Evaluation of the Sustainable Coupling Coordination of the Logistics Industry and the Manufacturing Industry in the Yangtze River Economic Belt
Bibliographic record
Abstract
In order to promote the sustainable and coordinated development of the logistics industry and the manufacturing industry in the Yangtze River Economic Belt of China and provide the policy makers with decision-making references, this paper explored the spatio-temporal evolution of the coupling coordination development level of the two industries. A three-stage super-efficiency SBM model, which eliminated the influence of environmental factors and random errors, was constructed to make it possible to conduct an in-depth comparative analysis on the effective decision-making units (DMUs), making the calculation results more accurate. This was the main contribution of this paper. Based on the new model considering undesirable output, this paper analyzed the panel data of 11 provinces and cities in the Yangtze River Economic Belt from 2007 to 2017 and investigated the coordination development level from the dimensions of time and space considering the energy input and carbon emissions of the two industries. Our main research findings were as follows. First, due to the relative lagging of the logistics industry in promoting the development of the manufacturing industry, the overall level of the coordination between the two industries was at a stage of limited coordination. Second, the regional differences were significant with a spatial evolution pattern of “high in the east and low in the west”. Third, environmental factors affected the input efficiency of the logistics industry and the manufacturing industry, especially the latter. Overall, this paper made theoretical and practical contributions to promoting the joint development of the two industries, improving the logistics industry and upgrading the manufacturing industry.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".