An integrated supplier selection methodology incorporating QFD and DEA with imprecise data

KARSAK E. E., DURSUN M.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.41, sa.16, ss.6995-7004, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 41 Sayı: 16
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1016/j.eswa.2014.06.020
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.6995-7004
  • Anahtar Kelimeler: Decision support, Supplier selection, Quality function deployment, Data envelopment analysis, Fuzzy weighted average, DATA ENVELOPMENT ANALYSIS, PRIORITIZE DESIGN REQUIREMENTS, QUALITY FUNCTION DEPLOYMENT, FUZZY-PROGRAMMING APPROACH, DECISION-MAKING, ORDINAL DATA, AHP APPROACH, MODEL, CHAIN, MANAGEMENT
  • Galatasaray Üniversitesi Adresli: Evet

Özet

Supplier evaluation and selection is an important group decision making problem that involves not only quantitative criteria but also qualitative factors incorporating vagueness and imprecision. This paper proposes a novel fuzzy multi-criteria group decision making framework for supplier selection integrating quality function deployment (QFD) and data envelopment analysis (DEA). The proposed methodology allows for considering the impacts of inner dependence among supplier assessment criteria through constructing a house of quality (HOQ). The lower and upper bounds of the weights of supplier assessment criteria are identified by adopting fuzzy weighted average (FWA) method that enables the fusion of imprecise and subjective information expressed as linguistic variables. An imprecise DEA methodology is implemented for supplier selection, which employs the weights of supplier assessment criteria computed by FWA utilizing the data from the HOQ and the supplier ratings with respect to supplier assessment criteria. The application of the proposed framework is demonstrated through a case study in a private hospital in Istanbul. (C) 2014 Elsevier Ltd. All rights reserved.