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Record W3004160145 · doi:10.5267/j.uscm.2019.10.003

Factors affecting the application of management accounting in Vietnamese enterprises

2020· article· en· W3004160145 on OpenAlexvenueno aff
Oanh Thi Tu Le, Thi Thu Phong Tran, Quoc Hung Nguyen

Bibliographic record

VenueUncertain Supply Chain Management · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseAccountingBusinessManagement accounting

Abstract

fetched live from OpenAlex

This paper aims to investigate factors affecting the application of management accounting in Vietnamese enterprises. Quantitative research was conducted and data was collected by sending questionnaires to 120 companies in the manufacturing, trading and service sectors in Vietnam. 6 factors were selected to measure the application of management accounting in enterprises through correlation and regression analysis. The results showed that 5 out of 6 factors positively associated with the level of management accounting application; including firm size, organizational culture, organizational structure, technology and human resources operations. In particular, corporate culture has the highest impact and opinion of managers has the lowest impact on management accounting application. Business environment has a negative impact on management accounting application in enterprises. Based on the research results, suggestions and recommendations are proposed for enterprises regarding application of management accounting. The research provided an overview of management accounting application and its benefits to enterprises. Whereby, it helps managers have a better understanding of management accounting and future directions for application. Moreover, the research results will be useful for managers to identify factors influencing their management accounting practices and improve the current management process applied in organizations.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.014
GPT teacher head0.224
Teacher spread0.210 · 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.

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

Citations12
Published2020
Admission routes1
Has abstractyes

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