A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness

  • Authors:

  • Tuğba Efendigil;Semih Önüt;Elif Kongar

  • Affiliations:

  • Department of Industrial Engineering, Yildiz Technical University, Yildiz, Istanbul, Turkey;Department of Industrial Engineering, Yildiz Technical University, Yildiz, Istanbul, Turkey;Departments of Mechanical Engineering and Technology Management, University of Bridgeport, Bridgeport, CT, USA

  • Venue:
  • Computers and Industrial Engineering
  • Year:
  • 2008

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Abstract

Growing environmental concerns have motivated businesses to carefully assess the environmental impact of their products and services at all stages of a life-cycle. Reverse logistics plays an important role in achieving ''green supply chains'' by providing customers with the opportunity to return the warranted and/or defective products to the manufacturer. An efficient reverse logistics structure may lead to a significant return on investment as well as a significantly increased competitiveness in the market. In order to ensure efficiency, many organizations outsource their reverse logistics activities by engaging third-party logistics providers that implement reverse logistics programs designed to gain value from returned products. The selection of third-party providers is a crucial step in initializing reverse logistics related practices. This study aims to efficiently assist the decision makers in determining the ''most appropriate'' third-party reverse logistics provider using a two-phase model based on artificial neural networks and fuzzy logic in a holistic manner. A numerical example is also included in the study to demonstrate the steps of the proposed model.