Dynamic Evaluation on Operational Efficiency of Publicly Traded Sports Companies Home and Abroad——DEA-Malmquist TFP Index
Bibliographic record
Abstract
This study tried to make a dynamic evaluation from the perspective of financial management on the operational efficiency of nine publicly traded sports goods companies(six at home three abroad),which was an essential part of an enterprise's core competitiveness.It was done through an analysis of the fiscal data collected from their yearly reports from 2008 to 2010 based on Data Envelopment Analysis(DEA) and Malmquist Total Factor Productivity(TFP) index.The results of this analysis indicated a general underperformance of these companies,among which only 6 companies were DEA efficient but their general average efficiency ratings kept going up on a yearly basis from 2007 to 2010.The Malmquist TFP index also indicated the annual TFP change for these sample firms during the study period was equal to-8.5% each year,which could be attributed mainly to failing technology and inefficient scale,the former factor most obvious in these Chinese companies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".