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  4. ANALYSIS AND MODEL PROPOSITION OF USER WILLINGNESS TO ADOPT MOBILE BANKING FINANCE+ SCENARIO SERVICES UNDER THE BACKGROUND OF DIGITAL TRANSFORMATION
 
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ANALYSIS AND MODEL PROPOSITION OF USER WILLINGNESS TO ADOPT MOBILE BANKING FINANCE+ SCENARIO SERVICES UNDER THE BACKGROUND OF DIGITAL TRANSFORMATION

Date Issued
2024
Author(s)
Lin, Jingying
Faculty of Business and Law 
Abstract
In the wave of digital transformation, Chinese banks have taken digital and scenario-based finance as primary strategic goals. The goal is to revolutionize the mobile banking experience and encourage frequent use of mobile banking services. However, assessing customer satisfaction with the various financial and contextual services mobile banking provides is crucial. The main objective of this study is to propose a model based on users' perception of financial usage in mobile banking scenarios and how the development of mobile banking finance and scenarios affects users' choice motivations. The study examined the interview records of 12 mobile banking users through qualitative in-depth interviews and utilized Nvivo qualitative analysis software to analyze the interview content. Through repeated thinking, sorting, and differentiating the data, nine core coding categories were formed. The coding was further refined and deepened to include Financial professionalism, Security, Marketing Stimulation, Innovative Products, Use Experience, Strong Relationship, Trust, Perceived usefulness, and Willingness to use. Based on these categories, a theoretical model of user willingness in the financial scenario of mobile banking has been proposed by referring to the optimized TAM model. The results may provide support to the banking industry in Macau in understanding customers' needs and fostering the positive development of mobile finance and the scene field in Macau.
Subjects

Finance+ scenarios

Banking in Macau

Grounded Theory

TAM model

Willingness to use

File(s)
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Name

M-BA 2024 LIN,JIN.pdf

Size

803.7 KB

Format

Adobe PDF

Checksum

(MD5):2e5824724f12c83569bb49043f28c1c4


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