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Hokkaido University Collection of Scholarly and Academic Papers >
Graduate School of Economics and Business / Faculty of Economics and Business >
Peer-reviewed Journal Articles, etc >
Analyzing tourists' satisfaction : A multivariate ordered probit approach
| Title: | Analyzing tourists' satisfaction : A multivariate ordered probit approach |
| Authors: | Hasegawa, Hikaru Browse this author →KAKEN DB |
| Keywords: | Bayesian analysis | | Gibbs sampling | | Markov chain Monte Carlo (MCMC) | | Metropolis-Hastings (M-H) algorithm |
| Issue Date: | Feb-2010 |
| Publisher: | Elsevier Ltd. |
| Journal Title: | Tourism Management |
| Volume: | 31 |
| Issue: | 1 |
| Start Page: | 86 |
| End Page: | 97 |
| Publisher DOI: | 10.1016/j.tourman.2009.01.008 |
| 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 Tourists' 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. |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/42486 |
| Appears in Collections: | 経済学院・経済学研究院 (Graduate School of Economics and Business / Faculty of Economics and Business) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 長谷川 光
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