Internal capabilities and SMEs performance: A case of textile industry in Pakistan
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
The small and medium-sized enterprises (SMEs) play an important role on the growth of the economies of developing countries. In Pakistan, SMEs hold about 90 percent of the total businesses including the textile industry. The performance of SMEs in the textile industry is influenced by several factors including the internal capabilities of the firms. Hence the primary objective of the study is to examine the relationship between the internal capabilities namely Innovation Capability, Absorptive Capacity and SMEs Performance among textile firms in Pakistan. The study is conducted using quantitative research. There are 377 questionnaires distributed among textiles SMEs of Pakistan and they were analyzed using some statistical tests. The results reveal that innovation capability and absorptive capacity influenced the performance of SMEs, positively.
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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 | 0.001 | 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 | 0.000 | 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