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Record W2732934696 · doi:10.5539/ijef.v9n7p222

Determinants of Foreign Direct Investment in Saudi Arabia: A Review

2017· review· en· W2732934696 on OpenAlexvenueno aff
Haga Elimam

Bibliographic record

VenueInternational Journal of Economics and Finance · 2017
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentOpenness to experienceInternational economicsForeign portfolio investmentBusinessEconomicsInvestment (military)Government (linguistics)Monetary economicsInternational tradeOpen-ended investment companyReturn on investmentMacroeconomicsProduction (economics)PoliticsPolitical science

Abstract

fetched live from OpenAlex

Foreign direct investment is identified as the major tool for the movement of international capital. Thus, the study has employed a review research to examine the determinants of foreign direct investment in Saudi Arabia. The results are significant as they have contributed towards determinants of foreign direct investment by comparing with previous studies. The results showed that trade openness, infrastructure availability, and market size play significant role in attracting foreign direct investment within a country. The inflow of foreign direct investment has a potential to benefit the investing entity as well as the host government. It also renders economic growth and socioeconomic transformation of the country. The flow of foreign direct investment in Saudi Arabia is affected by several factors including growth rate, GDP, exports and imports. It is the duty of the government to ensure the attractiveness of their country to maintain maximum flow of foreign direct investment, as it promotes sustained long-term economic growth by increased investment in the human capital.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.065
GPT teacher head0.309
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2017
Admission routes1
Has abstractyes

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