The Impact of Climate Variables on Seasonal Variation in Hong Kong Inbound Tourism Demand

Abstract

In this study, we quantify the link between climate variables, such as temperature, rainfall, humidity, number of tropical cyclones, and number of thunderstorms, and seasonal variation in the Hong Kong inbound tourism demand from mainland China, Taiwan, South Korea, and Japan using the average Euclidean distance (AED) statistics and tourism demand modeling approach. Seasonal variation is measured as the fluctuation in the number of tourists from one season to another. Based on the smallest AED value, results of this study showed that climate variables play a dominant role in shaping seasonal variation relative to season and country. The fluctuation of tourist numbers from one season to another is determined not only by climate variables (e.g., the temperature of Hong Kong vs. the temperature in the country of origin of the tourist) but also by economic factors, including price and income. The variation in the impact of relative temperature depends on the country of origin.

Keywords

seasonal variation climate variables average Euclidean distance statistics composite climate variable index Hong Kong tourism

Get full access to this article

View all access options for this article.

References

Amelung

Nicholls

Viner

2007. “Implications of Global Climate Change for Tourism Flows and Seasonality.” Journal of Travel Research 45 (3): 285–96.

Berrittella

Bigano

Roson

Tol.

R. S.

2006. “A General Equilibrium Analysis of Climate Change Impacts on Tourism.” Tourism Management 27 (5): 913–24.

Climate Change Business Forum. 2013. “How Will Hong Kong Be Affected by Climate Change? ” http://www.climatechangebusinessforum.com/en-us/hong_kong_context_affected.

Dwyer

Forsyth

Dwyer

2010. Tourism Economics and Policy. London: Channel View.

Dwyer

Kim.

2003. “Destination Competitiveness: Determinants and Indicators.” Current Issues in Tourism 6 (5): 369–414.

Engle

R. F.

1982. “Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of UK Inflation.” Econometrica 50 (4): 987–1007.

Frances

P. H.

Koehler.

A. B.

1998. “A Model Selection Strategy for Time Series with Increasing Seasonal Variation.” International Journal of Forecasting 14 (3): 405–14.

Goh

2012. “Exploring Impact of Climate on Tourism Demand.” Annals of Tourism Research 39 (4): 1859–83.

Goh

Law

Mok

H. M.

2008. “Analysing and Forecasting Tourism Demand: A Rough Sets Approach.” Journal of Travel Research 46 (3): 327–38.

10.

Hamilton

J. M.

Lau

M. A.

2004. “The Role of Climate Information in Tourist Destination Choice Decision-Making.” Centre for Marine and Climate Research, Hamburg University, Hamburg, Germany, November 25, Working Paper FNU-56.

11.

Hamilton

J. M.

Maddison

D. J.

Tol.

R. S.

2005. “Climate Change and International Tourism: A Simulation Study.” Global Environmental Change 15 (3): 253–66.

12.

Hamilton

J. M.

Tol.

R. S.

2007. “The Impact of Climate Change on Tourism in Germany, the UK and Ireland: A Simulation Study.” Regional Environmental Change 7 (3): 161–72.

13.

Harvey

A. C.

1990. Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge: Cambridge University Press.

14.

Hong Kong Tourism Board. 2013. A Statistical Review of Hong Kong Tourism 2012. HKTB, Hong Kong.

15.

Kozak

Uysal

Birkan

2008. “An Analysis of Cities Based on Tourism Supply and Climatic Condition in Turkey.” Tourism Geographies 10 (1): 81–97.

16.

Kulendran

Dwyer.

2010. Seasonal Variation versus Climate Variation for Australian Tourism: Executive Summary. Gold Coast, Australia: CRC for Sustainable Tourism Pty Ltd.

17.

Kulendran

Dwyer.

2012. “Modelling Seasonal Variation in Tourism Flows with Climate Variables.” Tourism Analysis 17 (2): 121–37.

18.

Kulendran

Wong.

K. K. F.

2011. “Determinants versus Composite Leading Indicators in Predicting Turning Points in Growth Cycle.” Journal of Travel Research 50 (4): 417–30.

19.

Lise

Tol.

R. S.

2002. “Impact of Climate on Tourist Demand.” Climatic Change 55 (4): 429–49.

20.

Maddala

G. S.

2001. Introduction to Econometrics. Chichester, UK: Wiley & Sons.

21.

Martín

Belén

2005. “Weather, Climate and Tourism a Geographical Perspective.” Annals of Tourism Research 32 (3): 571–91.

22.

Matzarakis

2001a. “Assessing Climate for Tourism Purposes: Existing Methods and Tools for the Thermal Complex.” Paper presented at the First International Workshop on Climate, Tourism and Recreation, Halkidiki, Greece.

23.

Matzarakis

2001b. “Climate and Bioclimate Information for Tourism in Greece.” Paper presented at the First International Workshop on Climate, Tourism and Recreation, Halkidiki, Greece.

24.

Mieczkowski

1985. “The Tourism Climatic Index: A Method of Evaluating World Climates for Tourism.” The Canadian Geographer 29 (3): 220–33.

25.

Niemira

P. M.

Klein.

P. A.

1994. Forecasting Financial and Economic Cycles. New York: John Wiley.

26.

Ridderstaat

Oduber

Croes

Nijkamp

Martens.

2014. “Impact of Seasonal Patterns of Climate on Recurrent Fluctuations in Tourism Demand.” Tourism Management 41:245–56.

27.

Skinner

C. J.

de Dear.

R. J.

2001. “Climate and Tourism—An Australian Perspective.” Paper presented at the First International Workshop on Climate, Tourism and Recreation. Halkidiki, Greece.

28.

Seip

L. K.

McNown.

2007. “The Timing and Accuracy of Leading and Lagging Business Cycle Indicators: A New Approach.” International Journal of Forecasting 23 (2): 277–87.

29.

Stern

de Hoedt

Ernst

2000. “Objective Classification of Australian Climates.” Australian Meteorological Magazine 49 (2): 87–96.

30.

Taylor

Ortiz.

R. A.

2009. “Impacts of Climate Change on Domestic Tourism in the UK: A Panel Data Estimation.” Tourism Economics 15 (4): 803–12.

31.

Zhang

Q. H.

Kulendran

Song.

2010. “Measuring the Returns on Hong Kong Tourism Marketing Expenditure.” Tourism Economics 16 (4): 853–65.