Market entry effects of large format retailers: a stakeholder analysis
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
Identifies the effects associated with the entry of a large format (“big box”) retailer into a new market, especially a smaller one. A large format retailer can be a discount department store, category specialist, warehouse club, superstore, supercenter or hypermarket. In order to identify these effects, a review was made of published and unpublished studies. In addition, interviews were conducted among key informants including developers, urban planners and professionals, economic development officers, retail executives and store managers. The result of this research includes a documentation, analysis and discussion of numerous effects, including benefits to the consumer, differences in the demographics of large format store shoppers, rapid growth in the sales and market share of the new entrant, growth in the community economy, growth and decline in various commercial sectors, decline in the economy of nearby markets, creation and losses of jobs, and increases and decreases in market efficiency. Given these effects, suggests implications for each community stakeholder. Listed are a large number of questions for future research.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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