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Service quality-based distributor selection problem: a hybrid approach using fuzzy ART and AHP-FTOPSIS

Author

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  • Mazaher Ghorbani
  • S. Mohammad Arabzad
  • Reza Tavakkoli-Moghaddam

Abstract

Evaluation and selection of distributors are important issues in supply chain management (SCM) and play an important role in making new market development. This paper provides a new method to categorise and select distributors. After determining criteria according to the service quality dimensions as a novel innovation, the fuzzy adaptive resonance theory (ART) algorithm is utilised to categorise distributors according to their similarity. Then, two multi-criteria decision making (MCDM) techniques (i.e., AHP and FTOPSIS) are utilised to arrange distributors in their relative category. Finally, a numerical example is illustrated to examine the validity of the proposed algorithm. Results show that integrating MCDM techniques and neural networks can remove their deficiencies and provide comprehensive approach for partner selection in supply chain.

Suggested Citation

  • Mazaher Ghorbani & S. Mohammad Arabzad & Reza Tavakkoli-Moghaddam, 2014. "Service quality-based distributor selection problem: a hybrid approach using fuzzy ART and AHP-FTOPSIS," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 13(2), pages 157-177.
    • Handle: RePEc:ids:ijpqma:v:13:y:2014:i:2:p:157-177
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    Cited by:

    1. Fatemeh Akhyani & Alireza Komeili Birjandi & Reza Sheikh & Shib Sankar Sana, 2022. "New approach based on proximity/remoteness measurement for customer classification," Electronic Commerce Research, Springer, vol. 22(2), pages 267-298, June.

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