Corporate culture, ethical stimulus, and managerial momentum: Theory and evidence
Bibliographic record
Abstract
Abstract Research on organizational culture and ethical decision making has shown that ethical trainings predict and interact with other institutional variables to establish an ethical culture, while other studies suggest that the exposition of moral symbols leads to an increase of individuals' moral awareness. This study examines whether the relation between managerial momentum and fund performance is contingent upon ethical stimuli, team composition and interactions between them. It thus bestows insights to better inform institutional investors (including those working with mutual funds, pension funds, and insurance) about the nature and impact of ethical stimuli, when coupled with managers' momentum and team size, on the prediction of overall return of managed funds. I develop a new measure of managers' momentum termed “managerial momentum” and test our proposed theory and hypotheses using large samples of U.S. and Canadian mutual funds. The evidence reveals that there is sizeable positive effect of both corporate culture with its ethical dimensions and ethical stimulus on the fund performance. Furthermore, there is subtle evidence that both factors divulge additional information about the fund performance, but their effects are conditional on higher managerial momentum or team size, suggesting that managerial momentum alone is not sufficient. However, it is necessary to have the institutional ethical climate and/or managers' continuous ethical training to achieve viable and resilient investment opportunities tailored to the needs of different clienteles.
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 | 0.013 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".