Terrorism and travel advisory effects on international tourism

The paper applies dynamic panel modeling to investigate the impact of terrorism and travel advice on global tourism. Annual arrivals data for 49 destinations and 15 leading countries of origin for the period 2010–2014 are used. Results indicate that casualties or fatalities from terrorism, absent travel advice, significantly reduce tourism demand. However, casualties (fatalities) combined with travel advice have a relatively larger adverse impact on tourism demand. The effects identified, however, are sensitive to country characteristics. Casualties (fatalities) as well as travel advice significantly weaken tourism demand for low-income countries but have no significant effect in high-income countries.     

The impacts of international tourism demand on economic growth of small economies dependent on tourism

This paper studies the impacts on economic growth of a small tourism-driven economy caused by an increase in the growth rate of international tourism demand. We present a formal model and empirical evidence. The ingredients of the dynamic model are a large population of intertemporally optimizing agents and an AK technology representing tourism production. The model shows that an increase in the growth of tourism demand leads to transitional dynamics with gradually increasing economic growth and increasing terms of trade. In our empirical application, an econometric methodology is applied to annual data of Antigua and Barbuda from 1970 to 2008. We perform a cointegration analysis to look for the existence of a long-run relationship among variables of economic growth, international tourism earnings and the real exchange rate. The exercise confirms the theoretical findings.     

The impacts of governance and institutions on inbound tourism demand: evidence from a dynamic panel data study

This study explores the impact of governance and institutions on inbound tourism demand in Malaysia using a dynamic panel data approach for 45 tourism source countries over the period 2005–2015. The results show that institutions play a very important role in explaining the behaviour of inbound tourism demand. To obtain a better picture, we investigate the response of international tourists to disaggregated institutional quality. We find that international tourists are more concerned about political stability, governmental effectiveness, regulations, laws, and corruption than voice and accountability. Therefore, policymakers should focus on ways to improve institutional quality to significantly increase international tourist arrivals.     

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.     

A meta-analysis of international tourism demand forecasting and implications for practice

Numerous studies on tourism forecasting have now been published over the past five decades. However, no consensus has been reached in terms of which types of forecasting models tend to be more accurate and in which circumstances. This study uses meta-analysis to examine the relationships between the accuracy of different forecasting models, and the data characteristics and study features. By reviewing 65 studies published during the period 1980–2011, the meta-regression analysis shows that the origins of tourists, destination, time period, modeling method, data frequency, number of variables and their measures and sample size all significantly influence the accuracy of forecasting models. This study is the first attempt to pair forecasting models with the data characteristics and the tourism forecasting context. The results provide suggestions for the choice of appropriate forecasting methods in different forecasting settings.     

Immigration and international inbound tourism: Empirical evidence from Australia

Immigration can potentially influence tourism flows. However, in spite of the vast number of studies on tourism demand modelling, the immigration-tourism linkage has not received much attention in the empirical literature. This paper seeks to address this gap. A dynamic demand model is developed and estimated using data from 1980 to 2008 for the 15 main markets of Australia. The explanatory variables included are income, own price, price of a substitute destination, airfare and immigration. The estimation results empirically establish the connection between immigration and inbound tourism. The short run and long-run immigration elasticities generated are 0.028 and 0.09 respectively. Additionally this paper demonstrates that omission of prices of substitutes affects the value of the own price elasticity of demand. The results have implications for future research and for stakeholders who can improve the efficiency of their planning exercises by taking into account additional information on immigration trends.     

International tourism demand in Asia: before and after the economic crisis

A subprime mortgage crisis erupted in the United States in 2007 and resulted in an economic crisis spread worldwide. This study focused on seven major Asian tourist destinations and investigated the changes in international tourism demand before and after economic crisis. The data period was January 2004 to December 2014. The results demonstrate the tourist numbers in each country was affected by the income variable. The decrease in tourist numbers was most significant during and after the economic crisis, indicating an increase in the sensitivity of tourists toward their economic-crisis-based income fluctuations, causing changes in their travel behavior.     

Measuring price elasticities of demand for outbound tourism using competitiveness indices

The real exchange rate (REX) has long been used as the proxy for prices in tourism demand models. However it has limitations, particularly when it comes to models of outbound tourism. As an alternative, a price competitiveness index (PCI) is developed and used as a proxy for prices in a model of outbound tourism from Australia. Results obtained show that while REX is statistically insignificant and yields a price elasticity of −0.002, PCI is significant and generates a price elasticity of −1.07. The results obtained show that PCI outperforms REX as the preferred price variable in modelling outbound demand on both theoretic and empirical grounds. Furthermore, this index can be used to monitor the inter-temporal competitiveness of a destination.     

Nonconstant reputation effect in a dynamic tourism demand model for Spain

Following the ideas of the Tourism Area Life Cycle (TALC) theory, we propose a dynamic econometric model for tourism demand where the reputation effect (the effect of the lagged demand on the current tourism demand) is not constant, but dependent on congestion. We test the model using panel data from Spanish regions during the period 2000–2013. Two estimations are performed depending on whether the tourists' origin is domestic or international. The results show that the reputation effect is not constant in both estimates, supporting the idea that tourism congestion influences tourist arrivals in Spain.     

The effects of SARS on the Hong Kong tourism industry: An empirical evaluation

The objective of this study is to assess the temporal impact of SARS on the tourists' arrival in Hong Kong. An econometric strategy was carefully selected to determine the existence of unit roots in data series containing the number of tourist arrivals from 36 source countries between 1978 and 2001. The existence of unit roots can detect the stationary properties of the series. The analysis finds that data series of 24 countries contain unit roots and hence any form of exogenous shocks, like the SARS epidemic, can have permanent impact on the number of tourist arrivals. Included in this category are Japan, Taiwan, the US and the UK, which are the main source of tourists for Hong Kong. The paper recommends that authorities take source-country-specific measures to manage the negative effect of SARS.     

Assessing the importance of international tourism for the Turkish economy: A social accounting matrix analysis

The international tourism sector has grown rapidly in Turkey since the 1980s and Turkey ranks among the top ten countries in terms of tourist arrivals and receipts. Previous studies on international tourism in Turkey are partial equilibrium studies which emphasized the importance of the sector for foreign exchange earnings, employment creation, and economic growth. The social accounting matrix (SAM) modeling approach is superior to partial equilibrium analysis as it takes into account intersectoral linkages. This paper analyzes the contribution of international tourism to the Turkish economy using two SAMs for 1996 and 2002, respectively. Two analyses are conducted using the SAM impact model: (i) sectoral comparison of GDP elasticities, and (ii) SAM impact analysis of international tourism on output, value-added, and employment. The results show that the GDP elasticity of international tourism is relatively low and the impact of foreign tourist expenditures on domestic production, value-added (GDP), and employment in Turkey are modest. The results imply the possibility of leakage of foreign tourist expenditures out of the economy.     

Agglomeration density and tourism development in China: An empirical research based on dynamic panel data model

To explain the significant disparity of tourism development across Chinese provinces, this paper conducts a dynamic panel data analysis of tourism development in China using statistical data of Chinese provincial tourism industry for the 2000–2009 periods. The estimated results provide empirical evidence on the relationship between the agglomeration and development of Chinese provincial tourism in firm level. The econometric analysis shows that the tourism density in agglomeration has a positive influence on local tourism development. It appears that the variance of tourism development across Chinese provinces can be explained by the differences in the density of tourism economic activities.     

Effects of budgetary constraints on international tourism expenditures

This paper implements a logistic transition regression model to examine the relationships between GDP per capita and international tourism expenditures across countries in 2001–2010 by types of savings regimes. While studies have focused on the effect of income on international tourism expenditures, none consider the nonlinear smooth transition status of savings and its impacts on discretionary spending and hence expenditure on tourism. The impact of income on tourism expenditures can vary under different savings regimes. The results show that in a low savings regime the effect of an increase in the GDP per capita on international tourism expenditures is more pronounced. In a high-savings regime, there is strong motivation for precautionary savings and tourism is considered a luxury; therefore such spending is crowded out by an increase in savings as GDP per capita increases. Although international tourism expenditures also increase with GDP per capita, they do so at a slower rate. These findings establish an accurate understanding of the effects of savings on international tourism expenditures.     

The response of hotel performance to international tourism development and crisis events

This study uses panel regression tests to examine the response of hotel performance to international tourism development and crisis events in Taiwan. Hotel performance measures are revenue (revenue per available room and occupancy rate), profitability (return on assets and return on equity) and stock performance. The crises were the earthquake on September 21, 1999 (the 9/21 earthquake), the terrorist attacks of September 11, 2001 in the US (the 9/11 terrorist attacks) and the outbreak of Severe Acute Respiratory Syndrome on April 22, 2003 (the SARS outbreak). This study makes four major contributions. First, test results confirm that international tourism development (ITD), proxied by the growth of total inbound tourist arrivals, has a more direct influence on hotel sales and profitability than it does on hotel stock performance. Second, this study identifies that the absence of a strong tie between ITD and hotel stock returns that was found in previous studies is due to the time-varying discount rate caused by investors’ changing expectations for the prospect of future cash flows from holding hotel stocks. Third, this study finds new evidence that while the poor performance of hotel stocks caused by the 9/21 earthquake and the 9/11 terrorist attacks was attributed to the loss of hotel sales revenue, the adverse effect of the SARS outbreak on hotel stock returns is attributed not only to decreased hotel sales revenue but also to the increased discount rate. Lastly, this study is the first to investigate whether the response of hotel stock returns to ITD depends on the state of economy and concludes that the response of hotel stock performance to ITD in business cycle contraction is statistically different from that in business cycle expansion. Further, although the influence of ITD on hotel stock performance is still irrelevant during expansion periods, ITD can significantly enhance hotel stock returns during contraction periods.     

An empirical analysis of the influence of macroeconomic determinants on World tourism demand

This paper considers three econometric models to determine the relationship between macroeconomic variables and tourism demand. Tourism demand is measured by the inbound visitor's population and also by on-the-ground expenditures. The database is an unbalanced panel of 218 countries over the period 1995–2012. There is evidence that an increase in the World's GDP per capita, a depreciation of the national currency, and a decline of relative domestic prices do help boost tourism demand. The World's GDP per capita is more important when explaining arrivals, but relative prices become more important when we use expenditures as the proxy for tourism demand. We cannot reject the hypothesis of a relative prices unitary elasticity of expenditures. Additionally, we have partitioned our data by income level and by Continent. Results are robust in the first partition, but less robust in the second, although the main conclusions still hold. Finally, we draw policy implications from our findings.     

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.     

Impact of unexpected events on inbound tourism demand modeling: evidence of Middle East Respiratory Syndrome outbreak in South Korea

This paper attempts to evaluate how South Korea’s inbound tourist arrivals from China have been affected by the Middle East Respiratory Syndrome (MERS) outbreak. Using quarterly data, the autoregressive distributed lag model (ADLM) is performed to capture the influence of the MERS outbreak. Estimation results of the general ADLM reveal that the MERS outbreak has a significant adverse impact on the total inbound tourist arrivals from China, as well as on tour arrivals; however, for business, official, and other types of tourist arrivals, its influence is insignificant. Furthermore, the error correction model is estimated to demonstrate the long-run equilibrium and short-run dynamics among the underlying variables. Our analysis not only provides empirical evidence on evaluating the impact of the MERS outbreak on different types of tourism demand, but also identifies main determinants and suggests appropriate model specifications for each type of tourist arrivals.     

The effect of international tourism on economic development: An empirical analysis

The expansion of international tourism in developing countries is generally considered to promote their economic development. In this paper, the impact of international tourism on economic development is modelled using an aggregate production function framework. It specifically investigates intersectoral externalities and marginal factor productivity differences between the international tourism sector and the rest of the economy. The net effect of international tourism on GDP per capita is examined via an empirical analysis of 37 developing economies. The results indicate that international tourism may positively affect economic development in these countries.     

Understanding the travel motivation and patterns of international students in Korea: using the theory of travel career pattern

This study examined the travel motivation of international students in Korea using the theory of travel career pattern (TCP). In particular, latent profile analysis (LPA) was applied to identify latent classes within international students. Based on the results, four latent profiles were derived and named “Core,” “Longing,” “Middle,” and “Veteran.” The results described the travel motivation and patterns across these four profiles to enhance the understanding of international students in the context of tourism. There were significant differences in travel patterns (i.e. travel companion and information sources) among the profiles segmented by motivation. This study has expanded travel motivation research by (a) applying TCP to an understudied population (i.e. international students in a non-English-speaking country); (b) comparing travel careers between the home country, Korea (i.e. a study abroad destination), and the third countries; and (c) highlighting LPA as a clustering tool to understand travel motivation.