Green Practice Motivators and Performance in SMEs: A Qualitative Comparative Anaysis
Bibliographic record
Abstract
Green practices are necessary to fight global warming and save scarce resources.SMEs, which represent more than 90% of organizations, play a critical role in this endeavor.This research uses a qualitative comparative analysis, based on Boolean mathematics, to explore SMEs' motivation to implement green practices and inquire about the resulting performance.This research model is based on Porter's Value Chain and Triandis' Theory of Reasoned Action.Fifteen (15) SMEs from three countries (Canada, Tunisia and Morocco) where interviewed for the research.Various groupings of SMEs' motivators associated with a high level of green practices were found.The grouping profiles involved the organizational culture, expected consequences, facilitating conditions, and socioeconomic factors.Implementing green practices was found to be beneficial to SMEs both in terms of financial and environmental performance.The specific green practices characterizing high financial performing SMEs varied among firms; the grouping profiles involved the inventory practices, waste treatment and disposal and inbound logistics.Green practices characterizing high environmental performing firms gathered in profiles based on the operations, waste treatment and R&D.No unique causal condition was found for green practice motivators but the culture revealed to be a sufficient condition for one of the green practice configurations, while inventory practices, operations, waste treatment and R&D appeared to be sufficient for specific configurations of high performing SMEs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.014 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".