Understanding sustainable outcomes in the digital age: The vital role of digital leadership in leveraging the impact of green innovation
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
The increasing complexities posed by green organizational challenges and technological advancements require a thorough grasp of the vital capabilities needed to maintain the firm’s sustainable performance. This study aims to explore the associations of green technological innovation and management innovation to sustainable performance and estimate to what extent digital leadership moderates these associations. The resource-based view (RBV) and socio-technical system theory (STS) are leveraged to conceptualize the research model. By adopting a survey-based approach on data gathered from 419 manufacturing and service firms, the PLS-SEM is the statistical approach conducted to test the validity of predictions The outcomes demonstrated that green technological innovation, green management innovation, and digital leadership are positively linked to sustainable performance. Furthermore, higher digital leadership strengthens the linkage of green technology and management innovation to sustainable performance. The outcomes made a powerful contribution to the current literature on green innovations and digital transformation, and substantial recommendations were inferred for organizations aiming to achieve environmental, social, and economic performance.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| 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