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Oikopolkuja

Linear to circular through sustainable management approaches and data-driven business models

Linear to circular

Aika

2.1.2025 – 31.12.2026

Koordinaattori/Päätoteuttaja

Åbo Akademi

Yhteistyökumppanit

  • Turun yliopisto
  • Valmet (Finland)
  • Forcit
  • Enersense

Rahoittaja

  • Business Finland (Beyond circularity (Valmet veturi) )

Budjetti

637 374 euroa

Åbo Akademin osuus budjetista

637 374 euroa (100%)

In tackling the waste-to-value challenge, an array of cutting-edge technologies, innovative business models, and pioneering services must be utilized. Such eco-innovations are pivotal for a circular economy and sustainable growth and accelerate the green transition, thus underpinning its socio-economic importance. The L2C project focuses on two central opportunities in the circular economy: novel data-driven lifecycle services and new technologies for closing material loops in industrial processes. Both areas are essential for developing a holistic, lifecycle-oriented approach to circular economy. An essential driver is the potential to revitalize existing plants that are classified as stranded assets (not environmentally or financially acceptable) to become sustainable through improvements and implementation of new technology. Closing material loops in industrial processes to enhance material efficiency refers both to existing circular processes and to linear processes which can be converted into circular processes. This is a key opportunity and challenge for industries providing components of the circular solution: identifying linear businesses that could in the future be circular.
This project aspires to create scalable, data-driven business models, significant for the companies involved and their global partners and customers. The challenge of developing these models comes with a few obstacles, often related to data accessibility, technological readiness, regulatory issues, and mindset barriers. To overcome these hurdles, root cause analyses are needed, supported by other frameworks that identify potential inefficiencies in different industry segments.

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