Editorial: Sustainable supply chain management (SSCM): challenges in the XXI century
Bibliographic record
Abstract
Taking an interest in the sustainable supply chain at the start of the 21st century means looking at the main factors that influence it today: technology, demand, culture, taking the human factor into account and sustainable sourcing strategies.This is what this special issue, dedicated to the sustainability of the supply chain in the 21st century, sets out to explore.Different fields and industrial sectors, particularly the agricultural and service sectors, were studied through intervention research, literature reviews and case studies.The seven articles presented address the key issues of sustainable supply chains.In summary, there are several lessons to be learned from these investigations.They have demonstrated the positive influence of technology and culture on the sustainability of the supply chain, the need to include immaterial and emotional elements, the importance of consumer knowledge coupled with the information system to consolidate sustainability, the role of consumers at the end of the chain in the implementation of a supply chain that is both resilient, transparent and sustainable, the need to overcome the barriers to the implementation of Industry 5.0 (I5.0), to achieve resilience and sustainability in the supply chain.Also, in setting up a circular ecosystem, there is a need for a central player, whether social, private or public, to support the efforts of local communities.Last but not least, it outlines that a sourcing strategy promotes supplier diversity (SD) and reduces social and economic inequalities.We understand that the sustainable supply chain is a multifactorial and interdisciplinary topic.This explains the variety of questions and research areas proposed in this special issue.In their article entitled "Circular supply chains and Industry 4.0: An analysis of interfaces in Brazilian foodtechs", Tiago Hennemann Hilario da Silva and Simone Sehnem aim to identify the interfaces between Industry 4.0 technologies and circular supply chains in food techs, through key stakeholders in the sector.The research was conducted in Brazilian food tech.Sixteen circular supply chain practices were identified, along with the enumeration of three different Industry 4.0 technologies already implemented in the food tech, verifying adherence to stakeholder theory issues.The results indicate that Industry 4.0 technologies generate efficiency in food tech circular supply chains, although they are still in their early stages.Resource circularity creates value for food tech when supported by Industry 4.0 technologies and stakeholder engagement, conditions that are crucial for resource circularity.The study also highlights the need for support from the public sector, including regulatory issues and tax exemptions for investment in new Industry 4.0 technologies.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.021 | 0.021 |
| Insufficient payload (model declined to judge) | 0.019 | 0.013 |
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".