The Double-Edged Impact of Social Media on Online Trading 3

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

Mihaylo College of Business & Economics, California State University, Fullerton, 800 N. State College

Blvd., Fullerton, CA 92831, U.S.A.

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

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 advisers are motivated

mation, and precious leaks that may not be known to to promote a personal image of a thought leader

those who do not blog, therefore motivating trading and inﬂuencer through social media (Putnam

decisions (Harjoto, Zaima, & Zhang, 2009). Financial Investments, 2015). The more people use social

bloggers compete to attract an audience by dissemi- media, the more they become likely to follow in-

nating a large amount of trading information and ﬂuencers’ recommendations and engage in online

have become important sources of information for trading. However, individuals blindly follow the

trading (Fotak, 2007). The more people spend time opinions or recommendations of inﬂuencers instead

using social media, the more they will be inﬂuenced of rationally making decisions on their own (Pelster

by bloggers and decide invest with online trading. & Gonzalez, 2016), exacerbating herding behaviors.

However, the crowd imitates the choices of famous

bloggers. Bloggers inﬂuence one another and fol- 2.4. Social network contacts

lowers imitate bloggers and share their predictions,

exacerbating herding behaviors. The personal contacts developed through social

networks inﬂuence-trading behaviors. Social con-

2.3. Inﬂuencers tacts use social networking sites to give visibility to

their trading decisions, through posts, to exchange

On February 21, 2018, Kylie Jenner posted an ad- information about trading decisions and encourage

verse tweet against Snapchat and, soon after, the each other to trade (Mudholkar & Uttarwar, 2015).

BUSHOR-1569; No. of Pages 11

4 L. Bizzi, A. Labban

Information coming from friends and social contacts Gentzkow, 2017). Fake news tends to spread

is perceived as trustworthy and individuals tend to rapidly through social media because people are

give more importance to word-of-mouth communi- less likely to question news when they see them-

cation from social contacts than from professional selves as part of a public social group (Jun, Meng,

experts (Garcia, 2013). & Johar, 2017), especially when it comes to youn-

Affective relationships lead individuals to imi- ger individuals who tend to trust online sources

tate the decisions of their friends in order to satisfy more than others (Warner-Søderholm et al.,

the need of belonging to a group (Kilduff, 1990). If 2018). As fake news become viral, it is likely to

contacts make a social media post about their trigger herding behaviors. Information reported

acquisition of a cryptocurrency or encourage trad- by online trading publishers often leverages ques-

ing, a friend may feel the desire to imitate them. tionable technical analysis that appeals to a

The constant information provided by social media large audience due to its simplicity but supports

contacts and accessed through notiﬁcations from impulsive decisions and herding behaviors.

mobile apps may exacerbate fear of missing out as

applied to trading decisions, motivating individuals

to trade in order to reduce the apprehension 3. An exploratory empirical study

and anxiety that stems from the possibility of miss-

ing out on rewards social contacts are enjoying In order to provide evidence for the effect of social

(Clor-Proell, Guggenmos, & Rennekamp, 2018). media on online trading, we conducted an explor-

Katsenelson (2018) argued that fear of missing atory empirical study on a random sample of

out may have been a core reason why many individ- 286 Americans. The sample selection was complete-

uals bought bitcoin and other cryptocurrencies. The ly random, without exclusion criteria, except for

more people use social media, the more they are adult age, to assess the observed effects on a

inﬂuenced by their network of contacts, increasing sample representative of the diversity of the entire

the likelihood to trade online. Moreover, friends will U.S. population. We measured social media use by

imitate one another’s trading decisions, which will asking respondents to indicate the amount of time

quickly spread in the social networks and exacer- they usually spend on social media each day. We

bate herding behaviors. then asked them to report how likely they are to

engage in online trading. Then, using indicators for

2.5. Online trading publishers online herding behavior, we asked them to assess

the likelihood, if they were to engage in online

Social media host a large number of pages from trading, that they would make trading decisions

new media publishers that specialize in dissemi- “following the choices others make when trading

nating online trading information. Online content online, blindly following the choices others make

published in social media is timely, constantly when trading online or looking at choices others

updated, and easily accessible. While acclaimed make rather than trying to understand future cash

media sources (e.g., The Wall Street Journal or ﬂow.” We then assessed the strength of the sources

Financial Times) often require a paid subscrip- of social media inﬂuence. First, we asked: “In

tion, these specialized publishers are mostly free general, how likely are you to consider the opinion

and targeted speciﬁcally to self-directed online of the following people on social media?” providing

traders. The more people use social media, the the following options: bloggers, inﬂuencers, my

more they get exposure to information about social media friends and contacts, people who write

online trading, which increases familiarity with articles in social media, and online news publishers.

it and encourages involvement. Information dif- Second, we focused speciﬁcally on assessing the

fused through social media publishers is likely to inﬂuence of social media sources on online trading

appeal because of sensationalism and extreme decisions and asked the following question: “If you

opinions that quickly exacerbate positive or neg- would ever do online trading, how likely are you to

ative views. Social media publishers spurred the consider the opinion of the following people on

diffusion of deliberate misinformation, or fake social media?” The answers provided were bloggers,

news, that attract interest because of their sen- inﬂuencers, my social media friends and contacts,

sational appeal. Social media are the perfect people who write articles in social media about

vehicle for the diffusion of fake news because online trading, and people who use social trading

content spreads without third-party ﬁltering, fact platforms (which was explained as websites in

checking, or editorial judgment, which allows which online traders share opinions and choices

individuals with no record or reputation to reach about online trading). Questions were rated using

as many readers as major publishers (Allcott & 5-point Likert scales.

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The double-edged impact of social media on online trading 5

Table 1. Empirical evidence from the exploratory study

Statistical Strength ( p-value): Medium High .

Results of the partial correlations control for: (1) gender, (2) age, (3) years of tenure in current organization, (4) education level,

(5) college business education, (6) number of books about business read.

Table 1 shows the results of the exploratory but a surprising 26% of heavy social media

study. The table reports partial correlation results users would blindly follow others when trading

that illustrate the effects of social media use con- online;

trolling for and therefore removing for the effect of

respondents’ differences in, age, gender, tenure of Heavy social media users are four times more

years inside their current organization, level of likely to follow others blindly when trading online

education, whether or not they received a college than light social media users; and

degree in business, and the amount of business

books they have ever read. These last two controls Heavy social media users are 64% more likely than

are important to observe differences among re- light social media users to look at choices others

spondents with or without business knowledge. make rather than trying to understand future

The table shows the difference in the responses cash ﬂow.

of individuals who report light use of social media

(1 hour or less per day) versus heavy use of social We can notice strong differences also when it comes

media (2 hours or more per day). We found strong to the inﬂuence of social media sources:

conﬁrmation for our empirical model. There is a

partial correlation of medium strength between 59% of heavy social media users are inﬂuenced by

social media use and online trading likelihood and bloggers against 37% of light social media users;

a strong partial correlation with all other indicators.

We can see that heavy social media users have 63% 45% of heavy social media users are inﬂuenced by

likelihood of considering online trading (moderately inﬂuencers comparatively to 25% of light social

or higher) against 55% of light social media users. media users;

The differences get very pronounced when it comes

to online herding behaviors: 89% of heavy social media users are inﬂuenced by

their social contacts, compared to 69% of light

78% of heavy social media users are likely (some- social media users; and

what likely or higher) to follow the choices of

others when trading online against 54% of light Heavy social media users are 78% more likely to

social media users; be inﬂuenced by people who write articles on

social media and 23% more likely to be inﬂu-

Only 4% of light social media users would blindly enced by online publishers than light social

follow the choices of others when trading online media users.

BUSHOR-1569; No. of Pages 11

6 L. Bizzi, A. Labban uencers. t or cost for fl fi uence of fake news. individuals. INDIVIDUALS fl with the company. Developing a better reliable information. BENEFITS/COST FOR relationship with the by biased in biases of social media. companies. Making better being less affected by the online trading decisions by No direct bene Making better online trading Making better online trading Individuals can get access to the company. Access to more better information for making develop stronger relationships to the in Opportunity to develop better their trading decisions and can decisions by being less affected relationships with employees of decisions by being less exposed ts fi , and s s value. ’ ’ ’ uencers and fl , investors prices. ’ decisions. responses to better ambassadors. ’ ts customer relations, ORGANIZATIONS Create company fi exposure, reducing Better control of the uence of in information and crisis media sources. Gaining effects of fake news on Minimizing the negative fl uence on the brand and the uctuations, and attracting maximizing their positive and possible direct sales. consumers and on security the determination of asset fl organizational attachment. Better communicating with management. Decrease the fl consumers the diffusion of information in search engine optimization, bene traders about the company. Bene also for employees and their attention from stakeholders. performance and risk. It also Better involving employees in consumers, traders, and social make, time, and communicate Understanding and anticipating relevance of outside bloggers in Protection from the deleterious in perception of company businesses. businesses. businesses. For all companies in all For all companies in all For all companies in all appeal to large masses. engaged in social media. audience on social media. customer base and a large For companies with a large For companies with a large of employees who are often For companies with a large base audience, with products mostly targeted to millennials and that nancial results. company. company. fi sentiment. t and do not damage the uencers, without paying through legal action. fi to ensure accuracy of feedback and monitor diffuse information to information about the report fl Create corporate blogs, Constant engagement in them, to ensure accurate Monitoring of social media in reporting and monitoring of Nurturing relationships with information shared, provide and promptly respond, even traders. Use social media to their social media exchanges for employees to ensure that customers, stakeholders, and sources to identify fake news Develop a social media policy study social media sentiments Investment in data analytics to and develop predictive models. participate in forums and blogs corporate social media pages to bene uencer fl RECOMMENDATION DESCRIPTION FOR WHICH COMPANIES? BENEFITS FOR Data Analytics Investment Corporate Blogging Management of Corporate Social Media Social Media Policy Social Media Intelligence Earned In Marketing Table 2. Recommendations for organizations

BUSHOR-1569; No. of Pages 11

The double-edged impact of social media on online trading 7 cant fi cant possibility fi marketed. INDIVIDUALS BENEFITS/COST FOR They acquire intangible from the funds invested. Highly risky for individuals. they do not acquire equity. possibility of not seeing any of not perceiving any return returns, gifts, or the right to possibility of fraud and Ponzi High possibility of fraud. High return for the funds provided. No risk for individuals because schemes. Signi receive the products if they are Risky for individuals. Signi cient funds. fi entrepreneur. ORGANIZATIONS insuf Risk of law violation. business. Risk of raising Easy way of raising funds, Easy way of raising funds, minimizing costs, avoiding minimizing costs, avoiding minimizing costs, avoiding No giving up ownership and retaining full control of the Ownership is given away but Quickest way of raising funds, intermediaries and regulations. intermediaries and regulations. intermediaries and regulations. control is often retained by the t fi cant fi capital. services. blockchain technology. innovative products and services. Effective when investors have signi and businesses related to that require little startup For startup companies, for For startup companies, for knowledge of the products/ organizations, for businesses in high-technology businesses For startup companies, mostly social enterprises, for nonpro securities. tender or other cryptocurrencies. Raising funds through crowdfunding websites in Raising funds through the providing ownership titles. tokens exchanged for legal emission of cryptocurrency Raising small funds through exchange for private company crowdfunding websites without ) Continued ( RECOMMENDATION DESCRIPTION FOR WHICH COMPANIES? BENEFITS FOR NonEquity Crowdfunding Equity Crowdfunding Initial Coin Offering (ICO) Table 2

BUSHOR-1569; No. of Pages 11

8 L. Bizzi, A. Labban

When we focus on the scenario of respondents However, the consequences for individuals will

engaging in online trading, the differences become be deleterious. Most online traders are likely to be

even more pronounced. Here, we can see that noise traders, who, due to their low ﬁnancial

bloggers inﬂuence 50% of heavy social media users literacy and to the biasing inﬂuence of social me-

against 29% of light social media users. Then, 54% of dia, do not base their decisions on fundamental

heavy social media users are inﬂuenced by inﬂu- analysis and on actual changes in the intrinsic value

encers compared to 29% of light social media users. of the securities or assets they trade. They will

Furthermore, social contacts inﬂuence 69% of heavy base their decisions on what others are doing on

social media users compared to 40% of light social social media; on sensational, imperfect, and bi-

media users. Last, a surprising 89% and 91% of heavy ased information diffused through social media; or

social media users are likely to be inﬂuenced, re- impulsive comments from social media celebrities

spectively, by people who write articles in social or on dubious technical analysis predictions re-

media about online trading and by people who use leased by uncredited social media sources. The

social trading platforms. Light social media users vast majority of self-directed traders–— over 90%

are respectively 70% and 45% less likely to be inﬂu- of them–— lose money with the aggregate portfolio

enced by the same sources. Overall, evidence of individuals suffering an annual performance

strongly supports our proposed ideas. penalty of 3.8% (Barber, Lee, Liu, & Odean,

2008). Therefore, social media could exacerbate

noise trading and make individuals lose money.

4. Consequences for organizations

and individuals

5. Recommendations for

While the model explains the effect of social media

organizations

use at the individual level, we can derive inferences

on aggregate consequences for organizations. So-

Social media can create both opportunities and

cial media use has been dramatically increasing in

threats for organizations. As the threat of risk

the last years. The percentage of U.S. adults using

creates challenges, there is also an opportunity

social media changed from 8% in 2006 to 50% in

to gain easy access to funds. Many startups resort

2012 to 69% in 2018 (PEW Research Center, 2018).

to getting funds through crowdfunding initiatives in

The daily worldwide time spent on social network-

which the social media inﬂuence on trading be-

ing sites has increased by 50% in the last 5 years,

comes relevant. However, as we mentioned, most

from 90 minutes in 2012 to 135 minutes in 2017

individuals who trade online risk losing their

(Statista, 2018). The increase in social media use

money. Should organizations beneﬁt from this kind

is likely to trigger systemic effects for organiza-

of opportunity? Here, we provide nine recommen-

tions, inﬂuencing aggregate performance and risk

dations for organizations in response to the chal-

of traded assets. Performance refers to the average

lenges of social media inﬂuence on online trading.

price in any asset traded in a speciﬁed period of

Table 2 summarizes the recommendations, brieﬂy

time and risk refers to the ﬂuctuation in prices in

describes them, highlights for which businesses

the assets traded in a speciﬁed period of time. The

they should be implemented, and isolates the ben-

increase of social media use positively affects per-

eﬁts and costs for both organizations and individual

formance by encouraging online trading, which in-

traders.

creases the supply of capital, providing new

liquidity to the market and therefore inﬂuencing

performance of assets traded. Increased social me- 5.1. Data analytics investment

dia does have other effects; it exacerbates herding

effects, which significantly influence fluctuations in A key recommendation is to invest in data analytics

prices by virtue of their strength, velocity, and to explore, examine, and understand social media

frequency. Information that goes viral on social sentiment. Social media sentiment affects the way

media spreads at incredible velocity and high fre- in which investors and traders perceive informa-

quency, being often difﬁcult to predict or control. tion and form opinions about the intrinsic value

The market may not always efﬁciently correct mis- of assets (Piñeiro-Chousa, Vizcaíno-González, &

priced assets, resulting in multiple and signiﬁcant Pérez-Pico, 2017). From the understanding of so-

ﬂuctuations. At the aggregate level, social media is cial media sentiment, organizations can develop

therefore likely to exercise a double-edged impact predictive models that anticipate the reaction of

for organizations, affecting both performance and traders and foresee evolution and ﬂuctuation in

risk of traded assets. the prices of securities. Bollen, Mao, and Zheng

BUSHOR-1569; No. of Pages 11

The double-edged impact of social media on online trading 9

(2011) found that by measuring the sentiment on that shape the opinions of masses. While companies

Tw i t t e r, it is possible to build a model that predicts should not pay inﬂuencers to diffuse information

(with 86% accuracy) whether the market will rise or that directly affects value perception, earned in-

fall 3 days later. Models could be tailored to the ﬂuencer marketing–— whereby inﬂuencers do not

speciﬁc characteristics of each company, for which receive money/compensation but rather gain via

different social media sentiments could translate association with the company–— may be advisable.

more or less intensely into responses from traders. Inﬂuencers do have personal relationships with

Companies can use this knowledge as a basis to management and use these relationships to gain

understand how their decisions can potentially legitimacy and obtain credibility for their recom-

affect market responses, to better time their de- mendations. Organizations should nurture their re-

cisions, and to better communicate and select lationships with inﬂuencers, attracting their

their decisions. interest and giving them access to information that

the inﬂuencers could choose to diffuse in order to

5.2. Managing corporate social media affect perceptions about the company. Positive

relationships with inﬂuencers could avoid that in-

Through corporate social media accounts, ﬁrms ﬂuencers spread dubious information about the

share information that reaches online traders, blog- company and give them the opportunity to verify

gers, inﬂuencers, publishers, or end consumers. whether the information they wish to share is

Through corporate social media, companies can accurate.

minimize the deleterious effects of social media

while maximizing positive effects. According to Kim 5.5. Corporate blogging

and Youm (2017), corporations use social media to

communicate information and provoke reactions A possible way to increase control over the infor-

from customers; these communications positively mation diffused and decrease relevance of outside

inﬂuence perceptions about company value, affect- bloggers in affecting prices of assets traded is to

ing trading decisions and the consequent perfor- invest in corporate blogging, creating ofﬁcial and

mance and risk of securities. Alexander and Gentry unofﬁcial blogs that attract trafﬁc and manage a

(2014) suggested organizations should use social large amount of information circulating about the

media to report ﬁnancial results, complying with company. Managing corporate blogs could be es-

SEC regulations. Through their posts, organizations sential for crisis management, as the company will

directly inﬂuence social media sentiment, which, in have an efﬁcient channel to explain facts when

turn, will affect the way in which investors and corporate scandals or problems occur. Mazboudi

traders make their decisions (Piñeiro-Chousa and Khalil (2017) argued that by sharing informa-

et al., 2017). tion on Twitter and blogs, organizations can

mitigate possible deleterious effects of stock ﬂuc-

5.3. Social media intelligence tuations. Corporate blogging can also be effective

in building relationships with customers, improving

Starbucks suffered signiﬁcant losses because of the search engine optimization, and increasing direct

Dreamers’ Day fake news, which went viral and sales through the blogs. Several companies have

misinformed individuals about the company’s ini- invested in corporate blogging. Caterpillar has

tiative to give discounts to undocumented immi- developed a network of blogs broken down by

grants. Companies can invest in social media industry and by categories within the industry,

intelligence to monitor the diffusion of fake news, which allow the company to engage with most

track back the sources that spread the informa- customers, help solve problems, ﬁnd creative

tion, and, if needed, ﬁght back with legal action. ideas, manage negative information, and attract

The purpose would be to develop a reputation that a large ﬂow of users interested in the company by

the company has an aggressive stance against de- diverting their attention from uncontrolled blog-

liberately harmful fake news in an attempt to gers to the ofﬁcial company blogs. Herding effects

discourage individuals with vicious intentions from could be mitigated as users may wish to verify

purposefully spreading them. whether the opinion shared by bloggers is based

on facts reported in the company’s blog. Bloggers

5.4. Earned inﬂuencer marketing or other social media sources may refrain from

sharing opinions that are not based on facts re-

Recently, companies have been investing in inﬂu- ported in the blogs, therefore increasing com-

encer marketing; here, they do not target the whole pany’s control on the information that may

segment population but rather speciﬁc inﬂuencers affect traders’ behaviors.

BUSHOR-1569; No. of Pages 11

10 L. Bizzi, A. Labban

5.6. Social media policy and established companies. The companies that

engage in equity crowdfunding promise ﬁnancial

A powerful resource to communicate information compensation. Social media that attract new inves-

about the company on social media and to control tors are likely to offer new opportunities for en-

whether the information about the company in trepreneurs to attract funds through equity

social media is accurate is the employees them- crowdfunding. Entrepreneurs could leverage social

selves. Companies have been developing social me- media sources to give visibility to their crowdfund-

dia policies that prescribe the behaviors employees ing initiatives in an attempt to raise capital. Al-

have to display when interacting in social media though there are successful cases of companies that

about their company. A social media policy is nec- managed to raise capital and appropriately reward

essary to avoid employees sharing sensitive infor- investors, crowdfunding is risky to individuals. The

mation about the company, as they could inﬂuence absence of regulations and control allowed the

perceptions about the company’s intrinsic value and proliferation of crowdfrauding, whereby individuals

possibly inﬂuence asset prices. A social media policy are given false promises and are often attracted by

is necessary to avoid employees’ opinions being Ponzi schemes in which the entrepreneur uses funds

taken as the company’s opinions, therefore possibly from later investors to reward early investors,

inﬂuencing perceptions about its value. A social spreading false claims that the company is proﬁt-

media policy is also important because employees able, thereby attracting more interest from inex-

could monitor misinformation about the company perienced investors (Baucus & Mitteness, 2016).

and report it to management or directly counter

misinformation by participating in blogs. Social me- 5.9. Initial Coin Offerings (ICO)

dia policies can also better engage employees and

improve relationships with them, overall beneﬁting An alternative form of crowdfunding, which recent-

the company. ly attracted worldwide attention, is the Initial Coin

Offering (ICO). Through the ICO, entrepreneurs

5.7. Nonequity crowdfunding raise funds through exchange of cryptocurrencies.

The traditional formula requires the entrepreneur

Companies can leverage social media to give visi- to create a new cryptocurrency associated with the

bility to their initiatives, to test, the market, and to project under development and sells the cryptocur-

attract small funds from multiple individuals. In- rency in the form of tokens that are exchanged for

deed, the argument that online traders often lack other popular cryptocurrencies such as bitcoin or

ﬁnancial literacy to make well-informed decisions ethereum. The entrepreneur should then exchange

and are biased by the inﬂuence of social media bitcoin or ethereum to ﬁnance the acquisition of

should be a warning for companies. While there assets. Hypothetically, if the project ends up being

are companies legitimately attempting to raise successful, the value of the tokens acquired by the

funds to ﬁnance the acquisition of assets that gen- investors should increase. Social media has strongly

erate proﬁts, there will be other companies that contributed to the diffusion of ICOs, raising

leverage crowdfunding to raise funds in an exploit- the visibility of entrepreneurial initiatives and al-

ative manner. The least risky way to raise funds lowing companies to raise funds at incredible

online is through crowdfunding websites such as speed. Unfortunately, the rate of success of ICO

Indigogo or Kickstarter. Small entrepreneurs of initiatives is extremely low and they are–— even

startups use these vehicles, often raising small more than crowdfunding initiatives–— prone to

funds from large masses without the exchange of scams and illegal activities.

ownership of the company. Entrepreneurs appeal to

the social cause of the initiative in order to obtain

funds. While individuals do not obtain ownership of 6. Summary

the company in exchange for their funds, they can

get exposure, intangible beneﬁts, or free products While academics have devoted considerable atten-

in the case in which the startup reaches the market. tion to understanding theinﬂuence of social mediaon

consumer behavior or employee behavior, there has

5.8. Equity crowdfunding been little attention focused on understanding how

social media can affect online trading behavior. This

Equity crowdfunding is the raising of funds from article raises the importance of understanding the

online sources and crowdfunding websites in ex- inﬂuence of social media on online trading and pro-

change for the provision of private equity. This is an poses that social media is creating a new class of

instrument used by small startups rather than large online traders whose behavior has a double-edged

BUSHOR-1569; No. of Pages 11

The double-edged impact of social media on online trading 11

Organizational Behavior and Human Decision Processes, 47

effect on organizations, affecting both performance

(2), 270—288.

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