Leadership in a time of financial crisis: what do we want from our leaders?
Bibliographic record
Abstract
Purpose – The purpose of this paper is to gain a nuanced understanding of what employees want from leaders in an organizational crisis context. Design/methodology/approach – The authors use a mixed methods approach to explore employee leadership preferences during organizational crisis and non-crisis times using the Multi Factor Leadership Questionnaire (Avolio and Bass, 2004), and qualitative interviews. The authors also investigate sex roles using the Bem Sex Role Inventory (Bem, 1981). Findings – The mixed method approach reveals some potential limitations in how leadership is typically measured. The qualitative findings highlight employees’ expectations of leaders to take action quickly while simultaneously engaging in continuous communication with employees during crisis. None of the components of transformational leadership encapsulate this notion. Originality/value – The mixed methods approach is novel in the crisis leadership literature. Had the authors relied solely on the quantitative measures, the importance of continuous communication during crisis would not have been apparent. As a result of this approach, the findings suggest that widely used and accepted measures of leadership may not adequately capture leadership in a crisis context. This is timely as it aligns with current literature which questions the way this construct is operationalized (Van Knippenberg and Sitkin, 2013).
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.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".