Study on the Operation Efficiency of Toll Roads in China from the Perspective of Scale Economy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although China’s toll highways are world-renowned, they suffer from indisputable operational inefficiencies. Operationally, China’s toll highway sector is characterized by an administrative monopoly. In particular, governmental loan-repayment highways have such characteristics as franchising, monopoly, and “one highway by one company.” Hence, this study concentrates on the relationship between economic performance, administrative monopoly, and scale efficiency with respect to toll highways, and explores how the China-specific administrative monopoly affects the transformation of toll highways from scale to efficiency. Using the globally referenced data envelopment analysis- (DEA-) Malmquist Index, this study first measures the operational efficiency of China’s toll highway sector from 2010 to 2017. Based on provincial panel data, this paper then discusses the relationship between toll highway scale and economic performance through system-generalized method of moments estimation and verifies the status quo of the transformation of toll highways from scale to efficiency. From the provincial and industrial perspectives, this study further verifies how an administrative monopoly restricts the transformation from scale to total factor productivity and scale efficiency through the unique operation pattern in the toll highway sector. Finally, this study conducts an extended analysis of the relationship between operational efficiency and debt in the toll highway sector. The administrative monopoly is found to increase the debt burden of the toll highway sector and to have a negative impact on the long-term sustainability of the sector.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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