Community-based management for low-digitalized communities using cross-cutting purchasing behavior

Yuya Ieiri*, Kaishu Yamaki, Reiko Hishiyama

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The need for community-based management to revitalize the economy of commercial areas by using consumer behavior analysis focusing on transactions has increased. Low-digitalized shopping communities, commercial communities that include retailing that have not introduced digital technologies, require community-based management using consumer behavior analysis. However, low-digitalized shopping communities cannot collect cross-cutting consumer behavior data using digital technologies such as point of sales (POS) systems. This difficulty obscures the novel management potential of applying such customer behavior analysis to community-based management. Our study aims to bridge the gap between low-digitalized shopping communities and community-based management using customer behavior analysis. To achieve this purpose, this study proposed a novel management approach using data collected using paper-based community currencies and its analysis method. Two field experiments were performed in low-digitalized shopping communities in Japan using two types of community currencies: from-to (FT) and customer attributes (CA). This study illustrated the possibility of community-based management in low-digitalized shopping communities and extending conventional retailing management methods using customer behavior analysis to community-based management.

Original languageEnglish
Article number21
JournalHumanities and Social Sciences Communications
Volume11
Issue number1
DOIs
Publication statusPublished - 2024 Dec

ASJC Scopus subject areas

  • General Arts and Humanities
  • General Economics,Econometrics and Finance
  • General Business,Management and Accounting
  • General Social Sciences
  • General Psychology

Fingerprint

Dive into the research topics of 'Community-based management for low-digitalized communities using cross-cutting purchasing behavior'. Together they form a unique fingerprint.

Cite this