A Longitudinal Study of American and Canadian Convenience Store Marketing Strategies
Bibliographic record
Abstract
Convenience stores are part of the Canadian and American landscape. Consumers depend on them for fuel, coffee, tobacco, snacks, fast-food, bathrooms, and more. Convenience stores account for more than one third of the retail brick-and-mortar sales. Yet, there is a paucity of marketing research on this retail format. The present study examines the marketing strategies of convenience stores in 2008 and 2018, assessing the changes in strategy over a decade in the U.S. and Canada. The findings indicate that convenience stores in both regions have been able to offer products and services that will bring about repeat sales and increase their profitability. Convenience stores offer customers time saving while providing what they value most: fast service, expedient locations, quality customer service and an adapted marketing mix.  Although there were more similarities than differences in marketing strategies in both regions, Quebec convenience stores were the most effective in implementing their marketing mix and adapting their strategy. Implications for convenience stores are discussed.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".