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

Abstract

This study was primarily conducted to develop a predictive model for customer experience regarding digital banking services at Vietnamese commercial banks, based on the integration of the Structural Equation Modeling (SEM) method and the Machine Learning method using Artificial Neural Networks (ANN). With data from 443 surveyed customers, the research findings reveal that the customer experience of digital banking services in Vietnamese commercial banks is influenced by six factors, including convenience perception, functional quality, service quality, brand perception, safety perception, and usability. Based on these findings, the author continues to develop a predictive model for the customer experience of digital banking services at Vietnamese commercial banks.