Does green innovation affect the financial performance of Multilatinas? The moderating role of ISO 14001 and R&D investment
Bibliographic record
Abstract
Abstract The purpose of this study is to explore the relationship between green innovation (GI) and financial performance (FP) in emerging markets multinationals from Latin America (Multilatinas). Aligned with the natural resource‐based view and institutional theory, and using moderated and hierarchical linear regression analyses with panel data from 86 listed firms during the period 2013–2017, we find that implementing effective GIs is not associated with greater FP. The paper also analyses the moderating effect of Environmental Management Systems (ISO 14001) and research and development (R&D) investment on the relationship between GI and FP. We find that Multilatinas' implementation of ISO 14001 does not affect the way they adopt GI and thus does not enhance their levels of FP, but a positive moderating effect is generated as companies increase their level of R&D investment. The paper expands knowledge of the way GI affects Multilatinas' FP, and these findings have policy implications for managers, policy makers, government and other institutions.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".