The goal of IJTTE is to broaden the knowledge of traffic and transport experts and academicians by promoting free access and provide valuable insight to transport related information, research and ideas. IJTTE will serve as a great resource for researchers and students across the globe.
Volume List  / Volume 9 (3)

Article

A FUZZY- AHP APPROACH TO EVALUATE THE CRITERIA OF THIRD -PARTY LOGISTICS (3PL) SERVICE PROVIDER

DOI: 10.7708/ijtte.2019.9(3).02


9 / 3 / 280-289 Pages

Author(s)

Stefan Jovčić - University of Pardubice, Faculty of Transport Engineering, Pardubice, Czech Republic -

Petr Průša - University of Pardubice, Faculty of Transport Engineering, Pardubice, Czech Republic -

Josef Samson - University of Pardubice, Faculty of Transport Engineering, Pardubice, Czech Republic -

Dragan Lazarević - University of Belgrade, Faculty of Transport and Traffic Engineering, Belgrade, Serbia -


Abstract

This paper deals with the criteria that should be taken into consideration when making a decision about Third-Party Logistics (3PL) service providers and their evaluation. Not all the criteria is equally important, so it is necessary to evaluate them in order to determine the priority and help the company to make a decision. The criteria for 3PL assessment were defined by consulting several experts in the field of logistics. It is very important to analyze and evaluate 3PL providers because there are a very large number of providers in the market and for the company it is very important to choose the right one, based on the relevant criteria. The methodology used for evaluation of the criteria is based on Fuzzy-AHP (Analytic Hierarchy Process) approach. This approach combines the Saaty’s scale (which gives the value of most importance in the statements-criteria) and fuzzy logic (which deals with the linguistic statements). The main result of the paper is to rank the criteria by importance and direct it for the further research in the field of 3PL.


Download Article

Number of downloads: 834

Keywords:
Third-Party Logistics (3PL) Service Provider; Fuzzy-AHP approach; 3PL evaluation criteria;


Acknowledgements:

This research paper was supported by SGS_2019_010.


References:

Akman, G.; Baynal, K. 2014. Logistics Service Provider Selection through an Integrated Fuzzy-Multi-criteria Decision Making Approach, Journal of Industrial Engineering: 16 pages.

 

Awasthi, A.; Govindan, K.; Gold, S. 2018. Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach, International Journal of Production Economics 195: 106-117.

 

Ayhan, B. M. 2013. A Fuzzy-AHP approach for supplier selection problem: A case study in a gear-motor company, International Journal of Managing Value and Supply Chains 4(3): 11-23.

 

Buckley, J. J. 1985. Fuzzy hierarchical analysis, Fuzzy Sets Systems 17(1): 233–247.

 

Chou, S-W.; Chang, Y-C. 2008. The implementation factors that influence the ERP (Enterprise Resource Planning) Benefits, Decision Support Systems 46(1): 149-157.

 

Cooper, O.; Tadikamalla, P.; Shang, J. 2012. Selection of a Third-Party Logistics Provider: Capturing the Interaction and Influence of Performance Metrics with the Analytical Network Process. J. Multi Crit. Decis. Anal. 19: 115–128, doi:10.1002/mcda.489.

 

Daugherty, PJ.; Stank, TP.; Rogers, DS. 1996. Third-Party Logistics Service providers: purchasers’ perceptions, International Journal of Purchasing and Materials Management 32(1): 23-9.

 

Guneri, A.F.; Yucel, A.; Ayyildiz, G. 2009. An integrated fuzzy-lp approach for a supplier selection problem in supply chain management, Expert Syst. Appl. 36: 9223–9228.

 

Jonas Yu, C.P. 2016. 3PL Implementing Corporate Social Responsibility in a Closed-loop Supply Chain: A Conceptual Approach Department of Distribution Management. Takming University of Science and Technology 56, Taipei City, Taiwan.

 

Junior, F.R.L.; Osiro, L.; Carpinetti, L.C.R. 2014. A comparison between Fuzzy AHP and Fuzzy TOPSIS methods to supplier selection, Applied Soft Computing 21: 194–209.

 

Kabir, G. 2012. Third party logistic service provider selection using fuzzy AHP and TOPSIS method, International Journal for Quality Research 6(1): 71-79.

 

Kannan, G.; Pokharel, S.; Kumar, P.S. 2009. A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider, Resources, Conservation and Recycling 54(1): 28–36.

 

Kilincci, O.; Onal, S.A. 2011. Fuzzy AHP approach for supplier selection in a washing machine company, Expert Systems with Applications 38(8): 9656-9664.

 

Mangla, S.K.; Kumar, P.; Barua, M.K. 2015. Risk analysis in green supply chain using fuzzy AHP approach: A case study. Resources, Conservation and Recycling 104: 375–390.

 

Menon, M.; McGinnis, M; Ackerman, K. 1998. Selection criteria for providers of third-party logistics services: an exploratory study, Journal of Business Logistics 19(1): 121–137.

 

Önüt, S.; Kara, S.S.; Işık, E. 2009. Long Term Supplier Selection Using a Combined Fuzzy MCDM Approach: A Case Study for a Telecommunication Company, Expert Systems with Applications 36(2): 3887-3895.

 

Perçin, S. 2008. Fuzzy multi-criteria risk-benefit analysis of business process outsourcing (BPO), Inf. Manag. Comput. Secur. 16: 213–234, doi:10.1108/09685220810893180.

 

Rattanawiboonsom, V. 2014. Effective Criteria for Selecting Third-Party logistics Providers: The Case of Thai Automotive Industry Rattanawiboonsom, World Rev. Bus. Res. 4: 196–205.

 

Rezaei, J.; Ortt, R. 2013. Multi-criteria supplier segmentation using a fuzzy preference relations based AHP, European Journal of Operational Research 225: 75–84.

 

Tadić, S.; Zečević, S.; Krstić, M. 2015. Ranking of Logistics System Scenarios Using Combined Fuzzy AHP-VIKOR Model, International Journal for Traffic and Transport Engineering 5(1): 54 – 63.

 

Tadić, S.; Zečević, S.; Krstić, M. 2014a. Ranking of Logistics System Scenarios for Central Business District, Promet – Traffic&Transportation 26(2): 159-167.

 

Tadić, S.; Zečević, S.; Krstić, M. 2014b. Combined fuzzy AHP-TOPSIS model for regional logistics conceptions evaluation, In Proceedings of XLI Symposium on Operations Research (SYM-OP-IS), Divčibare, 311-316.

 

Tadić, S.; Zečević, S.; Krstić, M. 2013a. Locating city logistics terminal using fuzzy AHP analysis – Case of Belgrade (in Serbian), Tehnika 68(4): 707-716.

 

Tadić, S.; Zečević, S.; Krstić, M. 2013b. Evaluation of regional logistics conceptions, In Proceedings of XL Symposium on Operations Research (SYM-OP-IS), Zlatibor, 515-521.

 

Tadić, S.; Zečević, S.; Krstić, M. 2012. City logistics terminal location selection using combined fuzzy AHP and fuzzy TOPSIS analysis, In Proceedings of the International conference on traffic and transport engineering, ICTTE, Belgrade, Serbia, 345-358.

 

Tsai, W.C. 2009. Fuzzy Measures of Supplier Evaluation under Lean Concepts, J. Oper. Res. Soc. 60: 1005–1011, doi:10.1057/palgrave.jors.2602643.

 

Vaidyanathan, G. A 2005. Framework for Evaluating Third-Party Logistics, Commun. ACM 48: 89–94, doi:10.1145/1039539.1039544.

 

Vijayvargiya, A.; Dey, A.K. 2010. An analytical approach for selection of a logistics provider, Management Decision (48)3: 403-418.

 

Yang, Y.; Hui,V. Y.; Chen, G. 2010. An analytic network process approach to the selection of logistics service providers for air cargo, Journal of the Operational Research Society 61(9): 1365-1376.

 

Zečević, S.; Tadić, S.; Krstić, M. 2016. Selection of the intermodal transport chain variant using AHP method, In Proceedings of the 3rd International Conference on Traffic and Transport Engineering - ICTTE, Belgrade, Serbia, 339-345.

 

Zečević, S.; Tadić, S.; Krstić, M. 2014. Ranking of logistics system scenarios using combined fuzzy AHP-VIKOR model, In Proceedings of XLI Symposium on Operations Research (SYM-OP-IS), Divčibare, 323-328.


Quoted IJTTE Works

RANKING OF LOGISTICS SYSTEM SCENARIOS USING COMBINED FUZZY AHP-VIKOR MODEL



Related Keywords

There is no related studies.