<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper uses big data evaluation models to predict market trends with the goal of promoting rural e-commerce development. A closely integrated algorithmic trading framework is constructed, and strategic evaluation indicators are proposed in traditional indicators. By analyzing the current situation and problems of online marketing of agricultural products, a series of development strategies and safeguards are formulated, and suggestions are made to establish QR code traceability and highlight personalized product development. The results show that age has a greater influence on the development of agribusiness. 65.73% of the 20-35 year olds choose to be willing to buy and do so through the Internet, which is 53.40% higher than the average, and 59.09% of the under-20 year olds choose to be unclear but willing to know, which is 28.64% higher than the average. The data studied and analyzed in this paper are useful for predicting the sales trend of the rural e-commerce market and promoting the development of rural e-commerce development.</p>
</abstract>

This paper uses big data evaluation models to predict market trends with the goal of promoting rural e-commerce development. A closely integrated algorithmic trading framework is constructed, and strategic evaluation indicators are proposed in traditional indicators. By analyzing the current situation and problems of online marketing of agricultural products, a series of development strategies and safeguards are formulated, and suggestions are made to establish QR code traceability and highlight personalized product development. The results show that age has a greater influence on the development of agribusiness. 65.73% of the 20-35 year olds choose to be willing to buy and do so through the Internet, which is 53.40% higher than the average, and 59.09% of the under-20 year olds choose to be unclear but willing to know, which is 28.64% higher than the average. The data studied and analyzed in this paper are useful for predicting the sales trend of the rural e-commerce market and promoting the development of rural e-commerce development.

Research on the influence factors and improvement path of rural e-commerce development based on neural network

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper uses big data evaluation models to predict market trends with the goal of promoting rural e-commerce development. A closely integrated algorithmic...

Research on the influence factors and improvement path of rural e-commerce development based on neural network

Data publikacji: 02 paź 2023

Zakres stron: -

Otrzymano: 07 gru 2022

Przyjęty: 12 kwi 2023

DOI: https://doi.org/10.2478/amns.2023.2.00447

Słowa kluczowe
Agribusiness development, Marketing programs, Strategy evaluation indicators, Qr code network, Market forecasting

© 2023 Qiao Zhao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the influence factors and improvement path of rural e-commerce development based on neural network

Data publikacji: 02 paź 2023

Zakres stron: -

Otrzymano: 07 gru 2022

Przyjęty: 12 kwi 2023

DOI: https://doi.org/10.2478/amns.2023.2.00447

Słowa kluczoweAgribusiness development, Marketing programs, Strategy evaluation indicators, Qr code network, Market forecasting

© 2023 Qiao Zhao, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Agribusiness development, Marketing programs, Strategy evaluation indicators, Qr code network, Market forecasting