Green Information Technologies and Systems: Employees’ Perceptions of Organizational Practices
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
In this study, we examine the extent to which employees recognize the importance of information technologies and systems (IT/S) in developing and implementing environmental initiatives. To address this question, we first review past research on this topic and draw on a framework for examining environmental motivating forces, strategies, and employee environmental orientations. We then analyze qualitative data based on in-depth interviews with employees in financial services organizations. Our aim is to develop a richer understanding of how employees currently view IT/S issues in relation to environmental sustainability and if similarities exist between different types of financial institutions. We also assess the extent to which these employee perceptions align with both actual organizational practices, as captured in interviews with information technology managers, and practices espoused by organizations, as reflected on their corporate websites. Our findings suggest that organizations are still in the infancy stage of awareness and adoption of “Green” IT/S. As a result, we identify four types of gaps: knowledge gaps, practice gaps, opportunity gaps, and knowing—doing gaps. We suggest that future research should draw on absorptive capacity, organizational learning, and social marketing theories to help align employees’ attitudes, cognitions, and behaviors and to drive environmental changes.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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