In a general urban planning context, in which sustainable active mobility progressively takes up increasing attention, studies of cyclists’ attitudes and behaviors represent a relevant step to help any enhancing measures for urban cycling. Among different categories, university student cyclists represent a still unidentified class, despite the relevant impacts in terms of mass and variability of attitudes in urban areas. The novelty of this paper is to propose an innovative overview on the specific category of university student cyclists. The integrated methodology, based on direct observation through GPS detection, GIS processing, and qualitative survey, permits the evaluation of some interesting issues related to students’ propensity to cycling and their mobility patterns. The approach finds relevance in speed, frequency of movements, routing, and related infrastructure preferences. The methodology has been applied to a sample of more than 300 students of the University of Bologna who were allowed an original university-designed bicycle from February 2021 to June 2021. The analysis was applied in the Bologna urban area and allowed the evaluation of students’ preferences of using existing cycle paths, when available, the limited relevance of speed factors, the main distribution of commuter journeys concentrated in the main avenues directed to city center, and other behaviors.

In the last decades, tourism in urban areas has been constantly increasing. The need for short-term accommodations has been coupled with the emergence of internet-based services, which makes it easier to match demand (i.e., tourists) and supply (i.e., housing). As a new mass tourist destination, Bologna, Italy, has been experiencing tensions between tourists and long-, mid-, or short-term renters. The possibility of easy profits for lessees has led to an increase in such housing, which can be rented out either for touristic reasons or not. This paper aims to unveil the contribution of short-term rental accommodations in distorting the real estate market and conditioning social and economic inequalities. To do this, multiple linear regression analyses (MLR) were performed between accommodation density, real estate market information, and indicators about social, economic, and demographic vulnerability and fragility. Analyses were based on official open data and datasets from a major web-based hospitality exchange platform, i.e., Airbnb, able to provide information on registered accommodations, e.g., type, characteristics (e.g., number of bedrooms and average rating), and location. Outputs of the analyses reveal the role of Airbnb in both rental market and social, economic, and demographic vulnerability and fragility and, hence, can be a solid tool for public policies, both housing- and tourism-related.

The need for clear and updated information is pivotal when authorities plan and perform routinary, periodic and emergency maintenance of both road network and their roadside assets, e.g., curbs, signals, and barriers. With particular regard to road barriers, the development of remote sensing technologies, such as Laser Imaging Detection and Ranging (LiDAR), has played a disruptive role in acquiring information, so the surveys today are predominantly automatic, faster, and less biased than the traditional (i.e., visual and manual) inventorying methodologies. However, even though they are accurate, these emerging procedures usually focus only on the surveyed elements and do not provide any other information about the surrounding environment or about the qualitative degradation of the elements. The primary objective of this research effort was to present a ranking methodology for enhancing road safety in urban contexts. Due to an innovative synthetic index which takes into account both the deterioration and the location of the surveyed elements, maintenance priority of road barriers was outlined in Bologna, Italy. All the collected information was georeferenced in a Geographic Information System (GIS) environment and hence plotted in thematic maps for an easier analysis. In addition, compliance to the norm was verified. The research was tested to provide public authorities with an effective tool in the evaluation of maintenance activities and road safety policies.

This paper is aimed at exploring and expanding the concept of mobility culture(s) (MC), with regard to its influence on public transportation (PT) usage share. Despite some factors being positively correlated with collective modes, the modal split is often skewed in favour of private or individual ones. To this end, a comprehensive analysis of 70 cities in Germany and Italy is conducted, employing geographically weighted regression (GWR) to assess the impact of some factors on the local share of PT. Factors examined include land use diversity, fare integration, service quality (measured as level of service), scheduling regularity and characteristics of the transit network maps. The findings of the study provide new perspectives on MC and suggest strategies for promoting sustainable and equitable transportation systems.