Bridging old and new: a comparison of the perceived value of firsthand and secondhand luxury among Millennials and Gen Z
Bibliographic record
Abstract
Purpose The purpose of this study is to explore Millennials and Gen Z consumers’ perceptions of secondhand luxury and shed light on the nuanced perceptions of firsthand and secondhand luxury. It investigates how secondhand luxury can provide meaningful access to high-end products without diminishing the perceived value of luxury brands. Design/methodology/approach Adopting an interpretive approach, this research conducted fifteen semi-directed interviews with Millennials and Gen Z luxury consumers who have experience buying both firsthand and secondhand luxury items. The research builds on the existing framework of perceived luxury value and introduces new components relevant to secondhand luxury. Findings The findings reveal that Millennials and Gen Z consumers view secondhand luxury as a valuable alternative, offering ethical and relational values often absent in traditional luxury. This study highlights significant differences in perceived value between firsthand and secondhand luxury, suggesting that brands must adopt distinct marketing strategies for each segment. Furthermore, integrating secondhand products into brand portfolios can enhance overall brand value. Originality/value This research contributes to the literature on luxury consumption by demonstrating that secondhand luxury does not devalue luxury brands; rather, it offers a unique market opportunity. This study provides a framework for luxury brands to refine their strategies and tailor their messaging to effectively engage Millennials and Gen Z consumers, emphasizing sustainability, uniqueness and accessibility.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".