Area-POS Data: A Novel Method for Commercial Area Management

Yuya Ieiri, Kaishu Yamaki, Sun Yue, Reiko Hishiyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Understanding consumers' purchasing behavior is a crucial component of commercial area management. This article proposes Area-POS data for elucidating consumer purchasing behavior in a commercial area. As a method of collecting Area-POS data, we focused on FT (from-to) type community currency, which determines the co-occurrence of stores used by customers (distributor store and destination store). Moreover, this study extended ABC analysis and association analysis, which are POS data analysis methods, to the analysis method of Area-POS data obtained by FT-type community currency. Field experiments were conducted to examine the effectiveness of these methods for collecting and analyzing Area-POS data. The results of these experiments identified stores with high visit frequency in the commercial area and clarified the primary co-occurrence relationships among stores in the area. The findings of this study show the effectiveness and potential of Area-POS data analysis for commercial area management.

Original languageEnglish
Title of host publication2022 13th International Conference on E-Education, E-Business, E-Management, and E-Learning, IC4E 2022
PublisherAssociation for Computing Machinery
Pages579-584
Number of pages6
ISBN (Electronic)9781450387187
DOIs
Publication statusPublished - 2022 Jan 14
Event13th International Conference on E-Education, E-Business, E-Management, and E-Learning, IC4E 2022 - Virtual, Online, Japan
Duration: 2022 Jan 142022 Jan 17

Publication series

NameACM International Conference Proceeding Series

Conference

Conference13th International Conference on E-Education, E-Business, E-Management, and E-Learning, IC4E 2022
Country/TerritoryJapan
CityVirtual, Online
Period22/1/1422/1/17

Keywords

  • ABC analysis
  • Area-POS data
  • association analysis
  • community currency

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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