Annals of Tourism Research xxx (2015) xxx–xxx
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Research Note
Happiness and inbound tourism Hassan F. Gholipour ⇑, Reza Tajaddini, Jeremy Nguyen Swinburne University of Technology, Australia
This paper investigates whether a nation’s happiness can be viewed as an asset that attracts international tourists. Subjective, intangible assets such as cultural and natural heritage sites are well established as motivating tourism; some individuals travel for emotional experience—‘‘to ‘feel’ rather than to ‘gaze’ (Poria, Butler, & Airey, 2003). Happiness influences long-term international travel: low happiness is associated with higher rates of emigration (Polgreen & Simpson, 2011). In this study, we examine whether higher national happiness attracts greater (i) international tourists and (ii) tourism revenues. The relationship between happiness and inbound tourism is of particular relevance to tourism authorities internationally. In recent years, many countries have launched tourism campaigns focusing on happiness in their countries: Fiji tourism authorities employed a global campaign ‘‘Fiji-where happiness finds you”; Bhutan, Thailand and Costa Rica have also used happiness campaigns to promote their tourism industries. Our study contributes to the literature in the following ways: we add to the literature examining non-economic determinants of international tourism; to the best of our knowledge, this is the first study to (i) propose that tourists may travel to sites of greater happiness, and (ii) investigate the relationship between happiness and inbound tourism using a large, multi-country dataset. Several studies have examined economic and non-economic determinants of inbound tourism (e.g. Lim, 1997; Sequeira & Nunes, 2008; Su & Lin, 2014). Using panel data and cross-sectional regression analyses, we hypothesize that—other things being equal—international tourists may travel towards happy destinations, because individuals have a fundamental preference for exposure to happiness (Aristotle, Greek philosopher, 384-322 BC). For the dependent variables we use two different measurements from the Euromonitor International database: international tourist arrivals (in thousands) per capita (ARRcap) and incoming tourist receipts (US$) per capita (RECcap). Per capita measures of international tourist arrivals and incoming tourist receipts control for the size of the destination country. For national happiness (HAPY), we use World Values Survey (WVS) responses to the question ‘‘All things considered, how satisfied are you with your life as a whole these days?”, measured on a ten-point scale ranging from 1 (completely dissatisfied) to 10 (completely satisfied). Mean reported life satisfaction in each country in any given time ⇑ Corresponding author. Tel.: +61 3 9214 3771. E-mail addresses:
[email protected] (H.F. Gholipour),
[email protected] (R. Tajaddini),
[email protected] (J. Nguyen). http://dx.doi.org/10.1016/j.annals.2015.12.003 0160-7383/Ó 2015 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Gholipour, H. F., et al. Happiness and inbound tourism. Annals of Tourism Research (2015), http://dx.doi.org/10.1016/j.annals.2015.12.003
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Research Note / Annals of Tourism Research xxx (2015) xxx–xxx Table 1 Panel fixed-effect regression results. Dependent variables
logHAPY logEXC logTAT HTG PS R-squared
logARRcap (1)
logRECcap (2)
0.038⁄ (1.826) 0.104⁄⁄⁄ (3.792) 0.213⁄⁄⁄ (3.012) 0.563⁄⁄ (2.192) 0.252⁄ (1.770)
0.021⁄⁄ (2.083) 0.152⁄⁄ (2.380) 0.206⁄⁄⁄ (3.407) 0.024⁄ (1.713) 0.358⁄⁄⁄ (3.124)
0.780
0.774
HAPY, EXC and TAT represent national happiness, exchange rate and tourist attractions, respectively. HTG measures a country’s cultural and natural heritage sites and PS is political stability. ARRcap and RECcap measure per capita international tourist arrivals and incoming tourist receipts. log is logarithm; number of observations is 112. tstatistics in parentheses. ⁄p < 0.1; ⁄⁄p < 0.05; ⁄⁄⁄p < 0.01.
period are calculated to measure of happiness for that country. Our data spans the last three WVS waves (1999–2004; 2005–2009; 2010–2014) for 63 countries.1 Sample countries are selected based on availability of happiness data at least for one WVS wave. We note that the data is an unbalanced panel, due to WVS data availability. We also include commonly used control variables in the panel specification of inbound tourism. The real exchange rate is included as a control variable to capture the effect of currency appreciation or depreciation on tourism demand (Saha & Yap, 2014). We measure the exchange rate variable (EXC) as national currency per U.S. dollar, expecting a positive estimated coefficient. We also include a measure of tourist attractions (TAT) as a control variable, expecting a positive relationship with inbound tourism (Saha & Yap, 2014). TAT measures tourism revenues (US$ million) to visitors’ sites and permanent attractions. Data for EXC and TAT are taken from Euromonitor International. In addition, high levels of political instability decrease international tourist arrivals and tourism revenues (Sequeira & Nunes, 2008). Therefore, we use Political Stability and Absence of Violence (PS) from the World Bank as a proxy for political stability in our estimation model. PS is assessed on a scale from approximately 2.5 to 2.5, with higher values indicating higher political stability in a country. World cultural and natural heritage sites (HTG) in a country have also been found to have a positive effect on inbound tourism (Saha & Yap, 2014). Data for HTG are obtained from UNESCO. To match the dependent variable and control variables to WVS happiness data, we calculate average annual values for other variables over the mentioned periods. For example: average tourism arrivals over the period of 2005–2009 are matched to happiness data for the 2005–2009 wave. This approach allows us sufficient observations to apply panel data analysis. Models are estimated using panel fixed effects methods; results are presented in Table 1. The coefficient of HAPY is positive and significant (columns 1 and 2, Table 1). These results support our hypothesis and suggest that a nation’s happiness may be an asset capable of attracting international tourism, akin to cultural and heritage intangible assets. If this is the case, happier countries may be able to attain economic benefits by recognizing population happiness as an intangible asset that
1 Algeria, Argentina, Australia, Azerbaijan, Belarus, Bosnia-Herzegovina, Brazil, Bulgaria, Canada, Chile, China, Colombia, Ecuador, Egypt, Estonia, Finland, France, Georgia, Germany, Guatemala, Hong Kong, Hungary, India, Indonesia, Iran, Israel, Italy, Japan, Kazakhstan, Macedonia, Malaysia, Mexico, Morocco, Netherlands, New Zealand, Nigeria, Norway, Pakistan, Peru, Philippines, Poland, Romania, Russia, Saudi Arabia, Serbia, Singapore, Slovenia, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Tunisia, Turkey, Ukraine, United Kingdom, United States, Uruguay, Uzbekistan, Venezuela, Vietnam.
Please cite this article in press as: Gholipour, H. F., et al. Happiness and inbound tourism. Annals of Tourism Research (2015), http://dx.doi.org/10.1016/j.annals.2015.12.003
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Research Note / Annals of Tourism Research xxx (2015) xxx–xxx Table 2 Cross-sectional regressions results. Dependent variables
logAHAPY logEXC logTAT HTG PS Constant R-squared
logARRcap (1)
logRECcap (2)
0.539 (0.827) 0.030 ( 0.746) 1.740⁄⁄⁄ (6.368) 0.063⁄⁄⁄ (8.508) 0.501⁄⁄⁄ (4.270) 6.726⁄⁄⁄ (5.519)
1.342⁄ (1.677) 0.706 ( 1.364) 0.134⁄ (1.651) 0.012 (0.986) 1.139⁄⁄⁄ (7.956) 1.197⁄ (1.618)
0.578
0.614
AHAPY, EXC and TAT represent national happiness, exchange rate and tourist attractions, respectively. HTG measures a country’s cultural and natural heritage sites and PS is political stability. ARRcap and RECcap measure per capita international tourist arrivals and incoming tourist receipts. log is logarithm; number of observations is 75. t-statistics in parentheses. ⁄p < 0.1; ⁄⁄⁄p < 0.01.
can be managed and marketed, sharing local people’s happiness with international visitors. Moreover, all control variables are statistically significant and have the expected signs. To ensure robustness of our findings, we consider another measurement of happiness: Average Happiness in Nations over 2000-2009 (AHAPY) from the World Database of Happiness, which records ‘‘How much people enjoy their life-as-a-whole on scale 0 to 10”. Happiness is measured for the period of 2000–2009; we took average values for the same period for all independent variables. Our sample for cross-sectional analysis includes 75 countries. The model is estimated using Ordinary Least Squares with heteroskedasticity-robust standard errors. As can be seen from column 2 of Table 2, the coefficient of happiness (AHAPY) is positive and significant when RECcap is a dependent variable. The level of happiness reported in a destination country is more significant in explaining tourism receipts than in explaining international tourist arrivals; a potential question for future research would be whether tourists with a higher propensity to spend are more influenced by happiness than other tourists. Taken together, our results suggest that international tourists prefer to travel to, and spend more in, happier countries. If national happiness is viewed as an intangible asset that affects tourism positively, then recent interests in national happiness and wellbeing by political leaders and economists (Stiglitz, Sen, & Fitoussi, 2009) have clear implications for the management of this asset, for which tourism industries are a stakeholder. There are implications for marketing: tourism companies and travel agencies stand to benefit from emphasizing the happiness characteristics of destinations, alongside traditional selling points. Future directions for research will involve identifying the personal characteristics (e.g. demographics, happiness levels, spending habits) of market segments most influenced by happiness considerations, and which factors most influence tourists’ perceptions of the happiness of potential destination countries. References Lim, C. (1997). Review of international tourism demand models. Annals of Tourism Research, 24, 835–849. Polgreen, L. A., & Simpson, N. B. (2011). Happiness and international migration. Journal of Happiness Studies, 12, 819–840. Poria, Y., Butler, R., & Airey, D. (2003). The core of heritage tourism. Annals of Tourism Research, 30, 238–254. Saha, S., & Yap, G. (2014). The moderation effects of political instability and terrorism on tourism development: A cross-country panel analysis. Journal of Travel Research, 53, 509–521.
Please cite this article in press as: Gholipour, H. F., et al. Happiness and inbound tourism. Annals of Tourism Research (2015), http://dx.doi.org/10.1016/j.annals.2015.12.003
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Research Note / Annals of Tourism Research xxx (2015) xxx–xxx
Sequeira, T. N., & Nunes, P. M. (2008). Does country risk influence international tourism? A dynamic panel data analysis. The Economic Record, 84, 223–236. Stiglitz, J., Sen, A., & Fitoussi, J. (2009). Report by the Stiglitz Commission on the Measurement of Economic Performance and Social Progress. Available at:
(accessed 11.11.2015). Su, Y. W., & Lin, H. L. (2014). Analysis of international tourist arrivals worldwide: The role of world heritage sites. Tourism Management, 40, 46–58. Received 13 October 2015. Revised 11 November 2015. Accepted 7 December 2015. Available online xxxx
Please cite this article in press as: Gholipour, H. F., et al. Happiness and inbound tourism. Annals of Tourism Research (2015), http://dx.doi.org/10.1016/j.annals.2015.12.003