The Impact of the Crisis on Investment Behaviour in Foreign Direct Investment Enterprises in Vietnam
Bibliographic record
Abstract
During the COVID-19 pandemic, companies were directly impacted by this global crisis, and Foreign Direct Investment (FDI) enterprises, with their unique investment cash flow, were no exception.This study aims to examine how the COVID-19 crisis impacted the investment cash flow of FDI enterprises.During the COVID-19 pandemic, Foreign Direct Investment (FDI) enterprises not only faced challenges in production and operations but also grappled with issues related to cross-border travel.Research based on the theory of investment relationship and crisis has been proposed by many researchers.The research was conducted on 45 FDI enterprises that have invested in Vietnam from 2013 to 2022.The study employs the Difference-in-Generalized Method of Moments (DGMM) to address endogeneity.The results indicate that COVID-19 has reduced the investment cash flow of FDI enterprises.Based on these research findings, the authors also propose several policy measures to assist stakeholders in making appropriate decisions during similar crises such as COVID-19.The study contributes to the forecasting of investment cash flows for FDI enterprises during similar crises such as COVID-19.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".