Efficiency evolution of coal‐fired electricity generation in China, 1999‐2007
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
Purpose The paper seeks to evaluate the changes in efficiency and productivity of coal‐fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Design/methodology/approach The paper incorporates data envelopment analysis with the Malmquist index to study the progress made in this sector. The model considers both economic and environmental factors by including the variables fuel consumption, labor, capital, sulfur dioxide emissions and electricity generated. A second model is constructed without the variable sulfur dioxide emissions to evaluate economic performances without taking environmental measures into consideration. Findings By comparing the two models, the paper identified provinces that favored economic performance over environmental performance, or vice versa. Also, it showed that the more efficient provinces tend to manage both economic and environmental efficiencies equally well, while the reverse is true for the least efficient provinces. The average total factor productivity growth in coal‐fired electricity generation of all provinces was 3.96 per cent for 1999‐2007, and this growth is mainly attributed to technological change. In addition, it found that the Eastern provinces are the most efficient and productive of the group. Research limitations/implications In the absence of provincial coal quality data, a key efficiency factor is missing from the analysis. Practical implications Efficiency improvement efforts in the Chinese generation sector should target the least efficient provinces identified in this paper. Practices in the most efficient provinces should be further investigated to be replicated when possible. Originality/value The paper provides a contemporary overview of Chinese provincial efficiency and productivity measures for policy makers and investors to improve China's coal‐fired electricity generation sector.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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