Serving differently: CEO regulatory focus and firm stakeholder strategy
Bibliographic record
Abstract
Abstract Research summary A fundamental question in stakeholder strategy research is why firms adopt certain strategies or approaches to engage with key stakeholders. Recent research suggests that CEOs' characteristics can influence their general decisions to engage with stakeholders, however, this work has yet to consider why CEOs might utilize specific stakeholder strategies. In this article, we demonstrate how CEO regulatory focus influences the nature of a firm's stakeholder strategy. Specifically, we argue that CEO prevention focus is positively associated with engagement in governance‐oriented initiatives and receptivity to governance‐oriented stakeholder activism, while CEO promotion focus is positively associated with engagement in socially‐oriented initiatives and receptivity to socially‐oriented stakeholder activism. We find strong support for our hypotheses in a sample of 374 publicly‐traded firms. Managerial summary The strategies a firm uses to engage with stakeholders can influence its performance, yet little is known about what makes firms focus on certain stakeholders over others. To better understand this, we examined CEO regulatory focus in a sample of large public companies. Our findings reveal that the way CEOs view decisions—either based on a sense of duty, obligations, and responsibility or as a means to achieve high ideals—influences their tendency to prioritize shareholder concerns or the concerns of a broader array of stakeholders. This suggests that executives should be aware of their own natural tendencies to inject their motivations into their firm's stakeholder strategy and consider avenues to balance their perspectives for the sake of the firm.
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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 | 0.009 | 0.032 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".