What motivates environmental and social sustainability in family firms? A cross‐cultural survey
Bibliographic record
Abstract
Abstract Evidence shows that positive family dynamics can motivate environmental and social strategies (ESS) in family firms. Using a stated choice method, we examine how family conflict, trust and socioemotional wealth (SEW) influence ESS choices and interact with other trade‐offs among family firms in two distinct cultural contexts: Chile and India. In Chile, we found that where there was more conflict, there were less ESS choices selected. However, in Chile, higher trust produced less relational conflict and more ESS preferences, suggesting supportive norms and group cohesion in these firms. Chilean respondents selected ESS choices more generally, which may be influenced by cultural dimensions that support sustainability, like uncertainty avoidance, indulgence and collectivism. Formal written sustainability visions in family firms created positive environmental norms in both countries and in Chile led to higher ESS preferences. Indian respondents with higher SEW were more likely to adopt ESS choices. Younger family firms in both countries were more likely to adopt ESS, suggesting generational dynamics and selectivity theory may be at play. Creating safeguards for maintaining positive emotional dynamics and tools for creating formal sustainability visions are important steps for enabling ESS among family firms.
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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 | 0.002 | 0.005 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".