MétaCan
Menu
Back to cohort
Record W3142174483 · doi:10.5539/ibr.v14n4p126

A Literature Review on the Location Determinants of FDI

2021· review· en· W3142174483 on OpenAlexvenueno aff
Feng Yang, Yan Wang

Bibliographic record

VenueInternational Business Research · 2021
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentMultinational corporationBusinessDeveloping countryEconomies of agglomerationInvestment (military)PreferenceEmpirical researchDistribution (mathematics)Market sizeEconomic geographyEconomicsInternational economicsInternational tradeEconomic growth

Abstract

fetched live from OpenAlex

Foreign direct investment (FDI) is an important force to promote economic growth and social development in both developed and developing countries, while the distribution of FDI in the world and within countries is extremely uneven. This paper systematically summarizes the main determinants that affect the location choice of FDI in recent theoretical and empirical studies, including institution and investment environment, trade cost and industrial agglomeration, market size and natural resource, cultural distance and social network. Based on the work of this paper, it is helpful to better understand the location preference of multinational enterprises (MNEs) in FDI activities, and provide a reference basis for the host country to attract investment and promote economic growth.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.013
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.144
GPT teacher head0.426
Teacher spread0.282 · 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 designSystematic review
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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business ResearchSame topicInternational Business and FDIFrench-language works237,207