Mô hình khám phá ý kiến khách hàng về ứng dụng IoT tại các cửa hàng bán lẻ dựa trên phương pháp phân tích quan điểm và máy học kết hợp=A model of discovering customer opinions about IoT applications for retail stores based on sentiment analysis and ensemble learning method

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Tác giả: Hảo Đinh Hoàn, Phạm Thị Minh Hòa, Hồ Thị Minh Nguyên, Phạm Nguyễn Hiền Phương, Hồ Trung Thành, Uyên Thẩm Thị Tú

Ngôn ngữ: vie

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Khoa học Đại học Mở Thành phố Hồ Chí Minh - Kinh tế và Quản trị kinh doanh, 2024

Mô tả vật lý: tr.45733

Bộ sưu tập: Metadata

ID: 481347

Thêm vào giỏ

IoT (Internet of Things) đã cách mạng hóa ngành bán lẻ nhờ đem lại những trải nghiệm mua sắm tối ưu và tạo ra hiệu quả kinh doanh cho doanh nghiệp. Công nghệ này ngày càng được ứng dụng rộng rãi tại các cửa hàng trên thế giới, và mở ra nhiều cơ hội mới cho ngành bán lẻ Việt Nam. Bài nghiên cứu hướng đến việc phân tích ý kiến khách hàng, những người quan tâm hoặc đã trải nghiệm mua sắm tại 06 cửa hàng bán lẻ nổi tiếng có ứng dụng IoT, theo các nhóm quan điểm tích cực, tiêu cực và trung lập. Bộ dữ liệu bao gồm 77,043 bình luận được thu thập từ các trang website và nền tảng mạng xã hội. Dữ liệu sau xử lý sẽ được đưa vào thực nghiệm mô hình phân tích quan điểm với 05 thuật toán máy học bao gồm K-Nearest Neighbors (KNN), Decision Tree, Random Forest, Hồi quy Logistic và mô hình học kết hợp (Ensemble model). Trong đó, kết quả phân tích và dự đoán quan điểm của khách hàng cho thấy mô hình học kết hợp đem lại hiệu quả tốt nhất với độ chính xác trung bình là 89%. Mô hình và kết quả nghiên cứu sẽ giúp các nhà quản trị phát triển chiến lược chuyển đổi số và kinh doanh phù hợp trong việc ứng dụng công nghệ IoT vào các cửa hàng bán lẻ, đặc biệt là tại thị trường Việt Nam.IoT (Internet of Things) has revolutionized the retail industry by providing an optimal shopping experience and improving business efficiency for enterprises. This technology is widely used at many retail stores worldwide and opens up new opportunities for retail in Vietnam. The research conducts sentiment analysis of customers who have experienced shopping or may be interested in purchasing products in the future from 06 retail stores with IoT applications to identify sentiments including positive, negative, and neutral. The dataset has 77,043 comments collected on websites and social media platforms. The cleaned data will then be used to experiment with 05 machine learning algorithms, including K-Nearest Neighbors (KNN), Decision Tree, Random Forest, Logistic Regression, and Ensemble model. In conclusion, the ensemble model has the highest average accuracy score of 89%. The model and research result provide a valuable reference to help administrators develop appropriate business and digital transformation strategies for applying IoT technology for retail stores, especially in Vietnam.

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