Challenges and Trends in Sustainable Corporate Finance: A Bibliometric Systematic Review
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
Sustainable corporate finance is an attractive field of study in sustainability literature; however, the literature lacks systematic bibliometric analysis that provides a comprehensive review to clarify state-of-the-art sustainable corporate finance and that discusses new opportunities and potential instructions for further studies. To address this gap, this study adopts a literature review, bibliometric analysis, network analysis and co-wording technique to systematically investigate the Scopus database. In total, 30 keywords listed at least three times are used and are divided into six clusters considering six fields of research, namely, corporate finance in corporate sustainability, sustainable competitive advantages, sustainable stakeholder engagement, circular economy, sustainable corporate finance innovation and risk management and sustainable supply chain ethics. This study contributes to examining the sustainable corporate finance bibliometric status to provide directions for future studies and practical accomplishment. The sustainable corporate finance knowledge gaps are (1) corporate finance in sustainability; (2) sustainable competitive advantages; (3) sustainable stakeholder engagement; (4) circular economy; (5) sustainable corporate finance innovation and risk management; and (6) sustainable supply chain ethics. The knowledge gaps and future directions are also discussed.
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.
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it