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Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective

As increasingly retail enterprises have adopted the omnichannel retailing strategy, both online-generated and offline-generated reviews should be considered to better understand the helpfulness of online reviews in the omnichannel retailing context. Drawing on the Elaboration Likelihood Model, the p...

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Autores principales: Zhang, Zhebin, Jiang, Haiyin, Zhou, Chuanmei, Zheng, Jingyi, Yang, Shuiqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9514054/
https://www.ncbi.nlm.nih.gov/pubmed/36176791
http://dx.doi.org/10.3389/fpsyg.2022.958386
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author Zhang, Zhebin
Jiang, Haiyin
Zhou, Chuanmei
Zheng, Jingyi
Yang, Shuiqing
author_facet Zhang, Zhebin
Jiang, Haiyin
Zhou, Chuanmei
Zheng, Jingyi
Yang, Shuiqing
author_sort Zhang, Zhebin
collection PubMed
description As increasingly retail enterprises have adopted the omnichannel retailing strategy, both online-generated and offline-generated reviews should be considered to better understand the helpfulness of online reviews in the omnichannel retailing context. Drawing on the Elaboration Likelihood Model, the present study attempts to examine the impacts of review label volume, review content length, and review label-content relevance on review helpfulness in the omnichannel retailing context. The empirical data of 2,822 product reviews were collected from Suning.com. The results of Negative Binomial Regression showed that both central cue (review label-content relevance) and peripheral cue (review content length) positively affect review helpfulness. Specifically, the positive effect of review content length on review helpfulness will be stronger when the online review is submitted from an omnichannel retailer’s online store. On the contrary, the positive effect of review label-content relevance on review helpfulness will be weaker when the online review is generated from an omnichannel retailer’s online channel.
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spelling pubmed-95140542022-09-28 Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective Zhang, Zhebin Jiang, Haiyin Zhou, Chuanmei Zheng, Jingyi Yang, Shuiqing Front Psychol Psychology As increasingly retail enterprises have adopted the omnichannel retailing strategy, both online-generated and offline-generated reviews should be considered to better understand the helpfulness of online reviews in the omnichannel retailing context. Drawing on the Elaboration Likelihood Model, the present study attempts to examine the impacts of review label volume, review content length, and review label-content relevance on review helpfulness in the omnichannel retailing context. The empirical data of 2,822 product reviews were collected from Suning.com. The results of Negative Binomial Regression showed that both central cue (review label-content relevance) and peripheral cue (review content length) positively affect review helpfulness. Specifically, the positive effect of review content length on review helpfulness will be stronger when the online review is submitted from an omnichannel retailer’s online store. On the contrary, the positive effect of review label-content relevance on review helpfulness will be weaker when the online review is generated from an omnichannel retailer’s online channel. Frontiers Media S.A. 2022-09-13 /pmc/articles/PMC9514054/ /pubmed/36176791 http://dx.doi.org/10.3389/fpsyg.2022.958386 Text en Copyright © 2022 Zhang, Jiang, Zhou, Zheng and Yang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Zhang, Zhebin
Jiang, Haiyin
Zhou, Chuanmei
Zheng, Jingyi
Yang, Shuiqing
Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective
title Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective
title_full Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective
title_fullStr Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective
title_full_unstemmed Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective
title_short Predicting review helpfulness in the omnichannel retailing context: An elaboration likelihood model perspective
title_sort predicting review helpfulness in the omnichannel retailing context: an elaboration likelihood model perspective
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9514054/
https://www.ncbi.nlm.nih.gov/pubmed/36176791
http://dx.doi.org/10.3389/fpsyg.2022.958386
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