The Study on the Operating Efficiency of Rural Banks Based on DEA Model: A Case of Jiangsu Province
Bibliographic record
Abstract
The paper takes Jiangsu province as example in Yangtze River Delta, which is economically developed regions. According to previous research and characteristics of rural banks in Jiangsu Province, the input indexes are selected as the number of employees, the number of outlets, total deposits, business and management fees. And the output indexes include total loans, net interest income and net profit. Using DEA model to analyze the operating efficiency of the 65 rural banks in 2016, the paper compares the operating efficiency in different regions and different types of originating bank. The analysis shows that, compared with the central and northern Jiangsu, operating efficiency of rural banks in southern Jiangsu is generally high. The comprehensive technical efficiency value of sample banks that originated by the state-owned banks and joint-stock banks is significantly higher than that originated by rural commercial banks and city commercial banks. Finally, the paper puts forward some suggestions on how to improve the operating efficiency of rural banks.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".