Board member monitoring behaviors in credit unions: The role of conscientiousness and identification with shareholders
Bibliographic record
Abstract
Abstract Research Question/Issue This research investigates the antecedents of board members’ monitoring behaviors at the individual level. The main idea is that individuals who are both conscientious and identified with shareholders are those most likely to adopt monitoring behaviors. Research Findings/Insights The study was conducted using a survey of 166 board members of a large Canadian credit union corporation. Data on monitoring behaviors were collected directly from the chairpersons of the boards they participate in. The results validate the hypothesized moderated mediation model in which perceived importance of monitoring by board members mediates the relationship between conscientiousness and actual monitoring behaviors, on the one hand, and identification with shareholders moderates the relationship between conscientiousness and the perception of the importance of monitoring, on the other hand. Theoretical/Academic Implications By investigating the mediating effect of the perceived importance of the monitoring role in the relationship between conscientiousness and monitoring behaviors, our study provides an empirical test of the attention‐based view in the context of boards of directors and thus contributes to opening the ‘black box’ of board behaviors. Further, by looking at the interactive effect of conscientiousness and identification with shareholders, our study brings new insights into the motivational drivers of directors’ monitoring behaviors. Practitioner/Policy Implications This study invites practitioners in charge of board members’ recruitment and selection to reconsider their practices in order to target individuals demonstrating high levels of conscientiousness. It also highlights the importance of implementing board cultures that value conscientiousness and emphasize shareholders’ interests.
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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 | 0.004 | 0.027 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".