A hybrid approach for predicting customers' individual purchase behavior

Peker S., KOÇYİĞİT A., EREN P. E.

KYBERNETES, cilt.46, sa.10, ss.1614-1631, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 46 Sayı: 10
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1108/k-05-2017-0164
  • Dergi Adı: KYBERNETES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1614-1631
  • Anahtar Kelimeler: Customer behavior models, Personalization, Machine learning, Customer segmentation, Hybrid approach, Predictive modeling, RECOMMENDER SYSTEMS, CONTEXT
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Purpose - Predicting customers' purchase behaviors is a challenging task. The literature has introduced the individual-level and the segment-based predictive modeling approaches for this purpose. Each method has its own advantages and drawbacks, and performs in certain cases. The purpose of this paper is to propose a hybrid approach which predicts customers' individual purchase behaviors and reduces the limitations of these two methods by combining the advantages of them.