Antecedents and consequences of structural change in North American retailing 1990–2010
Bibliographic record
Abstract
In this article secular trends and market conditions in North America are examined and linked to a series of major structural shifts and changes in US and Canadian retailing over the last two decades (1990–2010). Antecedents and consequences of developments, such as the emergence of category management as a new marketing paradigm, formation of a new value ‘Trinity’, and the rapid movement of markets towards dominant lower cost (value) retailers are reviewed, and their collective impact on other competitive market spaces, (for example, the department store industry and shopping centres), are critically examined. The study also reviews the emerging managerial imperatives in retailing – focusing especially on the centrality of inventory management, the rapid movement of merchandise and information, and the significance of new business processes beyond systems and analytics – as the key elements in a new strategic frontier for higher performance. The paper concludes the strategic review of the last two decades with a preview of the next two, as expectations for the North American retailing scene, both locally and globally, are outlined. The authors fear that the ‘extreme market share’ in the hands of a few retailers may be leading consumers to end up with less choice to shop, researchers with less ‘variance’ to examine, and a continent bereft of any significant retailing innovation in the years to come.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".