要观点是：在指令性学科专业目录尚不能彻底否定的前提下,允许并支持部分新兴学科升格,是政府优化学科管理制度的明智选择;创建旅游管理一级学科符合学术逻辑和社会需求逻辑,是旅游知识共同体当下的具体任务,意义不容小觑;遵从学理与应用相统一的逻辑,旅游管理一级学科的架构有对接本科专业目录设计、垂直设计和水平设计三种基本模式;推动旅游学科的升格,会引发学科基本命题的再思考,发挥带动学科内涵建设的作用。     

Movie Tourism—A New Form of Cultural Landscape?

Tourism originally was perceived as visitors travelling, whether within their own country or internationally, for pleasure. However, over the years, tourism has evolved into different components and labels. One is Movie Tourism. Although people have travelled due to novels they have read or historical occurrences, it would appear that movies based on these aspects have increased visitation. It would seem that Movie Tourism could be a new form of cultural landscape. Over time the appeal of destinations has grown and altered from the preconception that movies portray to audiences. It could further be perceived that Movie Tourism is connected to nostalgia and identity. A yearning for what life was or should be like, creating identities within historical settings, imaginary and/or factual. This paper is a discourse on the aforementioned and the tourist dollar value that Movie Tourism contributes to a country's economy.     

Density tourism demand forecasting revisited

This study used scoring rules to evaluate density forecasts generated by different time-series models. Based on quarterly tourist arrivals to Hong Kong from ten source markets, the empirical results suggest that density forecasts perform better than point forecasts. The seasonal autoregressive integrated moving average (SARIMA) model was found to perform best among the competing models. The innovation state space models for exponential smoothing and the structural time-series models were significantly outperformed by the SARIMA model. Bootstrapping improved the density forecasts, but only over short time horizons.This article also launches the Annals of Tourism Research Curated Collection on Tourism Demand Forecasting, a special selection of research in this field.     

Post-disaster tourism: building resilience through community-led approaches in the aftermath of the 2011 disasters in Japan

Abstract

Post-disaster tourism is often perceived as a form of Dark Tourism associated with death, loss and destruction. In Japan, the term Dark Tourism has gained prominence following the 2011 Great East Japan Earthquake and Tsunami. This paper focuses on a community-led approach to post-disaster tourism development, initiated in the coastal area of Minamisanriku and labelled by the locals Blue Tourism. From its inception Blue Tourism incorporated non-dark activities which concentrated on the beauty of nature, social and environmental sustainability and the development of an enriched tourist experience. Its co-creational ethos helped transform some of the negative narratives of loss associated with Dark Tourism into positive accounts of communal renewal and hope. The paper highlights the limitations of Dark Tourism to post-disaster recovery and contributes new insights to the community-based tourism literature. We argue that Blue Tourism is not a type of Dark Tourism but a form of resilience which builds around local place-based practices and traditional community knowledge. Consequently, it is capable of achieving sustainable disaster recovery and tourist satisfaction simultaneously.     

A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting

This study reviews 211 key papers published between 1968 and 2018, for a better understanding of how the methods of tourism demand forecasting have evolved over time. The key findings, drawn from comparisons of method-performance profiles over time, are that forecasting models have grown more diversified, that these models have been combined, and that the accuracy of forecasting has been improved. Given the complexity of determining tourism demand, there is no single method that performs well for all situations, and the evolution of forecasting methods is still ongoing.This article also launches the Annals of Tourism Research Curated Collection on tourism demand forecasting, which contains past and hot off the press work on the topic and will continue to grow as new articles on the topic appear in Annals.     

Learning and Ability to Pay

Summary

The decision whether to use time series or econometric methods to forecast demand is not clear. The literature reviewed only indicates that models should be simple and ideally be able to evolve over time. In 1997 two models were proposed to forecast the numbers from Britain skiing in Europe. The first used a learning curve approach and forecast a stationary market, whilst the second used a Varying Coefficient Model linking sales and ability to pay and forecast a gradually expanding market. This paper reviews the outcomes 1996-2000, the forecast performance of the two models and the stability of the structure of both when updated. It unequivocally suggests that the learning curve approach produced better forecasts. In the penultimate section a model that attempts to combine both approaches is developed. In this context the role of “historic” data is discussed. The paper concludes that the best forecasting approach will depend upon whether the market is stable and that the weight given to data must reflect the information content of that data.     

Insights into TripAdvisor's online reviews: The case of Tehran's hotels

User-generated data in TripAdvisor.com consists of considerable amount of useful information that can help managers to provide better services to their customers. This study aims to forecast a new user's rate to a hotel based on information of the hotel and user. To do so, all reviews on all hotels of Tehran on TripAdvisor.com as real data are selected and 8 different supervised machine learning models are applied to the data to select the best method including K-nearest neighbors (KNN), Naïve Bayes, decision tree, logistic regression, support vector machine, neural network, random forest, and gradient boosting. KNN algorithm which uses similarity and distance measures for classification is selected as the best method through conducted comprehensive comparisons, statistical analysis and data-based sensitivity analysis. Since this study investigates an intensive set of data of all hotels in a city in all time, some worthful managerial insights are presented.     

旅游合同解除制度的体系性解释

《旅游法》中的旅游合同解除制度,须结合《合同法》上的解除制度进行体系性解释。旅游合同的一般法定解除权应包括《合同法》第94条的规定。《旅游法》第67条的"不可避免事件",存在解释的空间。《旅游法》虽未明确旅游者的任意解除权,但无论是从合同性质路径还是合同具体内容导出合同义务路径,《旅游法》第65条都应被解释为旅游者任意解除权的依据。而旅游经营者的法定解除权,应秉持立法宗旨及旅游特性,对传染病、危害公共安全的物品、社会公德、违法活动等用语进行限定解释。在旅游合同解除效果上,应考虑到未履行部分费用、返程费用、履行利益及时间浪费赔偿的特殊性。     

Getting closer to whales—passenger expectations and experiences, and the management of swim with dwarf minke whale interactions in the Great Barrier Reef

Whale-watching tourism is a growth industry worldwide. In Australia, with whale-watchers approaching one million per annum there has been considerable effort to develop management regimes that protect the whales while enabling the development of a sustainable ecotourism industry. A mixture of National and State laws and regulations have governed the industry (Tourism based on free-ranging marine wildlife: opportunities and responsibilities, Wildlife Tourism Research Report No. 11, Status Assessment of Wildlife Tourism in Australia Series, CRC for Sustainable Tourism, Gold Coast, Queensland) but these have been mainly derived from experiences with humpback (Megaptera novaeangliae) whale watching from vessels at sea. In this article we describe the development and nature of new and rapidly growing swim-with-whales operations based on the dwarf minke whales (Balaenoptera acutorostrata) in the Great Barrier Reef of northern Queensland. The distinctly different quality of these operations raise interesting questions for long-term management (Towards sustainable management of the developing dwarf minke whale tourism industry in northern Queensland, CRC Reef Research Technical Report 27, James Cook University of North Queensland, 30pp (emended version of SC/50/WW1)).In the 1999–2000 seasons, 453 passengers (88.1% of respondents) swam with minke whales. Only 25% of visitors came specifically for the whale interactions and 43% learned of the whales on board the vessel. Passengers thus had low expectations about whales and encounters. A variety of factors, including the diving experience, particular dive sites, a range of wildlife species and socializing contributed to visitor satisfaction. Nonetheless, there was a significant correlation between visitor satisfaction and closeness of approaches by the whales, total number of whales seen and total time spent with whales. We discuss the key issues associated with swim-with-whales programs in the light of our findings. The cooperative engagement of tourism operators, researchers and government management agencies is a feature of this new industry.     

Perceived Impact of a Naval Base on a Tourism Destination

Perceptions toward tourism development have been explicitly and extensively investigated within the tourism literature. However, there is little study of perceptions toward non-tourism development (NTD) in tourist destinations. NTD in a tourist destination may be unavoidable, because as tourism grows, the destination may need more facilities and infrastructure to meet the needs of tourists and residents. Alternatively, the NTD may not enhance tourism at all, but rather compete for space and human, financial and political resources. The objective of this study is to reveal how residents of a small tourism-oriented island, JeJu Island in South Korea, would perceive NTD and examine ramifications of a naval base for tourism preferences. Residents were clustered into three groups based on their preferences for tourism activity, Tourism Supporters, Tourism Neutrals, and Tourism Opponents. Study results revealed that the three groups differed among socio-demographic variables as well as perceived cultural and local infrastructure impacts of NTD.     

中国旅游发展政策的历史演进(1949~2013)——一个量化研究的视角

文章从1949~2013年中央政府及相关部委发布的379个旅游政策文件的多维度统计分析入手,以全新的视角剖析了新中国成立以来我国旅游发展政策的演化历程。研究发现:(1)我国旅游政策演化是资源配置的行政化转向行政权力制约下的资源配置市场化过程。(2)旅游政策目标始终与国家经济社会发展的战略目标相一致,可大致分为服务外事、经济型事业、经济新增长点、国家战略性支柱产业四个阶段。(3)旅游政策工具以微观管制为主,对资本、土地、技术、人才等生产要素宏观调控能力不足。(4)旅游政策的制定部门范畴不断扩大,政策力度呈波动趋稳态势。研究认为,旅游经济的有效运行高度依赖于社会经济系统的制度安排。在《旅游法》颁布、旅游业进入全新的发展阶段后,技术进步、市场需求、企业竞合关系协同引领的产品业态与商业模式创新是未来产业效率提升的基本方向,宏观调控和公共服务将成为政府旅游管理的基本内容。