Study on mobile payment adoption in Vietnam
In Vietnam “The number of e-payments grew 22% in 2017 from the previous year to $6.14 billion, according to Statista, a local market research firm. The figure is projected to double to $12.33 billion in 2022” (TOMIYAMA, 2018) State-owned gas station operator Petro Vietnam Oil introduced a mobile pay...
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Format: | Theses |
Language: | English |
Published: |
2020
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Online Access: | http://repository.vnu.edu.vn/handle/VNU_123/70388 |
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Institution: | Vietnam National University, Hanoi |
Language: | English |
Summary: | In Vietnam “The number of e-payments grew 22% in 2017 from the previous year to $6.14 billion, according to Statista, a local market research firm. The figure is projected to double to $12.33 billion in 2022” (TOMIYAMA, 2018) State-owned gas station operator Petro Vietnam Oil introduced a mobile payment system in February, while M-Service, a major fin-tech company, plans to increase the number of subscribers to its MoMo online payment service to 50 million by 2020 from about five million today. The research focuses on 3 objectives: To find the factors that affect the customer in selecting the mobile-payment application in Vietnam, the relationship between those factors and propose suggestions and solutions for mobile-payment application providers to attract more customers as well as improve business efficiencies. The research constructs and develop on the ground of UTAUT theory with revised of Facilitating Factor, Trust factor and changes an independent variable. The research using Likert –scales 5 levels for 4 observation variables: Performance expectancy, social influence, effort expectancy Trust and one dependent variable Behavior Intention. The research using a frequency- scale 4 levels for one independent variable: E-commerce Use Behavior and one dependent variable: Use behavior. Among 6 hypotheses, 5 were not rejected and 1 was rejected. The research also provided the multiple linear regression equation and binomial logistic regression equation of computing variable value. Therefore, predicting the mobile payment usage behavior of frequency at 75.85% accuracies. |
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