Dynamic capabilities of institutional entrepreneurship
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
Purpose Although the concept of institutional entrepreneurship has been developed in the institutional theory literature to explain change in the normative context of organizations, little attention has been given to understanding what institutional entrepreneurs actually do to create change. The purpose of this paper is to begin to address this gap in the literature by drawing on the process, challenges, successes and lessons learned when a large multilateral organization (the United Nations Development Program) launched a new international multi-stakeholder initiative to facilitate inclusive business development. Design/methodology/approach This case study gathered qualitative data through key informant interviews, participant observation and a review of project documents and e-mail correspondence. Findings Drawing on institutional theory and the literature on dynamic capabilities, the research found that highly institutionalized organizations acting as institutional entrepreneurs need to manage two key tensions – legitimacy management and change process management – in order to influence change in their institutional fields. Originality/value This paper is the first to combine institutional theory and the dynamic capabilities literatures to understand the question What capabilities are required by organizations to succeed in changing their institutional fields?
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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