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Is the volatility of international tourism revenues affected by tourism source market structure? An empirical analysis of Turkey

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  • Seymur AÄŸazade
  • Egemen GüneÅŸ Tükenmez
  • Merve Uzun

Abstract

This study examines the effect of tourism source market structure on the volatility of tourism revenues in Turkey, using the number of tourists according to nationality and the data on international tourism revenues. The tourism source market structure was measured using the normalized Herfindahl–Hirschman index and the relative entropy index, which is based on the number of tourists visiting Turkey from 107 source markets. The volatility of tourism revenues and the effect of tourism source market structure on this volatility were assessed using the autoregressive conditional heteroskedasticity (ARCH) method. The results show that both variables measuring tourism source market structure affect the volatility of tourism revenues. Accordingly, the concentration of the tourism source market increases the volatility of tourism revenues, whereas source market diversification decreases it.

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  • Seymur AÄŸazade & Egemen GüneÅŸ Tükenmez & Merve Uzun, 2023. "Is the volatility of international tourism revenues affected by tourism source market structure? An empirical analysis of Turkey," Tourism Economics, , vol. 29(2), pages 291-304, March.
  • Handle: RePEc:sae:toueco:v:29:y:2023:i:2:p:291-304
    DOI: 10.1177/13548166211046070
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    1. Sung Yong Park & Sang Young Jei, 2010. "Determinants of volatility on international tourism demand for South Korea: an empirical note," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 217-223, February.
    2. Alegre, Joaquín & Cladera, Magdalena & Sard, Maria, 2013. "Tourist areas: Examining the effects of location attributes on tour-operator package holiday prices," Tourism Management, Elsevier, vol. 38(C), pages 131-141.
    3. Guaita Martínez, José Manuel & Martín Martín, José María & Salinas Fernández, Jose Antonio & Mogorrón-Guerrero, Helena, 2019. "An analysis of the stability of rural tourism as a desired condition for sustainable tourism," Journal of Business Research, Elsevier, vol. 100(C), pages 165-174.
    4. Vasilios Patsouratis & Zoe Frangouli & George Anastasopoulos, 2005. "Competition in tourism among the Mediterranean countries," Applied Economics, Taylor & Francis Journals, vol. 37(16), pages 1865-1870.
    5. Causevic, Senija & Lynch, Paul, 2013. "Political (in)stability and its influence on tourism development," Tourism Management, Elsevier, vol. 34(C), pages 145-157.
    6. Faruk Balli & Rosmy Jean Louis, 2015. "Modelling the tourism receipt's volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 22(2), pages 110-115, January.
    7. Liu, Yaping & Li, Yinchang & Parkpian, Parnpree, 2018. "Inbound tourism in Thailand: Market form and scale differentiation in ASEAN source countries," Tourism Management, Elsevier, vol. 64(C), pages 22-36.
    8. Balli, Hatice Ozer & Tsui, Wai Hong Kan & Balli, Faruk, 2019. "Modelling the volatility of international visitor arrivals to New Zealand," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 204-214.
    9. Law, Rob & Li, Gang & Fong, Davis Ka Chio & Han, Xin, 2019. "Tourism demand forecasting: A deep learning approach," Annals of Tourism Research, Elsevier, vol. 75(C), pages 410-423.
    10. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    11. Eugeni Aguiló & Joaquín Alegre & Maria Sard, 2003. "Examining the Market Structure of the German and UK Tour Operating Industries through an Analysis of Package Holiday Prices," Tourism Economics, , vol. 9(3), pages 255-278, September.
    12. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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