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Record W4221044666 · doi:10.3390/jrfm15030125

Fintech and Financial Health in Vietnam during the COVID-19 Pandemic: In-Depth Descriptive Analysis

2022· article· en· W4221044666 on OpenAlex
Robert Jeyakumar Nathan, Budi Setiawan, Mac Nhu Quynh

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of risk and financial management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
FundersMinistry of Higher Education, MalaysiaMultimedia University
KeywordsUnbankedFinancial literacyFinancial servicesFinTechBusinessFinancial inclusionGovernment (linguistics)MarketingPandemicPopulationLiteracyPopularityPaymentCoronavirus disease 2019 (COVID-19)FinancePsychologyEconomicsEconomic growthMedicine

Abstract

fetched live from OpenAlex

The growing popularity of smartphones and the proliferation of technology have accelerated the development of the digital payment industry. Fintech enables customers to access financial services more efficiently and faster than traditional business, especially during the COVID-19 pandemic due to health protocols, including restrictions on physical contact. This study investigates financial literacy, fintech adoption, and the impact of the COVID-19 crisis on the financial health of consumers in Vietnam. The relatively higher level of the unbanked population in Vietnam and the lower level of adult financial literacy compared with the ASEAN region motivated this study. Based on judgment sampling, participants were approached using the mall intercept technique, and those familiar with fintech were selected for the research interview. Thirty participants were interviewed and were given a survey form to be filled online using their mobile phones. Data analysis was conducted using IBM SPSS software version 23. Perceived ease of use, perceived usefulness, trust, brand image, government support, user innovativeness, and attitude are found to be significantly correlated with fintech adoption in Vietnam, while financial literacy was found to be not significantly correlated with fintech adoption. Furthermore, further analysis using multiple linear regression revealed user innovativeness and attitude have a positive impact towards fintech adoption, and in contrast, financial literacy showed significant negative impact on fintech. This inverse relationship could indicate that in Vietnam, fintech may play a role of bringing financial inclusion where people with lower financial literacy are able to use technology for financial transactions, which was previously inaccessible to them. This could also mean that Vietnamese with higher financial literacy do not see fintech as an important tool for their financial transactions, as they may already have strong access to traditional financial facilities. This research contributes to knowledge in the field of Fintech adoption in Vietnam at the time of the COVID-19 outbreak. To foster greater financial inclusivity and access for the Vietnamese consumers, policy makers could promote the development of fintech business infrastructure and regulatory sandboxes to foster fintech startups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.246
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it