IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i12p6550-d571253.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/12/6550/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/12/6550/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. à lvarez-Díaz, Marcos & González-Gómez, Manuel & Otero-Giráldez, María Soledad, 2019. "Low cost airlines and international tourism demand. The case of Porto's airport in the northwest of the Iberian Peninsula," Journal of Air Transport Management, Elsevier, vol. 79(C), pages 1-1.
    2. Martins, Luís Filipe & Gan, Yi & Ferreira-Lopes, Alexandra, 2017. "An empirical analysis of the influence of macroeconomic determinants on World tourism demand," Tourism Management, Elsevier, vol. 61(C), pages 248-260.
    3. Haiyan Song & Stephen F. Witt & Gang Li, 2003. "Modelling and Forecasting the Demand for Thai Tourism," Tourism Economics, , vol. 9(4), pages 363-387, December.
    4. Khan, Muhammad Tariq Iqbal & Yaseen, Muhammad Rizwan & Ali, Qamar, 2019. "Nexus between financial development, tourism, renewable energy, and greenhouse gas emission in high-income countries: A continent-wise analysis," Energy Economics, Elsevier, vol. 83(C), pages 293-310.
    5. Ridderstaat, Jorge & Oduber, Marck & Croes, Robertico & Nijkamp, Peter & Martens, Pim, 2014. "Impacts of seasonal patterns of climate on recurrent fluctuations in tourism demand: Evidence from Aruba," Tourism Management, Elsevier, vol. 41(C), pages 245-256.
    6. Marie Poprawe, 2015. "A panel data analysis of the effect of corruption on tourism," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2399-2412, May.
    7. Song, Haiyan & Gartner, William C. & Tasci, Asli D.A., 2012. "Visa restrictions and their adverse economic and marketing implications – Evidence from China," Tourism Management, Elsevier, vol. 33(2), pages 397-412.
    8. Haiyan Song & Gang Li & Stephen F. Witt & Baogang Fei, 2010. "Tourism Demand Modelling and Forecasting: How Should Demand Be Measured?," Tourism Economics, , vol. 16(1), pages 63-81, March.
    9. Nepal, Rabindra & al Irsyad, M. Indra & Nepal, Sanjay Kumar, 2018. "Tourist arrivals, energy consumption and pollutant emissions in a developing economy–implications for sustainable tourism," Working Papers 2018-10, University of Tasmania, Tasmanian School of Business and Economics.
    10. Chen, Ming & Chen, Zhi-Long, 2019. "Uncertain about your travel plan? Lock it and decide later: Dynamic pricing with a fare-lock option," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 1-26.
    11. Dogru, Tarik & Sirakaya-Turk, Ercan & Crouch, Geoffrey I., 2017. "Remodeling international tourism demand: Old theory and new evidence," Tourism Management, Elsevier, vol. 60(C), pages 47-55.
    12. 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.
    13. Stauvermann, Peter Josef & Kumar, Ronald Ravinesh, 2017. "Productivity growth and income in the tourism sector: Role of tourism demand and human capital investment," Tourism Management, Elsevier, vol. 61(C), pages 426-433.
    14. Richard Welford & Bjarne Ytterhus & Jason Eligh, 1999. "Tourism and sustainable development: an analysis of policy and guidelines for managing provision and consumption," Sustainable Development, John Wiley & Sons, Ltd., vol. 7(4), pages 165-177.
    15. Nuria Huete-Alcocer & Víctor Raúl López-Ruiz & Adriana Grigorescu, 2019. "Measurement of Satisfaction in Sustainable Tourism: A Cultural Heritage Site in Spain," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xueying Huang & Yuanjun Han & Xuhong Gong & Xiangyan Liu, 2020. "Does the belt and road initiative stimulate China’s inbound tourist market? An empirical study using the gravity model with a DID method," Tourism Economics, , vol. 26(2), pages 299-323, March.
    2. Tzu-Ming Liu, 2020. "Habit formation or word of mouth: What does lagged dependent variable in tourism demand models imply?," Tourism Economics, , vol. 26(3), pages 461-474, May.
    3. 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.
    4. Recep Ulucak & Ali Gökhan Yücel & Salih Çağrı İlkay, 2020. "Dynamics of tourism demand in Turkey: Panel data analysis using gravity model," Tourism Economics, , vol. 26(8), pages 1394-1414, December.
    5. Ghialy Yap & Shrabani Saha & Nelson O Ndubisi & Saif S Alsowaidi & Ali S Saleh, 2023. "Can tourism market diversification mitigate the adverse effects of a blockade on tourism? Evidence from Qatar," Tourism Economics, , vol. 29(4), pages 880-905, June.
    6. Nikeel Kumar & Ronald Ravinesh Kumar, 2020. "Relationship between ICT and international tourism demand: A study of major tourist destinations," Tourism Economics, , vol. 26(6), pages 908-925, September.
    7. Zhang, Hanyuan & Song, Haiyan & Wen, Long & Liu, Chang, 2021. "Forecasting tourism recovery amid COVID-19," Annals of Tourism Research, Elsevier, vol. 87(C).
    8. Umit Bulut & Emrah Kocak & Courtney Suess, 2020. "The effect of freedom on international tourism demand: Empirical evidence from the top eight most visited countries," Tourism Economics, , vol. 26(8), pages 1358-1373, December.
    9. Tarik Dogru & Umit Bulut & Ercan Sirakaya-Turk, 2021. "Modeling tourism demand: Theoretical and empirical considerations for future research," Tourism Economics, , vol. 27(4), pages 874-889, June.
    10. Mengmeng Qiang & Manhong Shen & Huiming Xie, 2019. "Cultural diffusion and international inbound tourism: Evidence from China," Tourism Economics, , vol. 25(6), pages 884-903, September.
    11. Silvia Emili & Paolo Figini & Andrea Guizzardi, 2020. "Modelling international monthly tourism demand at the micro destination level with climate indicators and web-traffic data," Tourism Economics, , vol. 26(7), pages 1129-1151, November.
    12. Nikeel N Kumar & Arvind Patel & Rup Singh, 2022. "Modelling tourism competitiveness in small Pacific island countries," Tourism Economics, , vol. 28(3), pages 692-713, May.
    13. Muhammad Khalid Anser & Zahid Yousaf & Usama Awan & Abdelmohsen A. Nassani & Muhammad Moinuddin Qazi Abro & Khalid Zaman, 2020. "Identifying the Carbon Emissions Damage to International Tourism: Turn a Blind Eye," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    14. Wamboye, Evelyn F. & Nyaronga, Peter John & Sergi, Bruno S., 2020. "What are the determinant of international tourism in Tanzania?," World Development Perspectives, Elsevier, vol. 17(C).
    15. Burak Darici & Ahmet Aydin & Fatih Ayhan & Merve Altaylar, 2023. "Macroeconomic Determinants of Tourism Demand Toward Emerging Markets," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(73-2), pages 837-864, December.
    16. Veli YILANCI & Sertaç HOPOĞLU & Hakan ERYÜZLÜ, 2023. "The impact of the economic policy uncertainty and geopolitical risks on tourism demand of Mexico," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(636), A), pages 147-164, Autumn.
    17. Alina-Petronela Haller & Georgia-Daniela Tacu Hârșan, 2023. "Longitudinal Analysis of Sustainable Tourism Potential of the Black Sea Riparian States Bulgaria, Romania and Turkey," IJERPH, MDPI, vol. 20(4), pages 1-24, February.
    18. Usman Khalid & Luke Emeka Okafor & Nusrate Aziz, 2020. "Armed conflict, military expenditure and international tourism," Tourism Economics, , vol. 26(4), pages 555-577, June.
    19. Quang Hai Nguyen, 2021. "Impact of Investment in Tourism Infrastructure Development on Attracting International Visitors: A Nonlinear Panel ARDL Approach Using Vietnam’s Data," Economies, MDPI, vol. 9(3), pages 1-20, September.
    20. Helena Nemec Rudez, 2018. "The Relationship between Income and Tourism Demand: Old Findings and New Research," Academica Turistica - Tourism and Innovation Journal, University of Primorska Press, vol. 11(1), pages 67-73.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6550-:d:571253. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.