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<p>Under the environment of rapid development of e-commerce platforms and Internet technology, consumers are more and more inclined to online shopping. This paper takes consumers’ perceived value as the main research object and adds platform attributes, such as function, content, brand, etc. The main factors affecting perceived usefulness, perceived entertainment, and perceived risk construct a theoretical model of the factors affecting consumers’ willingness to buy in cross-border e-commerce live streaming. In order to further analyze the importance of the factors influencing consumer purchase intention in cross-border e-commerce live streaming, this paper constructs a prediction model based on random forest according to the evolution of consumer purchase intention and the prediction of consumer purchase intention. Consumers’ perceived value of cross-border e-commerce platforms is not affected by perceived risk, as shown by the regression and prediction analyses. Perceived usefulness and perceived entertainment are affected by platform attributes accordingly. Cross-border e-commerce live streaming has the most significant impact on consumers’ willingness to buy, with platform features accounting for 17% of all influencing factors. The role of platform function in consumers’ purchase intention in cross-border e-commerce live streaming is demonstrated in this study.</p>
</abstract>

Under the environment of rapid development of e-commerce platforms and Internet technology, consumers are more and more inclined to online shopping. This paper takes consumers’ perceived value as the main research object and adds platform attributes, such as function, content, brand, etc. The main factors affecting perceived usefulness, perceived entertainment, and perceived risk construct a theoretical model of the factors affecting consumers’ willingness to buy in cross-border e-commerce live streaming. In order to further analyze the importance of the factors influencing consumer purchase intention in cross-border e-commerce live streaming, this paper constructs a prediction model based on random forest according to the evolution of consumer purchase intention and the prediction of consumer purchase intention. Consumers’ perceived value of cross-border e-commerce platforms is not affected by perceived risk, as shown by the regression and prediction analyses. Perceived usefulness and perceived entertainment are affected by platform attributes accordingly. Cross-border e-commerce live streaming has the most significant impact on consumers’ willingness to buy, with platform features accounting for 17% of all influencing factors. The role of platform function in consumers’ purchase intention in cross-border e-commerce live streaming is demonstrated in this study.

Analysis of Influencing Factors on Consumers’ Purchase Intention in Cross-border E-commerce Live Streaming

Applied Mathematics and Nonlinear Sciences

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

Under the environment of rapid development of e-commerce platforms and Internet technology, consumers are more and more inclined to online shopping. This paper...

Analysis of Influencing Factors on Consumers’ Purchase Intention in Cross-border E-commerce Live Streaming

Publié en ligne: 02 juil. 2024

Pages: -

Reçu: 17 févr. 2024

Accepté: 14 mai 2024

DOI: https://doi.org/10.2478/amns-2024-1515

Mots clés
Random forest, Regression analysis, Predictive analysis, Cross-border e-commerce live streaming

© 2024 Xiaoli Wu, published by Sciendo

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

Analysis of Influencing Factors on Consumers’ Purchase Intention in Cross-border E-commerce Live Streaming

Publié en ligne: 02 juil. 2024

Pages: -

Reçu: 17 févr. 2024

Accepté: 14 mai 2024

DOI: https://doi.org/10.2478/amns-2024-1515

Mots clésRandom forest, Regression analysis, Predictive analysis, Cross-border e-commerce live streaming

© 2024 Xiaoli Wu, published by Sciendo

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

Mots clés
Random forest, Regression analysis, Predictive analysis, Cross-border e-commerce live streaming