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

<p>Cross-border E-commerce has advanced greatly with the help of big data technology, cross-border payment and logistics maturity and improvement, and backing from the national “One Belt, One Road” policy. Firstly, based on the study of enterprise core competitiveness evaluation index system, one is proposed for the core competitiveness of Cross-border E-commerce enterprises, and an evaluation model based on SA-LSTM for the core competitiveness of Cross-border E-commerce enterprises is constructed. Then, with the research objective of refining the core competitiveness of Cross-border E-commerce enterprises, the model was applied to empirically analyze the core attractiveness of major domestically listed Cross-border E-commerce enterprises. The results show that laws and regulations have no significant influence on enterprise competitiveness, the regression coefficient is not significant, and the t-value = 1.793 &lt; 2. Hypothesis A is not verified. And the p-values of the technical environment, development potential, market demand, capital management, process cost, information sharing and service level are all less than 0.05, and the regression coefficients are all significant with t-values greater than 2, indicating that indicators B to H has a significant positive influence on enterprise competitiveness. This study reduces the barriers for SMEs to apply Cross-border E-commerce to participate in foreign trade, reduces the cost of enterprises, and improves their own competitiveness.</p>
</abstract>

Cross-border E-commerce has advanced greatly with the help of big data technology, cross-border payment and logistics maturity and improvement, and backing from the national “One Belt, One Road” policy. Firstly, based on the study of enterprise core competitiveness evaluation index system, one is proposed for the core competitiveness of Cross-border E-commerce enterprises, and an evaluation model based on SA-LSTM for the core competitiveness of Cross-border E-commerce enterprises is constructed. Then, with the research objective of refining the core competitiveness of Cross-border E-commerce enterprises, the model was applied to empirically analyze the core attractiveness of major domestically listed Cross-border E-commerce enterprises. The results show that laws and regulations have no significant influence on enterprise competitiveness, the regression coefficient is not significant, and the t-value = 1.793 < 2. Hypothesis A is not verified. And the p-values of the technical environment, development potential, market demand, capital management, process cost, information sharing and service level are all less than 0.05, and the regression coefficients are all significant with t-values greater than 2, indicating that indicators B to H has a significant positive influence on enterprise competitiveness. This study reduces the barriers for SMEs to apply Cross-border E-commerce to participate in foreign trade, reduces the cost of enterprises, and improves their own competitiveness.

An empirical analysis of the impact of Cross-border E-commerce on the competitiveness of SMEs based on the context of big data

Applied Mathematics and Nonlinear Sciences

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

Cross-border E-commerce has advanced greatly with the help of big data technology, cross-border payment and logistics maturity and improvement, and backing...

An empirical analysis of the impact of Cross-border E-commerce on the competitiveness of SMEs based on the context of big data

Pubblicato online: 07 ott 2023

Pagine: -

Ricevuto: 18 nov 2022

Accettato: 17 apr 2023

DOI: https://doi.org/10.2478/amns.2023.2.00503

Parole chiave
Cross-border E-commerce, big data technology, SA-LSTM model, Regression coefficient

© 2023 Tian Xie, published by Sciendo

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

An empirical analysis of the impact of Cross-border E-commerce on the competitiveness of SMEs based on the context of big data

Pubblicato online: 07 ott 2023

Pagine: -

Ricevuto: 18 nov 2022

Accettato: 17 apr 2023

DOI: https://doi.org/10.2478/amns.2023.2.00503

Parole chiaveCross-border E-commerce, big data technology, SA-LSTM model, Regression coefficient

© 2023 Tian Xie, published by Sciendo

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

Parole chiave
Cross-border E-commerce, big data technology, SA-LSTM model, Regression coefficient