The Effect of Green Concepts on Firm Performance Mediated by Sustainable Development
Bibliographic record
Abstract
The industry is currently showing a business paradigm shift towards sustainability in order to increase excellence and achieve long-term performance, one of which is through the implementation of green concepts.This study aims to examine the effect of green concepts, which consist of green accounting and green innovation on firm performance with sustainable development as mediating variables.The research focuses on manufacturing companies listed on the Indonesia Stock Exchange.Secondary data were analyzed using path analysis and bootstrapping techniques.The findings revealed a significant effect of green concepts on sustainable development.Sustainable development is proven to have a significant impact on improving firm performance, highlighting its pivotal role in linking green concepts to firm performance.However, green concepts have no direct significant effect on firm performance.The empirical examination of mediation effects demonstrates that the implementation of green concepts exhibits a significant indirect influence on firm performance through the mediation of sustainable development.The results of this study reinforce the role of sustainability-based strategies in bridging environmental and economic goals, particularly in the context of emerging economies.The findings underscore the importance of sustainability-oriented innovations and accounting practices for achieving long-term corporate success.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".