A hybrid quality function deployment and fuzzy decision-making methodology for the optimal selection of third-party logistics service providers

PERÇİN S., Min H.

INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS, cilt.16, sa.5, ss.380-397, 2013 (SSCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 5
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1080/13675567.2013.815696
  • Dergi Adı: INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.380-397
  • Anahtar Kelimeler: 3PL selection, quality function deployment, fuzzy linear regression, case study, ANALYTIC NETWORK PROCESS, LINEAR-REGRESSION, PROGRAMMING-MODEL, EFFICIENCY, AHP
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

As the third-party logistics service provider (3PL) industry continues to grow, the optimal selection of a 3PL has become one of the most challenging tasks due to a larger pool of qualified 3PLs and their variety of service offerings. This challenge calls for a systematic decision-aid tool which can not only handle the increased complexity of 3PL selection problems, but also reflect the realities of logistics outsourcing issues that cannot be easily quantified. The paper aims to propose a hybrid quality function deployment (QFD) and fuzzy decision-making methodology for solving 3PL evaluation/selection problem. First, QFD is utilised to structure specific customer service needs and match those needs to the characteristics of 3PL candidates. Fuzzy linear regression is then employed to determine a functional relationship between the 3PL user's logistics service needs and the 3PL characteristics. Finally, a zero-one goal programming model is used to select the most desirable 3PL under multiple decision criteria.