The Contextual Impact of Nonprofit Board Composition and Structure on Organizational Performance: Agency and Resource Dependence Perspectives
Bibliographic record
Abstract
Abstract We study the relation between stability of the nonprofit organization’s environment and its board structure and the impact of this relation on organizational performance from the perspectives of both Agency Theory and Resource Dependence (Boundary Spanning) Theory. The impact of board characteristics on organizational performance is contextual. Specifically, we predict and show for a sample of U.S. nonprofits that board mechanisms related to monitoring are more likely to be effective for stable organizations, whereas board mechanisms related to boundary spanning are more effective for less stable organizations. We find that the two theories are complementary and address different aspects of nonprofit performance, but the results are statistically stronger and more often consistent with resource dependence than with agency theory. Overall, this study supports Miller-Millesen’s (Nonprofit and Voluntary Sector Quarterly, 32: 521–547 2003) contention that, because the nonprofit environment is often more complex and heterogeneous than the for-profit world, no one theory describes all tasks of nonprofit boards.
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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 | 0.003 | 0.014 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".