A Quantitative Analysis on Tourists' Consumer Satisfaction via the Bayesian Ordered Probit Model

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  • ベイズ順序プロビットモデルによる観光満足度分析
  • ベイズ ジュンジョ プロビット モデル ニ ヨル カンコウ マンゾクド ブンセキ

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Abstract

This study aims to analyze tourists' consumer satisfaction (CS) via the Bayesian ordered probit model. The model is introduced in order to identify correlation between tourists' individual attributes, travel behaviors and CS. Tourists' CS survey conducted in Kamakura city is employed for the analysis. Model parameters are estimated by using Gibbs sampling which is one of the major methods of Markov-chain Monte Carlo simulation. Marginal effects are calculated in order to indicate relationship between tourists overall travel satisfaction by travel purpose, spots, tourists' attributes and related tourists' CS quantitatively. It is shown that the MCMC ordered probit model has advantages comparing with the ordered probit model via the maximum likelihood method when evaluating CS by considering tourists' subjective.

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