scholarly journals CPT-TODIM METHOD FOR INTERVAL NEUTROSOPHIC MAGDM AND ITS APPLICATION TO THIRD-PARTY LOGISTICS SERVICE PROVIDERS SELECTION

2021 ◽  
Vol 0 (0) ◽  
pp. 1-19
Author(s):  
Dan Zhang ◽  
Yong Su ◽  
Mengwei Zhao ◽  
Xudong Chen

The multiple attribute group decision making (MAGDM) has always been a concern in the research field. In this article, we establish the interval neutrosophic TODIM method based on cumulative prospect theory (CPT-IN-TODIM) for MAGDM issue. This new developed CPTIN-TODIM method has markedly superiority in describing decision maker’s psychological states, which utilizes the weight function to adjust weighting attributes distinguishing from the classical TODIM method. Then, this new developed method has been applied to select the third-party logistics service providers and been expound on the disparity with existing methods. Finally, the results of contrastive analysis indicate that this new developed method can lead to the appropriate conclusion and sticks out the differences between alternatives to provide clearer direction. Hence, the new developed CPT-IN-TODIM method is reliable and valid.

2021 ◽  
Vol 12 (1) ◽  
pp. 135-146
Author(s):  
E.A. Ejem ◽  
C.M. Uka ◽  
D.N. Dike ◽  
C.C. Ikeogu ◽  
C.C. Igboanusi ◽  
...  

Abstract This paper is focused on solving the evaluation and selection of 3PL’s by applying multi-criteria decision-making methods. Nigerian Breweries, Nigerian Bottling Company (NBC), AG Leventis, Kobo logistics, and Flour Mills of Nigeria (FMN) were understudied. The main criteria on which evaluation is based were established: Cost, Service level, Financial Capability, Reputation and Long-term relationship. A combination of two quantitative models was adopted in the study. Relevant data were collected through an oral interview with managers and key decision-makers at the companies. SWARA was first applied to the collated data to determine the relative weights of the criteria. Afterwards, the TOPSIS was applied to the weights developed using SWARA and on the performance of the selected service providers. After the analysis, the best service provider was identified as supplier 2 while the worst was supplier 5.


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