Upfront efforts for upcoming benefits? ISO 9001:2015 certification and firms’ performance in 33 countries
Bibliographic record
Abstract
This paper uses firm-level data from the World Bank Enterprise Survey (WBES) for the years 2013 and 2019 conducted in 33 countries to investigate the effect of certification to an international standard on firms’ performance. Unlike past studies that lumped together all international certificates a firm possesses before assessing its performance, we focus on the release of ISO 9001:2015 standard as a quasi-experiment and apply a kernel propensity score matching difference-in-difference method to panel data. We find that certification to ISO 9001:2015 increases firms’ total sales by 48.3%. This effect is higher than the one obtained from previous studies that combined all international certificates (45.8%). Results also show that small and medium-size enterprises (SMEs), as well as firms in the manufacturing sector appear to benefit more from international certification. The study further suggests that cost reduction, direct international exports, foreign participation, and access to credit are key potential drivers of the positive effect of ISO 9001:2015 certification on total sales.; Techniques
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".