Emotion in strategic management: A review and future research agenda
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
Emotion in strategic management has attracted increasing scholarly interest during the past twenty-five years. Researchers have demonstrated the nature and significance of emotion in strategic management from a broad range of perspectives across different levels of analysis. Given the expanding research on the topic, the time is ripe to synthesize this diverse and multifaceted body of knowledge. In a thematic synthesis of the literature, we address the following questions: how does emotion influence strategic management, and how can the field be further developed? We review emotion constructs used in the extant literature and identify three themes related to how emotions influence strategic management: the nonconscious influence of emotions, emotion regulation, and collective emotions. Based on these themes and our analysis, we propose three areas of future research to inspire the field to develop further: (1) scope conditions of emotion research in strategic management; (2) capturing emotion in strategic management; and (3) the ethics, power and politics of emotions in strategic management.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it