Bibliographic record
Abstract
Why do consumers value shopping online? We decompose the value of e-commerce to individual consumers and highlight the role of convenience, i.e., the avoidance of transportation costs. We complement household purchase panel data with precise locations of consumers and stores, and show that travel distance is a strong driver of consumer store choice and the substitution to the online channel. Using a structural model of retailer and channel choice, we report that during 2016-2018 the total value from e-commerce to consumers is equivalent to a 23% discount on all prices. Of this value, a quarter comes from convenience in the form of lower transportation costs, a quarter from intensified price competition, and the remaining half from new online retailers and online channels of existing offline retailers. We further demonstrate that consumer gains are heterogeneous. Consumers far from offline stores or experienced in online shopping will benefit more from e-commerce, whereas consumers who likely do not shop online still benefit indirectly from price competition. Finally, our results show that, as consumers gain more online shopping experience, substantial additional gains from e-commerce are yet to materialize in the future.
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.
How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".