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The double-edged impact of social media on online trading: Opportunities, threats, and recommendations for organizations

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  • Bizzi, Lorenzo
  • Labban, Alice

Abstract

While we understand well how social media channels sway consumers, there is little understanding of their influence on online trading behavior. We argue that social media are creating a new class of self-directed online traders by simultaneously encouraging and biasing trading decisions. Through an empirical study, we show that heavy social media users are more likely to engage in online trading but are largely affected by online herding behavior, and are four times more likely to blindly follow other traders. Bloggers, influencers, social network contacts, and social media news shape these users’ online trading behaviors. As online traders influenced by social media are unlikely to receive adequate returns, companies face an ethical dilemma: They could leverage social media to efficiently access funds but they risk inappropriately exploiting the inexperience of online traders biased by social media. We offer a set of nine practical recommendations for organizations to respond to these new challenges.

Suggested Citation

  • Bizzi, Lorenzo & Labban, Alice, 2019. "The double-edged impact of social media on online trading: Opportunities, threats, and recommendations for organizations," Business Horizons, Elsevier, vol. 62(4), pages 509-519.
    • Handle: RePEc:eee:bushor:v:62:y:2019:i:4:p:509-519
    DOI: 10.1016/j.bushor.2019.03.003
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    References listed on IDEAS

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    6. Gil Cohen, 2022. "Algorithmic Trading and Financial Forecasting Using Advanced Artificial Intelligence Methodologies," Mathematics, MDPI, vol. 10(18), pages 1-13, September.

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