Imagine if you could predict which small towns will suddenly become hotspots for workers because of remote work and green energy. This work uses big data to see why people move and where they are likely to settle next. It helps figure out if a place is actually attractive to new residents or if it's at risk of losing its population.
Companies and governments struggle to predict where people will move as remote work and green energy change what makes a city or town attractive. This leads to poor investment decisions and labor shortages.
A large-scale mobility dataset and agent-based models that simulate how the green and digital transitions shift population flows between EU regions.
If you are a developer dealing with uncertainty about where to build new housing — this project developed agent-based modelling that predicts changing regional attractiveness. This allows you to identify emerging growth areas before they peak.
If you are a recruiter dealing with talent shortages in specific regions — this project developed a regional typology to identify demographic risks. You can use these insights to adjust salary and benefit packages based on local attractiveness.
If you are a government agency dealing with declining populations in rural areas — this project developed place-based policies to attract people via better environmental conditions. This helps you create targeted incentives to bring in new residents.
Based on available project data, no pricing or commercial licensing costs are mentioned as the project is EU-funded research.
The project uses big data and agent-based modelling, but based on available project data, it is currently in the research and policy-design phase rather than a commercial product.
Based on available project data, the consortium consists of 9 partners including SMEs and universities, but specific IP agreements are not listed.
The project integrates primary data from a survey of over 11,000 responses with secondary big data to build its mobility datasets.
The project period runs from 2023-06-01 to 2026-05-31.
The consortium is heavily academic with 6 universities and 1 other research-oriented entity, but maintains a 22% industry ratio through 2 SMEs and 1 larger industry partner. This suggests the output will be scientifically rigorous but may require further translation to become a commercial software tool.
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