Promoting Sustainable Mobility: To What Extent Is “Health” Considered by Mobility App Studies? A Review and a Conceptual Framework

Promoting cycling and walking in cities improves individual health and wellbeing and, together with public transport, promotes societal sustainability patterns. Recently, smartphone apps informing and motivating sustainable mobility usage have increased. Current research has applied and investigated these apps; however, none have specifically considered mobility-related health components within mobility apps. The aim of this study is to examine the (potential) role of health-related information provided in mobility apps to influence mobility behavior. Following a systematic literature review of empirical studies applying mobility apps, this paper (1) investigates the studies and mobility apps regarding communicated information, strategies, and effects on mobility behavior and (2) explores how, and to what extent, health and its components are addressed. The reviewed studies focus on environmental information, especially CO2-emissions. Health is represented by physical activity or calories burned. The self-exposure to air pollution, noise, heat, traffic injuries or green spaces is rarely addressed. We propose a conceptual framework based on protection motivation theory to include health in mobility apps for sustainable mobility behavior change. Addressing people’s self-protective motivation could empower mobility app users. It might be a possible trigger for behavior change, leading towards healthy and sustainable mobility and thus, have individual and societal benefits.

Movers and stayers in STEM enrollment in Italy: who performs better?

Recently, the mobility behavior of Italian university students has garnered increasing interest from both social scientists and politicians. The very particular geographical characteristics of the country, together with the recognized persistence of a significant economic gap between the southern and northern regions, drive a large number of students to move from the first macro-region to the latter. As this phenomenon has several economic and social implications for policy-makers—at both central and local levels—it has led to various theories and prejudices. The present article will study the differences between the performance of STEM students who have decided to move from the south to the north and those who have decided to stay close to their hometowns. We devised multilevel modelling techniques to analyze this issue using administrative microdata from the Italian Ministry for Universities and Research (MUR), including eight cohorts of students from AY 2008–2009 to AY 2015–16, who enrolled in STEM fields after earning their high school diploma. One of the main findings is that individuals who moved from the south show lower levels of performance than their stayer counterparts who are enrolled in northern or central universities.

On estimating the predictability of human mobility: the role of routine

Given the difficulties in predicting human behavior, one may wish to establish bounds on our ability to accurately perform such predictions. In the case of mobility-related behavior, there exists a fundamental technique to estimate the predictability of an individual’s mobility, as expressed in a given dataset. Although useful in several scenarios, this technique focused on human mobility as a monolithic entity, which poses challenges to understanding different types of behavior that may be hard to predict. In this paper, we propose to study predictability in terms of two components of human mobility: routine and novelty, where routine is related to preferential returns, and novelty is related to exploration. Viewing one’s mobility in terms of these two components allows us to identify important patterns about the predictability of one’s mobility.Additionally, we argue that mobility behavior in the novelty component is hard to predict if we rely on the history of visited locations (as the predictability technique does), and therefore we here focus on analyzing what affects the predictability of one’s routine. To that end, we propose a technique that allows us to (i) quantify the effect of novelty on predictability, and (ii) gauge how much one’s routine deviates from a reference routine that is completely predictable, therefore estimating the amount of hard-to-predict behavior in one’s routine. Finally, we rely on previously proposed metrics, as well as a newly proposed one, to understand what affects the predictability of a person’s routine. Our experiments show that our metrics are able to capture most of the variability in one’s routine (adjusted $R^{2}$ R 2 of up to 84.9% and 96.0% on a GPS and CDR datasets, respectively), and that routine behavior can be largely explained by three types of patterns: (i) stationary patterns, in which a person stays in her current location for a given time period, (ii) regular visits, in which people visit a few preferred locations with occasional visits to other places, and (iii) diversity of trajectories, in which people change the order in which they visit certain locations.

Impacts of COVID-19 on Transport Modes and Mobility Behavior: Analysis of Public Discourse in Twitter

This study proposes a framework to analyze public discourse in Twitter to understand the impacts of COVID-19 on transport modes and mobility behavior. It also identifies reopening challenges and potential reopening strategies that are discussed by the public. First, the study collects 15,776 tweets that relate to personal opinions on transportation services posted between May 15 and June 15, 2020. Next, it applies text mining and topic modeling techniques to the tweets to determine the prominent themes, terms, and topics in those discussions to understand public feelings, behavior, and broader sentiments about the changes brought about by COVID-19 on transportation systems. Results reveal that people are avoiding public transport and shifting to using private car, bicycle, or walking. Bicycle sales have increased remarkably but car sales have declined. Cycling and walking, telecommuting, and online schools are identified as possible solutions to COVID-19 mobility problems and to reduce car usage with an aim to tackle traffic congestion in the post-pandemic world. People appreciated government decisions for funding allocation to public transport, and asked for the reshaping, restoring, and safe reopening of transit systems. Protecting transit workers, riders, shop customers and staff, and office employees is identified as a crucial reopening challenge, whereas mask wearing, phased reopening, and social distancing are proposed as effective reopening strategies. This framework can be used as a tool by decision makers to enable a holistic understanding of public opinions on transportation services during COVID-19 and formulate policies for a safe reopening.