<scp>CSR</scp> decoupling within business groups and the risk of perceived greenwashing
Bibliographic record
Abstract
Abstract Research Summary Given the growing legitimacy of corporate social responsibility (CSR), many firms engage in symbolic communication to showcase CSR without undertaking commensurate substantive actions. This “CSR decoupling” can create a risk of perceived greenwashing, which, in turn, may negatively affect a firm's performance. In this study, we explore an unexamined antecedent of decoupling: interfirm affiliation. Specifically, we use the structure of Business Groups (BGs) to investigate CSR decoupling across rather than within firms. We find that apex firms within a group are more likely to engage in CSR decoupling compared with non‐apex firms and, importantly, are partially shielded from greenwashing perceptions by the market. Our research contributes to the literatures on decoupling, perceived greenwashing, and the role of BGs and their CSR practices. Managerial Summary Companies that engage in symbolic communication about corporate social responsibility (CSR) without substantive actions risk being perceived as “greenwashers,” a perception that harms firm performance. Our study demonstrates how, in certain contexts where firms are affiliated with others, this may not occur. For instance, apex firms within Business Groups (BGs)—where firms are interconnected through equity and social relationships—can report on the CSR actions of non‐apex affiliates without providing commensurate substantive actions of their own. Importantly, the control and coordination abilities of these apex firms protect them from greenwashing perceptions. This study, therefore, demonstrates the role of BGs in shaping CSR practices and provides insights for managers to understand the potential risks and benefits of affiliations within BGs.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".