Evidence map›Paper›PMID 33488474›Full record

ArticleFrontiers in psychology2020

The Effect of Reviewers' Self-Disclosure of Personal Review Record on Consumer Purchase Decisions: An ERPs Investigation.

Jianhua Liu, Zan Mo, Huijian Fu, Wei Wei, Lijuan Song, Kewen Luo

Abstract read
In one paragraph

Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

6 authors.

Jianhua LiuSchool of Management, Guangdong University of Technology, Guangzhou, China.
Zan MoSchool of Management, Guangdong University of Technology, Guangzhou, China.
Huijian FuSchool of Management, Guangdong University of Technology, Guangzhou, China.
Wei WeiMBA School, Guangdong University of Finance and Economics, Guangzhou, China.
Lijuan SongSchool of Management, Guangdong University of Technology, Guangzhou, China.
Kewen LuoSchool of Management, Guangdong University of Technology, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personal review record, as a form of personally identifiable information, refers to the past review information of a reviewer. The disclosure of reviewers' personal information on electronic commerce websites has been found to substantially impact consumers' perception regarding the credibility of online reviews. However, personal review record has received little attention in prior research. The current study investigated whether the disclosure of personal review record influenced consumers' information processing and decision making by adopting event-related potentials (ERPs) measures, as ERPs allow for a nuanced examination of the neural mechanisms that underlie cognitive processes. At the behavioral level, we found that the purchase rate was higher and that the reaction time was shorter when the review record was disclosed (vs. when it was not), indicating that the disclosed condition was more favorable to the participants. Moreover, ERPs data showed that the disclosed condition induced an attenuated N400 component and an increased LPP component relative to the undisclosed condition, suggesting that the former condition gave rise to less cognitive and emotional conflict and to more positive evaluations. Thus, by elucidating potential cognitive and neural underpinnings, this study demonstrates the positive impact of reviewers' disclosure of personal review record on consumers' purchase decisions.

Indexed as

event-related potentialsLPPN400purchase decisionreview recordself-disclosure

Identifiers

PMID33488474
PMCPMC7820410

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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.