Thriving on adversity: entrepreneurial thinking in times of crisis
Bibliographic record
Abstract
Purpose The paper provides evidence-based managerial advice for preparing the organizations to find successful pathways through crises by priming the managerial decision-making towards either entrepreneurial thinking or resource conservation, and hence cascading the inventive or rigid state of mind through all management levels. Design/methodology/approach The general review is based on summarizing the peer-reviewed academic studies of organizational decision-making and acting in crisis situations, illustrated using the turnaround cases of Corticeira Amorim (reinventing itself when faced with emerging technological threats) and Kiddiegarten School (adjusting to the pandemic shock of social/human nature) Findings This study reveals that a set of dimensions in the crisis situation’s cognitive framing determines the firm’s response to adversity, freezing it in a rigid state or unfreezing it to stimulate an organization-wide entrepreneurial search for turnaround strategies. If managers sense having a lack of time to deal with adversity, or a lack of predictability, they become paralyzed with threat-rigidity mechanisms, stubbornly pursuing the established methods of doing business, which often were the cause of crisis in the first place. Hence, in situations requiring an immediate response, the dual threats of urgency and unpredictability become cognitive blinders, preventing organizations from pursuing new opportunities, exposing firms to the risk of being too slow, eroding their competitive advantage and, ultimately, going out of business. Originality/value Integrating the insights of three decades prior research of the topic of managerial decision making in crisis situations, this study proposes the novel leadership framework allowing to stimulate entrepreneurial behavior in adverse contexts.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".