Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques

Sarı M., Bayram S., Aydemir E.

TURKISH JOURNAL OF CIVIL ENGINEERING, cilt.37, sa.2, ss.105-136, 2026 (SCI-Expanded, Scopus, TRDizin) identifier identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 2
  • Basım Tarihi: 2026
  • Doi Numarası: 10.18400/tjce.1618975
  • Dergi Adı: TURKISH JOURNAL OF CIVIL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.105-136
  • Erciyes Üniversitesi Adresli: Evet

Özet

This study aims to predict the outcomes of construction disputes before they proceed to litigation and to foster a constructive environment between parties. Within the scope of the study, a total of 24 legal factors; 14 legal factors were identified through extensive literature review and 10 legal factors were identified through content analysis. These legal factors were used in three stages: Pre-Litigation (A, B) and Post-Litigation. Legal factors with significant relationships were tested with 24 different machine learning algorithms. NB Tree, Logit Boost and LMT algorithms achieved 63.79%, 63.66% and 86.90% accuracy for models A, B and C, respectively.