Araştırma Makalesi

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

Cilt: 37 Sayı: 2 2 Mart 2026
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Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques

Öz

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.

Anahtar Kelimeler

Destekleyen Kurum

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK)

Proje Numarası

122G126

Etik Beyan

Yazarlar, bu çalışmada rapor edilen çalışmayı etkilemiş gibi görünebilecek bilinen hiçbir rakip mali çıkarları veya kişisel ilişkileri olmadığını beyan ederler.

Teşekkür

Mahmut SARI'nın doktora tezinden yola çıkılarak hazırlanan bu çalışma, Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK) tarafından Sosyal ve Beşeri Bilimler Alanında Yenilikçi Çözümler Araştırma Projeleri Destekleme Programı (3005) kapsamında 122G126 hibe kapsamında desteklenmiştir.

Kaynakça

  1. Giang, D.T.H. and L. Sui Pheng, Role of construction in economic development: Review of key concepts in the past 40 years. Habitat International, 2011. 35(1): p. 118-125.
  2. Ringen, K. and A. Englund, The Construction Industry. Annals of the New York Academy of Sciences, 2006. 1076(1): p. 388-393.
  3. Iliev, B.Z., World Construction Market. Review of Business and Economics Studies, 2019. 7: p. 32-36.
  4. Lean, C.S., Empirical tests to discern linkages between construction and other economic sectors in Singapore. Construction Management and Economics, 2001. 19(4): p. 355-363.
  5. Jaber, F.K., N.A. Jasim, and F.M. Al-Zwainy, Forecasting techniques in construction industry: earned value indicators and performance models. Scientific Review Engineering and Environmental Sciences (SREES), 2020. 29(2): p. 234-243.
  6. Li, J., D. Greenwood, and M. Kassem, Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases. Automation in construction, 2019. 102: p. 288-307.
  7. Mengistu, D.G. and G. Mahesh, Challenges in developing the Ethiopian construction industry. African Journal of Science, Technology, Innovation and Development, 2020. 12(4): p. 373-384.
  8. Fenn, P., D. Lowe, and C. Speck, Conflict and dispute in construction. Construction Management and Economics, 1997. 15(6): p. 513-518.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yapı İşletmesi

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

20 Ekim 2025

Yayımlanma Tarihi

2 Mart 2026

Gönderilme Tarihi

13 Ocak 2025

Kabul Tarihi

19 Ekim 2025

Yayımlandığı Sayı

Yıl 2026 Cilt: 37 Sayı: 2

Kaynak Göster

APA
Sarı, M., Bayram, S., & Aydemir, E. (2026). Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques. Turkish Journal of Civil Engineering, 37(2), 105-136. https://doi.org/10.18400/tjce.1618975
AMA
1.Sarı M, Bayram S, Aydemir E. Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques. tjce. 2026;37(2):105-136. doi:10.18400/tjce.1618975
Chicago
Sarı, Mahmut, Savaş Bayram, ve Emrah Aydemir. 2026. “Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques”. Turkish Journal of Civil Engineering 37 (2): 105-36. https://doi.org/10.18400/tjce.1618975.
EndNote
Sarı M, Bayram S, Aydemir E (01 Mart 2026) Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques. Turkish Journal of Civil Engineering 37 2 105–136.
IEEE
[1]M. Sarı, S. Bayram, ve E. Aydemir, “Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques”, tjce, c. 37, sy 2, ss. 105–136, Mar. 2026, doi: 10.18400/tjce.1618975.
ISNAD
Sarı, Mahmut - Bayram, Savaş - Aydemir, Emrah. “Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques”. Turkish Journal of Civil Engineering 37/2 (01 Mart 2026): 105-136. https://doi.org/10.18400/tjce.1618975.
JAMA
1.Sarı M, Bayram S, Aydemir E. Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques. tjce. 2026;37:105–136.
MLA
Sarı, Mahmut, vd. “Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques”. Turkish Journal of Civil Engineering, c. 37, sy 2, Mart 2026, ss. 105-36, doi:10.18400/tjce.1618975.
Vancouver
1.Mahmut Sarı, Savaş Bayram, Emrah Aydemir. Early Prediction of Construction Disputes: Decision Support Systems with Machine Learning Techniques. tjce. 01 Mart 2026;37(2):105-36. doi:10.18400/tjce.1618975