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

Abstract

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

Evaluation of the Benefits Generated by Sustainability 4.0: A Study of the Perception of Banking Sector Customers

“…The first two factors are related to economic aspects and the last to environmental aspects. It is suggested that the points with greater agreement are precisely those to which the customer is already feeling the benefits, with the reduction in service time and the increased satisfaction and practicality in subscribing to financial services, which is in line with the main findings of studies by [9,32,34]. Furthermore, the use of digitalization in the banking segment makes a noticeable reduction in waste and unnecessary inputs for current demands.…”

“…Amiri et al [32] address the issue of implementing digital banking services amid the transformations generated by industry 4.0, considering changes in customer needs. The study proposes an innovative approach to group decision-making.…”

“…Thus, the questions, from worst to best, were: "I believe that 4.0 technologies can help the retention of employees who serve me in the banking sector"; "I believe that 4.0 technologies can increase the autonomy of elderly customers in the banking sector" and "I believe that 4.0 technologies can increase the quality of life of elderly customers in the banking sector". Regarding the issue of banking jobs, it is suggested that disagreement is associated with the initial perception of unemployment associated with technological replacement, despite the studies by [32,33] reaching the conclusion that there will be changes in the demands on the skills of bank employees, without debating in depth the impact on the number of jobs. Another concern perceived by customers is linked to the use of digital devices by older people, suggesting that there is no agreement that 4.0 technologies can benefit them in the use of day-to-day financial demands, as partially discussed by [26].…”

LOPCOW-OWA Modeli Yardımıyla Çok Boyutlu Banka Performans Değerlendirmesi

“…Amiri vd. [13] çalışmalarında BWM ve α-kesim analizinin yanı sıra yamuk bulanık sayılar kullanılarak dijital bankacılık uygulama göstergelerini değerlendirmişlerdir. Yurttadur ve Taşcı [14] çalışmalarında Türkiye'deki katılım bankalarının finansal performans ölçümünü CRITIC ve MAIRCA prosedürlerinden oluşan entegre bir model ile incelemişlerdir.…”