Exploring the Untapped Influence of Stakeholders in Organizational Rivalry
Bibliographic record
Abstract
Extant literature posits that past competitive interactions between rival firms serve as antecedent to psychological animosity as well as mutual forbearance, but since these outcomes are antithetical, it remains a puzzle how firms decide to aggressively respond or strategically forbear a rival’s attack. Despite the evidence that stakeholders influence organizational decisions, it is surprising that competitive dynamics scholarship did not examine this puzzle using a stakeholders’ perspective. My goal in this work is to investigate how stakeholders’ evaluation of rival’s actions affect focal firm’s decision to aggressively respond or strategically forbear, for which I utilize environmental action/response dyads of Coca-Cola and Pepsico over a period of 15 years (2006-2020). Findings suggest that some rival actions motivate focal firm to respond aggressively (influential actions) than others (skeptical and controversial actions), which is determined by the extent of stakeholders’ approval of those actions. This work is the first of its kind to qualitatively study rivalry in an environmental sustainability context at a dyadic level (Coca-Cola vs. Pepsico).
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".