Uncovering factors affecting consumers’ decisions for pre-owned electric vehicles
Bibliographic record
Abstract
As the electric vehicle (EV) market rises, the relevance of the used EV market becomes more significant in the context of environmental sustainability and green transportation. Hence, the study conducts data-driven investigations to comprehensively understand users’ preferences for pre-owned EVs. Full-time employed, highly educated, higher-income individuals living in detached homes or townhouses and owning personal parking amenities are more likely to purchase pre-owned EVs. The study used a latent class choice model to analyse the impact of hidden psychological factors and vehicle characteristics on “Experienced EV Drivers” and “New EV Drivers”. The latter class prefers sedans and home charging facilities while opting for pre-owned EVs. However, those concerned about EV charging infrastructure and price and those having a positive attitude toward automated vehicles were reluctant to purchase a pre-owned EV. Overall, the study provides target population-specific actionable policy insights aiming to promote the adoption and sustainable usage of EVs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".