Mobile 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.

移动技术彻底改变了各种业务流程。银行业就是其中之一。随着高效移动技术的引入，传统的银行业务正在逐渐发生变化。手机银行（m-banking）最近已成为提供持续实时客户服务的创新银行渠道。预计移动银行市场将在不久的将来扩大。目前市场上有各种类型的移动银行应用程序。然而，由于多种因素的参与，排序和选择有效的应用程序很困难。截至目前，很少有研究报告移动银行应用程序选择框架，留有进一步研究的余地。目前的研究提出了一种移动银行应用程序选择模型，该模型基于组合模糊最佳-最差方法（fuzzy-BWM）和通过与理想解决方案相似性的偏好顺序模糊技术（fuzzy-TOPSIS）。该研究分几个阶段进行，从识别潜在因素开始，然后进行成对比较和应用程序的最终排名。模糊集理论被应用于处理决策者的歧义。在第一阶段，模糊 BWM 用于确定因素的权重。此外，模糊TOPSIS 被应用于排名移动银行应用程序。本研究采用了一种新的模糊 BWM，它与现有的模糊 BWM 有很大不同，以解决优化的非线性问题。所提出模型的适用性已通过实际案例研究得到证明。通过执行敏感性分析进一步检验了该模型的有效性。该研究观察到应用程序功能、便利性和性能预期是选择移动银行应用程序的重要因素，其次是性能质量、安全性和兼容性。所提出的模型可以帮助金融机构和客户克服选择合适的移动银行应用程序的挑战。所提出的模型可用于对市场上的移动银行应用程序进行基准测试。和性能预期是选择移动银行应用程序的重要因素，其次是性能质量、安全性和兼容性。所提出的模型可以帮助金融机构和客户克服选择合适的移动银行应用程序的挑战。所提出的模型可用于对市场上的移动银行应用程序进行基准测试。和性能预期是选择移动银行应用程序的重要因素，其次是性能质量、安全性和兼容性。所提出的模型可以帮助金融机构和客户克服选择合适的移动银行应用程序的挑战。所提出的模型可用于对市场上的移动银行应用程序进行基准测试。