Research Article Open Access

Revenue Determinants in Tourism Market

Mohammad Mohebi1 and Khalid Abdul Rahim2
  • 1 Department of Business Management, Faculty of Management, Hormozgan University, Bandarabbas, Iran
  • 2 Institute of Agricultural and Food Policy Studies, University Putra, Malaysia

Abstract

Problem statement: Malaysian tourism industry has been growing considerably in recent years. The number of tourist arrivals has grown by 25% during 2006-2008. In comparison with Thailand and Singapore, Malaysia has more tourist arrivals but it has earned less income. The purpose of the study was to determine the major factors affecting inbound tourism expenditure in Malaysia. Approach: A panel data set for 14 origin countries, from 1998-2009 has been used to estimate tourism expenditure using gravity model. Results: The results of the expenditure model suggest that the Malaysian price index and distance have negative impact while per capita income of origin countries and Malaysian per capita income have positive impact on tourism expenditure. Conclusion: The own price elasticity indicates in short run that the tourism expenditure was inelastic to price. But in the long run tourism expenditure in Malaysia was elastic and potential tourists are more sensitive to the price changes. The lagged dependent variable's high coefficient (0.78) was represents that, our expectation has been right about consumer constancy to the destination. Based on the results, Singapore was a complementary destination meanwhile Thailand and Australia are substitute destination for Malaysia and finally SARS crisis negatively affected the tourism revenue.

American Journal of Applied Sciences
Volume 7 No. 12, 2010, 1593-1598

DOI: https://doi.org/10.3844/ajassp.2010.1593.1598

Submitted On: 23 September 2010 Published On: 31 December 2010

How to Cite: Mohebi, M. & Rahim, K. A. (2010). Revenue Determinants in Tourism Market. American Journal of Applied Sciences, 7(12), 1593-1598. https://doi.org/10.3844/ajassp.2010.1593.1598

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Keywords

  • Tourism expenditure
  • panel data
  • gravity model
  • origin countries
  • econometric
  • capita income
  • dependent variable
  • exchange rate
  • tourism demand
  • tourism revenue
  • lagged dependent