Impacts of Smart Configuration in Pedelec-Sharing: Evidence from a Panel Survey in Madrid
Bibliographic record
Abstract
Despite the recently increasing research interest, this is one of the first studies employing a panel sample of users and nonusers to understand the bike-sharing phenomenon (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>N</mml:mi><mml:mo>=</mml:mo><mml:mn fontstyle="italic">205</mml:mn></mml:math>). On the basis of a novel surveying technique, a case study on the clients of the state-of-the-art bike-sharing scheme of Madrid (Spain) is presented. BiciMAD is a system of the latest generation, namely, multimodal demand responsive bike-sharing: a fleet of electric pedal-assisted bicycles (pedelecs) with an advanced technology and unique smart service configuration to tackle challenges that may hinder the promotion of cycling and bike-sharing in the city. A statistical test has verified that there is a moderate association between previous intention and actual use of bike-sharing (Cramer’s V = 0.25) and both barriers and motivators of further use have been identified. Indicators on mobility patterns show that although drawing primarily from other sustainable modes of transport, bike-sharing has increased mobility (total number and distance of trips) and especially active travel but decreased the perceived travel time.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".