Author
Listed:
- Tsuyoshi Aburai
- Akane Okubo
- Daisuke Suzuki
- Kazuhiro Takeyasu
Abstract
Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. 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 we focus Fuji Shopping Street Town in this paper. These are analyzed by using Bayesian Network. 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. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.
Suggested Citation
Tsuyoshi Aburai & Akane Okubo & Daisuke Suzuki & Kazuhiro Takeyasu, 2018.
"Bayesian Network Analysis for the Questionnaire Investigation on the Needs at Fuji Shopping Street Town,"
Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 9(2), pages 46-68, May.
Handle:
RePEc:jfr:jms111:v:9:y:2018:i:2:p:46-68
DOI: 10.5430/jms.v9n2p46
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