A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making


Yayla A. Y., Oztekin A., Gumus A., Gunasekaran A.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, vol.53, no.20, pp.6097-6113, 2015 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 53 Issue: 20
  • Publication Date: 2015
  • Doi Number: 10.1080/00207543.2015.1022266
  • Journal Name: INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.6097-6113
  • Keywords: 3PL transportation, supplier selection, business analytics, fuzzy-AHP, fuzzy-TOPSIS, multi-criteria decision making, EXTENT ANALYSIS METHOD, 3RD-PARTY LOGISTICS, TOPSIS MODEL, SELECTION, AHP, ALTERNATIVES, INDUSTRY, GOALS
  • Yıldız Technical University Affiliated: Yes

Abstract

Third-party logistics (3PL) service provider selection for a strategic alliance is not an easy decision, and is constantly associated with uncertainty and complexity. For this reason, in this study, a hybrid fuzzy multi-criteria decision-making methodology is proposed to provide a systematic decision support tool for 3PL provider evaluation, especially for 3PL transportation provider. The proposed evaluation methodology consists of several steps. First, the strategic goal and sub-attributes are identified for 3PL service provider evaluation. After constructing the hierarchy, Buckley's fuzzy-analytical hierarchy process (AHP) extension algorithm is used to determine the evaluation criteria weights. Then, by using fuzzy-AHP results as input weights, the fuzzy-Technique for Order Preference by Similarity to Ideal Solution technique is conducted in order to identify the most suitable third-party providers. Finally, a real-life case study in a confectionary company is presented to demonstrate the potential use of the methodology and a sensitivity analysis is performed to analyse the hybrid methodology proposed here. In the conclusion of the study, future recommendations are presented.