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Record W2994321821 · doi:10.5430/ijfr.v11n1p417

Mobile Money, Financial Inclusion and Digital Payment: The Case of Vietnam

2019· article· en· W2994321821 on OpenAlex

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

VenueInternational Journal of Financial Research · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
FundersTrường Đại học Kinh tế - Luật, Đại học Quốc gia Thành phố Hồ Chí Minh
KeywordsMobile paymentFinancial inclusionFinancial transactionBusinessDatabase transactionPaymentCashIntermediaryFinancial intermediaryPayment service providerFinancial servicesFinancial systemDigital currencyMobile bankingService (business)CommerceFinanceMarketing

Abstract

fetched live from OpenAlex

The study provides an overview of mobile money account usage, financial inclusion and digital payment transaction trends in Vietnam, and considers the factors influencing these trends. In general, the rates of using mobile money service and account ownership at financial intermediaries in Vietnam are still low, and other indicators of digital transactions suggest low levels compared to those of countries with low- and middle- income as well as to the world averages. The research also shows that owning an account at a financial intermediary facilitates the use of mobile money. This is a positive trend, at least compared to the situation in some African countries. Finally, having an account at a financial intermediary and using mobile money services generally have a positive effect on the participation in non-cash transactions.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.033
GPT teacher head0.320
Teacher spread0.287 · 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