BUSHOR-1569; No. of Pages 11 Business Horizons (2019) xxx, xxx—xxx Available online at www.sciencedirect.com ScienceDirect www.elsevier.com/locate/bushor The double-edged impact of social media on online trading: Opportunities, threats, and recommendations for organizations a, b Lorenzo Bizzi *, Alice Labban a Mihaylo College of Business & Economics, California State University, Fullerton, 800 N. State College Blvd., Fullerton, CA 92831, U.S.A. b Seaver College, Pepperdine University, 24255 Pacific Coast Highway, Malibu, CA 90265, U.S.A. KEYWORDS Abstract While we understand well how social media channels sway consumers, fl Social media; there is little understanding of their in uence on online trading behavior. We argue Online trading; that social media are creating a new class of self-directed online traders by Social networks; simultaneously encouraging and biasing trading decisions. Through an empirical Blogging; study, we show that heavy social media users are more likely to engage in online Cryptocurrencies 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. # 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved. 1. The impact of social media on trading: The rise of online traders Bitcoin and cryptocurrencies represent a fascinat- * Corresponding author ing and timely case to study. A bitcoin traded in July E-mail addresses: [email protected] (L. Bizzi), [email protected] (A. Labban) 2010 for just $0.06, in January 2017 for $900, and in https://doi.org/10.1016/j.bushor.2019.03.003 0007-6813/# 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved. BUSHOR-1569; No. of Pages 11 2 L. Bizzi, A. Labban December 2017 for $19,700. In 2010, $100 invested attracted by the messages diffused by social would have turned into over $30 million in 2017. By media and are encouraged to use their financial the end of 2017, there were over 1,300 cryptocur- resources in online trading instead of using them rencies with a market capitalization of about $587 for alternative purposes, such as savings, mort- billion and $500 billion daily volume of online trans- gages, long-term investments, or consumption. This actions. After reaching their peak, the cryptocur- increases the supply of capital, market liquidity, rencies’ prices started dramatically fluctuating and capitalization, and, consequently, the performance bitcoin’s price dropped from $19,000 to about of traded assets. However, the new traders’ lower $5,000 in just a few months. One possible reason financial literacy–— compared to experienced or in- for both the performance and risk of cryptocurren- stitutional investors–— makes them vulnerable to the cies is the effect of social media on online trading, distorted messages spread via social media. Social which started from the beginning. The creator of media sources can influence herding behaviors Bitcoin, Satoshi Nakamoto, published a white paper in which traders blindly and quickly follow one online, disseminating information in over 500 posts another’s trading decisions, which cause swift fluc- in a social media forum. Bitcoin started attracting tuations in asset prices that influence risk of traded interest in 2011 when WeUseCoins published an financial assets. In light of these observations, we online video that went viral on social media, reach- illustrate the effects of social media use on online ing 6.4 million views. Social media diffused infor- trading, explore aggregate consequences for orga- mation about companies accepting bitcoin as nizations, and devise actionable recommendations payment and about the growth of cryptocurrencies. for organizations to exploit opportunities and Garcia, Tessone, Mavrodiev, and Perony (2014) stip- minimize threats. ulated that the volume of word-of-mouth commu- nications in social media and the volume of information search diffused through social media 2. A model for social media use and influenced price growth and fluctuations of Bitcoin. online trading Mai, Shan, Bai, Wang, and Chiang (2018) found that the user-generated content diffused through social Figure 1 portrays how social media use influences media had a significant impact on Bitcoin volume of online trading. The model presents five sources of transactions and performance. The cryptocurrency social media influence that affect online trading case is an example of how social media can signifi- behaviors in two ways: (1) online trading decision, cantly affect online trading, calling for the need to which refers to the decision to use personal finan- understand the phenomenon. cial resources for the acquisition through online The purpose of this article is to understand how trading of financial assets (e.g., stocks, securities, social media influence online trading. While we are cryptocurrencies) instead of using these resources already aware that social media affect decisions of for alternative uses (e.g., consumption, saving, institutional investors–— 44% of them reported using long-term investments); and (2) online herding be- social media to find content that can better inform havior, which is the decision to select the assets to investment decisions (Greenwich Associates, trade online as a function of the decisions or sug- 2014)–— there is an unexplored effect of social gestions made by others. The model anticipates media that academics have not yet considered. that the more people use social media, the Social media is creating a new class of online more affected they are by these social media influ- traders that has been growing in recent years. ences and the more likely they are to engage in According to Aite Group (2014), about 25% of online trading and online herding behavior. Sections U.S. adults are online self-directed traders, total- 2.1.—2.5. review the five social media sources of ing 54 million traders with $2.8 trillion in assets. influence, detailing how they specifically affect NASDAQ (2017) reported that in 2017, E-Trade online trading and online herding behaviors. Financial Corporation alone reached 3.6 million brokerage accounts that held $285 billion in secu- 2.1. Social trading platforms rities. Self-directed online traders tend to be young, with millennials controlling 68% of all at- Social trading platforms, such as ZuluTrade, Stock- risk assets, according to J.D. Power (2017). A study Twits, Seeking Alpha, Sharewise, Wikifolio, or by the Student Loan Report (2018) said that over eToro–— a platform that boasted 5 million accounts 20% of university students with loan debt used their in 2018–— offer information via decentralized crowd- borrowings for cryptocurrency trading. sourced stock assessments in which individuals copy The effects of social media on online trading the trading decisions of one another instead of is not entirely positive. Individuals are likely following financial recommendations provided by BUSHOR-1569; No. of Pages 11 The double-edged impact of social media on online trading 3 Figure 1. A model for the effect of social media on online trading behavior institutional investors. These specialized channels stocks of the company plummeted, leading to losses have been growing in popularity and attracting of $1.3 billion. A scrupulous analysis suggests there new traders (Wang et al., 2015). The more people were multiple possible causes behind the collapse, use social media, the more they get exposed to but still several suggest that the tweet may have information about social trading platforms, increas- somehow influenced the fluctuation. While bloggers ing the likelihood of engaging in online trading since are primarily known for their blogs, influencers do they perceive that online trading is easy and accessi- not necessarily have a website or blog but are ble to everyone. However, social trading platforms sought after by many individuals and are often at exacerbate herding behaviors because individuals the center of conversations rather than being the automatically imitate trading choices of the masses. person who guides them. Social media celebrities, through their comments and opinions, influence 2.2. Bloggers individuals who would like to be associated and identified with them (Shalev & Morwitz, 2011). Bloggers are perceived as credible sources that send Influencers are powerful human brands that posi- reliable quality signals, strongly influencing the per- tively impact the performance of companies asso- ceptions of individuals and their subsequent deci- ciated with them (Kupfer, vor der Holte, Kübler, & sions (Luo, Zhang, Gu, & Phang, 2017). Financial Hennig-Thurau, 2018). The motivation to be bloggers provide information about trading recom- recognized as influential members in a social mendations and forecasts, impacting trading deci- media network drives social media influencers sions (Saxton & Anker, 2013). Individuals perceive (Kietzmann, Hermkens, McCarthy, & Silvestre, bloggers report whispers, rumors, privileged infor- 2011). About 40% of financial