油井, 毅 Tokushima University
Okubo, Akane University of Shizuoka
Suzuki, Daisuke Fujisan Area Management Company
Takeyasu, Kazuhiro Tokoha University
Shopping streets at local city in Japan became old and are generally declining. In this paper, the area rebirth and/or regional revitalization of shopping street are handled. Fuji city in Japan is focused. Four big festivals are held at Fuji city (two for Fuji Shopping Street Town and two for Yoshiwara Shopping Street Town). Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street Town and Yoshiwara Shopping Street Town. Therefore Fuji Shopping Street Town is focused in this paper. These are analyzed by using Bayesian Network. These are analyzed by sensitivity analysis and odds ratio is calculated to the results of sensitivity analysis in order to obtain much clearer results. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. Fruitful results are obtained. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.
International Journal of Advanced Computer Science and Applications
The Science and Information Organization
This is an open access publication licensed under a Creative Commons Attribution 4.0 International License(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
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