Prediction of the Development Scale of Live E-commerce Based on Data Analysis and Research on Influencer Impact

Research Article
Open access

Prediction of the Development Scale of Live E-commerce Based on Data Analysis and Research on Influencer Impact

Yiheng Zhuang 1*
  • 1 Kunshan High School, Suzhou, China    
  • *corresponding author bettyxu0703@foxmail.com
Published on 25 June 2025 | https://doi.org/10.54254/3049-5768/2025.23448
JFBA Vol.2 Issue 1
ISSN (Print): 3049-5776
ISSN (Online): 3049-5768

Abstract

With the development of the internet, live e-commerce has emerged, where different influencers and product types correspond to varying marketing results. This paper focuses on the live e-commerce industry, reviewing the related research of domestic and international scholars such as Zhao Hongmei and Han Haoliang. It analyzes and predicts the types of influencers and various products, presenting the basic situation and statistical data of the online live streaming marketing market, and forecasting the future market scale. In addition, the paper takes Li Jiaqi and Dongfang Zhenxuan as examples to analyze the characteristics of similar influencers and the factors influencing their impact. A series of conclusions are drawn, which are of significant practical importance for understanding the development trends of live e-commerce.

Keywords:

live e-commerce, influencers, predictive models, impact analysis

Zhuang,Y. (2025). Prediction of the Development Scale of Live E-commerce Based on Data Analysis and Research on Influencer Impact. Journal of Fintech and Business Analysis,2(1),80-85.
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References

[1]. Zhao, H. M. (2024). Analysis of the marketing path of agricultural products relying on live streaming. Market Weekly, 37(29), 91–94.

[2]. Han, H. L., & He, S. X. (2024). Analysis and research on the influence of live streaming influencers on consumer purchasing behavior under the background of big data. Shopping Mall Modernization, (15), 53–55. https://doi.org/10.14013/j.cnki.scxdh.2024.15.036

[3]. Li, G. X., & Tang, P. W. (2024). A study on the inverted U-shaped influence of streamer group size on brand live streaming sales performance: An empirical study from the cosmetics industry. Journal of Marketing Science, 4(01), 18–35.

[4]. Jiang, F. (2019). The four major business model choices of live streaming. Media, (4), 2.

[5]. Li, L. P. (2025). Analysis of the influence mechanism of agricultural product e-commerce live streaming on consumers’ purchase intentions. Business Economic Research, (03), 122–125.

[6]. Guo, Y. (2025). Exploration of innovative paths for the live streaming e-commerce model based on big data analysis. Time-Honored Brand Marketing, (01), 112–114.

[7]. Zhao, Y. F., & Ma, Z. Y. (2024). The impact of the perceived value structure of live streaming e-commerce on consumers’ purchase intentions. International Business and Accounting, (23), 20–28 + 35.

[8]. Dong, Y. Z. (2024). A review of the current status, issues, and optimization paths of live streaming e-commerce. Hebei Enterprise, (12), 19–23. https://doi.org/10.19885/j.cnki.hbqy.2024.12.004

[9]. Wang, C. X. (2025). A study on the impact of live streaming e-commerce on the transformation and upgrading of traditional enterprises. Shopping Mall Modernization, (04), 33–35. https://doi.org/10.14013/j.cnki.scxdh.2025.04.010

[10]. Chen, Y. S., & Zhang, X. Y. (2025). A study on the factors influencing consumer purchase intentions in e-commerce live streaming. Modern Business, (01), 3–6. https://doi.org/10.14097/j.cnki.5392/2025.01.001

[11]. Guo, X. J. (2025). Exploration of the characteristics and innovative models of Douyin e-commerce. Economist, (01), 26–27.

[12]. Wang, Y. T., Chen, Y., Chen, S. Z., et al. (2025). Maximizing sales: The art of short video creation in livestream e-commerce. Computers & Industrial Engineering, 200, 110824.

[13]. Yongbing, J., Emine, S., Liguo, L., et al. (2024). How streamers enhance consumer engagement and brand equity in live commerce. Journal of Global Information Management (JGIM), 32(1), 1–29.

[14]. Liu, J. (2024). A method for identifying consumer emotional tendency in the ‘live streaming + e-commerce’ mode. International Journal of Web Based Communities, 20(3–4), 200–211.

[15]. Dawei, D. (2024). Analysis of the communication mode of short video platforms from the perspective of e-commerce live streaming fever. Philosophy and Social Science, 1(6).

[16]. Huang, Y., Makmor, N., & Mohamad, H. S. (2024). Research progress analysis of live streaming commerce based on CiteSpace. Heliyon, 10(16), e36029.

Cite this article

Zhuang,Y. (2025). Prediction of the Development Scale of Live E-commerce Based on Data Analysis and Research on Influencer Impact. Journal of Fintech and Business Analysis,2(1),80-85.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Journal：Journal of Fintech and Business Analysis

Volume number: Vol.2
Issue number: Issue 1
ISSN：3049-5768(Print) / 3049-5776(Online)

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References

[1]. Zhao, H. M. (2024). Analysis of the marketing path of agricultural products relying on live streaming. Market Weekly, 37(29), 91–94.

[2]. Han, H. L., & He, S. X. (2024). Analysis and research on the influence of live streaming influencers on consumer purchasing behavior under the background of big data. Shopping Mall Modernization, (15), 53–55. https://doi.org/10.14013/j.cnki.scxdh.2024.15.036

[3]. Li, G. X., & Tang, P. W. (2024). A study on the inverted U-shaped influence of streamer group size on brand live streaming sales performance: An empirical study from the cosmetics industry. Journal of Marketing Science, 4(01), 18–35.

[4]. Jiang, F. (2019). The four major business model choices of live streaming. Media, (4), 2.

[5]. Li, L. P. (2025). Analysis of the influence mechanism of agricultural product e-commerce live streaming on consumers’ purchase intentions. Business Economic Research, (03), 122–125.

[6]. Guo, Y. (2025). Exploration of innovative paths for the live streaming e-commerce model based on big data analysis. Time-Honored Brand Marketing, (01), 112–114.

[7]. Zhao, Y. F., & Ma, Z. Y. (2024). The impact of the perceived value structure of live streaming e-commerce on consumers’ purchase intentions. International Business and Accounting, (23), 20–28 + 35.

[8]. Dong, Y. Z. (2024). A review of the current status, issues, and optimization paths of live streaming e-commerce. Hebei Enterprise, (12), 19–23. https://doi.org/10.19885/j.cnki.hbqy.2024.12.004

[9]. Wang, C. X. (2025). A study on the impact of live streaming e-commerce on the transformation and upgrading of traditional enterprises. Shopping Mall Modernization, (04), 33–35. https://doi.org/10.14013/j.cnki.scxdh.2025.04.010

[10]. Chen, Y. S., & Zhang, X. Y. (2025). A study on the factors influencing consumer purchase intentions in e-commerce live streaming. Modern Business, (01), 3–6. https://doi.org/10.14097/j.cnki.5392/2025.01.001

[11]. Guo, X. J. (2025). Exploration of the characteristics and innovative models of Douyin e-commerce. Economist, (01), 26–27.

[12]. Wang, Y. T., Chen, Y., Chen, S. Z., et al. (2025). Maximizing sales: The art of short video creation in livestream e-commerce. Computers & Industrial Engineering, 200, 110824.

[13]. Yongbing, J., Emine, S., Liguo, L., et al. (2024). How streamers enhance consumer engagement and brand equity in live commerce. Journal of Global Information Management (JGIM), 32(1), 1–29.

[14]. Liu, J. (2024). A method for identifying consumer emotional tendency in the ‘live streaming + e-commerce’ mode. International Journal of Web Based Communities, 20(3–4), 200–211.

[15]. Dawei, D. (2024). Analysis of the communication mode of short video platforms from the perspective of e-commerce live streaming fever. Philosophy and Social Science, 1(6).

[16]. Huang, Y., Makmor, N., & Mohamad, H. S. (2024). Research progress analysis of live streaming commerce based on CiteSpace. Heliyon, 10(16), e36029.

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