Jong, Meng-Chang (2020): Empirical Review on Tourism Demand and COVID-19.
Preview |
PDF
MPRA_paper_103919.pdf Download (69kB) | Preview |
Abstract
Tourism is one of the most remarkable multi-faceted phenomena that contributes enormously to economic development for most countries around the globe. The steady growth of the world economy, rapid development in transportation systems, and visa facilitation have bolstered the industry by facilitating higher accessibility for tourists. However, tourism is a vulnerable and competitive industry that need to accommodate the rapid changes of tourist demand and economies as well as consider environment effects. Apart from these dynamic needs, an unexpected health crisis may also lead to devastating impacts on the tourism industry. The recent pandemic caused by the novel coronavirus of 2019 (COVID-19) has brought severe disruptions to the global economy, and specifically caused a tremendous decline in the tourism industry. It is one of the industries tremendously impacted by the outbreak, grounding airplanes and severely limiting the ability of people to travel abroad. Once the vaccines are available and movement restrictions are lifted, the tourism sector can be one of the key industries for economic recovery. More than ever, studies on tourism demand modelling and forecasting are crucial. A review of literature on tourism demand takes into account recent studies on the unprecedented COVID-19 pandemic.
Item Type: | MPRA Paper |
---|---|
Original Title: | Empirical Review on Tourism Demand and COVID-19 |
Language: | English |
Keywords: | Tourism demand; COVID-19; Panel analysis; ARDL; Forecasting; Gravity model |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C33 - Panel Data Models ; Spatio-temporal Models C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C87 - Econometric Software E - Macroeconomics and Monetary Economics > E1 - General Aggregative Models > E17 - Forecasting and Simulation: Models and Applications Z - Other Special Topics > Z0 - General |
Item ID: | 103919 |
Depositing User: | Meng-Chang Jong |
Date Deposited: | 10 Nov 2020 08:00 |
Last Modified: | 10 Nov 2020 08:00 |
References: | Akal, M. (2004). Forecasting Turkey’s tourism revenues by ARMAX model. Tourism Management, 25(5), 565-580. Chaiboonsri, C., Sriboonjit, J., Sriwichailamphan, T., Chaitip, P. & Sriboonchitta, S. (2010). A panel cointegration analysis: An application to international tourism demand of Thailand. Annals of the University of Petroşani, Economics, 10(3), 69-86. Eryigit, M., Kotil, E. & Eryigit, R. (2010). Factors affecting international tourism flows to Turkey: A gravity model approach. Tourism Economics, 16(3), 585-595. Foo, L. P., Chin, M. Y., Tan, K. L., & Phuah, K. T. (2020). The impact of COVID-19 on tourism industry in Malaysia. Current Issues in Tourism. Gouveia, S., Rebelo, J., Lina, L. G. & Guedes, A. (2017). International demand for the Douro (Portugal) river cruises: a gravity model approach. Tourism Economics 23(8): 1679-1686. Hao, F., Xiao, Q., & Chon, K. (2020). COVID-19 and China’s hotel industry: Impacts, a disaster management framework, and post-pandemic agenda. International Journal of Hospitality Management, 90, 102636. Jong, M. C., Puah, C. H., & Arip, M. A. (2020). Modelling tourism demand: An augmented gravity model. Jurnal Ekonomi Malaysia, 54(2), 105-122. Kaplan, F., & Aktas, A. R. (2016). The Turkey tourism demand: A gravity model. The Empirical Economics Letters, 15(3), 265-272. Liew, V. K. S. (2020). The effect of novel coronavirus pandemic on tourism share prices. Journal of Tourism Futures. Martin, C. A. & Witt, S. F. (1988). Substitute prices in models of tourism demand. Annals of Tourism Research, 15, 255-268. McCallum, J. (1995). National borders matter: Canada-U.S. regional trade patterns. The American Economic Review, 85(3), 615-623. Morley, C., Rossello, J., & Maria, S. G. (2014). Gravity models for tourism demand: Theory and use. Annals of Tourism Research, 48, 1-10. Peng, B., Song, H., Crouch, G. I., & Witt, S. F. (2015). A meta-analysis of international tourism demand elasticities. Journal of Travel Research, 54(5), 611-633. Polyzos, S., Samitas, A., & Spyridou, A. E. (2020). Tourism demand and the COVID-19 pandemic: An LSTM approach. Tourism Recreation Research, 1-13. Priego, F. J., Rossello, J., & Maria, S. G. (2015). The impact of climate change on domestic tourism: A gravity model for Spain. Regional Environment Change, 15(2), 291-300. Puah, C. H., Huan, S. H., & Thien, F. T. (2018a). Determinants of Chinese demand for tourism in Malaysia. Business and Economic Horizons, 14(3), 501-512. Puah, C. H., Jong, M. C., Ayob, N., & Ismail, S. (2018b). The impact of tourism on the local economy in Malaysia. International Journal of Business and Management, 13(12), 151-157. Puah, C. H., Thien, F. T., & Arip, M. A. (2014). Singaporean demand for tourism in Malaysia. Economic Annals-XXI, 11, 32-36. Puah, C. H., Thien, F. T., Arip, M. A., & Chin, M. Y. (2019). Modelling a tourism demand in Vietnam. International Journal of Economics and Management, 13(2), 319-329. Rossello-Nadal, J. (2001). Forecasting turning points in international visitor arrivals in the Balearic Islands. Tourism Economics, 7(4), 365-380. Shahbaz, M., Kumar, R. R., Ivanov, S., & Loganathan, N. (2017). The nexus between tourism demand and output per capita with the relative importance of trade openness and financial development: A study of Malaysia. Tourism Economics, 23(1), 168-186. Sharma, A., & Nicolau, J. L. (2020). An open market valuation of the effects of COVID-19 on the travel and tourism industry. Annals of Tourism Research. Shin., H., & Kang, J. (2020). Reducing perceived health risk to attract hotel customers in the COVID-19 pandemic era: Focused on technology innovation for social distancing and cleanliness. International Journal of Hospitality Management, 91, 102664. Soh, A. N., Puah, C. H., & Arip, M. A. (2019a). Construction of tourism cycle indicator: A signalling tool for tourism market dynamics. Electronic Journal of Applied Statistical Analysis, 12(2), 477-490. Soh, A. N., Puah, C. H., & Arip, M. A. (2019c). Forecasting tourism demand with composite indicator approach for Fiji. Business and Economic Research, 12(2), 477-490. Soh, A. N., Puah, C. H., & Arip, M. A. (2020). Tourism forecasting and tackling fluctuating patterns: A composite leading indicator approach. Studies in Business and Economics, 15(2), 192-204. Soh, A. N., Puah, C. H., Arip, M. A., & Kuek, T. H. (2019b). Oil price and Fijian tourism cycle: A Markov regime-switching model. International Journal of Energy Economics and Policy, 9(6), 199-192. Tanjung, A., Thien, F. T., Puah, C. H., Brahmana, R. K., & Sianturi, R. (2017). Macroeconomic determinants of Indonesian tourism demand in Malaysia. Advanced Science Letter, 23(4), 3159-3162. Thien, F. T., Puah, C. H., Hassan, M. K. H., & Arip, M. A. (2015). An ECM analysis of Thai tourism demand in Malaysia. Mediterranean Journal of Social Sciences, 6(3), 162-168. Wu, F., Zhang, Q., Law, R., & Zheng, T. (2020). Fluctuations in Hong Kong hotel industry room rates under the 2019 Novel Coronavirus (COVID-19) outbreak: Evidence from big data on OTA channels. Sustainability, 12(18), 7709. Xu, L., Wang, S., Li, J., Tang, L. & Shao, Y. (2020). Modelling international tourism flows to China: A panel data analysis with the gravity model. Tourism Economics, 25(7), 1047-1069. Yap, S. A. Y. I., Ayob, N., & Puah, C. H. (2020). Event tourism demand and selected macroeconomic variables: An econometrics view of the long-run and short-run relationships. International Journal of Business and Society, 21(1), 183-196. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/103919 |