Evidence map›Paper›PMID 35369237›Full record

ArticleFrontiers in psychology2022

Factors Affecting Intention of Consumers in Using Face Recognition Payment in Offline Markets: An Acceptance Model for Future Payment Service.

Dongyan Nan, Yerin Kim, Jintao Huang, Hae Sun Jung, Jang Hyun Kim

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. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

5 authors.

Dongyan NanDepartment of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul, South Korea.
Yerin KimDepartment of Applied Artificial Intelligence, Sungkyunkwan University, Seoul, South Korea.
Jintao HuangDepartment of Interaction Science, Sungkyunkwan University, Seoul, South Korea.
Hae Sun JungDepartment of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul, South Korea.
Jang Hyun KimDepartment of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Face recognition payment (FRP), an innovative financial technology service, is a recently developed mode of payment service that has garnered attention in the offline market, particularly in China. However, studies examining the adoption of FRP by consumers are scarce. Therefore, this study proposed a causal model built on the Unified Theory of Acceptance and Use of Technology, and key predictors related to the intention of using FRP were identified. The structural equation model-based results obtained from 305 Chinese participants demonstrated that the intention was most affected by relative advantage. In addition, performance expectancy, effort expectancy, social influence, and perceived risk also had a significant impact. However, trust was found to not significantly affect consumers' intentions, despite it negatively influencing perceived risk. Thus, the results of this study are expected to provide a set of guidelines for companies regarding the implementation of FRP.

Indexed as

face recognition paymentfinancial technology adoptionperceived riskrelative advantagetrust

Identifiers

PMID35369237
PMCPMC8969225

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.