Sustainable Transportation in The Brazilian Agroindustrial Supply Chain: A Literature Review
Bibliographic record
Abstract
Objective: This article aims to discuss the importance of incorporating sustainable transportation practices into the supply chains of the Brazilian agro-industry, highlighting their potential to reduce costs, increase operational efficiency, and enhance companies' reputation in an increasingly sustainability-focused global context. Theoretical framework: Agribusiness plays a vital role in the Brazilian economy, converting agricultural raw materials into higher value-added products and driving economic gains and job creation. However, transportation in this chain has a significant environmental impact, with Brazil heavily reliant on road transport, contributing to carbon emissions. Companies from various sectors are adopting sustainable transportation practices to address these challenges, recognizing the growing importance of sustainability as a business strategy to ensure competitive advantage in the global market. Method: The literature review was conducted in five detailed stages: formulation of the research question, identification and careful selection of relevant studies, analysis and synthesis of data, and description and dissemination of results. Scientific articles, book chapters, and technical reports published between 2015 and 2023 were considered, ensuring a solid and updated basis for analysis. Results and conclusion: The analysis of 102 studies highlighted the relevance of implementing sustainable transportation practices, such as the use of electric vehicles and bioenergy, in reducing greenhouse gas emissions and optimizing logistics costs. Intermodality also emerged as an effective strategy adopted to mitigate environmental impacts and strengthen competitiveness. However, there is a continuous need for future research to understand the nuances of sustainable transportation strategies in different segments and regions of the Brazilian agro-industrial supply chain. Research implications: This study emphasizes the urgency and importance of transitioning to sustainable transportation practices in the Brazilian agro-industry, highlighting the need for government intervention and investment in research to develop approaches tailored to the specific challenges of each sector and region. Additionally, it underscores the importance of public policies that incentivize and promote sustainability in supply chains. Originality/value: It significantly contributes to understanding the complexities of sustainable transportation in the Brazilian agro-industry, providing insights for companies and policymakers interested in promoting sustainability in supply chains. By filling knowledge gaps and presenting innovative perspectives, this study stands out for its original contribution and practical value.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".