Board reform versus profits: The impact of ratings on the adoption of governance practices
Bibliographic record
Abstract
Research summary: External stakeholders frequently attempt to influence organizations' adoption of new practices through the creation of public ratings. Based on the insights of performance feedback theory, we develop the theory of organizational reactions to external ratings to explain how firms' behaviors depend on their rating scores and their profitability. A central issue in our theory is the conflict between established internal goals and goals introduced by public ratings, with public ratings receiving lower priority than established profitability goals. Our theory suggests that, contrary to the expectations of the external stakeholders, firms targeted for criticism by ratings become less likely to adopt corresponding practices when their profitability is below aspirations. These arguments are supported in data on the diffusion of corporate governance practices in C anada. Managerial summary: Firms and their products are rated and ranked by external agencies ranging from C onsumer R eports to magazine rankings of admired, environmental, or well‐governed companies. We investigate whether such ratings affect firm behaviors, and especially whether they can incentivize poorly rated firms to improve their ranking when these firms' profitability is also low. Using the leading corporate governance ranking in C anada, we find that rankings could have adverse effects: when firms have both poor governance ranking and poor profitability they are less likely to adopt governance practices, contrary to the ranking creators' intentions. The findings show that there is a hierarchy of firms' goals, where the goal of profitability comes ahead of other goals imposed by external agencies through ratings and rankings . Copyright © 2016 John Wiley & Sons, Ltd.
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 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 | 0.003 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".