Red, blue, and green? The association between CEOs' political ideologies and green new product introductions
Bibliographic record
Abstract
Abstract Not all firms exhibit the same level of commitment to green new product introductions (GNPIs), yet our understanding of the factors underlying these disparities remains incomplete. Prior research has primarily focused on firm‐level factors, paying little attention to individual‐level antecedents of GNPIs. This imbalance in the GNPI literature contrasts with the broader innovation and general management literature, which displays an ever‐growing interest in the “human side of innovation,” acknowledging the relevance of Chief Executive Officers' (CEOs') political ideologies for organizational outcomes. Addressing this imbalance, our study examines the relationship between CEOs' political ideologies and their firms' GNPIs, along with the conditions that shape this influence. Grounded in social identity theory, our study first argues that the more liberal CEOs are, the more GNPIs their firms are likely to generate and that this association is amplified by CEO power. It then proposes that the more liberal CEOs are, the more likely they are to respond to adverse situations beyond their control (a Republican presidency or lower levels of consumer green sentiment) by initiating more GNPIs. It finally posits that the more liberal CEOs are, the fewer GNPIs they tend to initiate in response to adverse situations for which they are accountable (involvement in sustainability‐related scandals). We integrate data from seven databases into a longitudinal dataset comprising 89 firms and 192 CEOs over the period 2010–2020 to test our theoretical framework empirically. Time‐lagged panel regression analyses strongly support our theoretical arguments. Our findings contribute to the emergence of an individual‐level, microfoundational perspective on sustainable innovations, our knowledge about the organizational implications and boundary conditions of CEOs' political ideologies, and the treatment of multiple identities within social identity theory, especially the relationship between political and occupational identities. The implications of our findings extend to business practitioners, offering valuable insights for CEOs, boards of directors, and investors.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".