A Novel Integrated Provider Selection Multicriteria Model: The BWM-MABAC Model

  • Dmitri Muravev School of Naval Architecture, Ocean and Civil Engineering and State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, China; Nosov Magnitogorsk State Technical University, Department of Logistics and Transportation Systems Management, Mining Engineering and Transport Institute, Magnitogorsk, Russia
  • Nemanja Mijic University of defence in Belgrade, Department of logistics, Belgrade, Serbia
Keywords: Multicriteria decision-making, BWM, MABAC, MAIRCA, VIKOR, Supply chain


The supply chain is a very complex area aimed at obtaining the optimum from the point of view of all participants. In order to achieve the overall optimum and satisfaction of all participants, it is necessary to make an adequate evaluation and selection of providers at the initial stage. In this paper, the selection of providers is based on a new approach in the field of multicriteria decision-making. The weight coefficients were determined using the Best-Worst Method (BWM), whereas provider evaluation and selection were performed using the Multi-Attributive Border Approximation Area Comparison (MABAC) method, which is one of more recent methods in this field. In order to determine the stability of the model and the applicability of the proposed hybrid BWM-MABAC model, the results were compared with the MAIRCA and VIKOR models, and the results of the comparative analysis are presented herein. In addition, a total of 18 different scenarios were formed in the sensitivity analysis, in which the criteria change their original value. At the end of the sensitivity analysis, the statistical dependence of the results was determined using Spearman's correlation coefficient, which confirmed the applicability of the proposed multicriteria approaches.


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How to Cite
Muravev, D., & Mijic, N. (2020). A Novel Integrated Provider Selection Multicriteria Model: The BWM-MABAC Model. Decision Making: Applications in Management and Engineering, 3(1), 60-78. https://doi.org/10.31181/dmame2003078m