Developing a framework for the performance evaluation of sorting and grading firms of used clothing
Bibliographic record
Abstract
Purpose This paper aims to propose a framework for evaluating the performance of reverse value chain activities in the clothing industry operating at base of the pyramid. Specifically, the research explores firm and supply chain factors influencing clothing reverse value chain activities with a focus on developing economies. Design/methodology/approach The study adopted an explorative technique using direct observations and semi-structured interviews to collect information from eight companies and two traders. Internal resources and value chain capabilities were examined using theoretical underpinnings of resource-based view, transaction cost economics and base of the pyramid. Findings The paper identified multiple benefits of offshoring reverse value chain activities to the developing countries (at the base of the pyramid). Low operation cost, skilled manpower, business knowledge and location are found to be internal success factors. While favourable government legislation and domestic recycling markets are important external factors contributing to the success. Developing economies such as India contribute to firm performance by integrating, transforming, acquiring and co-creating the resources at base of the pyramid. Further, it was found that to achieve higher assets specificity, a few companies have opened their own shops in African countries, while others have opened sourcing branches in Canada or the USA to ensure good quality of raw materials. Collaboration and coordination among different value chain partners minimise cost and increases profitability. Innovation in the process such as clothes mutilation for recycling has created new business opportunities. Research limitations/implications Information was collected from only eight organisations and two traders from India. Future scholars may extend the research to generalise the findings by documenting similar phenomena. Practical implications The proposed framework can serve a basis for the practitioners to evaluate firm performance, and the insights can be used to achieve sustainability by engaging producers, employees, consumers and community using base of the pyramid approach. Originality/value The study provides unique insights into the prevalent export and re-exports phenomena of used clothing. The resource-based view, transaction cost economics and base of the pyramid strategy underpinned together to develop a framework for understanding reverse value chain activities of clothing.
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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 | 0.083 | 0.118 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.021 | 0.012 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".