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Record W1977538319 · doi:10.5430/ijba.v2n3p94

The Magnification Effects of Intra-firm Trade of Multinational Corporations

2011· article· en· W1977538319 on OpenAlexvenueno aff
Lina Lian, Haiying Ma

Bibliographic record

VenueInternational Journal of Business Administration · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsMultinational corporationSubsidiaryForeign direct investmentBusinessValue (mathematics)International tradeIncentiveEconomicsInternational economicsMarket economyFinance

Abstract

fetched live from OpenAlex

The 2008 financial crisis and the credit crunch severely restrict the ability of multinational companies to invest abroad and finance cross-boarder mergers and acquisitions; yet do not impair the intra-firm trade among parent firms, subsidiaries and branches. Intra-firm trade is a complement of foreign direct investment whether it is a market-access based FDI or for considerations of factor price differential motivations. Compared with arm’s length transactions, intra-firm trade of MNCs is highly contributable to unit the global-based affiliates under one set of rationales of operation mechanism, thus reel off the substantial benefits produced within the boundaries of the host nations. The essay starts with characteristics and incentives of intra-firm trade of MNCs, then analyzes in great details the related effects from the standpoints of international trade structure, international relations and the economy perspectives of the host countries. The author concludes that the sales of affiliates of multinational firms have long dwarfed the value of FDI injection to the host countries and the transfer price system is often illegally used for tax evasion purposes, thus shortchanging the earnings of the host nations. The author proposes corresponding countermeasures by the end.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.881
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.026
GPT teacher head0.240
Teacher spread0.214 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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