徳島大学 教育・研究者情報データベース(EDB)

Education and Research Database (EDB), Tokushima University

徳島大学ウェブサイトへのリンク

著作: Suzuki Daisuke/Okubo Akane/[]/Takeyasu Kazuhiro/Need identification and sensitivity analysis of consumers using Bayesian Network: A case of Fuji Shopping Street Town/[Journal of Computations & Modelling]

ヘルプを読む

「著作」(著作(著書,論文,レター,国際会議など))は,研究業績にかかる著作(著書,論文,レター,国際会議など)を登録するテーブルです. (この情報が属するテーブルの詳細な定義を見る)

  • 項目名の部分にマウスカーソルを置いて少し待つと,項目の簡単な説明がツールチップ表示されます.

この情報をEDB閲覧画面で開く

EID
344755
EOID
1042701
Map
0
LastModified
2022年5月5日(木) 21:21:05
Operator
[ADMIN]
Avail
TRUE
Censor
0
Owner
(no caption; EID=335540)
Read
継承
Write
継承
Delete
継承
種別 必須 学術論文(審査論文)
言語 必須 英語
招待 推奨
審査 推奨
カテゴリ 推奨 研究
共著種別 推奨 徳島大学以外での国内共著(徳島大学以外でのある一つの国に属する複数機関による共同研究 (国外研究者を含まない))
学究種別 推奨
組織 推奨
著者 必須
  1. (英) Suzuki Daisuke
    役割 任意
    貢献度 任意
    学籍番号 推奨
  2. (英) Okubo Akane
    役割 任意
    貢献度 任意
    学籍番号 推奨
  3. (no caption; EID=335540)
    役割 任意
    貢献度 任意
    学籍番号 推奨
  4. (英) Takeyasu Kazuhiro
    役割 任意
    貢献度 任意
    学籍番号 推奨
題名 必須

(英) Need identification and sensitivity analysis of consumers using Bayesian Network: A case of Fuji Shopping Street Town

副題 任意
要約 任意

(英) 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. 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 and Yoshiwara Shopping Street. Therefore we focus Fuji Shopping Street in this paper. These are analyzed by using Bayesian Network. Sensitivity analysis is also conducted. As there are so many items, we focus on "The image of the surrounding area at this shopping street" and pick up former half and make sensitivity analysis in this paper. 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.

キーワード 推奨
  1. (英) Fuji City
  2. (英) Area rebirth
  3. (英) Regional vitalization
  4. (英) festival
  5. (英) Bayesian Network
  6. (英) Back Propagation
発行所 推奨 (英) Scienpress Ltd
誌名 必須 Journal of Computations & Modelling(Scienpress Ltd)
(pISSN: 1792-7625, eISSN: 1792-8850)
ISSN 任意 1792-8850
ISSN: 1792-7625 (pISSN: 1792-7625, eISSN: 1792-8850)
Title: Journal of Computations & Modelling
Publisher: Scienpress Ltd
(No Scopus information.)
必須 8
必須 4
必須 29 63
都市 任意
年月日 必須 2018年 8月 初日
URL 任意 https://ci.nii.ac.jp/naid/120006501028/
DOI 任意
PMID 任意
CRID 任意 1050001202957848064
NAID 120006501028
WOS 任意
Scopus 任意
機関リポジトリ 112076
評価値 任意
被引用数 任意
指導教員 推奨
備考 任意