Evidence map›Paper›PMID 36176791›Full record

ArticleFrontiers in psychology2022

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

Zhebin Zhang, Haiyin Jiang, Chuanmei Zhou, Jingyi Zheng, Shuiqing Yang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhebin ZhangZhejiang University of Finance and Economics, Hangzhou, Zhejiang, China.
Haiyin JiangZhejiang University of Finance and Economics, Hangzhou, Zhejiang, China.
Chuanmei ZhouZhejiang University of Finance and Economics, Hangzhou, Zhejiang, China.
Jingyi ZhengZhejiang University of Finance and Economics, Hangzhou, Zhejiang, China.
Shuiqing YangZhejiang University of Finance and Economics, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

omnichannel retailingreview contextreview helpfulnessreview labelreview label-content relevance

Identifiers

PMID36176791
PMCPMC9514054

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.