Journals / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2014 / Cilt: 32 - Sayı: 2

A MCDM APPROACH WITH FUZZY DEMATEL AND FUZZY TOPSIS FOR 3PL PROVIDER SELECTION

Pages
222–239
Publication Date
2014-06-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In order to show the applicability and effectiveness of the proposed approach, a case study that consists of three decision makers, seven criteria and five alternatives is obtained to select two cargo companies for a firm that produces heat systems and wants to sell its specific products via internet.

📌 3 Key Takeaways

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Objective & Hypothesis:Especially, in the last 20 years, firms wanting to return core competencies and reduce costs are shown that they prefer outsourcing options in their logistics activities.
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Key Findings & Data:Therefore, third party logistics (3PL) provider selection is one of the most important decision making problems for the firms that using outsourcing.
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Conclusion & Impact:In order to show the applicability and effectiveness of the proposed approach, a case study that consists of three decision makers, seven criteria and five alternatives is obtained to select two cargo companies for a firm that produces heat systems and wants to sell its specific products via internet.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:3PL provider selection · multi criteria decision making · fuzzy DEMATEL

Abstract

Especially, in the last 20 years, firms wanting to return core competencies and reduce costs are shown that they prefer outsourcing options in their logistics activities. Therefore, third party logistics (3PL) provider selection is one of the most important decision making problems for the firms that using outsourcing. The selection of 3PL provider affects the success of not only the firm but also the supply chain. In this study, a multi criteria decision making approach that consists of fuzzy The Decision Making Trial and Evaluation Laboratory (DEMATEL) that is used to calculate the weights of criteria and fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is utilized to evaluate the alternatives is proposed for the selection of 3PL providers. In order to show the applicability and effectiveness of the proposed approach, a case study that consists of three decision makers, seven criteria and five alternatives is obtained to select two cargo companies for a firm that produces heat systems and wants to sell its specific products via internet.

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Cite This Article

BALİ, Ö., TUTUN, S., PALA, A., ÇÖREKÇİ, C. (2014). A MCDM APPROACH WITH FUZZY DEMATEL AND FUZZY TOPSIS FOR 3PL PROVIDER SELECTION. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 32 - Sayı: 2, 222–239. https://ajindex.com/articles/419441

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References (14)

  1. Jharkharia S.,.Shankar R, “Selection of logistics service provider: An analytic network process (ANP) approach”, Omega, 35, 274 – 289. 2007
  2. Li F., Li L., Jin C., R.Wang, et al., “3PL supplier selection model based on fuzzy sets”, Computers &OperationsResearch, 39, 1879–1884, 2012
  3. Liou J.J.H., Wang H.S., Hsu C.C., Yin S.L., “A hybrid model for selection of an outsourcing provider”, Applied Mathematical Modelling, 35, 5121–5133, 2011
  4. Marasco A., “Third-party logistics: A literature review”, International Journal of Production Economics, 113, 127–147, 2008
  5. Kulak, O. and Kahraman, C., “Fuzzy Multi-Criterion Selection Among Transportation Companies Using Axiomatic Design and Analytic Hierarchy Process”, Information Sciences, 170, 191-210, 2005
  6. Bottani, E. ve Rizzi, A., “A Fuzzy TOPSIS Methodology to Support Outsourcing of Logistic Services”, Supply Chain Management: An International Journal, 11 (4), 294-308, 2006
  7. Işıklar G., Alptekin E., Büyüközkan G., “Application of a hybrid intelligent decision support model in logistics outsourcing”, Computers & Operations Research, 34, 3701–3714, 2007
  8. Büyüközkan G., Feyzioğlu O., Nebol E., “Selection of the strategic alliance partner in logistics value chain”, International Journal of Production Economics, 113, 148–158, 2008
  9. Efendigil T., Önüt S., Kongar E., “A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness”, Computers & Industrial Engineering, 54, 269–287, 2008
  10. Kannan G., Pokharel S., Kumar P.S., “A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider”, Resources, Conservation and Recycling, 54, 28–36, 2009
  11. Liu, H.-T., Wang W.-K., “An integrated fuzzy approach for provider evaluation and selection in third-party logistics”, Expert Systems with Applications, 36, 4387–4398, 2009
  12. Liou J.J.H., Chuang Y.-T., “Developing a hybrid multi-criteria model for selection of outsourcing providers”, Expert Systems with Applications, 37, 3755–3761, 2010
  13. Chen, C.-T., Pai P.-F., Hung W.-Z., “An Integrated Methodology using Linguistic PROMETHEE and Maximum Deviation Method for Third-party Logistics Supplier Selection”, International Journal of Computational Intelligence Systems, 3, 4, 438-451, 2010
  14. Azadi M., Saen R.F., “A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors”, Expert System