Dynamic group decision-making for enterprise resource planning selection using two-tuples Pythagorean fuzzy MOORA approach

Abstract

Enterprise resource planning (ERP) is an artificial intelligence software that enables organizations to automate and efficiently administer their essential business processes. ERP software assists an organization with time and resource optimization for efficient operations. Choosing an appropriate ERP system for a specific organization has become challenging for decision-makers (DMs) since it involves navigating competing technical, organizational, and financial considerations. A complete, flexible, multi-criteria group decision-making (MCGDM) method based on the Pythagorean fuzzy set (PFS) is proposed in this article to help an organization choose the best option. The PFSs are used to rate both the criteria of an ERP alternative and the quality of the DMs. The collective assessment of the DMs, along with their preferences, is integrated using the Pythagorean fuzzy Einstein-ordered weighted operator (PFEOWO). The method based on the Removal Effects of Criteria (MEREC) is enhanced in a Pythagorean setting to find the Pythagorean weights of each ERP criterion. The Pythagorean weights of the criteria are combined with the DM’s preference using the Pythagorean fuzzy weighted average operator (PFWAO). These combined Pythagorean weights are integrated with the combined assessment of the DMs to produce the weighted Pythagorean decision matrix. Then, the MOORA approach is also enhanced in a PFS setting, and an improved Pythagorean fuzzy MOORA (PF-MOORA) is proposed to solve an MCGDM problem in an uncertain context. Data is generated for three DMs and five ERP packages with twelve characteristics to demonstrate the proposed PF-MOORA. Based on the suggested PF-MOORA method, the fifth and fourth ERP packages are optimal and least favorable, respectively. A sensitivity analysis is conducted by altering the criteria weights to measure the influence of the ERP ranking on the criteria weights. Finally, the proposed PF-MOORA is compared with existing crisp and Pythagorean multi-criteria decision analysis methods to demonstrate its coherence and resilience.