Ideology and the Micro-foundations of CSR: Why Executives Believe in the Business Case for CSR and how this Affects their CSR Engagements
Bibliographic record
Abstract
Existing research on executives’ belief in the business case for corporate social responsibility (CSR) is built on two premises. The first is that, in order to believe in the business case, executives need factual evidence that this business case indeed exists. The second premise is that those executives who do believe in the business case will readily invest in CSR-related activities. The results from our four studies tell a different story. We show that managers, rather than focusing on factual evidence, believe in the business case because they espouse a fair market ideology—the tendency to justify and idealize the market economy system. At the same time, even though managers espousing a fair market ideology believe in the business case for CSR, they are not more inclined to engage in CSR than managers who do not hold such an ideology, because they also experience weaker moral emotions when confronted with ethical problems. By drawing on system justification theory, we simultaneously explore antecedents and consequences of executives’ belief in the business case for CSR and of their moral emotions. In doing so, we help advance knowledge about the micro-foundations of CSR.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".