Circular Economy-Based Decision-Making Model for Contractor Selection

DEMİRBAĞ A. T., ALADAĞ H., IŞIK Z., Skibniewski M. J.

Buildings, cilt.15, sa.10, 2025 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15 Sayı: 10
  • Basım Tarihi: 2025
  • Doi Numarası: 10.3390/buildings15101665
  • Dergi Adı: Buildings
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: circular economy, contractor selection, fuzzy AHP, fuzzy TOPSIS, off-site construction
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Increasing environmental pollution has reinforced the necessity of implementing circular economy (CE) as a sustainable approach to reducing resource consumption, waste generation, and carbon emissions. Despite the construction industry’s significant environmental impact in terms of global carbon emissions, water consumption, and biodiversity loss, only 12% of its materials exhibit circular characteristics, necessitating improvements in terms of circularity in construction projects. This study develops a CE-based decision-making model for contractor selection, focusing on off-site construction (OSC), which offers greater circularity potential than conventional construction methods. The decision-making model, established through literature analysis and expert discussions, utilizes the fuzzy analytic hierarchy process (AHP) to evaluate CE criteria and employ the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine contractor suitability. The findings indicate that Material Circularity, Energy Circularity, and Product Circularity are the most influential criteria, with green procurement emerging as the highest-priority factor. The model was validated through a hypothetical case study involving four contractors experienced in sustainable construction. The results demonstrate the model’s capacity to produce sensitive outcomes in terms of decision-making.