Productivity and efficiency analysis of Taiwan's integrated circuit industry
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 purpose of this paper is to evaluate the productivity and efficiency of Taiwan's integrated circuit (IC) industry using DEA analysis and the Malmquist index (MI). Design/methodology/approach The Malmquist index, as a total factor productivity index based on distance functions, is estimated using DEA in this study. Findings Results indicate that as the asset size class becomes larger and larger, the associated companies become more and more inefficient. Also, results indicate a possible scale inefficiency in the IC industry investigated. Research limitations/implications This paper presents a DEA study to investigate the productivity and efficiency in IC industry. This performance analysis is important because Taiwan's IC industry stands in a critical global position as indicated by analysis of market share across various sub‐components of the industry. The resulting analysis might provide valuable managerial insights. Originality/value The originality of this paper is its application of specific analytical techniques to the productivity and efficiency if IC companies in Taiwan's companies. The MI is appropriate for measuring the productivity change because it does not require the assumption of a possibly unwarranted functional form on the structure of production technology, as required by the econometric method.
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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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| 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) | 0.000 | 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