An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS

Abstract

AbstractMobile technology has revolutionised various business processes. Banking is one of them. Traditional banking operations are gradually changing with the introduction of efficient mobile technologies. Mobile banking (m-banking) has recently emerged as an innovative banking channel that provides continuous real-time customer service. It is expected that the market for m-banking will expand in the near future. There are currently various types of m-banking applications in the market. However, ranking and selecting efficient applications is difficult due to the involvement of multiple factors. As of now, very few studies have reported the m-banking application selection framework, left scope for further research. The current study proposes an m-banking application selection model based on a combined fuzzy best–worst method (fuzzy-BWM) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy-TOPSIS). The research was carried out in several stages, beginning with the identification of potential factors and progressing to pair-wise comparisons and the final ranking of the applications. The fuzzy set theory was applied to handle the ambiguity of the decision maker. In the first stage, fuzzy-BWM was used to determine the weight of the factors. Further, fuzzy-TOPSIS was applied to rank the m-banking applications. The present study has adopted a new fuzzy BWM, which differs significantly from the existing fuzzy-BWM, to solve the nonlinearity problem of optimisation. The applicability of the proposed model has been demonstrated through a real-life case study. The efficacy of the model has been further examined by performing a sensitivity analysis. The study observed application functionality, convenience, and performance expectancy as significant factors in selecting an m-banking application, followed by performance quality, security, and compatibility. The proposed model can assist financial institutions and customers to overcome the challenges of choosing an appropriate m-banking application. The proposed model can be used to benchmark the m-banking applications in the market.