2021
DOI: 10.1007/s40747-021-00502-x
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An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS

Abstract: 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… Show more

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Cited by 16 publications
(6 citation statements)
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“…(3) The time of data collection is short, which can help enterprises quickly grasp the opportunity for improvement and meet the need for enterprises to pursue fast and accurate decision-making. (4) Making good use of the fuzzy performance evaluation, analysis and improvement model [28,29] can continuously enhance the bank APP operation performance and allow users to complete banking operations without going out. Not only does the model increase the bank's operating efficiency, but it also eases traffic congestion and parking as well as benefits energy saving and carbon reduction.…”
Section: Discussionmentioning
confidence: 99%
“…(3) The time of data collection is short, which can help enterprises quickly grasp the opportunity for improvement and meet the need for enterprises to pursue fast and accurate decision-making. (4) Making good use of the fuzzy performance evaluation, analysis and improvement model [28,29] can continuously enhance the bank APP operation performance and allow users to complete banking operations without going out. Not only does the model increase the bank's operating efficiency, but it also eases traffic congestion and parking as well as benefits energy saving and carbon reduction.…”
Section: Discussionmentioning
confidence: 99%
“…To rank options, the FT technique is employed. Recently, many researchers [18], [19] used FT to rank alternatives in various application areas such as IT risk analysis, stealth fighter aircraft selection. The FT algorithms is given in ( 18)-( 27).…”
Section: Fuzzy Technique For Order Preference By Similarity To Ideal ...mentioning
confidence: 99%
“…In addition, in order to eliminate the deficiencies of the intermittent EDAS method in practice, the model was updated and changed for the interval type data. In a study in which mobile banking rankings on seven Indian banks were investigated, Roy and Shaw [67] proposed an m-TOPSIS banking application selection model based on a combined fuzzy best-worst method (fuzzy-BWM) and a fuzzy TOPSIS (fuzzy-TOPSIS). In the analysis, the fuzzy-BWM technique was used to determine the weights of the factors, and the fuzzy-TOPSIS technique was used to rank the m-banking applications.…”
Section: Literature Reviewmentioning
confidence: 99%