Bibliographic record
Abstract
In this paper, we propose a theoretical model for testing paradox theory. We propose two paradoxical tensions—cognitive ambivalence and emotional ambivalence and develop hypotheses regarding their relationships with their antecedents and consequences. The antecedents include identity, business model, tight-loose coupling, and environmental characteristics such as munificence and dynamism. We propose that multiple identities, dual business models, tight coupling, environmental scarcity, and environmental dynamism may lead to higher levels of paradoxical tensions, which in turn, are likely to result in negative consequences in terms of performance at various organizational levels. However, employees and managers can use their paradoxical mindsets and paradoxical leadership, respectively, to intervene and moderate the negative effect of paradoxical tensions. Further, these moderation effects may be mediated by other factors such as strategic agility and ambidexterity to improve performance at various levels. We suggest methods to test the model and discuss implications for future research in paradox theory. Our paper responds to a call to innovate and strengthens a recent theory by drawing on ideas across disciplines and fields in an effort to solve modern challenges. Hence, this paper is relevant for the 2024 Annual Meetings of the Academy of Management theme: Innovating for the future.
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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 | 0.014 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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".