Continuous improvement strategies towards energy transition: The importance of individual employees' entrepreneurial orientation and learning processes
Bibliographic record
Abstract
Abstract At one hand, while research on entrepreneurial orientation (EO) continues to proliferate, only recently has attention been drawn to the individual entrepreneurial orientation (IEO) level. On the other hand, although organizational learning (OL) explains how organizations explore and exploit knowledge to enhance their innovation and performance, limited research has investigated the relationship between EO and OL. In this study, we develop and empirically test in an established Canadian energy provider a framework on the IEO‐OL‐performance relationship. We find that employees' innovative orientation and risk‐taking propensity are more positively related to exploratory learning, while proactive employees are more geared towards exploitative learning. We further unveil that exploitative learning is more positively related to continuous improvement than explorative learning. Our findings add to scant literature on the IEO‐OL‐performance relationship and provide managerial insights for energy sector firms on how IEO can assist with their transformational business strategies towards green and clean energy supply.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".