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 Algorithmic Purchase Decision Journeys of Generation Z and Millennials in Mobile Electronic Commerce
Tác giả hoặc Nhóm tác giả: Nguyen Thi Minh Tam; Ta Nguyet Phuong
Nơi đăng: Proceedings of 19th International Conference on Socio-economic and Environmental Issues in Development, 2024; Số: 19;Từ->đến trang: 1245-1260;Năm: 2024
Lĩnh vực: Kinh tế; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
This study investigates the artificial intelligence (AI) algorithmic pathways adopted by Generation Z and Millennials when engaging in mobile electronic commerce. The importance of the decision-making process in online shopping has been well-established in existing literature; however, recent research suggests that the actual decision routes of online users within these specific demographic groups may be overlooked. To address this gap, the study investigates four distinct algorithmic pathways within a decision-making model referred to as the Throughput Model. By analyzing the complex dynamics of purchase decision routes in an AI environment, the study reveals that diverse needs, information sources, and alternative evaluations contribute to variations in decision algorithmic pathways. Specifically, the study identifies four dominant pathways: quick buying, selected buying, casual buying, and traditional formal buying. These findings advance the understanding of researchers, businesses, and marketers, providing valuable insights to facilitate fair and independent decision-making strategies tailored to Generation Z and Millennials in the mobile electronic commerce context.
ABSTRACT
This study investigates the artificial intelligence (AI) algorithmic pathways adopted by Generation Z and Millennials when engaging in mobile electronic commerce. The importance of the decision-making process in online shopping has been well-established in existing literature; however, recent research suggests that the actual decision routes of online users within these specific demographic groups may be overlooked. To address this gap, the study investigates four distinct algorithmic pathways within a decision-making model referred to as the Throughput Model. By analyzing the complex dynamics of purchase decision routes in an AI environment, the study reveals that diverse needs, information sources, and alternative evaluations contribute to variations in decision algorithmic pathways. Specifically, the study identifies four dominant pathways: quick buying, selected buying, casual buying, and traditional formal buying. These findings advance the understanding of researchers, businesses, and marketers, providing valuable insights to facilitate fair and independent decision-making strategies tailored to Generation Z and Millennials in the mobile electronic commerce context.
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