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A multi-criteria decision making model for outsourcing inbound logistics of an automotive industry using the AHP and TOPSIS

Author

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  • N. Ramkumar
  • P. Subramanian
  • M. Rajmohan

Abstract

This paper focuses on the inbound logistics segment in the supply chain of automobile companies, which are known to be highly complex. This has always affected key business functions in the supply chain with respect to cost, coordination, and material delay issues. During third party logistics service provider (TPLs) selection, practitioners have started to concentrate on coordination, integration, and cooperation as some of the key areas to improve SC performance. In this context, we propose a model for selection of TPLs network with an objective to create a favourable environment for improving coordination and integration using analytic hierarchy process (AHP) and technique for order preference by similarity to ideal situation (TOPSIS) approach. A case of an automobile company is used to explain the model and potential expected benefits are discussed. A comparative analysis on decision-making certainty between the classical AHP and TOPSIS approach is also discussed.

Suggested Citation

  • N. Ramkumar & P. Subramanian & M. Rajmohan, 2009. "A multi-criteria decision making model for outsourcing inbound logistics of an automotive industry using the AHP and TOPSIS," International Journal of Enterprise Network Management, Inderscience Enterprises Ltd, vol. 3(3), pages 223-245.
    • Handle: RePEc:ids:ijenma:v:3:y:2009:i:3:p:223-245
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    Cited by:

    1. Mustafa Batuhan Ayhan, 2018. "A New Decision Making Approach for Supplier Selection: Hesitant Fuzzy Axiomatic Design," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1085-1117, July.
    2. Saverio Ferraro & Alessandra Cantini & Leonardo Leoni & Filippo De Carlo, 2023. "Sustainable Logistics 4.0: A Study on Selecting the Best Technology for Internal Material Handling," Sustainability, MDPI, vol. 15(9), pages 1-22, April.

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