Performance measurement of debt collection firms using spherical fuzzy aggregation operators

Cengiz Kahraman*, Sezi Cevik Onar, Basar Oztaysi

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9 Atıf (Scopus)

Özet

Debt collection is a problematic area of the lenders. When the lenders cannot collect their debts, they rent debt collection firms for their debts to be collected from borrowers. Selection among numerous collection firms is another challenging problem with several criteria under uncertainty. Based on the past performances of the collection firms, we rank these firms using a spherical fuzzy multiattribute decision making approach. Spherical fuzzy sets are a new extension of ordinary fuzzy sets developed by Kutlu Gundogdu and Kahraman [1] based on the independent membership, nonmembership, and hesitancy degrees on the unit sphere. The proposed multiattribute decision making method uses aggregation operators for spherical fuzzy sets and score functions. We present the application of a real project in Turkey.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIntelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference
EditörlerCengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga
YayınlayanSpringer Verlag
Sayfalar506-514
Sayfa sayısı9
ISBN (Basılı)9783030237554
DOI'lar
Yayın durumuYayınlandı - 2020
EtkinlikInternational Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey
Süre: 23 Tem 201925 Tem 2019

Yayın serisi

AdıAdvances in Intelligent Systems and Computing
Hacim1029
ISSN (Basılı)2194-5357
ISSN (Elektronik)2194-5365

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???event.eventtypes.event.conference???International Conference on Intelligent and Fuzzy Systems, INFUS 2019
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot23/07/1925/07/19

Bibliyografik not

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

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