KOREASCHOLAR

The fashion consumer purchase patterns and influencing factors through big data - Based on sequential pattern analysis -

Ki Yong Kwon
  • 언어ENG
  • URLhttp://db.koreascholar.com/Article/Detail/427270
복식문화연구 (服飾文化硏究)
31권 5호 (2023.10)
pp.607-626
복식문화학회 (The Costume Culture Association)
초록

This study analyzes consumer fashion purchase patterns from a big data perspective. Transaction data from 1 million transactions at two Korean fashion brands were collected. To analyze the data, R, Python, the SPADE algorithm, and network analysis were used. Various consumer purchase patterns, including overall purchase patterns, seasonal purchase patterns, and age-specific purchase patterns, were analyzed. Overall pattern analysis found that a continuous purchase pattern was formed around the brands’ popular items such as t-shirts and blouses. Network analysis also showed that t-shirts and blouses were highly centralized items. This suggests that there are items that make consumers loyal to a brand rather than the cachet of the brand name itself. These results help us better understand the process of brand equity construction. Additionally, buying patterns varied by season, and more items were purchased in a single shopping trip during the spring season compared to other seasons. Consumer age also affected purchase patterns; findings showed an increase in purchasing the same item repeatedly as age increased. This likely reflects the difference in purchasing power according to age, and it suggests that the decision-making process for purchasing products simplifies as age increases. These findings offer insight for fashion companies’ establishment of item-specific marketing strategies.

목차
I.􀀃 Introduction
II.􀀃 Background
    1.􀀎 Consumer􀀎 purchase􀀎 pattern
    2.􀀎 Factors􀀎 influencing􀀎 on􀀎 consumer􀀎 purchase􀀎pattern
    3.􀀎 Big􀀎 data􀀎 and􀀎 purchase􀀎 pattern
    4.􀀎 Sequential􀀎 pattern􀀎 analysis􀀎 and􀀎 purchase􀀎pattern􀀎
III.􀀃 Research􀀃 Method
    1.􀀎 Study􀀎 purpose
    2.􀀎 Brand􀀎 characteristics
    3.􀀎 Data􀀎 collection􀀎 and􀀎 analysis􀀎 methods
IV.􀀃 Results
    1.􀀎 Brand􀀎 A􀀎 characteristics􀀎 and􀀎 patterns
    2.􀀎 Brand􀀎 A􀀎 entire􀀎 sequential􀀎 pattern􀀎 analysis
    3.􀀎 Brand􀀎 A􀀎 seasonal􀀎 sequential􀀎 pattern􀀎 analysis
    4.􀀎 Brand􀀎 A􀀎 sequential􀀎 patterns􀀎 analysis􀀎 by􀀎 age
    5.􀀎 Brand􀀎 B􀀎 characteristics􀀎 and􀀎 patterns
    6.􀀎 Network􀀎 analysis􀀎 results
V.􀀃 Conclusion
저자
  • Ki Yong Kwon(Lecturer, Dept. of Fashion Design Kookmin University, Korea) Corresponding author