Venturing green: the impact of sustainable business model innovation on corporate environmental performance in social enterprises
Bibliographic record
Abstract
Purpose This study aims to explore the potential of social enterprises (SEs) in promoting sustainable practices, focusing on their role in reshaping corporate environmental performance (CEP) through sustainable business model innovation (SBMI). Specifically, it examines the impact of SBMI on CEP and the moderating effect of external collaboration (EC). Design/methodology/approach This study analyses the influence of SBMI on the CEP of 500 Canadian SEs. Chi-square tests, structural equation modelling, correlation analysis and regression analysis were used to assess the relationships between SBMI, CEP and EC. Findings Results reveal that SBMI positively influences CEP by enabling SEs to offer environmentally sustainable products and services. In addition, collaboration with diverse stakeholders significantly enhances the effectiveness of SBMI in achieving environmental objectives. Originality/value By incorporating ecological modernization theory and institutional theory, this study provides fresh insights into the environmental impact of SEs. It underscores the importance of SEs addressing regulatory, social and cultural factors to support their sustainability and legitimacy.
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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 | 0.013 |
| 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 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".