Elisabete Arsenio

Modern supply chain management focuses on minimizing environmental impacts, enhancing social responsibility, and ensuring economic viability. These challenges are further influenced by the European Union’s sustainability strategies and technological factors. Therefore, this research aims to provide a comprehensive analysis of European Union (EU) legislative acts (2019 to 2024) that guide the development of low-emission, energy-efficient, and technologically advanced road, rail, and maritime logistics, as well as the relationship between them and a set of eighteen Key Performance Indicators (KPIs) selected for the ADMIRAL project that can assist in achieving the supply chain sustainability goals. Findings indicate that the analyzed EU regulatory framework primarily focuses on emission reduction, with targets of a 55% reduction (compared to 1990) by 2030 and climate neutrality by 2050. This includes implementing less polluting fuels for maritime transport, using electric vehicles for road transport, and doubling rail freight by 2050 (compared to 2015), along with applying technology to integrate and digitalize freight transport (Electronic Freight Transport Information - eFTI). Moreover, the ADMIRAL KPIs could significantly support advancements in the technological readiness of companies by fostering the adoption of digital technologies, reducing greenhouse gas (GHG) emissions through less polluting freight solutions, and integrating solutions from various stakeholders in the logistics sector to provide better transparency on performance and solution integration.

To meet the EU’s net-zero emission target by 2050, promoting a shift from car dependence to more sustainable transportation options is essential. This research employs a stated choice experiment to investigate how shared e-scooters can be integrated into the evolving urban mobility landscape, using the city of Braga, Portugal, as a case study. By simulating hypothetical travel scenarios, the research examines how transport-related features, such as infrastructure quality, travel costs, safety measures (e.g., vehicle sensoring), and monetary rewards (e.g., gamified transportation), influence people’s willingness to adopt shared e-scooters for commuting and leisure trips. Results modeled in the software Biogeme show that although shared e-scooters are not the preferred option for commuting compared to cars, improvements in infrastructure and safety could boost their acceptance, especially for leisure trips. While for leisure trips, the increase in travel time would not decrease the willingness to use shared e-scooters. These insights support sustainable transportation strategies by demonstrating where shared electric micromobility can complement existing transit options and attract a broader user base. This research also demonstrates how stated choice modeling can inform targeted policy and infrastructure decisions, making shared micromobility a valuable component of a sustainable transportation system that helps achieve sustainability goals.

The Strategic Environmental Assessment (SEA) Directive of plans and programs represents a key tool for enabling an earlier integration of environmental issues into the preparation, adoption and implementation of plans and programs that are likely to have significant effects in the environment. Nevertheless, recent research in impact assessment and project appraisal noted that monitoring is still poorly performed, more than 20 years after the launch of SEA in Europe. Given the above context, this paper aims to address the following research questions: a) Which are the factors that hinder the SEA process and in particular the monitoring of environmental impacts in transport plans and programs? and b) Can any good practices be identified in terms of monitoring frameworks of transport impacts worldwide? The methodology includes a comprehensive review and in-depth analysis of available SEA studies in main scientific databases and use of data mining tools to enable mapping the range of factors and existing frameworks within the transport domain. Research results are expected to shed light on further SEA updates to facilitate an effective monitoring and follow-up in implementing transport plans and programs, to enable transitions to the sustainable mobility of people and goods.

Knowing the passengers’ final destinations, underlying motifs, and commuting habits is critical to optimise public transportation systems, guide urban planning and contribute to a more sustainable urban mobility. In entry-only Automated Fare Collection systems, the body of literature has focused on the spatial dimension by estimating alighting stops, overlooking the inference of robust alighting times. Moreover, discriminating between transfers and activities is pivotal for determining their ultimate destinations. However, current methods often struggle to adapt to the stochastic nature of passenger behaviour, further disregarding the multiplicity of routes and stops to access specific facilities and individual motivations. Further research is required to address an effective spatio-temporal and contextual inference in both challenges. With the above concerns in mind, this research uses data analytics to propose an enhanced methodology for the inference of OD matrices, with the final goal of providing a comprehensive view of OD mobility patterns across distinct age-sensitive profiles—youth, adults, and older adults. Our methodological framework integrates the following approaches: (i) alighting stop-and-time inference, (ii) ensembled model for transfer classification, (iii) indicators retrieved from statistical analysis of network vulnerabilities (e.g., number of transfers, walkability needs), frequent destinations and their underlying putative motifs against the city amenities and others points-of-interest. The reliability of alighting data (timestamp and location) inference is improved by integrating OpenStreetMap data and the past boarding data from bus and railway systems. Considering Lisbon as the target study case, we apply the methodology over smart card data collected both from metro and bus systems. A comparative analysis with state-of-the-art methods revealed that the enhanced framework for alighting and OD inference led to longer journey times for trips. Furthermore, throughout the day, the older adult group experiences longer transfer times on average compared to both the children and young adult segment and the adult segment.

Free-floating shared micromobility services have been present in cities all around the world, however little is still known about the interaction between shared e-bikes and e-scooters. In the last few years shared e-scooters have experienced rapid growth worldwide, which, in some cities, jeopardizes the usage of shared e-bike services. Thus, this research work aims to explore if free-floating shared e-bikes can disrupt the usage of established e-scooter services. A case study in the city of Braga, north of Portugal, is developed from September of 2022 until May of 2023 in order to allow the comparison and contrast of the trips made by each micromobility mode, travel time, main origin and destinations of trips, as well as trip characteristics (e.g., vehicle rotation, the total number of trips per micromobility mode, total distance traveled). Results show that shared e-bikes and e-scooters are only used within city boundaries, and most of the trips originated in the parish where population density is higher. In Braga, riders prefer e-scooters when using a shared micro vehicle, since more than 98% of the trips made in the period studied were made by this mode. Also, shared e-scooters traveled more than 260,000 km in these nine months, while only 2,400 km were traveled in e-bikes. In short, Braga has experienced a rapid establishment of shared e-scooters instead of shared e-bikes, it can be due to the fact that trips on e-scooters are seen to be fun, pleasant, and quicker by riders.

Shared e-scooters were introduced in urban public spaces as a way to promote a modal shift from cars in short-distance trips, as well as to improve sustainability, resilience, and equity in urban transport. However, the expansion of shared e-scooter services in 2019 proved that this mode of transport, without integrated planning strategies, can bring some problems to cities, which are related to the illegal parking of e-scooters, an increase in head injuries, and the lack of population diversity among users. Regarding the latest, this research work aims at conducting a case study in the city of Braga, Portugal to reveal who the actual and potential users of shared e-scooters are and how their socioeconomic profile (e.g., gender, age, income range, literacy, occupation) and usage patterns related to the ones found in other cities. For this, a revealed preference survey was deployed on the case study site, and the respondents’ profiles were statistically correlated with the socioeconomic characteristics of the city’s general population in order to assess if this mode of transport provides an equitable service. Results show that shared e-scooters are not equally used by people of different genders, ages, and income ranges. Information on e-scooter usage inequalities across the population is useful for the city to proceed with more socially equitable mobility policies.