Bibliographic record
Abstract
In assessing a strategic corporate social responsibility (CSR) initiative, I ask the question, does it provide the firm with a first-mover advantage (FMA)? Using the resource-based view, I construct a framework for predicting a FMA based on the CSR initiative possessing three strategic attributes: centrality, specificity and visibility. While marketers have long debated the first-mover advantage (FMA) in garnering market share, the translation into competitive advantage and superior profit performance has fuelled the debate in strategic management. As Lieberman and Montgomery argue the independent evolution of FMA and resource-based view when "taken separately, each suffers from serious deficiencies. We see a strong potential for synergy " (1998: 1112). While some might accept short-term costs as inevitable in meeting the firm's responsibility to society, corporate social responsibility (CSR) advocates assert it is possible for firm strategies to be aligned with societal objectives to generate benefits for the firm (Burke & Logsdon, 1996; Epstein & Roy, 2003; Griffin & Mahon, 1997; Waddock & Graves, 1997). This then brings us to the research questions this paper answers. Is there a strategic advantage to be a first-mover in
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.531 | 0.248 |
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".