Stakeholder Theory: Reviewing a Theory That Moves Us
Bibliographic record
Abstract
This article reviews the academic stakeholder theory literature as it developed between 1984 and 2007. The authors content analyzed 179 articles that directly addressed Freeman's work on stakeholder theory and found five themes: (a) stakeholder definition and salience, (b) stakeholder actions and responses, (c) firm actions and responses, (d) firm performance, and (e) theory debates. Themes were observed in multiple research fields, suggesting broad appeal. The authors noted a substantial rise in stakeholder theory's prominence since 1995 and documented that the theory has detractors insofar as it questions shareholders' wealth maximization as the most fundamental objective of business. The authors' recommendations include urging more empirical research across a broader set of organizations apart from large publicly traded corporations, more qualitative research to document cognitive aspects of how managers respond to stakeholder expectations, and a return to the theory's emphasis on the strategic benefits of stakeholder management, albeit with a broader view of firm performance.
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 | 0.018 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.010 | 0.022 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".