Appraisement and selection of third party logistics service providers in fuzzy environment

Purpose – The purpose of this paper is to develop a decision‐making procedural hierarchy for evaluation as well as selection of third‐party reverse logistics provider (3PL) under fuzzy environment.Design/methodology/approach – Due to uncertainty, vagueness arising from decision makers (DM) subjective judgment towards intangible (qualitative) selection criteria, fuzzy logic has been utilized to facilitate such a decision‐making process for 3PL evaluation and selection.Findings – Evaluating and selecting 3PL providers can be regarded as a multi‐criteria decision making (MCDM) process in which a decision maker chooses, under several selection criteria, the best suited alternative. The present study highlights a case study on evaluation and selection of 3PL service providers for a reputed Indian automobile part manufacturing company. The fuzzy based decision‐making tool applied here has been proved fruitful for its effectiveness.Research limitations/implications – There are many research issues remaining in t...

[1]  S. Hertz,et al.  Strategic development of third party logistics providers , 2003 .

[2]  Wei-Kai Wang,et al.  An integrated fuzzy approach for provider evaluation and selection in third-party logistics , 2009, Expert Syst. Appl..

[3]  Rajesh Gupta,et al.  Selection of 3pl Service Provider using Integrated Fuzzy Delphi and Fuzzy TOPSIS , 2010 .

[4]  S. Soh,et al.  A decision model for evaluating third-party logistics providers using fuzzy analytic hierarchy process , 2010 .

[5]  Geon Cho,et al.  Evaluating the service quality of third- party logistics service providers using the analytic hierarchy process , 2006 .

[6]  Ozalp Vayvay,et al.  A METHOD FOR SELECTING THIRD PARTY LOGISTIC SERVICE PROVIDER USING FUZZY AHP , 2009 .

[7]  T. Skjoett‐Larsen,et al.  Third party logistics – from an interorganizational point of view , 2000 .

[8]  C. Chou,et al.  MIDDLE MANAGERS SELECTION FOR THIRD-PARTY LOGISTICS SERVICE PROVIDERS , 2011 .

[9]  Martin Spring,et al.  Third party logistics : a literature review and research agenda , 2007 .

[10]  Wenli Li,et al.  An information granulation entropy-based model for third-party logistics providers evaluation , 2012 .

[11]  H. Zimmermann.  Fuzzy sets, decision making, and expert systems , 1987 .

[12]  Pradeep Kumar,et al.  Analytical modeling of third party service provider selection in lead logistics provider environments , 2010 .

[13]  Shaligram Pokharel,et al.  A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider , 2009 .

[14]  Shuo-Yan Chou,et al.  A revised method for ranking fuzzy numbers using maximizing set and minimizing set , 2011, Comput. Ind. Eng..

[15]  Pao-Long Chang,et al.  A fuzzy multi-criteria decision making method for technology transfer strategy selection in biotechnology , 1994 .

[16]  Dinesh Kumar,et al.  A loss function based decision support model for 3PL selection by 4PLs , 2010 .

[17]  Ying Luo,et al.  Area ranking of fuzzy numbers based on positive and negative ideal points , 2009, Comput. Math. Appl..

[18]  Tugba Efendigil,et al.  A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness , 2008, Comput. Ind. Eng..

[19]  Kannan Govindan,et al.  Selection of third party reverse logistics provider using Fuzzy extent analysis , 2011 .