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Record W2102724805

Theorizing Japanese FDI to China

2006· article· en· W2102724805 on OpenAlexvenueno aff
Khondaker Mizanur Rahman

Bibliographic record

VenueJournal of Comparative International Management · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentMultinational corporationChinaCompetitor analysisIncentiveInvestment (military)International tradeInternational economicsPosition (finance)EconomicsRobustness (evolution)Market economyBusinessPolitical scienceMacroeconomicsManagementLawPoliticsFinance
DOInot available

Abstract

fetched live from OpenAlex

Using mainly archival data, this paper examines the nature and causes of Japanese foreign direct investment (FDI) to China and theorizes it with inductive arguments. It proceeds as follows. After a brief introduction on China’s robustness in the global investment market, it introduces the position of Japan as investor in this country, and proceeds with an examination of the major theories of FDI. It then examines the underlying causes of Japanese FDI to China in view of those theories. The paper concludes that, in addition to many investment-alluring incentives, most prominently China over time has infused, fostered, created, and nurtured numerous competitive advantages (pull-factors) within its investment proliferating environment, which ultimately ushered FDI from Japan to it. Domestic factors as well as global investment competitors drive (push-factors) toward China further induced Japanese multinational corporations (MNCs) to boost investment into China.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.005
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.269
Teacher spread0.253 · 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 designTheoretical or conceptual
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

Citations0
Published2006
Admission routes1
Has abstractyes

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