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Cited by 258

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

The influence of identity-driven customer engagement on purchase intention

Open access
Prentice, Catherine, Han, Xiao Yun, Hua, Lian-Lian, Hu, Lin·2019·Journal of Retailing and Consumer Services

Abstract

Drawing on social identification theory and motivation of expectancy, the current study examines the relationship between social identification, customer engagement and purchase intention in the context of online communities. Social identification is operationalised into person-to-person and person-to-community identifications, whereas customer engagement into attitudinal and behavioural engagement. This study was undertaken with members from two of the most popular online communities in China. The study confirms that identifying with other members of the online community is significantly related to identification with the community; both identifications have a significant impact on customer engagement, which can lead to purchase intention.

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Registry

Crossref · 10.1016/j.jretconser.2018.12.014

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Metadata

Authors
Prentice, C., Han, X. Y., Hua, L.-L., & Hu, L.
Venue
Journal of Retailing and Consumer Services
Publisher
Elsevier BV
Published
2019-03
Volume
47
Pages
339-347
ISSN
0969-6989 (ISSN-L)
OpenAlex
W2909941303
Cited by
258
References
15
FWCI
51.00
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: The influence of identity-driven customer engagement on purchase intention. https://app.cochat.ai/papers/10.1016/j.jretconser.2018.12.014
The paper
Prentice, C., Han, X. Y., Hua, L.-L., & Hu, L. (2019). The influence of identity-driven customer engagement on purchase intention. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2018.12.014

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.