Determining The Optimal Mix of Institutional Geopolitical Power And ASEAN Corporate Governance on the Firm Value of Malaysia’s Multinational Corporations (MNCs)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this paper is to examine the relationship between institutional geopolitics, ASEAN corporate governance quality and the firm value of Malaysia’s multinational corporation (MNC). We used the data of MNCs in Malaysia that were active from 2009 to 2013 as an evidence of MNCs from emerging market economies. Descriptive analysis, factor analysis and panel data analysis have been utilized to test the equation model. We also propose optimization analysis by using differential evolution method to capture the optimal mix of institutional geopolitics and ASEAN_CG on the firm value of MNC. Results reveal that the geopolitics of G7(Canada, France, German, Italy, Japan, Europe, and the United States), BRICS (Brazil, Russia, India, China, and South Africa), and ASEAN (Brunei Darussalam, Cambodia, Indonesia, Lao PDR, Myanmar, Philippines, Singapore, Thailand, Vietnam, and Malaysia) are highly correlated with the firm value of Malaysia’s MNC. The power of institutional geopolitics, namely, military, material, and social power, influences firm value negatively and ASEAN_CG moderate the negative influence of institutional geopolitics on the firm value of MNC. Thus, it is importance for corporate management to understand the geopolitical changes of host countries’ and increase the compliance of ASEAN_CG in formulating their market value and segmentation strategies.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it