Why Best Buy's Dual Brand Strategy Failed in Canada
Bibliographic record
Abstract
This study investigates how the U.S.-based consumer electronics retailer Best Buy implemented its dual brand strategy in Canada following its acquisition of Future Shop in 2001. The study examines the differentiations between the two brands (Best Buy and Future Shop) in four aspects: geographical adjacency, store operation, product offering, and price structure. The study reveals that Best Buy takes a spatial proximity approach to store development with both Best Buy and Future Shop stores at many locations. Yet, their big box stores have very similar product offerings and price structure. Limited forms of differentiation are observed in store operations; however, they are insufficient to avoid cannibalization. Although the dual brand strategy should not be viewed as the only cause of Best Buy Canada losing its competitive edge in the Canadian consumer electronics market, it is a factor that affects its ability to reduce overhead costs in competition with online retailers and has led Best Buy to abandon this strategy in Canada.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".