Article: An intelligent analysis model for enhancing rural e-commerce sales efficiency in live streaming environments Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.37 pp.106 - 122 Abstract: Amidst the swift advancement of internet technology, live broadcast e-commerce has emerged as a pivotal driver for rural economic growth. However, the issue of low sales efficiency is becoming increasingly conspicuous, necessitating the development of effective solutions. Against this backdrop, this study investigates strategies to enhance the sales efficiency of rural e-commerce within the live broadcast context, with a focus on devising an intelligent analysis model to address the sales challenges. By precisely analysing the vast amounts of multi-source data generated during live broadcasts, the model employs data mining, machine learning, and deep learning algorithms for in-depth association analysis and feature extraction. Experimental results demonstrate that compared with outstanding deep learning models, the REISE model has reduced errors by approximately 25.60% and 22.31% in MAE metrics, 49.46% and 46.77% in MSE metrics, and 30.12% and 29.27% in RMSE metrics, respectively. Inderscience Publishers - linking academia, business and industry through research

Title: An intelligent analysis model for enhancing rural e-commerce sales efficiency in live streaming environments

Authors: Rong Zhou

Addresses: Business College, Zhengzhou Railway Vocational and Technical College, Zhengzhou, 450000, China

Abstract: Amidst the swift advancement of internet technology, live broadcast e-commerce has emerged as a pivotal driver for rural economic growth. However, the issue of low sales efficiency is becoming increasingly conspicuous, necessitating the development of effective solutions. Against this backdrop, this study investigates strategies to enhance the sales efficiency of rural e-commerce within the live broadcast context, with a focus on devising an intelligent analysis model to address the sales challenges. By precisely analysing the vast amounts of multi-source data generated during live broadcasts, the model employs data mining, machine learning, and deep learning algorithms for in-depth association analysis and feature extraction. Experimental results demonstrate that compared with outstanding deep learning models, the REISE model has reduced errors by approximately 25.60% and 22.31% in MAE metrics, 49.46% and 46.77% in MSE metrics, and 30.12% and 29.27% in RMSE metrics, respectively.

Keywords: rural e-commerce; live broadcast sales; intelligent analysis model; sales efficiency; data mining.

DOI: 10.1504/IJICT.2025.149181

International Journal of Information and Communication Technology, 2025 Vol.26 No.37, pp.106 - 122

Received: 21 Jul 2025
Accepted: 02 Sep 2025
Published online: 16 Oct 2025 *

Title: An intelligent analysis model for enhancing rural e-commerce sales efficiency in live streaming environments

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