Deciding to Adopt Telework: The Role of Experience, Trust, and Control Across Three Countries
Bibliographic record
Abstract
Since the outbreak of the COVID-19 pandemic, teleworking has experienced a significant resurgence and has become the focus of extensive research. While various aspects of telework have been explored, the influence of cultural elements—particularly control and trust—as well as prior experience, has received less attention. To address this gap, this study aims to comparatively examine how these factors influence managers ’ decisions to implement telework. To this end, data were collected from executives in three countries—France, Switzerland, and Canada—using an online survey. The comparative analysis focused on 359 questionnaires collected from the three countries. The results show that all three countries demonstrate favorable conditions for teleworking, based on cultural elements and prior experiences. However, Canada exhibits a stronger adaptation to teleworking compared to the other two countries. Furthermore, the role of control was more pronounced in France compared to the other two countries, whereas in Canada, a lower level of control is exercised. Additionally, trust plays a key role in explaining the stronger adaptation to teleworking.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".