Neutrosophic Sets and Systems (Mar 2021)

Comparative analysis of AHP, FAHP and NeutrosophicAHP based on multi-criteria for adopting ERPS

  • Amany A.Slamaa,
  • Haitham A. El-Ghareeb,
  • Ahmed Aboelfetouh

DOI
https://doi.org/10.5281/zenodo.4625680
Journal volume & issue
Vol. 41
pp. 64 – 88

Abstract

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Management business has successfully forced enterprises to rebuild its process and adopt technology that help in integrating all process across different departments, analysis information in real-time, improve decision-making. ERP is a key information system for these purposes. There are many criteria in choice ERPS based on enterprise and application. Hence, there are many consulting firms with huge number of experts and technicians in carrying out analysis, evaluation ERPs and supporting IT-department in enterprises in selecting suitable ERPS. As many systems are semi-similar in features or semi-suitable for specific organization which leads to confusing decision making. Hence, using Multi-criteria decision method (MCDM) is essential. Using decision-making tools doesn’t mean missing data or information about what decision is made for. But sometimes more information creates a confusing decision as in this case-study. The case-study covers two main folds; it provides proposed criteria of ERPS adoption and studies their weights, then decision making process that is established by AHP, FAHP and Neutrosophic-AHP. It compares between the results of these approaches and measures the priority/weight effect of adding sub-criteria. This study provides a comparative analysis of AHP, FAHP and Neutrosophic-AHP. This paper contributes in emphasize the accuracy of Neutrosophic set in decision making. It also emphasizes on importance of using multi-criteria (criteria and factors) in designing decision model special in information system that have many factors for one aspect. The paper also contribute in ERPS field by providing criteria that help decision maker board in adopting ERPS cares on enterprise's culture, vision and business processes.

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