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Consumer’s risk perception on the Belt and Road countries: evidence from the cross-border e-commerce

Author

Listed:
  • Jianping Li

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Yinhong Yao

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Yuanjie Xu

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jingyu Li

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Lu Wei

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xiaoqian Zhu

    (Chinese Academy of Sciences)

Abstract

Understanding consumer’s risk perception on the Belt and Road (B&R) countries is important for the development of cross-border e-commerce (CBEC) along these countries. However, most of the extant studies cannot properly analyze consumer’s risk perception due to the limited data collected by questionnaires. Therefore, this study proposes a text-mining-based framework to study consumer’s risk perception on the B&R countries based on massive textual online reviews collected from CBEC. In the proposed framework, the Latent Dirichlet Allocation model and sentiment analysis method are used to identify the main risk factors affecting consumer’s risk perception and calculate their sentiment score, the risk perception indicator is constructed to measure the magnitude of consumer’s risk perception. In the experiment, totally 66,661 reviews of the representative products from nine B&R countries are collected from Tmall Global. Six major risk factors are identified, and consumer’s risk perception on nine B&R countries is given.

Suggested Citation

  • Jianping Li & Yinhong Yao & Yuanjie Xu & Jingyu Li & Lu Wei & Xiaoqian Zhu, 2019. "Consumer’s risk perception on the Belt and Road countries: evidence from the cross-border e-commerce," Electronic Commerce Research, Springer, vol. 19(4), pages 823-840, December.
    • Handle: RePEc:spr:elcore:v:19:y:2019:i:4:d:10.1007_s10660-019-09342-x
    DOI: 10.1007/s10660-019-09342-x
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    References listed on IDEAS

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    Cited by:

    1. Chuanmin Mi & Yijing Wang & Lin Xiao, 2021. "Prediction on transaction amounts of China’s CBEC with improved GM (1, 1) models based on the principle of new information priority," Electronic Commerce Research, Springer, vol. 21(1), pages 125-146, March.
    2. Zi Hui Yin & Chang Hwan Choi, 2023. "The effects of China’s cross-border e-commerce on its exports: a comparative analysis of goods and services trade," Electronic Commerce Research, Springer, vol. 23(1), pages 443-474, March.
    3. Shugang Li & Fang Liu & Yuqi Zhang & Boyi Zhu & He Zhu & Zhaoxu Yu, 2022. "Text Mining of User-Generated Content (UGC) for Business Applications in E-Commerce: A Systematic Review," Mathematics, MDPI, vol. 10(19), pages 1-26, September.

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