Doing Good in Another Neighborhood: Attributions of CSR Motives Depend on Corporate Nationality and Cultural Orientation
Bibliographic record
Abstract
In the past few decades, consumers around the world have placed increasing value on corporate social responsibility (CSR). As a response, companies entering new markets have boosted spending in areas like cause-related marketing to improve their reputation and create goodwill among consumers in the host country. However, these efforts may not be effective for all consumers or in all countries. Drawing upon research on intergroup bias and attribution theory, the present work explores how consumers from individualistic (the United States and Canada) and collectivistic (South Korea and India) cultures form attributions and attitudes about the CSR activities of foreign and domestic firms. Across three studies, we find that collectivistic (but not individualistic) consumers make more altruistic (but not egoistic) attributions about the CSR motives of domestic (vs. foreign) companies, and that altruistic attribution leads to more positive attitudes toward the firm. We also showed that collectivists’ bias against foreign firms is attenuated when level of commitment to the cause (as conveyed by CSR duration) is high.
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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 | 0.008 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".