The Influence of Green Market Orientation on Business Performance: Exploring the Mediating Role of Green Innovation
Bibliographic record
Abstract
This study examines the impact of green market orientation (GMO) on business performance (BP), emphasizing the mediating role of green innovation (GI).Using a quantitative approach and Partial Least Squares Structural Equation Modelling (PLS-SEM), data were gathered from 128 owners/managers of MSMEs producing green products in northern India.The findings confirm that GMO significantly enhances BP by improving operational efficiency, customer satisfaction, and competitive advantage (e.g., GMO influences BP with a ß coefficient of 0.78).Additionally, GI is a key mediator, amplifying BP through sustainable practices and green product innovations.Despite these insights, the study is geographically limited and relies on self-reported data.The findings also highlight the critical need for companies to incorporate environmentally friendly strategies into their business practices to ensure enduring sustainability.Future research should explore diverse samples, objective performance measures, and the role of digital technologies in advancing green innovation and business outcomes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".