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Cloud-based ERP system selection based on extended probabilistic linguistic MULTIMOORA method and Choquet integral operator

  • Shui-xia Chen
  • Jian-qiang WangEmail author
  • Tie-li Wang
Article
  • 60 Downloads

Abstract

Cloud-based enterprise resource planning (ERP) is a combination of standard ERP system and cloud flexibility. Adopting a suitable cloud-based ERP system is an uncertain multi-criteria decision-making problem. Probabilistic linguistic term sets (PLTSs) can be used to address the uncertainty in such problem. On the basis of PLTSs, we introduce an innovative two-step comparative method for the evaluation of cloud-based ERP systems. The extended multiple multi-objective optimisations by ratio analysis method within PLTSs are proposed to obtain the class of cloud-based ERP vendors. Two classes, namely, accepted and rejected, are obtained. Then, we select the suitable cloud-based ERP packages in the accepted class. We put forward the probabilistic linguistic Choquet integral operator to aggregate the ERP package evaluation matrices given the interrelationships between criteria. Subsequently, a new comparison method is introduced to obtain the final results. We conduct an illustrative example to prove the rationality of the presented method. The feasibility of this model is verified by comparative analysis and validity test.

Keywords

Cloud-based ERP system selection Multi-criteria decision-making Probabilistic linguistic term sets MULTIMOORA method Choquet integral operator 

Mathematics Subject Classification

03E72 

Notes

Acknowledgements

The authors would like to thank the editors and anonymous reviewers for their great help on this study. This work was supported by the National Natural Science Foundation of China (No. 71571193) and Postgraduate Survey Project of Central South University (No. 2018dcyj035).

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interests regarding the publication of this paper.

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Copyright information

© SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional 2019

Authors and Affiliations

  1. 1.School of BusinessCentral South UniversityChangshaPeople’s Republic of China
  2. 2.Management SchoolUniversity of South ChinaHengyangPeople’s Republic of China

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