ỨNG DỤNG PHƯƠNG PHÁP SEM-NEURAL NETWORK ĐỂ XÂY DỰNG MÔ HÌNH DỰ BÁO TRẢI NGHIỆM KHÁCH HÀNG VỀ DỊCH VỤ NGÂN HÀNG SỐ TẠI CÁC NGÂN HÀNG THƯƠNG MẠI VIỆT NAM

Anh Hoang Le, , Le Nguyen Hoai Thi, Luong Tran Hoang Huong, , La Phu Hao and Nguyen Thi Thuy Nga
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Anh Hoang Le: Ho Chi Minh University of Banking

No vrmp9, OSF Preprints from Center for Open Science

Abstract: The client experience has been improved by the recent growth of digital banking services (PwC, 2018). Finding the variables that influence how customers experience this service is the issue that now interests researchers and commercial banks. This study focuses on identifying the factors impacting consumers' experiences with digital banking services at Vietnamese commercial banks in an effort to provide a solution to the aforementioned problem. This study is also the first to combine interaction estimation through a structural equation modeling (SEM), and machine learning techniques through an artificial neural network (ANN) model to create a predictive model of customer experience on digital banking services in Vietnamese commercial banks. The SEM model estimation results indicate that perceived convenience, functional quality, and service quality, brand awareness, safety perception, and usability are the elements influencing the customer's experience utilizing digital banking services. In order to improve the customer experience of digital banking services at Vietnamese commercial banks, the study has developed a customer experience forecasting model and provided some managerial implications.

Date: 2022-11-13
New Economics Papers: this item is included in nep-ban, nep-big, nep-cmp and nep-sea
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:vrmp9

DOI: 10.31219/osf.io/vrmp9

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