FDI Regimes, Investment Screening Process, and Institutional Frameworks: China versus Others in Global Business
Bibliographic record
Abstract
The main purpose of this paper is to investigate and analyse foreign direct investment (FDI) regimes and their screening processes, institutional frameworks, and business environments in world trade. China's FDI regime is specifically compared with that of the United States, Australia, Canada, and the United Kingdom. Other countries (France, Germany, Japan, Hong Kong, and Switzerland) were also included in the discussion to evaluate their regulatory and investment issues. By using interdisciplinary literature, secondary data, and research surveys and reports from multilateral institutions, the study investigates the changing profile of FDI regimes in world trade. The paper reveals that China's FDI regime has embraced significant changes to attract foreign investment. Currently, the Chinese market is open yet restricted in its own regulatory environment and institutional hurdles. Investment regimes in the United States, Australia, Canada, and the United Kingdom continue to change to attract foreign investment that is critical to their economies. We believe that more country- and industry-specific studies are needed to investigate FDI regimes and their institutional frameworks. In today's world trade, China is particularly an interesting case study since the country aggressively attracts foreign investment while keeping its hybrid economy. Policymakers, multinational corporations (MNCs), governments, and researchers need to pay attention to today's changing FDI regimes because of growth opportunities and MNC expansion. The study provides useful discussion and meaningful implications that can be used by policy analysts and practitioners worldwide.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".