An extended MEREC-EDAS approach with linguistic pythagorean fuzzy set for selecting virtual team members

Virtual teams (VT) have become increasingly popular due to modern technology. VT allows talented people from different places with different skills to work towards a common goal through network media. In order to form a more versatile VT, selecting VT members becomes a critical step. Based on the linguistic Pythagorean fuzzy sets (LPFS), this paper proposes an integrated approach to select VT members by means of the method based on standard removal effects (MEREC) and the method based on the mean solution distance of direct and indirect uncertainty (DIUEDAS). Firstly, decision information is described by LPFS. Secondly, MEREC is used to determine the criteria weights. Finally, the decision-making and evaluation laboratory (DEMATEL), failure mode and effects analysis (FMEA), and EDAS are combined to select the optimal VT members under the premise of evaluating the uncertainty in selecting VT members. In addition, this paper proposes a new method for determining expert weights. At the end of the paper, the model and the expert weight determination method are applied to the case of a port selecting VT members, and the effectiveness of the model proposed is demonstrated by comparative analysis in this paper.