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Record W1496217683

Pengaruh Foreign Direct Investment (FDI) dan Daya Saing Terhadap Ekspor (Studi Pada Sektor Industri Manufaktur Indonesia Tahun 2004-2013)

2015· article· id· W1496217683 on OpenAlexaboutno aff
Aulia Hadin Salsabila

Bibliographic record

VenueJurnal Administrasi Bisnis S1 Universitas Brawijaya · 2015
Typearticle
Languageid
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentBusinessQuarter (Canadian coin)Ordinary least squaresGlobalizationInvestment (military)International economicsInternational tradeEconomicsMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Globalization in the economic field has encourage economic participation between countries. Every economy in the world has the goal to master and compete in the global market. Export is one of the economic activities undertaken to market their products outside national borders. By doing so, export requires a driving factor, the driving factors used in this study are FDI (Foreign Direct Investment) and competitiveness.The aim of this study is to determine the influence of FDI and competitiveness against exports on Indonesia’s manufacturing industries. This study using an equations model analysis with Ordinary Least Square (OLS) from the first quarter of 2004 – the fourth quarter of 2013. According to the result of simultaneous test indicating that FDI and competitiveness has significant effect on export .Furthermore, the partial test results indicates that each variable of FDI and competitiveness showed a significant effect on export. Keywords : FDI, Competitiveness, RCA, and Exports.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.033
GPT teacher head0.225
Teacher spread0.192 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2015
Admission routes1
Has abstractyes

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