Strategies for Developing an Environmentally Sustainable Supply Chain: Differences Between Manufacturing and Service Sectors
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT This research illuminates the debate on whether there are differences between the manufacturing and service sectors in the matter of developing a sustainable environmental supply chain. Over the past 5 years a survey has been conducted with 800 large European companies, of which half are in the manufacturing sector and half in the service sector. The hypotheses within the survey are related to strategies for developing an environmental supply chain. They were derived from a literature review and were tested by means of a chi‐square test. The survey questionnaire enabled the respondents to give some viewpoints about the hypotheses. In this way, strategies for developing the supply chain such as ISO 14001, the Eco‐Management and Audit Scheme (EMAS), Life Cycle Assessment (LCA), auditing, waste management systems, reverse logistics, environmental indicators, remanufacturing and reuse have been investigated. Results show interesting and unexpected differences between manufacturing and service sectors that can lead to further research, practical implications and even suggestions for the surveyed companies. For instance, the viewpoints of manufacturing and service industries differ over ISO 14001 and EMAS implementation in the supply chain. In addition, service industries approach the implementation of auditing, reverse logistics, reuse and remanufacturing in a way different from that of manufacturing. Other strategies are considered essential by both sectors. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it