Research on relationship between customer interaction and customer loyalty in clothing online brand community based on meta-analysis

LI Jiong; CHEN Lihong

doi:10.12299/jsues.21-0185

Volume 35 Issue 1

Sep. 2022

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LI Jiong, CHEN Lihong. Research on relationship between customer interaction and customer loyalty in clothing online brand community based on meta-analysis[J]. Journal of Shanghai University of Engineering Science, 2022, 36(1): 55-61, 90. doi: 10.12299/jsues.21-0185

Citation:

LI Jiong, CHEN Lihong. Research on relationship between customer interaction and customer loyalty in clothing online brand community based on meta-analysis[J]. Journal of Shanghai University of Engineering Science, 2022, 36(1): 55-61, 90. doi: 10.12299/jsues.21-0185

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Research on relationship between customer interaction and customer loyalty in clothing online brand community based on meta-analysis

doi: 10.12299/jsues.21-0185

LI Jiong^1
,,
CHEN Lihong^{2
,
,}

1.
School of Textiles and Fashion, Shanghai University of Engineering Science, Shanghai 201620, China
2.
Shanghai International Fashion Innovation Center, Donghua University, Shanghai 200051, China

Received Date: 2021-09-08
Publish Date: 2022-09-26

Abstract

Abstract

In order to obtain the quantitative integration results of the relationship between online brand community customer interaction and customer loyalty, and understand the relationship between them in the clothing field, the meta-analysis method was used to study 5137 independent samples of 16 related literatures published at home and abroad from 2011 to 2020. It was found that all dimensions of online brand community customer interactions play a moderate role in promoting customer loyalty and community types play a moderating role in the relationship between customer interaction dimensions and customer loyalty. A phased summary of the research between the two was made, research focus was adjusted according to their own community types while customer interaction had been concerned, and the relationship between them in the clothing field was predicted. Finally, some suggestions were put forward for the community operation of clothing online brands.
- meta-analysis,
- customer interaction,
- customer loyalty,
- clothing online brand community

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References(49)

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