WHAT IS “LUXURY” TO GENERATION Y?
Bibliographic record
Abstract
In the last decades, numerous articles have been written on luxury products (goods and services), their importance in terms of consumption, the growth of this market segment, their importance in the eyes of the consumer, etc. Yet one thing remains elusive: what exactly is a luxury product? If one is to believe the existing literature, luxury products range from anything (and everything) a producer wishes to make us believe is “luxurious”: the rarest of items (an original masterpiece from a renaissance painter, for example), a high quality handbag made of the finest materials and selling for thousands of dollars, an horrendously overpriced piece of clothing bearing the name of an unknown (yet French or Italian sounding) designer that is made in China or Bangladesh. The current paper looks at the most important future clientele of luxury products: members of Generation Y. It identifies what, in their eyes, make a product/brand “luxurious”. Through a literature review, we first review the most generally accepted definitions of luxury. We then proceed to present the results of our quantitative research conducted in Québec which highlight the characteristics that members of this subgroup consider to be necessary components of a luxury brand or product. This paper concludes on some possible avenues to an acceptable definition of “luxury” and recommendations to participants in this industry on the points to emphasize in their brand promotion and product design and production.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".