Strategic Decision-Making and Performance in Social Enterprises: Process Dimensions and the Influence of Entrepreneurs’ Proactive Personality
Bibliographic record
Abstract
Abstract Different organizational perspectives surrounding social enterprises (SEs) have burgeoned over the past few years. However, integrating financial sustainability with social value remains a “black box” with respect to entrepreneurial strategic decision-making (SDM). Drawing from decision theories and the proactivity perspective of personality-based SDM literature, we investigate the impact of synoptic (rationalistic) and incremental (adaptive) process models, and moderate these approaches with the entrepreneur’s proactive personality traits on SEs’ financial and social performance. Our results show that when a rational and intuitive SDM develops in conjunction, financial performance improves. In contrast, a departure from rationality in favor of incremental decision-making processes advances only the social performance of SEs. A proactive entrepreneurial personality positively moderates strategic cognitions in improving SEs’ both financial and social objectives. On the other hand, when proactivity moderates rationality, the financial performance of SEs declines.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".