A Continuous Model for Multistore Competitive Location
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a simple model to determine the location strategies of two retail firms planning to open a number of stores in a geographical market. Firms try to maximize their profit under a leader-follower type competition in which the number of stores is made endogenous by the introduction of fixed costs. A novel methodology is developed in which firms’ strategies are defined in terms of their location densities. This methodology leads to a model that is solvable analytically, and to several results on competitive location strategies. First, it is shown that if the follower decides to enter a market, he enters at least as strongly as the leader. Second, the leader can effectively deter entry even if she is severely cost-disadvantaged. However, in some cases the leader is better off by allowing the follower to enter the market. Third, the leader may also let the follower enter the market in some situations where she has a cost advantage. It is also shown that in situations where both firms enter the market, their location strategies are quite insensitive to model parameters.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it