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Record W4212826076 · doi:10.5267/j.ac.2021.11.003

Determining factors affecting the transition of financial statement preparation from VAS to IFRS in enterprises in Vietnam

2022· article· en· W4212826076 on OpenAlexvenueno aff
Duy Thuc Nguyen, Thi Tha Nghiem, Thanh Long Tran, Duc Hai Nguyen

Bibliographic record

VenueAccounting · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsInternational Financial Reporting StandardsBusinessAccountingFinancial statementVietnameseViewpointsChristian ministryFinanceOrder (exchange)Audit

Abstract

fetched live from OpenAlex

According to the Ministry of Finance's roadmap for applying IFRS in Vietnam, listed enterprises on the stock market and state-owned enterprises holding the dominant power are the first group of enterprises to alter the preparation of financial statements according to Vietnamese Accounting Standards (VAS) to the application of International Financial Reporting Standards (IFRS). The voluntary application period is from 2022 to 2025 and the period after 2025 will be the mandatory one. This study was conducted to determine the factors affecting the transition from preparing financial statements following VAS to IFRS for this group of enterprises. The study involved surveying managers and chief accountants at 120 enterprises belonging to the group of companies listed on the stock market, state-owned enterprises holding the dominant power, with the adoption of a regression analysis method. The research results show that five factors are affecting the transition of financial reporting from VAS to IFRS in this group of enterprises, with the order of influence being ranked from high to low, respectively as (i) Size and operation characteristics of the enterprise; (ii) Competence of accountants; (iii) Viewpoints of the enterprise administrators; (iv) Applied accounting regime, and (v) Enterprise owners. On that basis, the study proposes some recommendations for the transition from preparing financial statements according to VAS to IFRS for enterprises to meet the Ministry of Finance's roadmap for IFRS application.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.003
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 score0.069
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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