Title :
Applying Self-Organizing Map Network to Analyze Tourism Risk Perception and Travel Insurance: An Empirical Study
Author :
Chou, Pai-Lung ; Lin, Chao-Hsin ; Hsu, Shuo-Fen ; Liu, Hsiang-Hsi
Author_Institution :
Nat. Kaohsiung First Univ. of Sci. & Technol., Kaohsiung
Abstract :
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.
Keywords :
insurance; neural nets; risk management; travel industry; neural network; selforganizing map network; tourism risk perception; travel insurance; Chaos; Data mining; Decision making; Insurance; Multidimensional systems; Neural networks; Neurons; Risk analysis; Risk management; Vector quantization;
Conference_Titel :
Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
Conference_Location :
Kumamoto
Print_ISBN :
0-7695-2882-1
DOI :
10.1109/ICICIC.2007.184