CSR, monitoring cost and firm performance during COVID-19: balancing organizational legitimacy and agency cost
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose COVID-19 induced uncertainty in the firms’ business transactions, financial markets and product-market competition, causing a severe organizational legitimacy crisis. Using the organizational legitimacy perspective and agency theory, this paper aims to study the relationship between prior corporate social responsibility (CSR) activities, monitoring cost (MC) and firm performance. Design/methodology/approach This study uses a quarterly panel (16,924 firm-quarter observations from 61 countries for CSR and 53,345 firm-quarter observations from 55 countries for MC) for 14 quarters from January 2018 to June 2021. This study uses panel fixed-effect regression models to estimate the effect of CSR activities and MC (measured as audit fees) on firm performance during the COVID-19 period. Findings This study finds a U-shaped relationship between CSR and firm performance. This relationship is strengthened during COVID-19. In contrast, this study finds an inverted U-shaped relationship between firm MC and firm performance. However, this relationship is weakened during the pandemic. Originality/value This study contributes to theory and practice on maintaining organizational legitimacy and reducing agency costs during the pandemic. This study shows that firms’ prior legitimacy-gaining practices, such as CSR activities and MC, provide an opportunity to increase firm value. To balance agency costs and legitimacy benefits, firm managers also need to identify the optimal level of CSR activities and MC.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it