Analyzing tourists' satisfaction : A multivariate ordered probit approach

• Hasegawa, Hikaru

抄録

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.

収録刊行物

• Tourism Management

  Tourism Management 31 (1), 86-97, 2010-02

  Elsevier Ltd.

キーワード

• Bayesian analysis
• Gibbs sampling
• Markov chain Monte Carlo (MCMC)
• Metropolis-Hastings (M-H) algorithm

詳細情報

• CRID: 1050282813979038080
• NII論文ID: 120001768671
• HANDLE: 2115/42486
• ISSN: 02615177
• 本文言語コード: en
• 資料種別: journal article
• データソース種別:
  • IRDB
  • CiNii Articles
  • KAKEN