Forecasting Foreign Tourist in Thailand by Artificial Neural Network

被引:1
作者
Chaivichayachat, Bundit [1 ]
机构
[1] Kasetsart Univ, Dept Econ, Ladyaow Chatuchak Bangko 10900, Thailand
关键词
Tourism in Thailand; Forecasting Tourist Number; Artificial Neural Network (ANN); DEMAND;
D O I
10.1166/asl.2018.12247
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Tourism sector is an important sector for Thai economy even in the period of economic slowdown. Thai government has been allocated a significance budget to promote tourism. Then, number of reign tourists during 2003 to 2015 increased sharply. The empirical works suggested that the number of foreign tourists is the most important variable to set up the policy for promoting tourism. Therefore, this paper aims to forecast the number of foreign tourist in Thailand for the variety of scenario including the normal, positive and negative condition by set up the model called Artificial Neural Network (ANN). The estimated ANN with quarterly data during 2003 to 2015 can be employed for ex pose forecast with only 5.5 percent of forecast error. Tourist income and government budget to promote tourism, are the most important factors for forecast foreign tourists in Thailand. For the ex ante forecast, the results show the increasing in foreign tourists although the negative condition were assumed. For policy suggestions, the government budget should be implemented continuously to get the continuous growth in tourism sector. Moreover, the policy on supply side of the tourism sector should be implemented together with the government budget spending for promoting tourism in order to sustain the growing in tourism sector.
引用
收藏
页码:9251 / 9254
页数:4
相关论文
共 24 条
[1]  
[Anonymous], 2005, THESIS
[2]  
Asadi M. M., 2016, INT J HUMANITIES CUL, V1597
[3]  
Azevedo, 2011, P INT C TOUR MAN STU, VII
[4]   Market segmentation - A neural network application [J].
Bloom, JZ .
ANNALS OF TOURISM RESEARCH, 2005, 32 (01) :93-111
[5]  
Cankurt S., 2015, Balkan Journal of Electrical & Computer Engineering, V3, P42
[6]  
Chaivichayachat B., 2014, INT C ADV EC MAN SOC
[7]  
Claveria O., 2013, 201313 RES I APPL EC
[8]   Forecasting tourism demand to Catalonia: Neural networks vs. time series models [J].
Claveria, Oscar ;
Torra, Salvador .
ECONOMIC MODELLING, 2014, 36 :220-228
[9]  
Ctaveria O., 2014, 201417 U BARC RES I
[10]  
Cuhadar M., 2014, International Journal of Business and Social Research, V4, P12, DOI DOI 10.18533/IJBSR.V4I3.431