Cost Efficiency Analysis of Taiwan Biotech and Pharmaceutical Industry: The Application of Stochastic Meta Frontier Model
Why this work is in the frame
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Bibliographic record
Abstract
After the 1980s, Taiwan government has prepared a plan to promote strategies and accelerate the biotechnology development for Taiwan’s biotech and pharmaceutical industry. Biotech and pharmaceutical industry technology intensity have a significant connection with the research and development activities and firm performance. Based on the two-step stochastic meta frontier model developed by Huang, Huang and Liu (2012), this study establishes translog cost function. The purpose of the study is to estimate the performance of cost efficiency for firms in the Taiwan biotech and pharmaceutical industry, and to analyze group-specific and firm-specific environmental variables. The empirical results show that it is basically a 15.87% cost inefficiency for the average cost efficiency of Taiwan biotech and pharmaceutical industry. Firms’ operating scale and industrial environment development are supported by the government to encourage cost efficiency. Considering the differences between sub-industries, the empirical results indicate that the R&D activity promotes the growth of cost efficiency in both pharmaceutical and medical equipment industry. For the relation of agency issues and cost efficiency, Convergence-of-Interest Hypothesis exists in the pharmaceutical industry, and Conflict-of-Interest Hypothesis exists in the medical equipment industry.
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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 | 0.003 | 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 | 0.000 |
| 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