A multi-criteria evaluation model based on hesitant fuzzy sets for blockchain technology in supply chain management


Colaka M., KAYA İ., ÖZKAN B., Budakc A., KARAŞAN A.

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, cilt.38, ss.935-946, 2020 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 38 Konu: 1
  • Basım Tarihi: 2020
  • Doi Numarası: 10.3233/jifs-179460
  • Dergi Adı: JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
  • Sayfa Sayıları: ss.935-946

Özet

Nowadays, more companies are trying to implement blockchain technology (BT) that enables to increase the quality of the products/services to their supply chains in order to improve their performance. BT can be applied to different sectors according to their specific needs. Evaluation of BT with respect to sectors needs considering several factors and it can be considered as a multi criteria decision making (MCDM) problem. In this paper, the appropriateness of BT in Supply Chain Management (SCM) according to different sectors has been evaluated by using a MCDM methodology based on hesitant fuzzy sets (HFSs). The suggested MCDM methodology consists of Delphi method, hesitant fuzzy Analytic Hierarchy Process (HF-AHP) and Hesitant Fuzzy Technique for Order Preference by Similarity to Ideal Solution (HF-TOPSIS) methods. In the first stage, the criteria and sub-criteria utilized for performance evaluation of BT in supply chain management have been determined by using Delphi method. The weights of main and sub-criteria have been obtained through HF-AHP method and finally, the alternative sectors have been ranked according to results of HF-TOPSIS method. For this aim, a hierarchical MCDM problem that consists of 5 main and 17 sub-criteria has been created and the alternative sectors have been evaluated. As a result, medicine/drug and jewelry sectors have been respectively determined as the most and the least suitable alternatives in order to implement BT by means of the proposed HFSs based methodology. Finally, a sensitivity analysis has been conducted to show the importance of the main criteria weights on ranking of alternatives.