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Record W7125890079

Revitaliser par le vélo ? : évaluer l'impact des pistes cyclables sur l’offre de restauration dans les artères commerciales à Montréal (2005–2020)

2025· other· fr· W7125890079 on OpenAlexaboutno aff
Jia Yu

Bibliographic record

VenueEspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique) · 2025
Typeother
Languagefr
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)ESPACEInstitutional change
DOInot available

Abstract

fetched live from OpenAlex

Dans un contexte où les municipalités cherchent à concilier développement économique local et transition socio-écologique, les pistes cyclables sont de plus en plus mobilisées comme outils d’aménagement urbain. Ce mémoire examine dans quelle mesure ces infrastructures, au-delà de leur fonction de mobilité, peuvent agir comme catalyseurs de transformations commerciales. Bien que certaines études soulignent des effets positifs à l’échelle de rues ou d’artères spécifiques (hausse de fréquentation ou chiffre d’affaires), les retombées de ces infrastructures de mobilité actives à l’échelle de la ville et du quartier demeurent peu explorées. Pour répondre à cette question, cette recherche s’appuie sur des données longitudinales issues du Registre des Entreprises du Québec et du Service de l’urbanisme et de la mobilité de la Ville de Montréal, couvrant la période de 2005 à 2020. En mobilisant une approche quasi-expérimentale, le Event Study Analysis (ESA), le mémoire évalue l’impact de l’implantation des pistes cyclables en prenant les restaurants comme indicateur principal d’activité économique locale. À la croisée des espaces commerciaux, des tiers-lieux de consommation et des transformations des modes de vie urbains, les restaurants (cafés, établissements de restauration, bar et bistro) constituent un point d’observation particulièrement pertinent pour saisir les effets localisés des politiques de mobilité active sur le tissu économique des quartiers. Les analyses incluent également un indice de gentrification afin de contrôler pour l’incidence des transformations socioéconomiques locales sur l’activité commerciale. Les résultats ne montrent pas d’effet généralisé sur l’ensemble du territoire. Cependant, certains quartiers centraux, comme Ville-Marie — en particulier autour de l’axe de Maisonneuve — illustrent que certaines artères bénéficient plus nettement de l’effet structurant des infrastructures cyclables. Dans ce cas, la hausse locale du nombre d’établissements de restauration semble avoir été favorisée par une connectivité accrue entre les pôles d’attraction que sont les institutions universitaires, les zones résidentielles des quartiers centraux et les espaces commerciaux du centre-ville. Le cas de l’arrondissement Ville-Marie doit ainsi être interprété comme un exemple où les pistes cyclables agissent comme des amplificateurs économiques localisés, et non comme une preuve que ces infrastructures suffisent à elles seules pour induire une revitalisation à l’échelle du quartier. Finalement, l’inclusion de la variable de contrôle binaire associée à la gentrification vise à s'assurer que les résultats reflètent l’effet des pistes cyclables sur la l’augmentation du nombre d’établissements de restauration, plutôt que des transformations socioéconomiques préexistantes.<br /><br />In a context where municipalities seek to balance local economic development with socio-ecological transition, bike lanes are increasingly being used as tools for urban planning. This thesis examines to what extent these infrastructures, beyond their mobility function, can act as catalysts for commercial transformations. While several studies highlight positive effects at the scale of specific corridors and streets (increased foot traffic or revenue), the broader impact of these active mobility infrastructures at the city and neighborhood levels remains underexplored. To address this question, this research relies on longitudinal data from the Quebec Business Register and the Urban Planning and Mobility Service of the City of Montreal, covering the period from 2005 to 2020. Using a quasi-experimental approach, specifically an Event Study Analysis (ESA), the thesis assesses the impact of bike lane implementation by using restaurants (cafés, dining and nightlife establishments) as the primary indicator of local economic activity. Positioned at the intersection of commercial spaces, third places of consumption, and the transformation of urban lifestyles, restaurants serve as a particularly relevant observation point for capturing the localized effects of active mobility policies on neighborhood economic dynamics. Finally, the analysis also includes a gentrification index to evaluate whether socio-economic transformation dynamics modulate the observed effects on commercial activity. The results do not show a generalized effect across the entire territory. However, certain central neighborhoods, such as Ville-Marie — particularly around the Maisonneuve axis — illustrate that some corridors benefit more significantly from the structuring effect of bike lane infrastructures. In this case, restaurant growth appears to have been supported by enhanced connectivity between key attraction points, such as university institutions, residential areas of central neighborhoods, and downtown commercial spaces. The case of Ville-Marie should therefore be interpreted as an example where bike lanes function as localized economic amplifiers, rather than as proof that these infrastructures alone are sufficient to induce neighborhood-scale revitalization. Finally, the inclusion of a binary control variable associated with gentrification is intended to ensure that the results reflect the effect of bike lanes on restaurant growth, rather than pre-existing socio-economic transformations.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.042
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.557
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.042
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0040.011
Scholarly communication0.0050.005
Open science0.0020.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.064
GPT teacher head0.319
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueEspaceINRS Institutional Digital Repository (Institut National de la Recherche Scientifique)French-language works237,207