The first model concerns tourist satisfaction and its key antecedents and consequences.
This study develops a tourist satisfaction assessment system based on a dual-model framework and demonstrates its general applicability.
Then, the authors apply the Penalty-Reward-Contrast analysis proposed by Randall Brant [29] to establish tourist satisfaction levels based on multi-criteria ratings.
Specifically, the paper addresses the issue of how to deploy the House of Quality (HoQ) to improve accommodation service innovation processes and tourist satisfaction effectively and efficiently.
Structural equation modelling is employed to investigate the relationships amongst the constructs in the theoretical framework, and is then used as a basis for the computation of sectoral-level tourist satisfaction indexes.
By applying the aggregated approach based on Rough Set Theory and Recency, Frequency and Monetary architecture, the tourist satisfaction levels can be captured after the aforementioned approach is executed.
The effect of valid sellers' ratings on raising regretful tourist e-satisfaction was also confirmed.
Due to increasing online sales of Asian tourism, discussion of the factors influencing Asian online tourist e-satisfaction is an issue of critical importance.
The major purpose of the study was to enhance regretful (e.g. high tendency-to-regret) tourist e-satisfaction by providing post-purchase information (sellers' ratings) to reduce post-purchase cognitive dissonance in the high uncertainty avoidance context (e.g. Taiwan).
This research concluded that intrapersonal constraints had a negative influence on preference, while neither interpersonal nor structural dimension influenced tourists' participation or satisfaction.
