Investor Information Behavior
Much of what is known about investor information behavior is based on individual investors and often focuses exclusively on information use. This research nonetheless provides a helpful foundation for this study. Reporting on their study utilizing a telephone survey of 911 randomly sampled U.S. investors, Hira and Loibl (2006, 2009) demonstrate the types and constellations of sources investors use. They found that the investors in their study (65% of whom were male and 35% of whom were female) fell into five clusters of information use: high, online, moderate, workplace, and low. Investors in the high and online categories were self-reliant, information driven and practice multisource, diversified, high-information use strategies. Unfortunately, these investors constituted only 22% of investors studied. They were also highly likely to be male, well-educated, and possess the largest financial assets. The moderate group (24%) practiced a broad but less frequent information use strategy and was also highly likely to be male and well educated. The remaining 54% of investors, who constitute the low and work-place oriented information users, were primarily female with the lowest educational levels and financial assets. Their strategies were characterized by the use of few, if any, formal, mediated information sources and the nonadoption of technology for investment information.
Older studies, including McKay et al. (1996), Peter D. Hart Research Associates (1997), and Mezick (2001), suggested that investors prefer printed sources of information, such as newspapers, magazines, and annual reports. For example, Mezick found 77% of investors cited magazine and newspapers as the most frequently used sources of information for investors. Friends and relatives (69%), web pages (54%) and search engines (36%) followed. Financial advisors, television and stockbrokers were each cited by less than 6% of those surveyed as primary information sources. Hira & Loibl's (2006) findings were quite different: investors in their study cited financial advisors (28%), magazines and newspapers (22%), the Internet (21%), and the workplace (10%) as the most often used sources of financial information. Friends, television, radio, and classes all followed with less than a 5% response for each.
Even as early as 2001, however, Mezick found that the growing popularity of the Internet was having an impact on investors’ information use. Fifty-five percent of respondents in her study reported using the Internet daily or weekly, whereas only 6% used library sources with that frequency for investment information. Williamson (2008, 2010) and Williamson and Kingsford Smith (2010), who studied information use by 520 online investors (most of whom were male, outnumbering women five to one) found that 82% of their participants used the Internet for investment-related information: brokers’ websites were the most often used sources of information, followed by company investor relations websites, advice from brokers or analysts via email, general financial information portals, and financial data or charting services. Traditional media were used as well; 79.2% of online investors indicated they obtained information from newspapers and 55.5% from electronic media (radio and TV) at least “frequently.” The majority of participants in their study (62.8%) reported rarely receiving information or advice from family, friends and acquaintances. However, Williamson (2008) reported that “this result turned out to be questionable during the individual interviews. There was much more discussion with family and friends than people either wanted to admit, or thought of admitting” (p. 10).
Mezick's participants described convenience (38%), currency (14%) and ease of use (14%) as primary reasons for Internet adoption. Williamson (2008, 2010) and Williamson and Kingsford Smith (2010) also provide some insight into how online investors select information. In interviews with 26 investors selected from their larger pool of 520, they found that convenience/ease of access and content were important criteria to all their participants, whereas reliability/accuracy, currency/timeliness, and speed of access were important to the majority of them. It is important to note that adoption of technology for investing and investment information seeking varies markedly by sex. In one study, women were 20% less likely to use the Internet for investing information and three times less likely to trade on the Internet (Hira & Loibl, 2006). When asked why they do not use the Internet for investing and investment information, 85% of female investors surveyed indicated they preferred working with people, 49% worried about security, and 44% found financial websites confusing.
Barber and Odean (2001) discovered that the Internet may transform investors’ information behaviors. Because the Internet reduces the costs of some information, but not others, it may impact source selection. They write:
The Internet especially facilitates comparisons of real time data, and thus has changed investors’ focus by emphasizing the importance of speed and immediacy. While the serious individual investor of a decade ago may have checked stock positions once a day in the morning paper, casual investors now check theirs several times a day. Many more investors pay attention to short term—even intraday—returns than ever before. (p. 48).
Other effects of Internet adoption are clear. According to Barber and Odean (2001) new communication channels on the Internet and the popularity of online trading are closely related: the explosion in web-based investment information is “substituted for brokerage firm guidance, supporting (if not inflating) the sense of confidence for the retail investor” (Barber & Odean, 2001, p. 42). Their research indicates that “when people are given more information on which to base a forecast or assessment, the accuracy of their forecasts tends to improve much more slowly than their confidence in the forecasts. Although the improved accuracy of forecasts yields better decisions, additional information can lead to an illusion of knowledge and foster overconfidence, which leads to biased judgments” (Barber & Odean, 2001, p. 46). The trend to bypass professional investment advice is particularly troublesome because inexperienced nonprofessional investors earn lower returns as their use of unmediated information rises relative to their use of mediated-information (Elliott, Hodge, & Jackson, 2008). Furthermore, in lieu of professional advice, investors “turn to numerous sources of fundamental and technical market information, to chatroom gossip, to online journalists, and to sophisticated advice engines. However the quality of such cyber-resources varies greatly. If investors are unable to distinguish high quality advice from low, they are unlikely to pay more for quality. Indeed with so much information available for free on the Internet, many investors will be unlikely to pay anything for information alone” (Barber & Odean, 2001. p. 44). Thus the abundance and immediacy of Internet-based information strengthens the illusion of being informed (Barber & Odean, 2001). Because investors are heavily influenced by mass media, which lures them to purchase “attention grabbing” stock, greater exposure to more information may also alter the types of companies in which they choose to invest (Barber & Odean, 2008).
Williamson (2008, 2010) and Williamson and Kingsford Smith (2010) also identified several problematic effects of investors going online, including participants’ higher levels of trust in information sources than might be warranted, a predilection for speed in the delivery of information and the impact of information overload, which they speculate may be greater on information seekers less experienced than most of those who participated in their study. Overall, Williamson and Kingsford Smith conclude, however, that online investors are a “relatively engaged and knowledgeable group,” which, they add, is “by contrast to the wider populations of investors who research demonstrates are extremely difficult to engage, even in their own self-interest” (Williamson and Kingsford Smith, 2010, p. 69).
Online Information Sharing and Use
In addition to literature on investor's information use, research on information sharing and use in virtual communities provides a useful context for this study. Several authors have examined the exchange of health information in online groups (see, for example, Donnelle & Hoffman-Goetz, 2009; Burnett & Buerkle, 2004; Wikgren, 2001, 2003. Savolainen (2001) studied consumer information exchange in a Finish newsgroup. These studies generally find richer information environments than were expected. Strandberg (2008) and O'Connor and Rapchack (2012) examined online information use in political discussion forums and found that virtual environments are not always collaborative. Political discussion boards often included “negative comments, superficial topics, and unsubstantiated claims rather than true conversations” (Strandberg, 2008, p. 83). Clearly information behavior in online communities varies with the make-up of their membership and the nature of the interests that unite them.
A few studies have examined investors’ online forums. Antweiller and Frank (2004) examined 1.5 million postings to assess the impact of investors’ online discussions on the market. They found that contentious discussions induce trading, that forum discussions predict market volatility and that forum content reflects public information extremely rapidly. They discovered that discussions about news preceded and predicted treatment of that same topic in print newspapers by about 48 hours and concluded that internet investor boards do contain useful information.
However, some studies describe negative aspects of investor chat forums. Langevoort (2002) asserts that the “illusion of control provided by the Internet combined with an immediate audience for hype, fraud, or even ordinary opinion can make investors in chat groups more vulnerable” (Langevoort, 2002, p. 15). The Financial Industry Regulatory Authority (FINRA), an organization that regulates the behavior of professional securities brokers, does delineate acceptable behavior of professionals within social media. They prohibit professionals from posting content that is “unbalanced, overly positive or predicts an imminent price increase” (FINRA, 2011, p. 2). But the agency is still concerned about investor manipulation in chat forums and plans to issue more regulations in the near future (FINRA).
Park, Konana, Gu, Kumar, and Raghunathan (2010) analyzed 502 postings from the largest finance message board in South Korea. They found that investors exhibit confirmation bias, the tendency to seek out information that confirms what they already believe, when they select and use information from message boards. This well-documented tendency is exacerbated in virtual communities, because they enable people to interact with individuals who share their beliefs and opinions (Frick, 2011). Barber and Odean (2001) agree that “investors are more likely to visit chatrooms of like-minded investors and, if controversies ensue, they are likely to be convinced by those with whom they already agree. Investors who believe that additional information makes them better investors are unlikely to seek out or attend to evidence that indicates otherwise” (p. 47). Park et al. (2010) also demonstrate that investors with stronger confirmation bias also exhibit greater overconfidence. Consistent with the findings of other studies, overconfident investors in their study also had higher expectations about their performance, traded more frequently, and realized lower returns. They conclude that “these results suggest that participation in virtual communities increases investors’ propensity to commit investment mistakes and is likely to be detrimental to their investment performance” (Park, et al., 2010, p. 1).
Additional literature on group investing is also relevant to this study, although research in this area is slim and its findings are ambiguous and even contradictory. Barber and Odean (2000) demonstrate that overall, investment clubs do not perform well. During their 18-month study, 60% (n = 100) of participating clubs underperformed the market by an average of 4. Club returns were also consistently lower than individual returns by 2 pps (points per share) per year. Hens (2008) supported Barber and Odean's findings. However, Gort and Gerber (2008) compared the returns of individual investors to those of groups of investors and came to different conclusions. They note “large performance discrepancies across groups” and concluded that “the best groups significantly outperform individuals” (Gort & Gerber, 2008, p. 24). They found that a high level of information exchange (where members not only share information but also evaluate and weigh contradictory information) was the best predictor of strong market performance. “Only if the group members’ opinions are communicated and discussed, do groups outperform individuals” (Gort & Gerber, 2008, p. 24).
Though investors’ group information behaviors have been studied in face-to-face contexts, little is known about it in virtual communities. Existing studies about investors in online forums tend to focus on individual information behavior instead. This study will begin to address that gap. Burnett (2000) categorized the types of interactions in online communities and, with Buerkle, revised them in a 2004 study. He separated them into two broad categories; interactive and noninteractive behaviors. Although non-interactive behaviors, often called “lurking” are important, they are beyond the scope of this study. Burnett categorized interactive behaviors, which require active posting of messages, as fundamentally either hostile or collaborative. He furthermore divided collaborative behaviors into those that are explicitly information-oriented and those that are not. These typologies will be used for data analysis in this study and will be discussed at greater length in the Methods and Findings sections of this article.
Collaborative Information Behavior
Although both collaborative and noncollaborative interactions will be considered, this article will focus on analyzing collaborative, information-oriented behavior. Thus, a brief discussion of research on collaborative information behavior (CIB) provides a useful context for this work. Karunakaran, Spence, and Reddy (2010) define CIB as “the totality of behavior exhibited when people work together to identify an information need, retrieve, seek and share information, evaluate synthesize and make sense of the found information, and then utilize the found information” (p. 2). Reddy and Jansen (2008) and Reddy, Jansen, and Spence (2010) describe four triggers for CIB: (1) complexity of information need, (2) lack of immediately accessible information, (3) lack of domain expertise, and (4) fragmented information resources.
Collaborative information behavior has been identified as occurring in both organizational and nonorganizational contexts (Karunakaran et al., 2010). When CIB occurs in investor forums, where participation is voluntary, rather than in organizations, where it is mandatory, it occurs within a greater context of community building. Burnett (2000) describes these online exchanges of texts as virtual communities that “function as social spaces supporting textual ‘conversations’ through which participants can find both socio-emotional support and an active exchange of information” (p. 3). Burnett and Jaeger (2008) argue that these communities can be viewed as “computer-mediated small worlds” with the same types of normative attitudes and behaviors that shape information behavior found in the nonvirtual world (p. 10)1. These social norms “provide a shared understanding of propriety and correctness of those visible aspects of social activities within the world,” including information sharing and use (Burnett & Jaeger, 2008, p. 6). Burnett and Buerkle (2004) note that the variance between communities can provide an important means for understanding the small worlds that exist in the communities. This study will extend the literature of virtual CIB by describing a previously unknown social information environment and providing an additional point for comparison.