The Impact of Walmart Supercenter Conversion on Consumer Shopping Behavior
Bibliographic record
Abstract
This paper presents an empirical study of the impact of Walmart supercenter conversion on consumer shopping behavior. By using a difference-in-difference estimator, we find that Walmart gains 41% in weekly revenue from the conversion. Decomposing the revenue gains into components attributable to store visits and per-visit expenditures, we find that the majority of these gains were due to larger expenditures, with a much smaller impact from store visits. By contrast, among competing retailers, grocery stores experience the most significant loss (20% weekly revenue) mostly from fewer store visits, with a much smaller impact attributable to per-visit expenditure. Taken together, these findings show that consumers may benefit from reduced shopping costs by making fewer overall trips and increasing their Walmart basket sizes. In addition, we find that overall revenue gains for Walmart from conversion outweigh the small cannibalization loss at the existing Walmart supercenters located farther away. Finally, from category-level analyses, we find evidence of increases in category-level spending in preexisting categories in the converted supercenter. However, we also find that positive demand externality is more pronounced in food categories, mainly as a result of increased purchase incidence. We discuss the implications of our findings for academics and retail managers. This paper was accepted by Pradeep Chintagunta, marketing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".