Product-Oriented Web Technologies and Product Returns: An Exploratory Study
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
Internet retailers have been making significant investments in Web technologies, such as zoom, alternative photos, and color swatch, that are capable of providing detailed product-oriented information and, thereby, mitigating the lack of “touch and feel,” which, in turn, is expected to lower product returns. However, a clear understanding of the relationship between these technologies and product returns is still lacking. Our study attempts to fill this gap by using several econometric models to explore the said relationship. Our unique and rich data set from a women's clothing company allows us to measure technology usage at the product level for each consumer. The results show that, in this context, zoom usage has a negative coefficient, suggesting that a higher use of the zoom technology is associated with fewer returns. Interestingly, we find that a higher use of alternative photos is associated with more returns and, perhaps more importantly, with lower net sales. Color swatch, on the other hand, does not seem to have any effect on returns. Thus, our findings show that different technologies have different effects on product returns. We provide explanations for these findings based on the extant literature. We also conduct a number of tests to ensure the robustness of the results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.010 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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