Organizational Learning for Environmental Sustainability: Internalizing Lifecycle Management
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
Implementing a substantial environmental strategy that addresses all phases of the product lifecycle is a complex and demanding challenge that most organizations fail to convincingly overcome. Based on a case study of five frontrunner companies located in Italy and Norway, this study explores the factors that promote, or hinder, the learning process underlying the implementation of substantial measures for lifecycle management and how this can contribute to further internalizing environmental sustainability throughout the organization. The article contributes to the literature on organizational learning and environmental sustainability by showing, from a dynamic perspective, the enablers of organizational learning required for internalizing lifecycle management in organizations. A new framework for environmental sustainability based on the 4Is (intuiting, interpreting, integrating, and institutionalizing) organizational learning model is put forward in line with the concept of lifecycle management. Managerial implications 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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it