UNRAVELING CIRCULAR ECONOMY DYNAMICS IN THE EU: A BAYESIAN NETWORK ANALYSIS


Çinicioğlu E. N.

ECO4ALL mid-term International Conference, Iasi, Romanya, 9 - 10 Mayıs 2025, ss.134-143, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.47743/eco4all.2025.1.9
  • Basıldığı Şehir: Iasi
  • Basıldığı Ülke: Romanya
  • Sayfa Sayıları: ss.134-143
  • İstanbul Üniversitesi Adresli: Evet

Özet

This study applies Bayesian Network (BN) modelling to assess changes in the interdependencies among key Circular economy (CE) indicators across two timeframes:2012-2016 and 2017-2021. Using data from EURUSTAT monitoring framework, we analyse how variables such as material footprint, material import dependency, and private investment in Circular Economy interact over time. Structure learning is conducted separately for each period, followed by posterior updates based on selected evidence. The results reveal a temporal shift in material sourcing. While high material consumption in the earlier period is primarily supported by domestic resources, the later period showed increased dependency on imported materials under similar conditions. Furthermore, high private investment in Circular economy does not automatically reduce material import dependency and may coincide with higher external reliance, suggesting delayed impacts or structural limitations.