Evaluation of Digital Banking Implementation Indicators and Models in the Context of Industry 4.0: A Fuzzy Group MCDM Approach

Modern technologies have changed human life and created a generation of customers who different needs compared to the past. Considering Industry 4.0 its drivers, implementation digital banking (DB) has faced various challenges that are caused by emerging trends. Both DB contemporary concepts, decision-makers often with uncertainties in their decisions regarding indicators. For this purpose, novel multi-criteria group decision-making approach been developed utilizing best–worst method (BWM) α-cut analysis as well trapezoidal fuzzy numbers (TFNs). By reviewing literature using experts’ opinions, criteria determined, considering an uncertain environment, prioritized proposed method. Then, available models alternatives examined based on decision importance each criterion. This research contributes existing identifying prioritizing necessary for successful DB, taking into account trends technological advances driven 4.0. Subsequently, study prioritizes prevalent these criteria. proposes decision-support framework dealing ambiguity, lack information, insufficient knowledge, uncertainty decision-making. The uses TFNs imprecision doubt decision-makers’ preferences. Additionally, presents enables experts arrive at more reliable results. can help improve quality complex situations. results show resources, rules regulations, customer satisfaction most important implementing DB. In addition, open, blockchain, social crucial significantly cover