Efficiency Evaluation in Search Advertising
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
ABSTRACT In this article, we use data envelopment analysis combined with principal component analysis to evaluate the efficiency of online retailers in search advertising. We examine various efficiency model specifications involving several resource and performance‐related variables in search advertising. Our analysis based on 200 retailers suggests different efficiency patterns for multichannel and Web‐only retailers. The results of our efficiency pattern analysis indicate that the performance metrics, impressions, online sales, click‐through rate , and conversion rate together reveal differences in efficiency mainly for multichannel retailers. On the other hand, ad positions in sponsored and organic links reveal differences in efficiency for Web‐only retailers. In terms of overall efficiency, we find that multichannel retailers occupy relatively most of the top positions. These results contribute to organizational level understanding of search advertising practices in online retailing and offer insights into keyword management, resource utilization, and performance metrics in search advertising campaigns.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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