Carlos Gayán-Navarro, Marcos Sanso-Navarro (p)

Mehmet Guney Celbis

This paper investigates the economic effects of mass shootings taking advantage of a unique dataset with detailed information about their location. Using recent advances in difference-in-differences methods, we assess the influence of the attacks on employment and housing prices at three levels of geographical disaggregation. Obtained results show that the economic impact of mass shootings is more evident when census tracts are considered as the spatial unit of analysis, and when they are perpetrated in public spaces. Furthermore, mass shootings affect to a greater extent the employment of those sectors that are more reliant on face-to-face interactions.

Mehmet Guney Celbis (p), Louafi Bouzouina

Martin Mariš

Car use contributes to greenhouse gas emissions, congestion, air pollution, and inequitable access to mobility options. While prior research has identified broad determinants of car use, a deeper understanding of how household and neighborhood-level factors interact in shaping commuting choices is needed. This study investigates the spatial and socioeconomic determinants of car use in three major French urban regions—Lyon, Lille, and Marseille—each representing distinct urban forms with differing levels of public transport accessibility and mobility behavior. The core research question is: To what extent household and spatial factors influence car use, and how do their effects vary across different urban contexts?

The study integrates two key data sources: 1- the 2021 French population census (Logements ordinaires – Recensement de la population), which provides extensive household-level data, including demographics, housing characteristics, and commuting behavior. 2- a set of spatial indicators derived using QGIS, capturing features such as public transport network extent, cycling infrastructure, and accessibility to key amenities. These datasets are merged at the IRIS level, the smallest statistical spatial unit in France, to enable a fine-grained analysis of how urban form and socioeconomic conditions shape transport behavior.

The methodological approach applies tree-based ensemble learning methods, particularly Extreme Gradient Boosting (XGBoost), to capture complex, nonlinear relationships between explanatory variables and car use. Gradient Boosting is well-suited to handling high-dimensional data and allow for flexible modeling without imposing restrictive assumptions. Thanks to the possibilities for regularization provided by the XGBoost algorithm, car use can be predicted in a more generalizable way. To improve interpretability, the study employs SHAP (SHapley Additive exPlanations) values, which quantify the marginal contributions of each factor to car use. This approach allows for a transparent analysis of how variables such as income, employment status, transit proximity, and neighborhood design interact in influencing mobility choices. The effect sizes of model variables and their directions can be measured for each neighborhood in an interactive and nonlinear fashion, while avoiding ceteris paribus results. Therefore, by leveraging spatial analysis and explainable AI, this study aims to uncover actionable insights that can inform policies promoting sustainable transport alternatives such as public transit, walking, and cycling. The findings will contribute to urban planning and transport policy by highlighting which interventions are most effective in reducing car use under different urban and socioeconomic conditions. Understanding these dynamics is critical for designing targeted policies that mitigate congestion and emissions while ensuring equitable access to sustainable mobility.

Martin Mariš (p)

Fabiano Compagnucci

Restoring the competitiveness of the European manufacturing sector and closing the innovation gap with the US and China remain key priorities for the EU. The European Commission, as the EU's principal executive body, primarily relies on regulatory simplification and reforms in fiscal, labour, and industrial policies, implemented mainly at the member-state level (Competitiveness Compass for the EU, 2025). This paper revisits traditional location-based theories to explain regional competitiveness in the EU manufacturing sector, emphasizing the role of industrial density in shaping economic performance. There is considerable variation in industrial density among the EU member states on the regional level. There is evidence that regions with significant manufacturing bases are prone to innovate and retain the competitiveness advantage in the global environment (Porter, 1990, 1998), able to attract skilled workers with significant spillover effects (Marshall, 1890) and realize the economies of scale (Krugman, 1991).
The central focus of the study is the manufacturing employment density measured as the number of workers employed in manufacturing per kilometre square at the NUTS3 regional level. Within the research scope, one basic sample and two subsamples are determined:
• Manufacturing density of regions – includes all EU NUTS3 regions.
• Manufacturing hubs – regions with the highest manufacturing density, where industrial activity is concentrated
• Manufacturing deserts - regions with the lowest manufacturing density, highlighting industrial decline or underdevelopment areas.
In particular, geographical distribution and the potential appearance of "spread" and "polarization" effects between the manufacturing centres among the regions are investigated using spatial analysis methods. For this purpose, the Cluster and Outlier Analysis (Anselin and Local Moran's I) and Incremental Spatial Autocorrelation will investigate spatial relations at the regional level. Finally, the economic implications of manufacturing distribution among the research samples will be evaluated.
There is a relatively extensive body of evidence on applying individual regional development theories worldwide in later economic policy formulation (Pitelis & Kelmendi, 2011; Maier & Tödling, 1998; Fratesi, 2023; OECD, 2018).
This paper's novelty lies in its integrated approach to linking manufacturing employment density with location-based competitiveness. It provides empirical evidence on the spatial dynamics of industrial localization. The findings offer valuable insights for regional policy, with implications for income distribution and economic growth.

Fabiano Compagnucci (p), Alena Myshko, Arsène Perrot

Joanna Dominiak

This work focuses on the recent transitions and structural changes that occurred in the logistics sector in the last two decades and on the effects of these changes at the local level. Starting from an institutional approach, the paper discusses its transformation from a highly fragmented sector characterised by a substantial number of SMEs specialising in basic services to a consolidated and vertically integrated one. While logistics has developed alongside industrial activities for a long time, its transition towards an independent economic sector was affected by various factors, which perform as both barriers and facilitators, such as industrial decline, geopolitical shifts, climate change and sustainability challenges and others.
The increasing entry of multinational companies in national markets (more than in the past) and the expansion of outsourcing and subcontracting have changed the number of intermediate actors and suppliers involved as well as the rules of the competition. The effects of such transformations will be discussed and assessed through the Pomezia-Santa Palomba case study, the only area in central Italy which has increased its specialisation in logistics in the last decade. Situated along the Scandinavian - Mediterranean corridor, the concentration and further development of logistics activities in this area is rooted in the territory’s industrial history with diversified manufacturing, and the vicinity to the metropolitan area of Rome. By adopting a mixed methods approach relying on a quantitative analysis based on the ASIA and ORBIS Orbis-Bureau Van Dijk databases (for employees and firms) and qualitative data (from interviews, observations and visual materials), we will describe, from the one hand, how a new actors system has risen and, from the other hand, how the socioeconomic and environmental local dimensions have responded to these changes.

Joanna Dominiak (p)

Marcos Sanso-Navarro

The last decade has been characterized by a high intensity of various types of crisis phenomena, which cause significant changes in the functioning of society and the economy. The year 2020 began with the COVID-19 pandemic, which completely transformed the services market. Even before it ended, there was another accumulation of crisis phenomena related to the armed conflict in Ukraine. The services sector, which has not yet regained its economic condition after the pandemic, faced further challenges related to rising inflation, shortages in the availability of certain products and the energy crisis. All these elements significantly influenced the functioning of the services market both in Poland and around the world. The main purpose of the presentation is to present changes in the economic condition of the services sector measured by the turnover in individual sections in Poland compared to the other EU countries in 2012-2023. The analysis used indicators for the services sector published by Eurostat.
The analysis leads to the following conclusions. During the period under review, the pandemic had the greatest impact on changes in the turnover of service companies. Hotel, catering and tourist services suffered the most as a result of the crisis. The transport industry recorded significant declines. These entities experienced significant fluctuations in demand (related to the waves of the pandemic and the restrictions imposed at that time). The most resistant services turned out to be the ICT sector and business services, which transitioned to remote mode relatively easily. Analysis at the level of individual EU member states indicates significant differences in the turnover dynamics of service companies. The general rule is that the turnover dynamics in the "old countries" in the western part of the EU is lower than in the eastern part of the continent. These countries are also more resistant to crises and the COVID-19 pandemic. Southern European countries, and Greece in particular, are affected by the problem of low or even negative average quarterly turnover dynamics in the period 2005-2023 in basically all observed sectors. The effect of the war in Ukraine is observed at the end of the analyzed period. In the H section it reduces the dynamics. This effect is spatial in nature and its impact weakens with the distance from Ukraine.