Title of article :
Analyzing touristsʹ satisfaction: A multivariate ordered probit approach
Author/Authors :
Hasegawa، نويسنده , , Hikaru، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Pages :
12
From page :
86
To page :
97
Abstract :
This article considers a Bayesian estimation of the multivariate ordered probit model using a Markov chain Monte Carlo (MCMC) method. The method is applied to unit record data on the satisfaction experienced by tourists. The data were obtained from the Annual Report on the Survey of Touristsʹ Satisfaction 2002, conducted by the Department of Economic Affairs of the Hokkaido government. Furthermore, using the posterior results of the Bayesian analysis, indices of the relationship between the overall satisfaction derived from the trip and the satisfaction derived from specific aspects of the trip are constructed. The results revealed that the satisfaction derived from the scenery and meals has the largest influence on the overall satisfaction.
Keywords :
Gibbs sampling , Markov chain Monte Carlo (MCMC) , Metropolis–Hastings (M–H) algorithm , Bayesian analysis
Journal title :
Tourism Management
Serial Year :
2010
Journal title :
Tourism Management
Record number :
2330666
Link To Document :
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