潜在クラスモデルを利用した取引データのセグメンテーション  [in Japanese] A Segmentation of Transaction Data using a Latent Class Model  [in Japanese]

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Author(s)

    • 佐藤 栄作 SATO Eisaku
    • 東京大学大学院総合文化研究科 博士課程 Ph.D.student, Graduate School and College of Arts and Sciences, The University of Tokyo
    • 椿 広計 TSUBAKI Hiroe
    • 筑波大学大学院経営政策科学研究科 Graduate School of Business Sciences, Tsukuba University

Abstract

In this article, we proposed a segmentation method of transaction data by making use of a Latent Class Model. In the analysis, not only a standard Latent Class Model, but also a model that relaxed the assumption of local independence was applied to the transaction data of a convenience store. Consequently, based on the AIC criterion, a model with six classes was adopted. All of these segments were interpreted as having a different purchace-intentions. Additionally, the purchase-intention of a coming-into-the-store visitor and the size of the purchase could be guessed from transaction data. Furthermore, it was shown that the information acquired by analyzing transaction data by our method may translate into useful information for working on a store policy corresponding to the characteristics of the coming-to-the-store visitors of a convenience store from a practical viewpoint.

Journal

  • The Japanese journal of behaviormetrics

    The Japanese journal of behaviormetrics 30(1), 121-133, 2003-03-29

    The Behaviormetric Society of Japan

References:  16

Cited by:  2

Codes

  • NII Article ID (NAID)
    110003812559
  • NII NACSIS-CAT ID (NCID)
    AN0008437X
  • Text Lang
    JPN
  • Article Type
    Journal Article
  • ISSN
    03855481
  • NDL Article ID
    6700418
  • NDL Source Classification
    ZE1(社会・労働--社会科学・社会思想・社会学) // ZD43(経済--統計)
  • NDL Call No.
    Z6-1106
  • Data Source
    CJP  CJPref  NDL  NII-ELS 
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