Evidence map›Paper›PMID 34234728›Full record

ArticleFrontiers in psychology2021

A Study of Young Chinese Intentions to Purchase "Online Paid Knowledge": An Extended Technological Acceptance Model.

Aiting Xu, Wei Li, Zhiyu Chen, Shouzhen Zeng, Llopis-Albert Carlos, Yuhan Zhu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Aiting XuSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, China.
Wei LiSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, China.
Zhiyu ChenSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, China.
Shouzhen ZengSchool of Business, Ningbo University, Ningbo, China.
Llopis-Albert CarlosInstituto Universitario de Ingeniería Mecánica y Biomecánica (I2MB), Universitat Politècnica de València - Camino de Vera s/n, Valencia, Spain.
Yuhan ZhuSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Under the catalysis of knowledge anxiety and cognitive surplus, knowledge sharing platforms has experienced rapid growth, which has accelerated the integration of knowledge resources online. As with all new successful and sustainable business products, the consumers will play an important role in the future development of online paid knowledge. Therefore, we constructed an extended technological acceptance model by examining factors that influence young Chinese people's willingness to pay for online paid knowledge. The study surveyed 405 young Chinese participants, in which the extended technological acceptance model was tested by using structural equation modeling. Findings indicate that perceived ease of use is positively associated with perceived usefulness and associated attitudes, whereas perceived usefulness and attitude is positively associated with purchase intention. Perceived risk and group conformity are found to indirectly affect consumers' willingness to pay. The study advances the current body of knowledge by empirically testing the impact of perceived risk and the role of cultural influence (group conformity) on purchasing intention. Finally, theoretical and practical implications are discussed.

Indexed as

cross-cultural psychologyonline paid knowledgeperceived risk theorypurchase intentionstructural equation modeltechnology acceptance model

Identifiers

PMID34234728
PMCPMC8255359

What OpenQuestion holds

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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.