Analysis of launch strategy in cross-border e-Commerce market via topic modeling of consumer reviews

Feifei Wang, Yang Yang, Geoffrey K. F. Tso, Yang Li*

*Corresponding author for this work

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Spurred by the policy of China’s Belt and Road Initiative, Chinese e-Commerce companies have found great opportunities in selling goods overseas. The cross-border e-Commerce shares similarities of launch and marketing strategies with domestic e-Commerce, but also has substantial differences. How to make strategic adjustments to better adapt to the overseas market is of great concern to cross-border e-Commerce companies. Analyzing behaviors of overseas consumers could offer an effective way to address this issue and has attracted great interest of researchers. Consumer comments, cheap and abundant by its nature, provides an easy access for analysis of consumer behaviors. In this paper, we focus on consumer reviews of a specific product, the cellphones, and apply topic modeling techniques to investigate the differences between behaviors of domestic and overseas consumers. We find that consumers from domestic and overseas focus on different aspects of product. In addition, the foreign consumers care more about product quality and tend to make description of technique details. On the contrary, domestic buyers pay more attention on consumer services and intend to comment in generalities. All these findings could help e-Commerce companies design better launch strategies in cross-border e-Commerce market.
    Original languageEnglish
    Pages (from-to)863–884
    JournalElectronic Commerce Research
    Volume19
    Issue number4
    Online published23 Jul 2019
    DOIs
    Publication statusPublished - Dec 2019

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 17 - Partnerships for the Goals
      SDG 17 Partnerships for the Goals

    Research Keywords

    • Consumer behavior
    • Consumer reviews
    • Cross-border
    • e-Commerce
    • Regularized regression
    • Topic models

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