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The Determinants of Tourist Expenditure Per Capita in Thailand: Potential Implications for Sustainable Tourism

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  • Wanvilai Chulaphan

    (Faculty of Economics, Maejo University, Chiang Mai 50290, Thailand)

  • Jorge Fidel Barahona

    (Faculty of Economics, Maejo University, Chiang Mai 50290, Thailand)

Abstract

Tourism authorities in Thailand have consistently pursued profit-seeking mass tourism, resulting in the detriment of the natural resources in major tourist destinations. In response, sustainable tourism projects centered on preserving the environment have been established but neglect the financial needs of tour operators. The objective of this study was to investigate the determinants of tourist expenditure per capita in Thailand using a dataset consisting of 31 countries from 2010 to 2017. The analysis was based on an autoregressive distributed lag model (ARDL) and used a panel estimated generalized least square (ELGS). Generating such knowledge is essential for tourist authorities to develop profitable and sustainable tourism projects in tourist destinations whose natural resources have been affected by profit-seeking tourism. The tourism expenditure per capita is positively affected by word of mouth, income, and the rising prices in other major tourist destinations in Asia. However, it was negatively affected by relative levels of price and corruption. Sustainable tourism projects can be used to develop activities that will help distinguish Thailand from other tourism destinations in Asia. However, in implementing these sustainable tourism initiatives, the mark-up should be minimized to keep tourist prices in Thailand competitive.

Suggested Citation

  • Wanvilai Chulaphan & Jorge Fidel Barahona, 2021. "The Determinants of Tourist Expenditure Per Capita in Thailand: Potential Implications for Sustainable Tourism," Sustainability, MDPI, vol. 13(12), pages 1-14, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6550-:d:571253
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    1. Tzong-Shyuan Chen & Chaang-Iuan Ho, 2022. "The Application of a Two-Stage Decision Model to Analyze Tourist Behavior in Accommodation," Economies, MDPI, vol. 10(4), pages 1-21, March.

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