Developing a Sustainable Business Model in the Bioeconomy: A Case Study of an Amazon Rainforest Enterprise
Bibliographic record
Abstract
The importance of incorporating sustainability into business models is well recognized, particularly in the bioeconomy industry, where enterprises rely on natural resources as role material.This study aims to analyze how a bioeconomy (BE) enterprise operating in the Amazon rainforest has integrated sustainability into its business model.A case study was conducted with Latin America's largest activated carbon enterprise, a B Corp (Benefit Corporation) certified by B Lab and aligned with the Sustainable Development Goals (SDGs).Data were collected from various stakeholders in the babassu coconut (raw material) supply chain.The findings reveal that incorporating sustainability into the business model required long-term actions (approximately 30 years) and was influenced by internal and external inductors.This study contributes to the literature by proposing a sustainable business model framework, detailing the implementation of each business model element.Furthermore, the environmental and social outcomes of the SBM are presented.Managerial implications are provided to guide enterprises in integrating sustainability into their business model.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".