The Importance of Corporate Social Responsibility Strategic Fit and Times of Economic Hardship
Bibliographic record
Abstract
Abstract Previous research investigating the relationship between corporate social responsibility (CSR) and corporate financial performance (CFP) reveals the importance of industry specificity. Drawing on strategic stakeholder theory, we argue that the strategic fit between CSR activities and value chain activities contributes to industry‐specific effects in the CSR–CFP relationship. Given the multidimensional nature of CSR, some CSR activities will be more impactful for certain industries than others, because industries differ in value chain activities and salient stakeholders. Specifically, we propose and test a set of hypotheses for two industries positioned on the different ends of the industry spectrum based on their ecological footprint – healthcare and resource extraction. We further examine the industry specificity of the CSR–CFP relationship by exploring external economic conditions (the 2008–2009 recession) as a boundary condition. Our study contributes to the extant literature by demonstrating the role of strategic fit between CSR and value chain activities in explaining the influence of CSR on CFP. Additional testing of this mechanism in times of economic hardship adds a unique aspect to our theoretical and empirical contributions.
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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 | 0.015 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".