A deep hybrid learning model for customer repurchase behavior

Jina Kim, HongGeun Ji, Soyoung Oh, Syjung Hwang, Eunil Park and Angel P. del Pobil

Journal of Retailing and Consumer Services, 2021, vol. 59, issue C

Abstract: Smartphones have become an integral part of our daily lives, which has led to the rapid growth of the smartphone market. As the global smartphone market tends to remain stable, retaining existing customers has become a challenge for smartphone manufacturers. This study investigates whether a deep hybrid learning approach with various customer-oriented types of data can be useful in exploring customer repurchase behavior of same-brand smartphones. Considering data from more than 74,000 customers, the proposed deep learning approach showed a prediction accuracy higher than 90%. Based on the results of deep hybrid learning models, we aim to provide better understanding on customer behavior, such that it could be used as valuable assets for innovating future marketing strategies.

Keywords: Deep learning; Smartphone; Customer repurchase; Online review (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:joreco:v:59:y:2021:i:c:s0969698920313898

DOI: 10.1016/j.jretconser.2020.102381

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