The role of foreign direct investment on increasing the amount of export
Bibliographic record
Abstract
Improving livelihood and increasing in welfare and life quality of people always have been some of the most important concerns among politicians in each country.Therefore, addressing economy and trying to reach maximum growth play essential role on having sustainable growth.One of the determinant factors in the economic growth is attraction of direct foreign investments, successfully.Direct foreign investment not only leads to capital and modern technology in absorbent country but also it causes increasing in production capacities particularly in export products.Therefore, it helps host country in context of communicating with international economy through development of export markets and research and development (R & D).In this paper, we present an empirical study to find important factors influencing foreign direct investment based on factor analysis.The study designs and distributes a questionnaire consist of 30 questions among some experts.The proposed study uses Skewness analysis to reduce the factors into 22 items and reports 5 important factors including Economic, Feasibility, Infrastructure, Incentive and Resource.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".