Intended Use of IPO Proceeds and Survival of Listed Companies in Malaysia
Bibliographic record
Abstract
In the context of Malaysian companies’ survival, the potential role of intended use of proceeds as an influential factor remains unfamiliar. This study examines the link between the intended use of IPO proceeds and the survival of 423 Malaysian listed companies over the period of 2000–2014. This study distinguishes the use of IPO proceeds into three segregations: growth opportunities, debt repayment, and working capital. Employing the Accelerated Failure Time (AFT) survival model, the overall evidence shows a statistically significant effect of the intended use of IPO proceeds for growth opportunities and debt repayment on companies’ post-IPO survival. Furthermore, company survival was found to be consistently improved when they allocated less than 50% of their IPO proceeds, regardless of the purposes (growth, repay debt or general). These results highlight the importance of the intended use of IPO proceeds on the survival of newly listed companies, and provide insights for policymakers on the management of IPO proceeds for long-term survival.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".