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An empirical analysis of navigation behaviors across stock and cryptocurrency trading platforms: implications for targeting and segmentation strategies

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  • Hwang Kim

    (Chung-Ang University)

Abstract

This study examines and compares the behaviors of private investors in cryptocurrency and stock trading platforms. To this end, we propose a Tobit model for private investors who navigate across cryptocurrency and stock trading apps and identify factors associated with cryptocurrency and stock trading platform usage. We apply our model to unique mobile app usage data from August 2020 to March 2021, covering two waves of the COVID-19 cxpandemic in South Korea and the global speculative cryptocurrency bubble. We find that cryptocurrency and stock private investors differ considerably, in terms of demographics as well as such behaviors as loss-aversion, optimism, addiction, herding, cross-trading, and response to the pandemic. Our analysis also discovers potential competition between cryptocurrency and stock trading platforms in targeting their customers, e.g., private investors. Furthermore, we reveal behavioral profiles of segments of private investors of cryptocurrency and stocks, so the trading platforms can discover them. This study offers important managerial implications for trading platforms, to target and manage their private-investor customers.

Suggested Citation

  • Hwang Kim, 2024. "An empirical analysis of navigation behaviors across stock and cryptocurrency trading platforms: implications for targeting and segmentation strategies," Electronic Commerce Research, Springer, vol. 24(3), pages 2113-2141, September.
    • Handle: RePEc:spr:elcore:v:24:y:2024:i:3:d:10.1007_s10660-022-09612-1
    DOI: 10.1007/s10660-022-09612-1
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