Tourism Supply Efficiency: An Analysis of Countries in the Asia-Pacific Region
Abstract
The objective of this research is to analyze the factors affecting the tourism supply and its efficiency of the tourism supply for countries in the Asia-Pacific region. The method uses the stochastic frontier with Maximum Likelihood Estimation (MLE) analyzed by Frontier software. 4.1. The data were collected from panel data from 2010 - 2019 for 23 countries. The results of the study revealed that 1) Tourism investment from the private sector and timing factors positively affect the tourism supply of countries in the Asia-Pacific region, while the tourism labor value factor has a negative effect on the tourism supply of countries in the region 2) For the technical performance measurement of tourism supply in each sub-region in the Asia-Pacific region, the average is between 0.387 and 0.657. East Asia shows the highest technical efficiency in China, Hong Kong, Japan, Macau and Mongolia while South Asia has the lowest technical efficiency in Bangladesh, India, Nepal, Pakistan, Sri Lanka and the Maldives, respectively.
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[3] Battese, G.E., Coelli, T.J. 1995. A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20: 387 - 399.
[4] Borensztein, E., De-Gregorio, J., Lee, J.W. 1998. How does foreign direct investment affect economic growth? Journal of International Economics, 45, 115 - 135.
[5] Chen, C.F. 2007. Applying the stochastic frontier approach to measure hotel managerial efficiency in Taiwan. Tourism Management, 3(28), 696 – 702.
[6] Chokcharoen, N., Nonthapot, S. 2018. Efficient Measurement of Tourism Supply in Asia-Pacific Region Countries. Paper presented at the 7th Academic Management Science 2018. Tak: Kamphaeng PhetRajabhat University.In Tak, Thailand.
[7] Debreu, G. 1951. The coeffcient of resource utilization. Econometrica, 19, 273– 292.
[8] Assaf, G.A. 2012. Benchmarking the Asia Pacific tourism industry: A Bayesian combination of DEA and stochastic frontier. Tourism Management, 33(5), 1122-1127.
[9] Koopmans, T.C. 1951. Activity Analysis of Production and Allocation. New York, NY: Cowles Commission Monographs, John Willey & Sons.
[10] Krishna, G.I., Alicia, N.R., Kim, K.T. 2005. Measuring Efficiency Externalities from Trade and Alternative Forms of Foreign Investment. Center for Efficiency and Productivity Analysis.
[11] Lapsatid, T. 2007. Testing the Production Efficiency of Foreign Investment Inflows. Master of Economics, Chulalongkorn University.
[12] Levine, R., Renalt, D. 1992. A sensitivity analysis of cross-country growth regression. American Economic Review, 82, 942-963.
[13] Levine, R., Carkovic, M. 2002. Does Foreign Direct Investment Accelerate Economic Growth. University of Minnesota, USA.
[14] Machmud, A., Nandiyanto, A.B.D., Dirgantari, P.D. 2018. Technical Efficiency Chemical Industry in Indonesia: Stochastic Frontier Analysis (SFA) Approach. Pertanika Journal of Science and Technology, 26 (3): 1453 – 1464.
[15] Nangkalaphiwat, Y. 2014. Preparation of Thai labor in tourism industry for the ASEAN economic community integration. APHEIT International Journal, 20 (2), 158-169.
[16] Nonthapot, S., Lean, H.H. 2015. International tourism market analysis in the greater Mekong sub-region: a panel data approach. Pertanika Journal of Social Sciences & Humanities, 23(4): 945 – 966.
[17] Nonthapot, S. 2017. Causality between capital investment in the tourism sector and tourist arrivals in ASEAN. Journal of Advanced Research in Law and Economics.8(8): 2504-2511.
[18] Nonthapot, S. 2020. The relationships among the five key foreign tourist markets in the greater Mekong sub-region. Decision Science Letters, 9(4), 511-520.
[19] Saleh, A.S., Assaf, A.G., Nghiem, H.S. 2012. Efficiency of the Malaysian hotel industry: a distance function approach. Tourism Analysis, 17(6), 721-732. DOI:10.3727/10835 4212X13531051127 186.
[20] The Pacific Asia Travel Association. 2019. Travel trends report 2019–2023. Available at: https://www.pata.org/asia-pacific-visitor-forecasts-2019-2023-full-report-now-available/.
[21] The World Bank. 2020a. International tourism, number of arrivals. Available at: http://data.worldbank.org/indicator/ST.INT.ARVL.
[22] The World Bank. 2020b. International tourism receipts. Available at: http://data.worldbank.org/indicator/ST.INT.RCPT.CD.
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[26] World Travel & Tourism Council. 2020b. Domestic Tourism Spending. Available at: https://www.wttc.org/datagateway/.
[27] World Travel & Tourism Council. 2020c. Government Individual Expenditures. Available at: https://tool.wttc.org/.
[28] World Travel & Tourism Council. 2020d. Capital Investment. Available at: https://www.wttc.org/datagateway/.
[29] Zhang, J., Jensen, C. 2007. Comparative advantage: explaining tourism flows. Annals of Tourism Research, 34 (1). 223-243.
Published
2021-06-30
How to Cite
NONTHAPOT, Sakkarin.
Tourism Supply Efficiency: An Analysis of Countries in the Asia-Pacific Region.
Journal of Environmental Management and Tourism, [S.l.], v. 12, n. 4, p. 1139-1149, june 2021.
ISSN 2068-7729.
Available at: <https://journals.aserspublishing.eu/jemt/article/view/6205>. Date accessed: 03 dec. 2024.
doi: https://doi.org/10.14505//jemt.v12.4(52).26.
Section
Article
Copyright© 2024 The Author(s). Published by ASERS Publishing 2024. This is an open access article distributed under the terms of CC-BY 4.0 license.