DOMESTIC TOURISM RESTART: UNDERSTAND THAI TRAVELERS’ HOTEL STAYING PREFERENCE UNDER NEW NORMAL ENVIRONMENT
Keywords:
Hotel, Thai traveler, Hotel staying preference, Tourism, New normalAbstract
During the first quarter of 2020, World Health Organization declared Covid-19 as a global pandemic and health has become a major concern worldwide. It then has substantially shaped global society in various ways including traveling and staying preference. In Thailand, during the second and third quarter of 2020, limiting the spread of Covid-19 was witnessed with less than 10 new confirm cases per day, on average. Hence, the recovery of Thai tourism and hospitality sector started under new normal environment with strict measures being implemented nationwide. The purpose of this study is to understand Thai travelers’ staying preference during this unpredictable situation. We aim to capture factors that influence Thai travelers’ hotel staying preference. Four types of preference included in this study are location, pricing, government subsidy and social media influence. Since the result from our exploratory data analysis revealed that the relationship between the dependent variable and some independent variables does not exploit linear structure, tree-based method will be used with secondary data from June to August 2020. We draw statistical inference from “variable important plot” and “partial dependence plot” and then perform validation of regression tree. To sum up, location, pricing, government subsidy and social media influence are important variables in predicting hotel staying preference. Overall, the government subsidy is the most important variable. Next, the lower the price, the greater occupancy rate, except for three high cost of living and global tourist destination provinces. Shifting to geographical location, visitors prefer to stay near Bangkok as we see occupancy rate goes down when distance from the capital goes up, on average. Finally, “social media influence” positively correlates with over 50 provinces staying preference. Recommendation for practitioner and future research are stated as well.References
Barsky, J. (2012). Points, price, promotions? How guest selects hotel around the world. Retrieved from http://bit.ly/1Rc3WaI
Baruca, P. Z., & Civre, Z. (2012). How do guest choose hotel. Academica Turistica, 1, 75-84.
Brannen, S., Ahmed, S., & Newton, H. (2020). Covid-19 reshapes the future: Center for strategic and international studies (CSIS). Retrieved from https://www.csis.org/ analysis/covid-19-reshapes-future
Callan, R. J. (1998). Attributional analysis of customers’ hotel selection criteria by UK Grading scheme categories. Journal of Travel Research, 36, 20-34.
Chou, T., Hsu, C., & Chen, M. (2008). A fuzzy multi criteria decision model for international tourist hotel location selection. International Journal of Hospitality Management, 28, 293-301.
Chu, K. S., & Choi, T. (2000). An importance- performance analysis of hotel selection factors in the Hong Kong hotel industry: A comparison of business and leisure travelers. Tourism Management, 21, 363-377.
Dolnicar, S., & Otter, T. (2003) Which hotel attributes matter? A review of previous and framework for future research. Proceedings of the 9th Annual Conference of the Asia Pacific Tourism Association, 1, 176-188.
Kalatzis, N., Roussaki, L., Matsoukas, C., & Paraskevopolos, M. (2018). Social media and Google trends in support of audience analytics: Methodology. In Data analytics 2018: The seventh international conference on data analytics and architecture (pp. 41-45). n.p.
Kim, M. R. (2014). The relationship between leisure traveler’s hotel attribute satisfaction and overall satisfaction. FIU Hospitality Review, 31(1), 12.
McCharty, L., Stock, D., & Verma, R. (2010). Hot travellers use online and social media channels to make hotel choice decisions. Cornell Hospitality Report, 10(18), pp. 6-18.
Ministry of Tourism and Sport, Department of Tourism. (2020). Tourist Statistics 2020. Retrieved from https://www.mots.go.th/more_news_new.php?cid=594
Monetary Policy Committee. (2020). ‘Item: monetary policy decisions, financial and credit measures’. In Minutes of Analyst Meeting 14 October 2020 (pp. 17-23). Bangkok: Bank of Thailand.
Noone, M. B., & McGuire, K. A. (2015). Impact of attitudinal loyalty on the frequent unmanaged business traveler’s use of price and consumer reviews in hotel choice. Journal of Revenue and Pricing Management, 15(1), 20-36.
Saugestad, S. (2012). Hotel websites still tops for the consumers: Wallop. Retrieved from http://bit.ly/2A1zRuH
Singh, D., & Torres, E. (2015). Hotel online reviews and their impact on booking transaction value. In XVI Annual conference proceedings (pp. 992-999). n.p.
Surawattananon N. (2019). Tourism and the role that drives Thai businesses A hero is necessary or a true hero?. Bank of Thailand. Retrieved from https://
www.bot.or.th/Thai/ResearchAndPublications/articles/Pages/Article_29Oct2019.aspx
Tsai, H., Yeung, S., & Yim, P. H. (2011). Hotel selection criteria used by mainland Chinese and foreign individual travelers to Hong Kong. International Journal of Hospitality & Tourism Administration, 12(3), 252-267.
Varkaris, E., & Neuhofer, B. (2017). The influence of social media on the consumers’ hotel decision journey. Journal of Hospitality and Tourism Technology, 8(1), 101-118.
Xue, X. H., & Cox, C. (2008). Hotel selection criteria and satisfaction levels of the Chinese business traveler. Journal of China Tourism Research, 4(3-4), 261-281.
Yusoff, F. M., & Abdullah, F. S. C. (2010). What really matters when choosing a hotel? The case of middle east tourists in Kuala Lumpur, Malaysia. Journal of Business research, 63, 45-62.
Zhang, Z., & Ye, Q. (2011). Determinants of hotel room price: An exploration of travelers’ hierarchy of accommodation needs. International Journal of Contemporary Hospitality Management, 23(7), 972-998.
