Angela Stefania Bergantino, Valentina Costa (p), Ilaria Delponte, Claudio Ferrari, Mario Intini, Alessio Tei

Lucia Rotaris

Accessibility is a key-factor for regional socio-economic development, as supported by numerous studies and international initiatives linking regional connectivity to economic performance. Nevertheless, inconsistencies in data availability, standardization, and collection may hamper transferable and comprehensive assessments. This study addresses these gaps by defining innovative geospatial accessibility KPIs to evaluate regional infrastructure endowment and its impacts on socio-economic development, focusing on Italy's NUTS-3 regions. By implementing an hybrid approach, present research integrates infrastructure-based and activity-based measures, thus creating a geodatabase that combines socio-economic, geographical and infrastructural data. Similar database supports advanced spatial queries and geostatistical modelling, thus enabling regional economic assessments. Research questions target the dependency of economic growth rates on connectivity or percolation indexes and the correlation between infrastructure-based accessibility and regional economic structures. Expected outcomes aim to improve regional data maintenance systems and provide insights concerning how infrastructures influence economic growth and specialization. Study findings will contribute to the design of more detailed and targeted economic policies and planning, addressing the limitations of current methodologies and providing a more comprehensive evaluation of regional infrastructural assets and their impacts on economic development and specialization.

Lucia Rotaris (p), Romeo Danielis, Mariangela Scorrano

Alessandro Gardelli

Car sharing among peers presents a promising opportunity to enhance the environmental sustainability of urban transport systems. It can complement public transport services and active mobility options, helping to alleviate congestion, reduce emissions, and foster a more sustainable urban environment. Moreover, it can contribute to social inclusion by providing access to mobility for individuals who cannot afford the high costs associated with owning and maintaining a car. In northern European countries, peer-to-peer car sharing is already a popular and well-established model. However, in Italy, it remains underutilized, largely due to an undefined regulatory framework and the lack of awareness among the population.
The purpose of our research is to investigate the key technical features that can promote both the demand and supply of these sharing services in Italy. To this aim, we administered an online survey to a sample of the Italian population, including residents from the cities of Trieste and Taranto. By analyzing the data using discrete choice models, we identified the factors most important to potential renters and car owners.
Our findings reveal that potential renters are primarily concerned with the cost of the service, including the fare and the value of the deductible, as well as the walking distance to access the car. Car owners, instead, are more focused on the amount they can charge for their vehicle, the level of insurance coverage, and the availability of an app or platform feature to unlock the car. Additionally, for both groups, the fee charged by the platform manager to facilitate the match between supply and demand plays a crucial role in the attractiveness of the service.
These results have important implications for both policymakers and operators. For policymakers, understanding the preferences of both renters and car owners is essential for crafting regulations that create a conducive environment for the growth of peer-to-peer car sharing services. Effective regulation can help overcome current barriers, such as insurance and tax uncertainties, and allow the market to achieve the critical mass needed to make these services viable. For operators, the findings offer valuable insights into how to design platforms that meet the needs of both supply and demand, ensuring a smoother and more efficient operation. By focusing on the right pricing structures, insurance options, and user-friendly features, operators can better match the needs of car owners and renters, contributing to the success of this sustainable mobility model.

Angela Stefania Bergantino, Alessandro Gardelli (p), Mario Intini, Frank Witlox

Gianluca Monturano

When analyzing cyclists' route choice, studies often overlook subjective or soft factors. This not only reduces the informational power but also leads to less precise analysis. This study aims at illustrating to what extent cyclists' route choice is function of their subjective exposure to micro-scale elements of the surrounding environment. To achieve this, we map-match 8,947 GPS trajectories of repeated bike commuting trips in the city of Bari, southern Italy, and compare them to their respective shortest paths. We operationalize subjective exposure to micro-scale elements of the surrounding environment by applying semantic segmentation techniques to Google Street Views. Additional data on land use attributes and street and traffic elements contribute to the modeling of route choice as a function of these factors of interest. Furthermore, we identify systematic avoidance with street segments that belong to the shortest paths, enabling the visualization of critical edges in Bari’s street network.

Angela Stefania Bergantino, Mario Intini, Gianluca Monturano (p)

Valentina Costa

This work aims to investigate and study the accessibility of citizen services, such as mobility, education, and healthcare, within Italian municipalities. To this end, we employ predictive machine learning methodologies for cluster analysis and network analysis. We use for our estimates a unique local dataset, which integrates municipal socioeconomic variables with advanced engineering features, obtained by analyzing the geo-spatial and road distances between public services and by analyzing the service networks present on the Italian territory. The use of such indicators provides a comprehensive and detailed view of the factors that influence accessibility to services, also allowing to formulate policy recommendations aimed at improving the efficiency of public policies and ensuring a fair distribution of citizen services. Our research highlights the importance of integrating technological approaches with socio-economic data to uncover patterns not visible through traditional methods. This fosters a deeper understanding of how the interconnection between regions and services influences accessibility. The results of our study aim to guide policy makers in identifying areas requiring priority interventions and to support the development of data-driven strategies for balanced and functional territorial policies. This approach is crucial to address Italian territorial heterogeneities, promoting sustainable development that respects the needs of all citizens and ensures equal access to essential services. Our results suggest that municipalities with better connectivity to key public services tend to experience greater socioeconomic well-being. The observed disparities in accessibility across regions point to the need for a more nuanced policy approach, tailored to the challenges of each area. Our project presents itself as a significant scientific contribution, offering innovative and applicable solutions to improve the quality of life in Italian municipalities. In particular, our results support the idea that enhancing infrastructure and ensuring a more equitable distribution of services can reduce regional inequalities.