The Intervention Analysis of the Interrupted Incidents’ Impacts on Malaysian Tourist Arrivals to Songkhla Province in Thailand
Abstract
This study evaluated the impacts of the interrupted incidents on the monthly Malaysian tourist arrivals to Songkhla province in Thailand from January 2004 to December 2019. By applying the Seasonal Autoregressive Integrated Moving Average or SARIMA with intervention model, the estimated coefficients of the most parsimonious model, the SARIMA (1,1,0) (1,0,0)12, with intervention model, showed four categories of interrupted incidents that were significantly affected the number of arrivals. These four categories included the insurgency incidents, the political unrests, the natural disasters, and the dieses outbreaks. Most of interrupted incidents significantly decreased the number of arrivals inducing losses in tourism incomes around 370 to 1,031 million baht. However, this study surprisingly found that two insurgency incidents occurring in Narathiwat, a neighbouring province of Songkhla, significantly caused temporary increases in Malaysian tourist arrivals to Songkhla and led to the increase in the tourism income of Songkhla at around 289 million baht. Lastly, based on the estimated model, the forecasts of monthly Malaysian tourist arrivals in 2020 were in the range between 187,633 to 273,929 persons. Then, the forecast of total arrivals to Songkhla in 2020 was approximately 2,471,092 persons or 21.61 percentage increased from the total arrivals in 2019.
References
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[23] Sriboonjit, J., et al. 2010. Economic determinants of long-term equilibrium in Malaysian tourist arrivals to Thailand: Implications for tourism policy. International Journal of Intelligent Technologies and Applied Statistics, 3 (4): 421-435. DOI: https://doi.org/10.6148/IJITAS.2010.0304.04
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[2] Chambers, P., Srisompop J., and Napisa Waitoolkiat, N. 2019. Introduction: Conflict in the Deep South of Thailand: Never-ending stalemate? Asian International Studies Review, 20: 1-23. DOI:https://doi.org/10.16934/isr.20.1.201906.1
[3] Chinnakum, W., and Pimonpun, B. 2017. Modelling Thailand tourism demand: A dual generalized maximum entropy estimator for panel data regression models. Thai Journal of Mathematics (Special Issue): 67-78.
[4] Department of Industrial Promotion. "Songkhla Special Economic Development Zone." Songkhla Special Economic Development Zone. Available at: https://www.oss.songkhla.go.th/files/com_content/2016-12_956254b91513d0b.pdf
[5] Drakos, K., and Ali M. K. 2003. Regional effects of terrorism on tourism in three Mediterranean countries. Journal of Conflict Resolution, 47 (5): 621-641. DOI: https://doi.org/10.1177/0022002703258198
[6] Haque, T.H., and Haque, M.O. 2018. The swine flu and its impacts on tourism in Brunei. Journal of Hospitality and Tourism Management, 36: 92-101. DOI: https://doi.org/10.1016/j.jhtm.2016.12.003
[7] Huang, J.-H., and Min, J. C. H. 2002. Earthquake devastation and recovery in tourism: The Taiwan case. Tourism Management, 23: 145-154. DOI: https://doi.org/10.1016/S0261-5177(01)00051-6
[8] Ingram, Hadyn, Saloomeh Tabari, and Wanthanee Watthanakhomprathip. 2013. The impact of political instability on tourism: case of Thailand. Worldwide Hospitality and Tourism Themes, 5(1): 92-103. DOI:https://doi.org/10.1108/17554211311292475
[9] Ismail, Zuhaimy, Suhartono, Azizi Yahaya, and Riswan Efendi. 2009. Intervention model for analyzing the impact of terrorism to tourism industry. Journal of Mathematics and Statistics, 5 (4): 322-329. DOI:https://doi.org/10.3844/jmssp.2009.322.329
[10] Iyavarakul, T. 2019. On the causual nexus between terrorism and tourism: Empirical evidence from the South Thailand insurgency. Development Economic Review, 13(1): 28-41.
[11] Jeong, D.-B. 2016. Optimal forecasting for sales at convenience stores in Korea using a seasonal ARIMA-Intervention model. Journal of Distribution Science, 14 (11): 83-90. DOI:https://doi.org/10.15722/jds.14.11.201611.83
[12] Joo, H., et al. 2019. Economic impact of the 2015 MERS outbreak on the Republic of Korea's tourism-related industries. Health Security, 17 (2): 100-108. DOI: https://doi.org/10.1089/hs.2018.0115
[13] Laipaporn, J. and Praprom, C. 2020. The impact of laws enforcement on the fish landings at Pattani fishery port by using SARIMA with intervention model. Chiang Mai University Journal of Economics, 24 (1): 93-110.
[14] Lee, M. H., Suhartono, and Bahrom Sanugi. 2010. Multi input intervention model for evaluating the impact of the Asian crisis and terrorist attacks on tourist arrivals. Matematika, 26 (1): 83-106.
[15] McAleer, M. et al. 2010. An econometric analysis of SARS and Avian Flu on international tourist arrivals to Asia. Environmental Modelling and Software, 25 (1): 100-106. DOI:https://doi.org/10.1016/j.envsoft.2009.07.015
[16] Min, J.C. H., Lim, C. and Kung, H.-H. 2011. Intervention analysis of SARS on Janpanese tourism demand for Taiwan. Quality & Quantity, 45: 91-102. DOI: https://doi.org/10.1007/s11135-010-9338-4
[17] Mohamed Mustafa and Abdul Majeed. 2021. Impact of seasonality variation on travel and tourism sector: A study of the post-civil unrest in Arugam Bay in Sri Lanka. Journal of Asian Finance, Economics and Business, 8 (1): 431-442. DOI: https://doi.org/10.13106/jafeb.2021.vol8.no1.431
[18] Neumayer, E. 2004. The impact of political violence on tourism: Dynamic Cross-National estimation. Journal of Conflict Resolution, 48 (2): 259-281. DOI: https://doi.org/10.1177/0022002703262358
[19] Paudel, Tulsi, Thakur Dhakal, Wen Ya Li, and Yeong Gug Kim. 2021. A macro analysis of tourist arrival in Nepal. Journal of Asian Finance, Economics and Business, 8 (1): 207-215. DOI:https://doi.org/10.13106/jafeb.2021.vol8.no1.207
[20] Ranga, M., and Pradhan, P. 2014. Terrorism terrorizes tourism: Indian tourism effacing myths? International Journal of Safety and Security in Tourism and Hospitality, 1(5): 26-39.
[21] Rossello, J., Santana-Gallego, M. and Awan, W. 2017. Infection disease risk and international tourism demand. Health Policy and Planning, 32: 538-548. DOI: https://doi.org/10.1093/heapol/czw177
[22] Song, J. 2016. A study on demand forecasting for Jeju-bound tourists by travel purpose using seasonal ARIMA-Intervention model. Journal of the Korean Data & Information Sciences Society, 27 (3): 725-732. DOI: https://doi.org/10.7465/jkdi.2016.27.3.725
[23] Sriboonjit, J., et al. 2010. Economic determinants of long-term equilibrium in Malaysian tourist arrivals to Thailand: Implications for tourism policy. International Journal of Intelligent Technologies and Applied Statistics, 3 (4): 421-435. DOI: https://doi.org/10.6148/IJITAS.2010.0304.04
[24] Vu, J. C., and Turner, L.W. 2006. Regional data forecasting accuracy: The case of Thailand. Journal of Travel Research, 45 (2): 186-193. DOI: https://doi.org/10.1177/0047287506291600
[25] Wongsathan, R. 2018. "SARIMA intervention based forecast model for visitor arrivals to Chiang Mai, Thailand. Asia-Pacific Journal of Science and Technology, 23 (4): 1-14. DOI:https://doi.org/10.14456/apst.2018.19
[26] Wu, L., and Hayashi, H. 2014. The impact of disasters on Japan's inbound tourism demand. Journal of Disaster Research, 9: 699-708. DOI: https://doi.org/10.20965/jdr.2014.p0699
[27] Ministry of Tourism and Sports. "Domestic Tourism Statistics Q1-Q4 (classify by region and province)." Tourism statistic. Available at: https://www.mots.go.th/more_news_new.php?cid=618
[28] World Tourism Organization. "International Tourism Highlights 2019 Edition." World Tourism Organization. Available at: https://www.e-unwto.org/doi/pdf/10.18111/9789284421152
Published
2021-09-30
How to Cite
PRAPROM, Chakorn; LAIPAPORN, Jetsada.
The Intervention Analysis of the Interrupted Incidents’ Impacts on Malaysian Tourist Arrivals to Songkhla Province in Thailand.
Journal of Environmental Management and Tourism, [S.l.], v. 12, n. 6, p. 1513-1522, sep. 2021.
ISSN 2068-7729.
Available at: <https://journals.aserspublishing.eu/jemt/article/view/6431>. Date accessed: 27 apr. 2024.
doi: https://doi.org/10.14505//jemt.v12.6(54).08.
Section
Article
Copyright© 2023 The Author(s). Published by ASERS Publishing 2023. This is an open access article distributed under the terms of CC-BY 4.0 license.