National Differences in Stakeholder Pressure to Adopt Codes of Ethics: A Four-Country Study
Bibliographic record
Abstract
Academic research related to the perceived value of ethics codes in different national contexts has been limited despite burgeoning interest by managers, government officials and members of international nonprofit organizations. The purpose of this study is to assess the relationship between promoting a positive external firm image and stakeholder pressure to adopt codes of ethics. Moreover, we assess the extent to which market and non-market stakeholder pressure varies across national borders. A survey instrument developed in the United States is adapted to a cross-national setting and hypotheses related to codes of ethics are tested. Empirical results based on 540 respondents from four nations, Peru, China, the United States and Canada, support that national differences exist with respect to perceptions of ethics codes. A significant relationship between creating an external image and perceived pressure from stakeholders is also identified. Study limitations, managerial implications, and promising future research directions are also discussed.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".