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.