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Record W4409108451 · doi:10.3390/jrfm18040189

The Impact of Digital Transformation on Economic Integration in ASEAN-6: Evidence from a Generalized Least Squares (GLS) Model

2025· article· en· W4409108451 on OpenAlexvenueno aff
Thi Anh Tuyet Le

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsGeneralized least squaresTransformation (genetics)Least-squares function approximationEconometricsEconomicsMathematicsStatisticsChemistry

Abstract

fetched live from OpenAlex

This study analyzes the impact of digital transformation on the international economic integration of ASEAN-6 countries during the period of 2000–2023 using the Generalized Least Squares (GLS) estimation method. The findings indicate that factors such as fixed broadband subscriptions (FixB), fixed telephone subscriptions (FixT), and the value added from medium- and high-tech manufacturing (MHT) have a positive and statistically significant effect on trade openness (TO). Conversely, mobile cellular subscriptions (MB) and the percentage of individuals using the Internet (IU) exhibit a negative impact on economic integration, reflecting the uneven development of digital infrastructure across countries. Based on these results, the study suggests policy implications, including substantial investment in digital infrastructure, technological advancement in production, and improved accessibility to digital services to foster more effective economic integration. ASEAN-6 countries should adopt tailored development strategies that emphasize innovation and the development of a skilled digital workforce to enhance their competitiveness both regionally and globally.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.243
Teacher spread0.222 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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