New Index ESG Leaders & Investment Decisions in Indonesia Relating to ESG Principles
Bibliographic record
Abstract
We investigated investors awareness of their investment decisions on the new index called ESG Leaders in the Indonesian stock exchange. We used structural equation model (SEM) to analyze the data from a survey with 103 respondents. We also used qualitative method with semi-structured interviews (SSI) from 10 industry players as respondents. We used a triangulation method to better interpret the results from SEM and SSI. We found that investment decisions were related to environmental and governance issues. The social issues, the environmental horizon, the purpose of investment and the moderating investment horizon consisting of short-term, mid-term and long term did not relate to investment decisions. The results from SSI were rather different from the survey. The investment decisions were related to environment, governance, and social issues as well, while the investment horizon was for the long term. The purpose of investment was to have a return that was higher than the market. The findings provide valuable insight for the ESG index issuer to create more awareness to attract more investors. This research was the first to explore the determinants of investment decisions on ESG Index equities. This research presents empirical evidence from retail and institution investors that they have faith in investing in the ESG Index and they are waiting for more active socialization from regulators.
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How this classification was reachedexpand
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".