MétaCan
Menu
Back to cohort
Record W3154293643 · doi:10.5267/j.ac.2021.4.014

Factors affecting the attraction of foreign direct investment: A study in northwest of Vietnam

2021· article· en· W3154293643 on OpenAlexvenueno aff
Phuong Tran Hoa, Hà Nguyễn Thị Thu, Duong Nguyen Duc

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentOpenness to experienceDeveloping countryContext (archaeology)Competition (biology)RestructuringInternational economicsEconomic restructuringBusinessEmpirical researchHuman capitalEconomicsInternational tradeMarket economyEconomic growthMacroeconomics

Abstract

fetched live from OpenAlex

Foreign direct investment (FDI) plays an important role in economic growth for developing countries where there is always a shortage of investment capital. Its role is manifested through promoting economic restructuring, expanding markets, promoting exports, developing human resources and providing new technologies for development. Therefore, FDI has always been addressed as the top concern of governments in developing countries. However, FDI inflows often fluctuate because of many factors related to the competitive environment, such as market size, economic openness, competition in labor resources, etc. There are many empirical studies related to FDI inflows. However, most of these studies are carried out in developed countries. Meanwhile, in developing countries, there is not as much as this kind of study. On the other hand, the empirical research results are not consistent. This article will analyze the factors affecting FDI in the Northwest region of Vietnam in the context of global economic integration in the period of 2000 - 2019, from which we draw out the policy implications that can be applied to Vietnam.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.253
Teacher spread0.221 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAccountingSame topicInternational Business and FDIFrench-language works237,207