Capabilities and Strategic Entrepreneurship in Public Organizations
Bibliographic record
Abstract
Public organizations are relatively understudied in the strategic entrepreneurship literature. In this article, we submit that public organizations are usefully analyzed as entities that create and capture value in both the private and public sectors and that a capabilities lens sheds important new insights on their behavior. As they try to create and capture value, public organizations can act entrepreneurially by creating or leveraging bundles of capabilities, which may then shape subsequent entrepreneurial action. Such processes can involve complex interactions among public and private actors. For example, public organizations often partner with private firms to produce existing products, create new products, and establish new markets which, in turn, generate new capabilities for both public and private actors. Yet such coevolutionary processes are not guaranteed to create value, and capabilities acquired in the pursuit of public interests may, over time, enable activities that damage those same interests. We show how a capabilities approach helps explain the nature and evolution of public organizations and we apply this approach to a series of cases on the growth and diversification of public organizations, the private provision of public goods, and related issues. Copyright © 2013 Strategic Management Society.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".