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One of the main factors that can impact the cost of holidays to a particular destination is the exchange rate; exchange rate fluctuations impact the overall price of the holiday and should be expected to effect tourism demand. This paper aims to scrutinize the volatility of the real effective exchange rate between the source market relative to the holiday destination and tourism demand volatility, where the influence of disaggregated data is noted.

The study uses multivariate conditional volatility regressions to simulate the time-varying conditional variances of international visitor demand and exchange rates for the relatively mature Caribbean tourist destination of Barbados. Data on the country’s main source markets, the UK, the USA and Canada is used, where the decision to disaggregate the analysis by market allows the authors to contribute to policymaking, particularly the future of tourism marketing.

The volatility models used in the paper suggests that shocks to total arrivals, as well as the USA and UK markets tend to die out relatively quickly. Asymmetric effects were observed for total arrivals, mainly due to the combination of the different source markets and potential evidence of Butler’s (1980) concept of a tourist area’s cycle of growth. The results also highlight the significance of using disaggregated tourism demand models to simulate volatility, as aggregated models do not adequately capture source market specific shocks, due to the potential model misspecification. Exchange rate volatility is postulated to have resulted in the greater utilization of packaged tours in some markets, while the effects of the market’s online presence moderates the impact of exchange rate volatility on tourist arrivals. Markets should also explore the potential of attracting higher numbers of older tourist, as this group may have higher disposable incomes, thereby mitigating the influence of exchange rate volatility.

Some of the explanatory variables were not available on a high enough frequency and proxies had to be used. However, the approach used was consistent with other papers in the literature.

The results from the paper suggest that the effects of exchange rate volatility in key source markets were offset by non-price factors in some markets and the existence of the exchange rate peg in others. In particular, the online presence of the destination was one of those non-price factors highlighted as being important.

In most theoretical models of tourism demand, disaggregation is not normally considered a significant aspect of the model. This paper contributes to the literature by investigating the impact real effective exchange rate volatility has on tourism demand at a disaggregated source country level. The approach highlights the importance of modeling tourism demand at a disaggregated level and provides important perspective from a mature small island destination.

该研究采用多元条件波动回归来拟合相对成熟的加勒比海旅游目的地巴巴多斯的国际游客需求和汇率的时变条件方差。本研究逐一分析了该国主要客源市场（英国, 美国和加拿大）的数据, 从而为政策制定, 尤其是对今后的旅游营销做出贡献。

汇率是影响到特定目的地度假成本的主要因素之一。汇率波动会影响整体的度假成本, 并会影响旅游需求。基于按客源地分类的数据, 本文详细研究了客源市场相对于度假目的地的实际有效汇率的波动性以及旅游需求的波动性。

本文使用的波动模型表明, 汇率冲击对入境总人数以及美国和英国市场影响短暂。冲击对总入境人数产生的不对称效应, 主要是由于不同的客源市场加总和巴特勒（1980）关于旅游区增长周期概念所致。本文结论还凸显了使用基于客源地数据的旅游需求模型来模拟波动性的重要性, 因为加总数据不能充分捕获具体客源地市场的冲击从而产生模型设定作物。汇率波动会引起某些市场中团体游客的增加, 而目的地的线上热度影响会调节汇率波动对游客人数的影响。市场还应探索吸引更多老年游客的潜力, 因为该群体的可支配收入可能更高, 从而减轻了汇率波动的影响。

由于一些解释变量的数据频率不够高, 本文不得不使用一些替代指标。所使用的方法与文献中的其他论文一致。

该论文的结果表明, 在某些客源地市场, 汇率波动的影响会被某非价格因素所抵消, 而在另一些主要客源地市场, 固定汇率的存在刚好规避了汇率波动产生的影响。目的地的线上热度是重要的非价格因素之一。

在大多数旅游需求理论模型中, 按客源地拆分的数据通常不被视为模型的重要方面。本文的理论贡献则是通过研究实际有效汇率波动对不同客源国的旅游需求的影响强调了旅游需求建模中使用基于客源地数据的重要性, 并以一个成熟的小岛目的地为角度进行了阐述。

Uno de los principales factores que pueden afectar al costo de las vacaciones a un destino en particular es el tipo de cambio; Las fluctuaciones del tipo de cambio afectan a el precio general de las vacaciones y es normal que afecten a la demanda turística. Este documento analiza la volatilidad del tipo de cambio efectivo real entre el mercado de origen en relación con el destino de vacaciones y la volatilidad de la demanda turística, donde se observa la influencia de los datos desagregados.

El estudio emplea regresiones de volatilidad condicional multivariadas para simular las variaciones condicionales variables en el tiempo de la demanda de visitantes internacionales y los tipos de cambio para el destino turístico caribeño relativamente maduro de Barbados. Se emplean datos sobre los principales mercados de origen del país, el Reino Unido, los Estados Unidos de América y Canadá, donde la decisión de desagrerar el análisis por mercado permite a los autores contribuir a la formulación de políticas, en particular al futuro del marketing turístico.

Los modelos de volatilidad utilizados en el documento sugieren que los shocks en las llegadas totales, así como en los mercados de los Estados Unidos y el Reino Unido, tienden a desaparecer con relativa rapidez. Se observaron efectos asimétricos para las llegadas totales, principalmente debido a la combinación de los diferentes mercados de origen y la evidencia potencial del concepto de Butler (1980) del ciclo de crecimiento de un área turística. Los resultados también resaltan la importancia de utilizar modelos desagregados de demanda turística para simular la volatilidad, ya que los modelos agregados no capturan adecuadamente los shocks específicos del mercado de origen, debido a la posible especificación errónea del modelo. Se postula que la volatilidad del tipo de cambio influye en una mayor utilización de los paquetes turísticos en algunos mercados, mientras que los efectos de la presencia del mercado en linea (online) moderan el impacto de la volatilidad del tipo de cambio en las llegadas de turistas. Los mercados también deberían explorar el potencial de atraer un mayor número de turistas mayores, ya que este grupo puede tener mayores ingresos disponibles, mitigando así la influencia de la volatilidad del tipo de cambio.

Algunas de las variables explicativas no estaban disponibles en una frecuencia alta y se tuvieron que utilizar proxies. Sin embargo, el enfoque utilizado fue consistente con otros artículos en la literatura.

Los resultados del documento sugieren que los efectos de la volatilidad del tipo de cambio en los mercados de origen clave fueron compensados por factores no relacionados con los precios en algunos mercados y la existencia de la vinculación del tipo de cambio en otros. En particular, la presencia en línea (online) del destino fue uno de esos factores no relacionados con el precio destacados como importantes.

En la mayoría de los modelos teóricos de la demanda turística, la desagregación normalmente no se considera un aspecto significativo del modelo. Este documento contribuye a la literatura al investigar el impacto que la volatilidad efectiva del tipo de cambio real tiene sobre la demanda turística a nivel de país de origen desagregado. El enfoque resalta la importancia de modelar la demanda turística a un nivel desagregado y proporciona una perspectiva importante desde un destino insular pequeño y maduro.

The purpose of this paper is to identify the core factors that determine tourism demand in four inbound markets of Hong Kong.

The general-to-specific approach was adopted as a step-by-step approach to identify the major determinants of tourism demand in Hong Kong.

The study revealed word of mouth and income of source market are core determinants of tourism demand in all four inbound markets.

Knowledge of core determinants of tourism demand is useful to destination management organizations and tourism business owners for strategic planning and decision making to increase total revenues.

The purpose of this paper is to review the current literature in the field of tourism demand forecasting.

Published papers in the high quality journals are studied and categorized based their used forecasting method.

There is no forecasting method which can develop the best forecasts for all of the problems. Combined forecasting methods are providing better forecasts in comparison to the traditional forecasting methods.

This paper reviews the available literature from 2007 to 2017. There is not such a review available in the literature.

This study examines whether international tourism demand in the Visegrád countries is influenced by countries' risk rating on environmental, social and governance (ESG) factors, as non-economic factors relating to ESG risks have been ignored by previous researches on determinants of international tourism demand.

The study investigates panel data for the Visegrád countries comprising the Czech Republic, Hungary, Poland and Slovakia over the period 1995–2019. Recently developed techniques of augmented mean group (AMG) and common correlated effects mean group (CCEMG) estimators are employed so as to take care of cross-sectional dependence, nonstationary residuals and possible heterogeneous slope coefficients.

The regression estimates suggest that besides economic factors, the perception of international tourists regarding ESG risk is another important determinant of international tourism demand in the Visegrád countries. The study also established that income levels in the tourists' originating countries are the most critical determinant of international tourism demand to the Visegrád countries.

The research outcomes of the study include the need for the Visegrád countries to direct policies towards further mitigating their ESG risks in order to improve future international tourism demand in the area. They also need to ensure exchange rate stability to prevent volatility and sudden spikes in the relative price of tourism in their countries.

The purpose of this communication is to contribute to the understanding of the causes of the variation in the regional distribution of the demand for tourism in OECD countries. Our contention is that exchange rate fluctuations since 1970 have strongly influenced both cyclical and long‐term patterns of international tourism behaviour. Except for works by Gerakis and Artus the literature covers this aspect only marginally. However, their pioneering econometric analyses do not satisfy a number of fundamental objections to the measurement of tourism demand.

The chapter aims to examine the interrelationships between aviation and Asian inbound tourism demand to Australia. First, the chapter introduces key factors in the economics of tourism demand and the empirical work in assessing the aviation–tourism demand relations. Based on 2005–2016 annual time series data across 12 of Australia’s main Asian markets, a dynamic panel regression model is applied to empirically examine the factors influencing tourism demand including exchange rates and disposable income. Using a generalized method of moments approach, the study accounts for the endogenous relations between levels of international air services availability (proxied by seat capacity) and tourism demand. The results suggest, on average, the generative effect of aviation exists albeit with small magnitude (0.1–0.5% increase in tourism demand per 100,000 additional seat capacity). The chapter concludes with a discussion on the shifting inbound tourism balance toward Asia and the implications for aviation policy to meet the high Asian tourism growth targets.

This study aims to measure the relationship between demand and exchange rate shocks in the tourism industry.

A panel data set is constructed covering the period between 1995 and 2017, and the data set includes the top 26 countries that host 10 million tourists and above in the world as of 2017. The standard errors of the series are used as an indicator of shocks. First, the cross-sectional dependency, stationarity and the homogeneity of the series are examined; second, a panel cointegration analysis is implemented; third, long-term panel cointegration coefficients are analyzed with Dynamic Common Correlated Effects (DCCE) approach; and, finally, Dumitrescu and Hurlin’s (2012) Granger non-causality test is used to detect the causality.

The preliminary analyses show that the variables are cross-sectional dependent and heterogeneous and are stationary in their first difference; hence, the effects of the shocks are temporary. On the other hand, as a result of the panel cointegration analysis, it is found that both series are cointegrated over the long-term. However, the long-term coefficients estimated with the DCCE approach are found not to be statistically significant. Finally, as a result of the Dumitrescu and Hurlin’s (2012) Granger non-causality test, it is concluded that there is a causality running from exchange rate shocks to demand shocks.

To the best of the authors’ knowledge, the cointegration between the tourism demand shocks and exchange rates shocks has not been investigated before, and therefore, this study is considered to be a pioneering study that will contribute to the literature.

This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism has been identified as a new tourism sub-sector with high potential, and is thus expected to boost economic growth and sustainability.

This study reviews the literature on the determinants of educational tourism demand. Even though the existing literature is intensively discussed, mostly focusing on the educational tourism demand from an individual consumer's perspective, this study makes an innovation in line with the aggregate demand view. The study uses data that consist of the enrolment of international students from 47 home countries who studied in Malaysia from 2008 to 2017. The study utilised the dynamic panel method of analysis.

This study affirms that income per capita, educational tourism price, price of competitor countries and quality of universities based on accredited programmes and world university ranking are the determinants of educational tourism demand in both the short and the long term. Also, a dynamic effect exists in educational tourism demand.

The results imply that government should take the quality of services for existing students, price decisions and QU into account to promote the country as a tertiary education hub and achieve sustainable development.

Research on the determinants of the demand for educational tourism is rare in terms of macro data, and this study includes the roles of QU, competitor countries and dynamic effects.

This paper aims to propose a hybrid-forecasting model for long-term tourism demand forecasting. As such, it attempts to model the tourism demand in the Philippines, which is a relatively underrepresented area in the literature, despite its tourism sector’s growing economic progress.

A hybrid support vector regression (SVR) – seasonal autoregressive integrated moving averages (SARIMA) model is proposed to model the seasonal, linear and nonlinear components of the tourism demand in a destination country. The paper further proposes the use of multiple criteria decision-making (MCDM) approaches in selecting the best forecasting model among a set of considered models. As such, a preference ranking organization method for enrichment of evaluations (PROMETHEE) II is used to rank the considered forecasting models.

The proposed hybrid SVR-SARIMA model is the best performing model among a set of considered models in this paper using performance criteria that evaluate the errors of magnitude, directionality and trend change, of a forecasting model. Moreover, the use of the MCDM approach is found to be a relevant and prospective approach in selecting the best forecasting model among a set of models.

The novelty of this paper lies in several aspects. First, this paper pioneers the demonstration of the SVR-SARIMA model’s capability in forecasting long-term tourism demand. Second, this paper is the first to have proposed and demonstrated the use of an MCDM approach for performing model selection in forecasting. Finally, this paper is one of the very few papers to provide lenses on the current status of Philippine tourism demand.

The purpose of this paper is to investigate antecedents of households' local demand for domestic tourism in Jordan.

A sample of 600 households is surveyed and a two‐stage demand model is estimated. Stage 1 identifies the antecedents of the probability of entering the domestic tourism market. Stage 2 identifies the antecedents of households' expenditures on domestic tourism. The Heckit method is used to estimate the first stage and the OLS is used to estimate the second stage.

Certain socio‐economic factors (household characteristics, individual characteristics and ability variables) impact the local demand for domestic tourism, as do price and income variables.

The generalizability of results to other countries is limited.

Identification of antecedents of local demand for domestic tourism helps governments to formulate and modify future tourism strategies.

This paper contributes to the literature by including socio‐economic variables in the domestic tourism demand model. Further, there is a dearth of studies in Jordan in general and regarding domestic tourism in particular.