Foreign Direct Investment, Brand Value, and Economic Performance: A Multinational Analysis
Bibliographic record
Abstract
The visibility and dependability of multinational corporations’ products increase with the fact that they introduce their goods to markets in other nations through foreign direct investments. The method for presenting products to international markets through foreign direct investments reveals the product’s reputation and therefore the brand’s development value. This study examines the relationship between foreign direct investments and brand value in Australia, Canada, China, France, India, Japan, Spain, the USA, and the UK for the period 2007-2023. The majority of studies in the literature attempt to explain the impact of brand value on foreign direct investments. However, very few studies explain the impac foreign direct investments on brand value and 1st generation unit root tests were generally used. Unlike existing studies, In this study, the second-generation unit root test, Durbin-Hausman cointegration, and Common Correlated Effects Mean Group estimation methods were used. As a result, it is anticipated that this study will contribute to the literature in this regard. The findings show that increases in foreign direct investments boost brand value.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".