Advancing research on project management in hybrid organizations: insights from the social enterprise literature
Bibliographic record
Abstract
Purpose This paper aims to understand the challenges of managing projects in hybrid organizations. The authors explore how organizations with persistent competing institutional logics strive to balance competing priorities, and the authors craft a research agenda to examine the capabilities to manage projects in hybrid organizations. Design/methodology/approach The authors focus on the social enterprise hybrid organizational form to study how such organizations manage persistent competing social and economic logics. The authors review the project management and social enterprise literature to generate new insights and suggest future research directions for theory development for project management. Findings The understanding of the influences of the institutional context on the management of projects is still quite limited. The authors propose that project managers need adaptive capabilities to address how the dual logics, and their corresponding different expectations, can be flexibly combined. The objective is not to reduce the complexity due to the different logics, which is the focus of much of the literature on institutional complexity. Instead, the focus is on how to incorporate dual logics into a successfully blended hybrid organization. Originality/value There is a dearth of literature about how projects are successfully managed in hybrid organizations with persistent competing institutional logics, like social enterprises, and important questions remain to be answered. This paper offers new insights on the capabilities required to flexibly combine dual logics that would generally compete and create conflict on projects in hybrid organizations.
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.
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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".