Economic evaluation of grocery store nets in cities – a model approach
Bibliographic record
Abstract
The rapid transformation of the grocery business in cities from small to larger units during the last decades has resulted in grocery store nets with fewer nodes.Cost reductions as well as cost increases associated with the structural change are present, with a poorly understood net effect.Earlier research indicates that retail trade is subject to an increasing-returns illusion when increasing consumer participation in performing the service reduces the amount of service actually performed by the firm.This is still to a large extent an unexplored issue of utmost policy relevance.In this paper a total cost model will be presented that focuses on this research question.Its components, grocery prices in retailing and consumers transport cost functions, are estimated from empirical data and derived from a specific spatial structure respectively.Our conclusion is that the increasing returns are not an illusion but due to external costs somewhat exaggerated.The costs associated with the transport and time use by consumers are more than well compensated by the scale economies related to larger stores.When the transport network is severely congested, however, we have a situation closer to the scenario with an increasing-returns illusion.But we can clearly state that the structural change in grocery retailing is welfare enhancing when the capacity utilization in the transportation system is balanced.From a policy perspective the results of this study clearly suggest that issues regarding local service should be an integral part of strategic urban transport planning.With infrastructure and transportation systems that enable easy and affordable access with cars in the city, a significant number of people will find it optimal to use large stores for grocery shopping.Restrictive policies at the more detailed level, currently applied in many countries, will clearly be ineffective since they are counteracted by forces released by more strategic choices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 source (direct Gemma or distilled Codex), 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".