Analysis of Travel Satisfaction Conditions Using Bayesian Networks
Kyoko Kabasawa, Koichi Tsujii · IEEJ Transactions on Electronics Information and Systems · 2025
This study analyzes the factors influencing travel satisfaction based on a survey on travel satisfaction, focusing on conditions that contribute to higher satisfaction. In addition to demographic factors such as gender and age, the analysis also considers variables such as the number of previous trips, travel expenses, and whether a travel companion is present. First, we conducted a statistical test to examine whether there are gender differences in attitudes toward travel. Next, a Bayesian network analysis was performed to identify combinations of factors that lead to higher satisfaction. Additionally, decision tree analysis was used to explore the specific conditions under which satisfaction levels are likely to be higher. Based on these findings, the paper proposes recommendations for how to encourage higher travel satisfaction for different genders by considering the key factors that influence satisfaction in travel planning. The results suggest that both individual preferences and travel conditions should be carefully considered when designing travel experiences. Furthermore, the analysis results aim to enable travel service providers to develop services that take new attributes into account, rather than relying on conventional rules of thumb in service development.