Mobile phone data rarely records whether a person is male or female, so researchers are developing new statistical methods to infer gender from travel patterns hidden in digital footprints. This matters because transport planners currently rely on outdated travel surveys that miss how women and men move differently through cities. Women often make shorter, more complex trips—dropping children at school, shopping, visiting healthcare—while men’s journeys tend to be simpler commutes. Without gender-disaggregated data, policies promoting cycling and walking risk being designed around male travel habits, leaving women’s needs invisible. If the methods succeed, transport authorities could use existing mobile phone data to map gender differences in mobility at street-by-street resolution, without costly new surveys. This would allow cities to target infrastructure investments—such as safer cycle lanes or better-lit walking routes—where they would most benefit women. The project uses Scotland as a test case, working with Sustrans and Scottish policymakers to ensure outputs directly inform the country’s “just transition” to sustainable transport. The research is applied, not fundamental: it builds new analytical tools from existing data to solve a specific policy problem.
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This project aims to experiment with new ways to measure gender differences in everyday mobility using (geographic) digital footprint data, which is collected from people's interactions with mobile phones and other devices. While these data provide detailed information about people's movement, they only rarely have information on their gender. We will develop new methods for disaggregating these data based on gender and explore how travel patterns differ at an unprecedented level of spatio-temporal resolution. We will work with data sources available from the Urban Big Data Centre at the University of Glasgow, combining detailed movement data with evidence on the relationship between gender and transport. With a focus on active travel, we will look at what differences might be detected in the data based on gender. Our process will allow for a reproducible method to examine these gender differences from new forms of mobility data. Our project will use Scotland as a case study to develop our methods as there is a rich data landscape available with a wide range of digital footprint data on travel and transport. Additionally, we maintain a close connection with Sustrans, the UK leading charity aimed at favouring active travel, and the Scottish policy context, currently working towards just transitions for the transport sector. We will carry out our research through working with partners to gain input on how best to develop outputs that can inform policy (WP1). Gathering data on travel choices and other characteristics from existing surveys and research will inform a working model of gender differences in mobility (WP2). Using this knowledge, we will use digital footprint data to map and analyse mobility traces for different genders, applying a level of confidence measure to the patterns found (WP3). The project's findings will be used to inform transportation policies and sustainability transitions. By understanding how gender differences in mobility patterns impact transportation systems, policymakers can develop more inclusive and effective policies that promote sustainable mobility for all.
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