Between responsive gestures and adaptive actions: deciphering the differential impact of CSR strategies on stock market performance
Bibliographic record
Abstract
Purpose This paper offers a fresh perspective on this debate by exploring the direct relationship between a firm’s stock price performance and its CSR activities, placing particular emphasis on the underlying intent or motive behind the CSR initiatives. Design/methodology/approach This research examines the relationship between a firm’s stock price and its corporate social responsibility (CSR) activities, distinguishing between responsive and adaptive CSR. While responsive CSR, often a response to negative events, elicits immediate positive stock performance, adaptive CSR initially triggers negative stock performance. However, long-term analysis reveals adaptive CSR leads to positive stock performance, especially for family firms. The study challenges the notion of market myopia, suggesting the market values responsive CSR in the short term but recognizes the long-term benefits of adaptive CSR over time. Clear communication about adaptive CSR intentions and benefits may help in accurate market valuation. Findings This research examines the relationship between a firm’s stock price and its CSR activities, distinguishing between responsive and adaptive CSR. While responsive CSR, often a response to negative events, elicits immediate positive market reactions, adaptive CSR initially triggers negative reactions. However, long-term analysis reveals adaptive CSR leads to positive returns, especially for family firms. Practical implications The study challenges the notion of market myopia, suggesting the market values responsive CSR in the short term but recognizes the long-term benefits of adaptive CSR over time. Clear communication about adaptive CSR intentions and benefits may help in accurate market valuation. Originality/value First, it expands on previous studies by exploring how the different motivations behind CSR activities lead to varying effects on stock returns. Second, it sheds new light on the subject of market myopia. The findings demonstrate that adaptive CSR initiatives can initially trigger market reactions similar to those caused by perceived over-investment, in contrast to the more favorable response to responsive CSR activities.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".