Does Sustainable Finance Work on Banking Sector in ASEAN?: The Effect of Sustainable Finance and Capital on Firm Value with Institutional Ownership as a Moderating Variable
Bibliographic record
Abstract
Management in the banking industry is not solely focused on financial performance but also on the sustainability of their portfolios. To achieve this, banks need to incorporate sustainable finance into their balance sheet. In addition, a global phenomenon has emerged where investors have demanded the inclusion of sustainable finance in portfolios. This financial instrument served to support the global agreement on climate change, which they were committed to making a reality. The impact of sustainable finance on firm value remains a question. Therefore, this study aimed to examine the effect of sustainable finance and capital on firm value within the banking industry, focusing on entities listed on the ASEAN stock market from 2015 to 2021. To assess investor demand for involvement in sustainable finance, a moderating variable was included in the model. Furthermore, this study used a quantitative design and a purposive sampling technique with panel data regression analysis for the hypothesis testing. The results showed that sustainable finance and capital had a significant effect on firm value. Institutional ownership moderated the relationship between sustainable finance and firm value, although it did not moderate the link between capital and firm value. This indicated that banks prioritized sustainable finance due to its positive impact on their operations, ultimately leading to an improvement in firm value. Furthermore, institutional ownership influenced the relationship between sustainable finance and firm value, as banks strived to comply with international society or enhance firm value. This study incorporated profitability ratios and firm size as the control variables.
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.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".