Navigating Unprecedented Times: How Managers’ Empathetic Adjustments in a Crisis Influence Employee Effort in a Competitive Environment
Bibliographic record
Abstract
ABSTRACT When organizational crises arise, one way that managers can help employees cope is to provide empathetic adjustments, where managers adjust downward performance expectations for all employees while communicating the adjustment with empathy. In a competitive environment, we explore whether providing an empathetic adjustment to employees during a crisis affects their postcrisis effort. We conduct an experiment and observe that an empathetic adjustment significantly improves the postcrisis effort of top and bottom performers. The increase in postcrisis effort of top performers can be attributed to the effect of the adjustment, whereas the increase in postcrisis effort of bottom performers can be attributed to the effect of empathy. In a supplemental survey, we find a range of positive effects of empathetic adjustment, including increased engagement, reduced burnout, and lower turnover intentions. Data Availability: Data are available from the authors upon request. JEL Classifications: G31; G32; G33; M21.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".