Why is the circle not closing? : A study about circularity in the Scandinavian building industry
The building industry is a major contributor to environmental problems, due to its substantial consumption of raw materials and waste generation. Given its major environmental footprint, a transition toward more sustainable building practices is both urgent and crucial. The circular economy (CE) model has emerged as a promising approach to enhance the sustainability of the building industry. Despite increased awareness of CE and its potential economic and environmental benefits, the transition toward a more circular building industry remains limited. The widespread adoption of CE practice in this industry is hindered by several barriers, which span economic, regulatory, technical, logistical, cultural, and behavioral factors. A deeper understanding of these barriers is essential to achieve a circular building industry. This study aims to explore the barriers to CE adoption in the building industry from the perspective of four leading contractor companies in Sweden and Norway. Applying a qualitative approach, it draws on seven semi-structured interviews, document analysis of the companies annual-and sustainability reports, and a literature review to provide a deeper understanding of the barriers the building industry face in adopting CE practices. The findings of this study reveal that the transition to a circular building industry is hindered by a complex web of interconnected barriers, embedded in the economic logic, regulatory frameworks, cultural norms, and operational practices that shape the industry. This study contributes to a deeper understanding of the structural and institutional challenges that contractor companies encounter in the transition to a circular building industry. It offers valuable insights for policymakers and industry stakeholders seeking to facilitate the transition toward a more sustainable and closed -loop building industry.
Institutions
- Uppsala University (SE)
Publication Details
- Journal
- KTH Publication Database DiVA (KTH Royal Institute of Technology)
- Published
- 2025-01-01
- Primary Topic
- Machine Learning in Bioinformatics
- Type
- article
- Field-Weighted Citation Impact
- 0.00