Applying Self-Organizing Map Network to Analyze Tourism Risk Perception and Travel Insurance: An Empirical Study

This research explored the relationship between travel insurance behavior and the tourism risk perception for civil servants in Taiwan. A total of 657 valid questionnaires were collected through this survey. Then we carry on self-organizing map (SOM) neural network to distinguish the willingness-to-pay of travel insurance among different divisions. We combine the u-matrix and the degree of risk divisions to build the tourism risk perception matrix and then to analyze the civil servants' attributes. The result revealed that respondents own the characteristic of lower perceived risk were highest purchasing demand of travel insurance.