| Project/Area Number |
18K01904
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Review Section |
Basic Section 07090:Commerce-related
|
|---|
| Research Institution | Nippon Bunri University |
|---|
Principal Investigator |
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
斎藤 参郎 福岡大学, 公私立大学の部局等, 研究特任教授 (50111654)
岩見 昌邦 和光大学, 経済経営学部, 講師 (60629541)
|
|---|
| Project Period (FY) |
2018-04-01 – 2024-03-31
|
| Project Status |
Completed (Fiscal Year 2023)
|
| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
|
|---|
| Keywords | 時系列分析 / 複数の商業施設入館者数日時データ / VARモデル / 人流ビッグデータ / 時系列データ予測 / 状態空間モデル / 分次の商業施設入館者数データ / 商業施設入館者数データ |
|---|
| Outline of Final Research Achievements |
In this study, we investigated the characteristics of visitor number fluctuations and the interactions among multiple commercial facilities in the central area of Fukuoka City by employing time series analysis on the visitor count data and human flow big data provided by large-scale commercial facilities. Although the development of the estimation and prediction model using the State Space Model (SSM), which was initially planned, was not completed, we were able to analyze the relationships among the visitor counts of commercial facilities by applying the Vector Autoregressive (VAR) model. As a result, we successfully elucidated the periodicity of visitor count data, the interactions among facilities, and the correlation between event occurrences and visitor numbers, thereby obtaining valuable insights. These findings are expected to contribute to the management strategies of commercial facilities and urban planning proposals, as well as have potential applications in other cities.
|
| Academic Significance and Societal Importance of the Research Achievements |
本研究の学術的意義は、大規模商業施設の入館者数データと人流ビッグデータを用いて、入館者数の変動特性と施設間の相互作用を明らかにし、ベクトル自己回帰モデルを適用して商業施設間の関連性を定量的に分析した点にある。
社会的意義としては、本研究の成果が商業施設の経営戦略や都市計画への提言に活用できる点が挙げられる。入館者数の変動特性や施設間の相互作用を考慮することで、効果的なマーケティング戦略の立案や最適な商業施設の配置計画が可能となり、他都市への応用も期待される。
|
