Abstract
-This study focuses on providing meaningful information to vulnerable road users (VRUs) to support their objectives and perceptions while navigating urban spaces, employing a novel route planning concept. Through three focus group sessions, a comprehensive survey was conducted to identify the needs and concerns of VRUs, leading to the development of an integrated and collaborative mobile application for active mobility. The application encompasses route calculation, prioritizing safety, comfort, civic participation, and empathy. The solution aims to bridge citizen users and city managers, facilitating alerts, historical information on safety and comfort, and collaborative problem-solving and sharing of urban attractions. A prototype of the concept was developed and extensively tested by potential users, and subjective evaluation and feedback demonstrated the usefulness and added value of the integrated and collaborative approach. This study highlights the proposed solution relevance and differentiation from official alerts, user experiences, and civic participation, positioning it as a comprehensive solution for active mobility.

Abstract
We consider the problem of selecting bases for firefighting activities (e.g., vigilance, water refill, initial attack) and links between them in the context of wildfire promptness. Bases can be facilities, such as watchtowers and water tanks, or positions from where an initial attack is conducted. It is assumed that it is advantageous to connect bases in such a way that resources (e.g. ground crews) can quickly move between them. The general problem is modelled in a general way as integration of a set covering problem (for selecting the location of the bases) and a travelling salesman problem where the cities are the selected locations and the arcs the links that connect them. We propose a mixed integer programming model where objectives are addressed by lexicographic optimization. The first objective is related to cover potential ignition points with a high estimate of their initial spread rate of the fire at the detection time. Computational experiments are discussed for a scenario, of an actual landscape, with parameters estimated from a fire behaviour model that takes into account slope, fuels, and wind. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Abstract
This paper investigates the relationship between school principals' managerial practices and two key mensions of school performance: students' cognitive outcomes and school climate. School performance assessed using a classical Data Envelopment Analysis (DEA) framework, complemented by both unconditional robust and conditional robust models to evaluate the influence of managerial practices on school efficiency. We introduce a methodological innovation that allows for a nuanced analysis of how contextual variables-specifically, principals' managerial practices-affect performance, both individually and through their interactions. The analysis is based on 2019 INVALSI data from a nationally representative sample of 8th grade students in Italian schools. The findings show that principals' practices, as well as the ways in which these practices interact, play a significant role in shaping school efficiency, particularly by promoting a positive supportive school climate.

Abstract
Education 5.0 is a new paradigm in education posing many challenges and opportunities. This paper uses qualitative methods to explore students’ and teachers’ experiences with online learning to understand the challenges, benefits, and vision for a successful blended learning model, proposing a dynamic framework for blended learning. Results of in-depth interviews show the three main challenges of blended learning: pedagogical design, technological design, and environment/ setup design. Finally, the study discusses insights into future directions for developing Education 5.0, including the need for ongoing research, collaboration communities, curricula personalization, and innovation in the field. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Abstract
The stochastic dynamic inventory-routing problem (SDIRP) is a fundamental problem within supply chain operations that integrates inventory management and vehicle routing while handling the stochastic and dynamic nature of exogenous factors unveiled over time, such as customer demands, inventory supply and travel times. While practical applications require dynamic and stochastic decision-making, research in this field has only recently experienced significant growth, with most inventory-routing literature focusing on static variants. This paper reviews the current state of research on SDIRPs, identifying critical gaps and highlighting emerging trends in problem settings and decision policies. We extend the existing inventory-routing taxonomies by incorporating additional problem characteristics to better align models with real-world contexts. As a result, we highlight the need to account for further sources of uncertainty, multiple-supplier networks, perishability, multiple objectives, and pickup and delivery operations. We further categorize each study based on its policy design, investigating how different problem aspects shape decision policies. To conclude, we emphasize that large-scale and real-time problems require more attention and can benefit from decomposition approaches and learning-based methods.

Abstract