From cooperation to collaboration: an overview of supply chain relationships in a circular economy
Bibliographic record
Abstract
Purpose: Since the development of supply chain management, it is recognized that supply chain relationships are an essential element that leads to the competitiveness of supply chains (Lambert and Cooper, 2000), and now it is clear they are essential for achieving supply chain sustainability and circular economy (Sudusinghe and Seuring, 2022). However, there is a variety of relationships in supply chains, and different types of relationships are useful in different circumstances (Heide and John, 1990). Managing circular supply chains requires managing both, forward and reverse flows of final products, semi-finished products and materials, as well as by-products, and is based on business relationships with multiple buyers and suppliers. The purpose of this study is to investigate a) what kind of supply chain relationships are present in circular supply chains and b) which kind of relationships lead to improved circular economy practices, increased circularity and better economic, environmental, and social sustainability outcomes. Research Approach: There is an abundance of literature on supply chain and business relationships, and now there is an increasing number of studies on circular supply chains. However, there is a lack of insights that indicate which kind of relationship results in increased circularity and better sustainability outcomes. Thus, a systematic literature review can help explore and systematise the current knowledge on supply chain relationships in the circular economy, as well as reveal directions for future studies. Following the procedure for conducting a systematic literature review (Tranfield et al., 2003), upon selection of specified keywords and search parameters in Scopus and Web Of Science databases, we obtained 147 articles. Our findings are based on the content analysis of the 97 articles relevant articles. Findings and Originality: Our preliminary findings indicate that relationships formed between companies and supply chains in a circular economy are very diverse. While companies engage to develop cooperative and collaborative relationships, coordination between companies takes place as well. We also found that next to these types of relationships, there are relationships also which are somewhat particular to the circular economy context: leasing/renting, symbiotic relationships and sharing. To our knowledge, research on these relationships is just emerging, as well as their impact on improved economic, environmental, and social sustainability of companies and their supply chains. Research Impact: The findings from the literature review show future research opportunities in relation to a) developing cooperative and collaborative relationships relevant for organizing forward and backward logistics flows and reverse logistics practices, as well as b) initiating and developing relationships particular for circular economy context: leasing/renting, symbiotic relationships and sharing. Practical Impact: To manage multiple material flows, companies are engaging with many suppliers, buyers and other stakeholders. Better management of these relationships can result in the improved economic and environmental performance of companies.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.027 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".