Jonas Fahlbusch

Since 2015, free-floating bicycle schemes have been flourishing worldwide due to their easy booking and mobile payment systems. Despite numerous publications, there remains a significant gap in understanding how app users select their bikes and how spatial barriers, such as intersections or temporary availability uncertainty (during peak times), influence their choices. In order to explore the factors affecting users’ preferences while using the smartphone app, an online survey was conducted in China in 2022. The study evaluates traveller preferences for bicycle usage based on visual stated preference scenarios in which screenshots with potential bike pick-up locations were presented to the respondents. Mixed logit and nested multinomial logistic regression were applied to 9512 valid observations from 1189 respondents. The findings reveal that walking and cycling distance, reservation time, cost, number of intersections, and risk are estimated to have a significant influence on which bicycle is chosen or whether walking is preferred. All parameters have the expected sign, though we observe significant heterogeneity among users. The nested structure furthermoreprovides evidence that travelers are more likely to change their bicycle choice than their reservation status. For example, extending the time a bike is reservable by 5 min can be as valuable as reducing the walking access time by 50–100 m or increasing the fare by 1 CNY. Our results further highlight the importance of detailed locational decisions where shared bicycles are placed. If the operator is able to place bicycles in locations where many travelers do not have to cross intersections, this can offset price increases.

Background: This paper proposes a conceptual framework for a multifunctional mobility hub (MMH) that co-locates shared e-mobility services, urban logistics, and charging/storage infrastructure within a single site. Aimed at high-density European cities, the MMH model addresses current gaps in both research and practice, where multimodal mobility services, logistics, and energy are rarely planned in an integrated manner. Methods: A mixed-methods approach was applied, including a systematic literature review (PRISMA), expert interviews, case studies, and a stakeholder workshop, to identify synergies across fleet types and operational domains. Results: The analysis reveals key design principles for MMHs, such as interoperable charging, the functional separation of passenger and freight flows, and modular, scalable infrastructure adapted to urban constraints. Conclusions: The MMH serves as a preliminary concept for planning next-generation mobility stations. It offers qualitative insights for urban planners, operators, and policymakers into how multifunctional hubs may support lower emissions, more efficient operations, and shared infrastructure use.

E-participation platforms, such as iVoting and Join in Taiwan, provide digital spaces for citizens to engage in deliberation, voting, and oversight. As a forerunner in Asia, Taiwan has implemented these platforms to enhance participatory democracy. However, there is still limited research on the specific content debated on these platforms. Utilising recent advancements in Natural Language Processing, the content of proposals that users have submitted between 2015 and 2025 is explored. In this study, a pipeline for mining text corpora scraped from these platforms in the context of political analysis is proposed. The pipeline is applied to two datasets which have different characteristics. A topic model for each of the two platforms is generated and later evaluated with OCTIS (Optimizing and Comparing Topic Models Is Simple) and compared to different baselines. Our research highlights the trade-offs between model performance and processing time, emphasizing the balance between accuracy and meaningful topic creation. By integrating a translation pipeline from Chinese to English within the text-mining process, our method also demonstrates a solid approach to overcome language barriers. Consequently, our method is adaptable to e-participation platforms in various languages, providing decision-makers with a more comprehensive tool to understand citizens’ needs and enabling the formulation of more informed and effective policies.