Corporate Social Actions and Reputation: \nFrom Doing Good to Looking Good
Bibliographic record
Abstract
While corporate social responsibility (CSR) has garnered the attention of scholars over the past three decades, most attention has been focused on a link to financial performance. Grounded in stakeholder theory and a resource-based view of the firm considering the cospecialized intangible assets of CSR and reputation, this research explores the evolution of corporate social actions and firm reputation over time. We draw on data from the KLD database on corporate social actions and concerns, and on the Fortune most-admired company database to examine the relationship between corporate social behaviour and reputation over time. \n\tIn the thesis, we argue that starting with the broad premise that any corporate social action or gesture can initially enhance corporate reputation, the firm is then both encouraged and also expected to go further. Accordingly, we propose subsequent actions are needed to meet stakeholder expectations to be able to improve or at least sustain firm reputation. We find that over the timeframe of our study that corporate social actions do experience the predicted positive linear growth. \n\tDrawing on a sample of 285 major US firms and a 2002-2006 time frame to provide a 1425 firm year panel, we find corporate social actions to be strongly related to corporate reputation, while the change in corporate social actions also predicts a change in corporate reputation. We also found support for the hypothesis that corporate social actions directed to technical stakeholders have the most significant impact on firm reputation. We do not however find the expected influence of concerns over corporate social actions directed to institutional stakeholders on firm reputation, leading to the intriguing question: why not? \n\tWe provide detailed illustrations with five of the sampled firms and interpret their CSR-reputation relationships. These findings expand our understanding of the effect of the change over time in corporate social actions and the ensuing effect on corporate reputation. We extend the applicability of our findings to management, discuss limitations and propose future research directions.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".