Traffic calming and the local economy: rAVENUE provides reliable evidence for Austrian small and medium-sized cities for the first time

The downtown economy in small and medium-sized Austrian cities is under pressure: changing consumer behavior, competition from online retail and out-of-town shopping centers, and the lingering effects of the COVID-19 pandemic are all compounding the challenges. Traffic-calming measures play an important role in this context – yet their impact on the local economy has so far been studied only sporadically. Changes to downtown commercial areas regularly meet with resistance from local business owners, who fear a loss of revenue due to reduced accessibility by car.

In contrast, international studies suggest that the importance of car traffic is often overestimated, while pedestrians contribute more to local revenue than previously assumed. Especially for small and medium-sized Austrian cities – which rely more heavily on cars and have weaker public transportation systems – reliable evidence is almost entirely lacking.

rAvenue fills this gap by conducting the first systematic study of the economic impacts of traffic calming in Austrian cities with populations of up to approximately 65,000 residents. The project follows an explicit impact chain logic – traffic calming leads to effects on economic development through increased pedestrian traffic – and implements an innovative two-stage research design to achieve this.
The detailed longitudinal analysis (10-20 cities) examines the economic effects through a before-and-after comparison based on sales trends, turnover, pedestrian traffic volumes, industry structure, and real estate prices, with an in-depth look at catchment areas and customer feedback. The cross-sectional overview analysis (20-30 cities) quantifies the relationship between traffic calming measures and pedestrian traffic on a broad empirical basis, using, among other things, disaggregated grid data; a difference-in-differences approach, as a quasi-experimental strategy, provides the best possible approximation of causal effects.

To this end, rAvenue combines, for the first time, GIP time series (2017-2025), the location database from Standort + Markt, mobile phone data, grid-based accessibility indicators, modal-split models (GENERATE), walkability scores (NetAScore), parking data, and qualitative primary surveys. Gender and diversity are embedded as integral dimensions of the research.
As a result, rAvenue provides a robust evidence base that is differentiated by city type, type of measure, and spatial context. It helps to bring objectivity to emotionally charged debates and supports future urban transformation processes, whose economic effects can thus be better assessed in advance. The findings are presented in a format tailored to specific target audiences – as a policy brief for policymakers, as stakeholder fact sheets for business leaders and planners, and as a final report ready for publication. In this way, rAvenue makes a direct contribution to overcoming a key barrier to the implementation of the mobility transition.