Hsiao-I Kuo

Assessing impacts of SARS and Avian Flu on international tourism demand to Asia.

Abstract The purpose of this paper is to investigate the impacts of infectious diseases including Avian Flu and severe acute respiratory syndrome (hereafter SARS) on international tourist arrivals in Asian countries using both single datasets and panel data procedures. An autoregressive moving average model together with an exogenous variables (ARMAX) model are used to estimate the effects of these diseases in each SARS- and Avian Flu-infected country, while a dynamic panel model is adopted to estimate the overall impact on the region of these two diseases. The empirical results from both approaches are consistent and indicate that the numbers of affected cases have a significant impact on SARS-affected countries but not on Avian Flu-affected countries. However, since the potential damage arising from the Avian Flu and subsequent pandemic influenza is much greater than that resulting from the SARS, the need to take the necessary precautions in the event of an outbreak of Avian Flu and pandemic influenza warrants further attention and action. Therefore, the empirical findings of this study could add to the knowledge regarding the relationship between tourism and crisis management, especially in so far as the management of transmissible diseases is concerned.

An econometric analysis of SARS and Avian Flu on international tourist arrivals to Asia

Abstract This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu are compared directly according to the number of human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.

Estimating the Impact of Avian Flu on International Tourism Demand Using Panel Data

This paper investigates the impacts of avian flu on global and Asian tourism using panel data procedures. Both static and dynamic fixed effects panel data models are adopted to estimate the impacts of this infectious disease. The empirical results from static and dynamic fixed effects panel data models are consistent and indicate that the number of affected poultry outbreaks has significant impacts on the international tourism of global and Asian affected countries. The high mortality rate among humans, the potential of a global flu pandemic and some media frenzy with hype and speculation might adversely affect the images of these infected destinations as a safe tourist destination. Moreover, it was found that the average damage to Asian tourism was more serious, which might have been induced by an ineffective suppression in numerous Asian infected countries. In addition, Asia was the earliest affected region and the area infected most seriously by avian flu, both in humans and in poultry. Since the potential risks and damage arising from avian flu and the subsequent pandemic influenza are much greater than for previous diseases, the need to take necessary precautions in the event of an outbreak of avian flu and pandemic influenza warrants further attention and action in modelling and managing international tourism demand and risk.

A spatiotemporal statistical model of the risk factors of human cases of H5N1 avian influenza in South-east Asian countries and China

OBJECTIVES This article aims to quantify the risk factors associated with the human cases of H5N1 avian influenza in South-east Asian countries and China; a dangerous region for this disease that has the potential for a pandemic outbreak. STUDY DESIGN A statistical model with time and spatial dimensions was built to capture the international spread patterns of this disease. METHODS The grid search method was used to fit the model with 2004-2006 data. The grid search approach is a simple procedure that allows the fit of any function to data. RESULTS This study found that: (1) when the number of domestic H5N1 human cases increases by one person in a certain time period, the chance that the country will have a human case in the next period increases by 22.10%; (2) when the number of human cases in a neighbouring country increases by one person in a certain time period, the chance that the country will have a human case in the next period increases by 1.62%; (3) when the number of avian cases in a neighbouring country increases by one, the chance that the country will have a human case increases by 0.02%; (4) as the human population increases by one unit, the chance that the country will have a human case increases by 0.10%; (5) when the quantity of imported poultry increases by 1000 metric tons, the chance that the country will have a human case increases by 0.03%; (6) when the outbreak of the disease among domestic birds increases by one, the chance that the country will have a human case increases by 0.19%; and finally (7) when the number of birds destroyed increases by 1000, the chance that the country will have a human case decreases by 0.30%. CONCLUSIONS These findings shed new light on the spatiotemporal characteristics of the epidemic, and thus need to be taken into consideration in interdisciplinary and scientific discussion of the disease.

Expenditure-based segmentation: application of quantile regression to analyse the travel expenditures of baby boomer households

The substantial size of the senior worldwide population and its demands have drawn considerable attention, making it the ‘silver economy’ or ‘senior’ market. Baby boomers, those born in the years after the Second World War, or more typically between 1946 and 1964, are the specific focus of this research interest. This paper estimates the determinants of travel expenditures in baby boomer senior households in Taiwan. The traditional ordinary least squares (OLS) approach, combined with quantile regression analysis, is adopted to capture both the mean and quantile behaviours of travel expenditures in baby boomer households, using the 2008 Survey of Family Income and Expenditure (SFIE) in Taiwan. The OLS model is used to obtain the average (mean) expenditure behaviour, whereas quantile regression analysis captures the extreme behaviours of the two tails of travel expenditures in baby boomer households. The estimation outcomes have important policy implications for travel marketers and operators in the tourism industry who seek to understand baby boomer senior consumers.

Estimating the Impact of Whaling on Global Whale Watching

After the commercial whaling moratorium was enacted in 1986, whale watching became one of the fastest growing tourism industries worldwide. As whaling was regarded as an activity incompatible with whale watching, the possible resumption of commercial whaling caused an urgent need to investigate the potential negative effects of whaling on the whale-watching industry. We examine the potential impacts of whaling on the global whale-watching tourism industry using unbalanced panel data model. The empirical results indicate that the resumption of commercial whaling has the potential for a negative effect on the global whale-watching industry, especially for nations that are engaged in whaling.

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

ABSTRACT 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.