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- W4280581302 abstract "The advancement of information technology has changed traditional manufacturing and business methods, resulting in the emergence of a new business mode known as electronic commerce (E-Commerce). Owing to its obvious benefits, E-Commerce has been extensively employed in a short time, creating a group of E-Commerce enterprises. Establishing financial management strategies that are appropriate for E-Commerce enterprises is critical since it not only aids executors in formulating better financial policies but also benefits enterprises’ administration and market competitiveness. Most of the retail stores in the technological environment are taking different dimensions in their performance through this enterprise E-Commerce. In this study, an E-Commerce system is implemented for retail marketing using lightweight deep learning technology. The deep Lagrangian multiplier approach is used to promote the user’s purchase behavior and to determine whether the estimated optimal transaction quantity is achieved. The user can utilize the mobile application with the internetworking facility to place the order for required products. The proposed system showed the highest performance achieving 98.78% accuracy as compared to the existing system with 92.46% accuracy." @default.
- W4280581302 created "2022-05-22" @default.
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- W4280581302 date "2022-05-11" @default.
- W4280581302 modified "2023-10-18" @default.
- W4280581302 title "Enterprise E-Commerce Management Strategies Based on Light Weight Deep Learning Model in the Context of New Retail" @default.
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- W4280581302 doi "https://doi.org/10.1155/2022/1946521" @default.
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