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Record W2778776359 · doi:10.5430/ijfr.v9n1p132

Multi-Criteria Decision-Making Model Evaluating the Performance of Vietnamese Commercial Banks

2017· article· en· W2778776359 on OpenAlexvenueno aff
Dinh Xuan Cuong, Hoang Thi Minh Hien, Tran Long

Bibliographic record

VenueInternational Journal of Financial Research · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsnot available
Fundersnot available
KeywordsVietnameseAnalytic hierarchy processMultiple-criteria decision analysisComputer scienceRank (graph theory)TOPSISFuzzy logicIdeal solutionProcess (computing)Decision-making modelsOperations researchHierarchyPreferenceOrder (exchange)Artificial intelligenceEngineeringBusinessMathematicsStatisticsEconomicsFinance

Abstract

fetched live from OpenAlex

The commercial banks (CBs) performance evaluating has been a necessary problem in currently integration trend and usually implemented by a committee of experts under criteria selected. Therefore, it is considered as a Multi - Criteria Decision - Making model (MCDM). Nowadays, there have been many researches proposing various standards and models to evaluate and rank CBs. But in Vietnam, the number of studies related to the Vietnamese banking evaluation model have still been limited. As a result, this study develops a multi-criteria decision model integrating Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy the Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The proposed model has evaluated and ranked five Vietnamese commercial banks including CTG, VCB, BIDV, TCB and MB. The paper revealed their ranks. Besides, the results of the research show that the Analytical Hierarchy Process (AHP) model is suitable for applying it to the process evaluating bank performance.

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)0.038
metaresearch head score (Gemma)0.137
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.971
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.137
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0100.002
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 head0.529
GPT teacher head0.634
Teacher spread0.104 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations7
Published2017
Admission routes1
Has abstractyes

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