記述言語：日本語   掲載種別：研究論文（大学，研究機関等紀要）   出版者・発行元：香川大学経済学部  

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掲載種別：研究論文（学術雑誌）  

© 2020 Informa UK Limited, trading as Taylor & Francis Group. This study identifies the extent to which cross-buying behaviors can be attributed to consumer motives, store patronage, and marketing efforts. Their explanatory power is empirically examined using a panel survey and purchase history data for fashion products of 3,052 customers patronizing an online shopping mall. Motivation explains merely 4% of the variation in the number of product categories purchased during the study period, surpassed by the variation explained by store patronage (8%) and marketing efforts (38%). These results suggest that, while motivation may be a necessary antecedent for cross-buying, it is insufficient as a ‘standalone’ driver, as behavior is largely driven by customers’ responses to marketing efforts.

DOI： 10.1080/0965254X.2020.1811997

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：ELSEVIER SCIENCE INC  

This study explores how lifestyle can explain the heterogeneous customer lifetime values (CLVs) among various market segments, We develop a latent class model of purchase frequency, lifetime duration, and purchase amount to infer segment-level CLV. Customers' membership to each segment is presumed to depend on their lifestyle patterns. The proposed model is then applied to the transaction and lifestyle data of customers in an online fashion retail market. The empirical analysis reveals four customer segments that each has a unique lifestyle pattern: Individualistic Innovators, Rational Followers, Self-actualized Experts, and Integrated Shoppers. These segments differ in their magnitude of average CLV, partially explainable by segment members' lifestyle characteristics. The paper finally discusses some implications for improving customer relationships and raising revenues.

DOI： 10.1016/j.jbusres.2019.02.049

Web of Science

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：ELSEVIER SCIENCE BV  

This study addresses how the heterogeneity of customer profitability in different segments can be explained by the behavioral characteristics of their members. We categorize customers into several segments based on the purchase rate, lifetime duration, and average spending estimated from purchase history data. Segment-level customer lifetime values are then calculated and combined with past purchase amounts to assign the segments to several tiers. A latent class model of purchase frequency, retention rate, and purchase amount is developed and applied to a large-scale online transaction dataset of fashion products. The analysis reveals that innovators, brand-conscious customers, mobile device users, and shop loyal customers are more likely to belong to valuable segments. The results are consistent over age cohorts. These findings provide novel insights into the impacts of behavioral characteristics on the profitability of online fashion customers as well as managerial implications for online marketers to design effective customer tier programs.

DOI： 10.1016/j.elerap.2018.100822

Web of Science

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開催年月日： 2023年

会議種別：口頭発表（一般）  

開催地：明治大学和泉キャンパス  

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開催年月日： 2023年

会議種別：口頭発表（一般）  

開催地：香川大学  

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開催年月日： 2022年

会議種別：口頭発表（一般）  

開催地：大阪府立大学  

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開催年月日： 2022年

会議種別：口頭発表（一般）  

開催地：香川大学  

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開催年月日： 2019年

会議種別：口頭発表（一般）  

開催地：南山大学  

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