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

<p>Cross-border e-commerce has developed rapidly with network globalization, convenience, and mobility characteristics, and its operation mode is highly popular in the international trade industry. This paper analyzes cross-border e-commerce marketing strategies based on the SCOR model, aiming to seek scientific and reasonable methods to improve cross-border e-commerce companies’ precision marketing speed and accuracy and gain greater advantages in the fiercely competitive environment. This paper uses the SCOR model to identify the possible risks of marketing in the cross-border e-commerce industry. The characteristics of the supply chain are studied, and the relevant risk factors are identified from a holistic perspective. By comparing the two risk assessment methods of the fuzzy integrated evaluation method and the BP wavelet neural network model, the advantages of the BP wavelet neural network model in this paper are proved, and then the method is chosen as the risk assessment method and verified by example.</p>
<p>Furthermore, through questionnaire surveys, we obtain information about consumers’ purchasing ability, purchasing channels, and satisfaction with cross-border e-commerce operation services to clarify consumers’ psychology and provide data support for operation strategy improvement research. The results show that: the consumption ability of people aged 20 to 25 to purchase cross-border products is concentrated in the range of 400 to 1000 yuan/month; the consumption ability of people aged 26 to 40 to purchase cross-border e-commerce products is concentrated in the range of 1000 to 1500 yuan/month, and the number of people whose purchasing ability is above 1500 yuan/month reaches 2%; the consumption ability of people aged 41 to 55 to purchase products is concentrated in the range of 600 to 1000 yuan/month, followed by 1000 to 1500 yuan/month. The next is 1000-1500 yuan/month. Overall, the purchasing power of people in each age group is medium. Among them, the purchasing power of people aged 26 to 40 is the strongest. Therefore, it is necessary to develop targeted and personalized marketing programs, improve consumer stickiness, pay attention to the significance of big data for accurate marketing, and improve the overall marketing level of enterprises.</p>
</abstract>

Cross-border e-commerce has developed rapidly with network globalization, convenience, and mobility characteristics, and its operation mode is highly popular in the international trade industry. This paper analyzes cross-border e-commerce marketing strategies based on the SCOR model, aiming to seek scientific and reasonable methods to improve cross-border e-commerce companies’ precision marketing speed and accuracy and gain greater advantages in the fiercely competitive environment. This paper uses the SCOR model to identify the possible risks of marketing in the cross-border e-commerce industry. The characteristics of the supply chain are studied, and the relevant risk factors are identified from a holistic perspective. By comparing the two risk assessment methods of the fuzzy integrated evaluation method and the BP wavelet neural network model, the advantages of the BP wavelet neural network model in this paper are proved, and then the method is chosen as the risk assessment method and verified by example.
Furthermore, through questionnaire surveys, we obtain information about consumers’ purchasing ability, purchasing channels, and satisfaction with cross-border e-commerce operation services to clarify consumers’ psychology and provide data support for operation strategy improvement research. The results show that: the consumption ability of people aged 20 to 25 to purchase cross-border products is concentrated in the range of 400 to 1000 yuan/month; the consumption ability of people aged 26 to 40 to purchase cross-border e-commerce products is concentrated in the range of 1000 to 1500 yuan/month, and the number of people whose purchasing ability is above 1500 yuan/month reaches 2%; the consumption ability of people aged 41 to 55 to purchase products is concentrated in the range of 600 to 1000 yuan/month, followed by 1000 to 1500 yuan/month. The next is 1000-1500 yuan/month. Overall, the purchasing power of people in each age group is medium. Among them, the purchasing power of people aged 26 to 40 is the strongest. Therefore, it is necessary to develop targeted and personalized marketing programs, improve consumer stickiness, pay attention to the significance of big data for accurate marketing, and improve the overall marketing level of enterprises.

Optimization analysis of cross-border e-commerce marketing strategy based on the SCOR model

Applied Mathematics and Nonlinear Sciences

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

Cross-border e-commerce has developed rapidly with network globalization, convenience, and mobility characteristics, and its operation mode is highly popular...

Optimization analysis of cross-border e-commerce marketing strategy based on the SCOR model

Online veröffentlicht: 09. Aug. 2023

Seitenbereich: -

Eingereicht: 14. Nov. 2022

Akzeptiert: 17. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00164

Schlüsselwörter
Cross-border e-commerce, E-commerce marketing, Strategy optimization, SCOR model, BP wavelet neural network

© 2023 Fang Zhou, published by Sciendo

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

Optimization analysis of cross-border e-commerce marketing strategy based on the SCOR model

Online veröffentlicht: 09. Aug. 2023

Seitenbereich: -

Eingereicht: 14. Nov. 2022

Akzeptiert: 17. Feb. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00164

SchlüsselwörterCross-border e-commerce, E-commerce marketing, Strategy optimization, SCOR model, BP wavelet neural network

© 2023 Fang Zhou, published by Sciendo

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

Schlüsselwörter
Cross-border e-commerce, E-commerce marketing, Strategy optimization, SCOR model, BP wavelet neural network