Resisting the Giants: Small Retail Entrepreneurs vs. Mega-Retailers - An Empirical Study
Bibliographic record
Abstract
Mega-retailers are widely criticized as causing devastation among smaller retailers, particularly in mid-sized markets in the United States. Others argue that small retailers can survive “in the shadow of the retail giants,” by offering levels of customer service that the mega-retailers can’t provide due to their very size. This paper reports the findings of an empirical study of the perceived impact of the recent opening of box-retailers, such as Costco and Home Depot on locally owned/operated small retailers in the northeastern Ontario city of Greater Sudbury, Canada from 1999 to 2003. The sample included 78 smaller store owners, on average in operation for the last 21 years. Aggregate results confirmed the hypotheses that small retailers suffered lower sales and clientele since the arrival of mega-retailers, and could clearly identify their and mega-retailers’ respective competitive advantages and disadvantages as compared to each other. Respondents had a significant perception of having an advantage over their mega-competitors in the areas of Store Cleanliness, Value for the Customer, Products’ Quality, and Store Layout. While a number of respondents suffered lower sales, about one-third of them (the Resisting Retailers) had average sales growth of over 21%. Differentiation and Niche Marketing were the main aspects of a successful competing strategy adopted by resisting retailers against mega-retailers. Some of the strategic moves adopted by resisting retailers amounted to a “Vacuum Strategy,” which includes the refusal to carry brands available at mega-stores, and the refusal to service such brands or to have anything to do with megaretailers, refusing any alliance with them and making it known to customers.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".