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Comprehensive Analysis of Mobile Payment's Customer Loyalty: The SEMANN Approach
by
Dang, Tri-Quan
, Duc, Dang Thi Viet
, Nguyen, Luan-Thanh
in
Artificial neural networks
/ Brand loyalty
/ Consumers
/ COVID-19
/ Customer services
/ Customers
/ Developing countries
/ Disease transmission
/ Information systems
/ LDCs
/ Mobile commerce
/ Neural networks
/ Pandemics
/ Payment systems
/ Payments
/ Risk perception
/ Shelter in place
/ Technology Acceptance Model
/ User behavior
2025
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Comprehensive Analysis of Mobile Payment's Customer Loyalty: The SEMANN Approach
by
Dang, Tri-Quan
, Duc, Dang Thi Viet
, Nguyen, Luan-Thanh
in
Artificial neural networks
/ Brand loyalty
/ Consumers
/ COVID-19
/ Customer services
/ Customers
/ Developing countries
/ Disease transmission
/ Information systems
/ LDCs
/ Mobile commerce
/ Neural networks
/ Pandemics
/ Payment systems
/ Payments
/ Risk perception
/ Shelter in place
/ Technology Acceptance Model
/ User behavior
2025
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Do you wish to request the book?
Comprehensive Analysis of Mobile Payment's Customer Loyalty: The SEMANN Approach
by
Dang, Tri-Quan
, Duc, Dang Thi Viet
, Nguyen, Luan-Thanh
in
Artificial neural networks
/ Brand loyalty
/ Consumers
/ COVID-19
/ Customer services
/ Customers
/ Developing countries
/ Disease transmission
/ Information systems
/ LDCs
/ Mobile commerce
/ Neural networks
/ Pandemics
/ Payment systems
/ Payments
/ Risk perception
/ Shelter in place
/ Technology Acceptance Model
/ User behavior
2025
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Comprehensive Analysis of Mobile Payment's Customer Loyalty: The SEMANN Approach
Journal Article
Comprehensive Analysis of Mobile Payment's Customer Loyalty: The SEMANN Approach
2025
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Overview
This research aims to bridge this gap by employing the Expectation-Confirmation Theory to elucidate the underpinnings of customer loyalty in mobile payment. This study examines mobile payment customer loyalty using the Expectation- Confirmation theory and second-order constructs of perceived usefulness and perceived risk. The model was tested on 213 mobile payment users using a partial least square structural equation modeling-artificial neural network (PLS-SEM-ANN), capturing linear and nonlinear relationships. Mobile payment system adoption is more likely in people who can understand and analyze complex concepts like risk perception and perceived usefulness. ANN analyses show that confirmation and satisfaction are the most critical factors affecting satisfaction and continuance intention in mobile payment usage. An integrated model that accounts for 40.5% of customer loyalty variance examines feature-level perceived utility and risk to understand mobile payment better. The study ranks factors that sustain mobile payment usage, guiding executive decisions. Perceived usefulness, a secondorder construct, positively affects continuance intention in mobile payment loyalty. Notably, the study reveals loyalty drivers essential for developing nations' post-pandemic economic recovery. These findings help developing countries' mobile payment service providers and management increase usage and customer loyalty.
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