Third-party logistics (3Pls) provider selection via Fuzzy AHP and EDAS integrated model

In the global competitive environment, companies not only improve the quality of service and increase the efficiency, they also decrease the cost by means of third-party logistics (3PLs). 3PLs, therefore, is an important strategy for companies desiring to gain a competitive advantage and 3PLs provider selection plays a critical role for the success of outsourcing. Nevertheless, the level of uncer­tainty in the selection process is relatively high and need to be carefully considered. Hence, in order to select a proper 3PLs provider, integration of the Fuzzy AHP and Evaluation based on Distance from Average Solution (EDAS) has offered a novel integrated model, in which Fuzzy AHP is used for calculating priority weights of each criteria and EDAS is employed to achieve the final ranking of 3PLs providers. Besides, in order to demonstrate the applicability of the proposed model, it is validated by a case study. Cost together with quality, and professionalism are found to be the most important factors for 3PLs provider selection. Consequently, the advantage of this model is that it is simple to apprehend and easy to apply. The use of the proposed model leads to the selection of suitable alternative successfully in other selection problems. First published online: 23 Apr 2017

[1]  MardaniAbbas,et al.  Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014 , 2015 .

[2]  Hayri Baraçli,et al.  A fuzzy multi-criteria decision making methodology based upon the interval type-2 fuzzy sets for evaluating renewable energy alternatives in Turkey , 2015 .

[3]  Adiel Teixeira de Almeida,et al.  Multicriteria decision model for outsourcing contracts selection based on utility function and ELECTRE method , 2007, Comput. Oper. Res..

[4]  An-Chin Cheng.  A fuzzy multiple criteria comparison of technology valuation methods for the new materials development , 2013 .

[5]  Aicha Aguezzoul,et al.  Third-party logistics selection problem: A literature review on criteria and methods , 2014 .

[6]  Ali Emrouznejad,et al.  Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach , 2012, Expert Syst. Appl..

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

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

[9]  AlkhatibSaleh Fahed,et al.  A novel technique for evaluating and selecting logistics service providers based on the logistics resource view , 2015 .

[10]  Wen-Chin Chou,et al.  A hybrid fuzzy MCDM approach for evaluating website quality of professional accounting firms , 2012, Expert Syst. Appl..

[11]  Edmundas Kazimieras Zavadskas,et al.  Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014 , 2015, Expert Syst. Appl..

[12]  Ravi Shankar,et al.  Selection of logistics service provider: An analytic network process (ANP) approach , 2007 .

[13]  Edmundas Kazimieras Zavadskas,et al.  Market Segment Evaluation and Selection Based on Application of Fuzzy AHP and COPRAS-G Methods , 2012 .

[14]  Jurgita Antucheviciene,et al.  Applying fuzzy MCDM for financial performance evaluation of Iranian companies , 2014 .

[15]  Massimiliano M. Schiraldi,et al.  A logistics provider evaluation and selection methodology based on AHP, DEA and linear programming integration , 2011 .

[16]  E. Zavadskas,et al.  Performance evaluating of rural ICT centers (telecenters), applying fuzzy AHP, SAW-G and TOPSIS Grey, a case study in Iran , 2012 .

[17]  Gülçin Büyüközkan,et al.  Application of a hybrid intelligent decision support model in logistics outsourcing , 2007, Comput. Oper. Res..

[18]  Aidas Vasilis Vasiliauskas,et al.  Principle and benefits of third party logistics approach when managing logistics supply chain , 2007 .

[19]  Teixeira de AlmeidaAdiel.  Multicriteria decision model for outsourcing contracts selection based on utility function and ELECTRE method , 2007 .

[20]  Tien-Chin Wang,et al.  Optimizing partners’ choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR , 2009 .

[21]  J. Korpela,et al.  An Integrated Approach for Truck Carrier Selection , 1999 .

[22]  BüyüközkanGülçin,et al.  Application of a hybrid intelligent decision support model in logistics outsourcing , 2007 .

[23]  Chao-Che Hsu,et al.  Integrating DANP and modified grey relation theory for the selection of an outsourcing provider , 2013, Expert Syst. Appl..

[24]  Angappa Gunasekaran,et al.  A hybrid data analytic methodology for 3PL transportation provider evaluation using fuzzy multi-criteria decision making , 2015 .

[25]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[26]  Golam Kabir.  THIRD PARTY LOGISTIC SERVICE PROVIDER SELECTION USING FUZZY AHP AND TOPSIS METHOD , 2012 .

[27]  S. G. Deshmukh,et al.  Selection of Third-Party Logistics (3PL): A Hybrid Approach Using Interpretive Structural Modeling (ISM) and Analytic Network Process (ANP) , 2005 .

[28]  Felix T. S. Chan,et al.  Design of a knowledge-based logistics strategy system , 2005, Expert Syst. Appl..

[29]  T. Baležentis,et al.  An integrated assessment of Lithuanian economic sectors based on financial ratios and fuzzy MCDM methods , 2012 .

[30]  Gülşen Akman,et al.  Logistics Service Provider Selection through an Integrated Fuzzy Multicriteria Decision Making Approach , 2014 .

[31]  Alev Taskin Gumus,et al.  Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology , 2009, Expert Syst. Appl..

[32]  Ö. Aydin,et al.  A new software development for Fuzzy Multicriteria decision‐making , 2009 .

[33]  Edmundas Kazimieras Zavadskas,et al.  Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS) , 2015, Informatica.

[34]  Hokey Min,et al.  A hybrid quality function deployment and fuzzy decision-making methodology for the optimal selection of third-party logistics service providers , 2013 .

[35]  Kim Hua Tan,et al.  Leveraging the supply chain flexibility of third party logistics - Hybrid knowledge-based system approach , 2008, Expert Syst. Appl..

[36]  Trung Thanh Nguyen,et al.  A novel technique for evaluating and selecting logistics service providers based on the logistics resource view , 2015, Expert Syst. Appl..

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

[38]  Fatih Ecer,et al.  A hybrid banking websites quality evaluation model using AHP and COPRAS-G: a Turkey case , 2014 .

[39]  Andrius Jarzemskis.  Determination and Evaluation of the Factors of Outsourcing Logistics , 2006 .

[40]  James J. H. Liou,et al.  Developing a hybrid multi-criteria model for selection of outsourcing providers , 2010, Expert Syst. Appl..

[41]  A. Rizzi,et al.  A fuzzy TOPSIS methodology to support outsourcing of logistics services , 2006 .

[42]  Gwo-Hshiung Tzeng,et al.  Fuzzy MCDM approach for planning and design tenders selection in public office buildings , 2004 .

[43]  R. Banomyong,et al.  Selecting logistics providers in Thailand: a shippers' perspective , 2011 .

[44]  Cengiz Kahraman,et al.  Fuzzy multicriteria evaluation of health research investments , 2014 .

[45]  Zhang Ying,et al.  Study on the third party logistics service providers' performance evaluation based on the weighted entropy and analysis process of grey relation , 2010, 2010 International Conference on Management Science & Engineering 17th Annual Conference Proceedings.

[46]  Vinod Kumar,et al.  Optimal selection of third-party logistics service providers using quality function deployment and Taguchi loss function , 2015 .

[47]  Zeger Degraeve,et al.  Total cost of ownership purchasing of a service: The case of airline selection at Alcatel Bell , 2004, Eur. J. Oper. Res..

[48]  Lei Gao,et al.  Identifying preferred management options: an integrated agent-based recreational fishing simulation model with an AHP-TOPSIS evaluation method. , 2013 .

[49]  F. Ecer.  Turkey PERFORMANCE EVALUATION OF INTERNET BANKING BRANCHES VIA A HYBRID MCDM MODEL UNDER FUZZY ENVIRONMENT , 2015 .

[50]  Gülçin Büyüközkan,et al.  Selection of the strategic alliance partner in logistics value chain , 2008 .