Evidence map›Paper›PMID 32973617›Full record

ArticleFrontiers in psychology2020

Exploring the Novel Input Attributes Affecting eWOM.

Safdar Hussain, Kaishan Huang, Zahida Ilyas, Ben Niu

Open access · goldAbstract 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
5.0field-weighted citation impact, top 4% of its field
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

2 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
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

4 authors at 2 institutions in 2 countries.

Safdar HussainCollege of Management, Shenzhen University, Shenzhen, China.
Kaishan HuangGreat Bay Area International Institute for Innovation, Shenzhen, China.
Zahida IlyasDepartment of Applied Psychology, Lahore College for Women University, Lahore, Pakistan.
Ben NiuCollege of Management, Shenzhen University, Shenzhen, China.
Shenzhen University · CNLahore College for Women University · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electronic word of mouth (eWOM) has become significantly important in online communities, which are influential sources of instant information on the internet. This study examines the eWOM input attributes linked to consumers' information adoption behavior in the context of information-related interaction. This study uses a structural equation modeling approach by choosing participants from Fujian and Guangdong provinces of China. The results reveal that eWOM input attributes studied positively influence information-related interactions. An individual's perception of value enhances the performance of products or services, which is an essential predictor of information adoption. Furthermore, information usefulness and related interactions are key eWOM message characteristics affecting information adoption on the internet. This study contributes to the eWOM input attributes and message characteristics literature by exploring information-related interaction as a new mediator to consumers' online information adoption. The authors provide suggestions for marketers and firms to dynamically develop strategies in response to consumers' concerns while making a purchase online.

Indexed as

information-related interactioninformation usefulnessonline opinionspurchasing behaviorWOM and eWOM

Identifiers

PMID32973617
PMCPMC7471601
OpenAlexW3080635948

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.