The Mirror Effect: Corporate Social Responsibility, Corporate Social Irresponsibility and Firm Performance in Coordinated Market Economies and Liberal Market Economies
Bibliographic record
Abstract
Abstract We investigate the classic management debate of agency versus institutional pressures through the application of the varieties of capitalism literature. In particular, we examine corporate social responsibility (CSR), corporate social irresponsibility (CSiR) and their relationships with firm performance in two types of capitalist systems: coordinated market economies (CMEs) and liberal market economies (LMEs). We note that while the CSR literature has tended to develop a balanced view on the influence of agency and institutional pressures, the CSiR literature has tended to emphasize the influence of agency. The latter appears to be a result of the fundamental attribution bias, where irresponsible corporate behaviours are attributed to individual managers or organizations, rather than the institutional environment. Our results, which include five years of data across 16 countries, show significantly greater CSR and significantly lower CSiR in CMEs compared with LMEs. Further, we find a positive relationship between CSR and firm performance in CMEs but not LMEs, and a negative relationship between CSiR and firm performance in LMEs but not CMEs. Overall, our results demonstrate the influence of the institutional environment, suggesting that corporate behaviours mirror the external environment.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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".