Factors affecting Iran's tourism demand: An application of linear regression model with symmetric and asymmetric fuzzy coefficients

Articles in Press

Document Type : Research Paper

Authors

1 Associate Professor, Economics Department, Faculty of Economics and Management, University of Sistan and Baluchestan, Zahedan, Iran.

2 Assistant Professor, Economics Department, Faculty of Economics and Management, University of Sistan and Baluchestan, Zahedan, Iran

Abstract

Considering the role of tourism on the economic growth and development of each country, correct knowledge of the variables affecting the demand for tourism and the extent of the impact of each of them causes the authorities to provide appropriate infrastructure to attract tourists. In this paper ، using the linear regression model with symmetric and asymmetric fuzzy coefficients in the environment of GAMS and MATLAB programs ، the tourism demand function in the Iranian economy is analyzed. The main purpose of this study is to apply a special method to analyze the factors affecting the tourism demand function in Iran for the period 1375-1397. Based on the estimated results, it can be stated that in the fuzzy regression model with different coefficients, the view of the tourism demand function is the same for all membership levels of 0.1 to 0.9, even a very small change in the value of the view is not observed, indicating no Sufficient attention is paid to the existing potentials in this industry. On the other hand, by changing the elongation coefficients, there is no change in the amount of the objective function (tourism demand), which indicates the existence of a long-term relationship and stability of the tourism demand function in Iran. Also, the highest amount of tourists' expenses is in the membership level of 0.2, which indicates the prosperity of this industry. The results also show that the real exchange rate of 9.78 and oil prices of 9.81 have the greatest impact on tourism spending. To evaluate the estimation results, the most common criteria of MSE, RMSE, MAPE, MAE have been used, which shows the extraordinary efficiency of the regression model with fuzzy coefficients.

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Main Subjects

Majlis and Rahbord

Articles in Press, Accepted Manuscript
Available Online from 02 March 2024

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