«Friedemann Polzin Helen Toxopeus Erik Stam June 2016 The wisdom of the crowd in funding. Information heterogeneity and social networks of crowdfunders ...»
Sustainable Finance Lab working paper
The wisdom of the crowd in funding.
Information heterogeneity and social networks of crowdfunders
Friedemann Polzin*,1,3, Helen Toxopeus2, & Erik Stam3
This version: June 2016
Abstract: Crowdfunding has opened funding of innovative projects to large crowds. This
type of funding might tap into wisdom of crowds that were disconnected from the funding
process before. We distinguish between in-crowd and out-crowd (with and without ties to the project creators) funders, in order to test for heterogeneity in the information used by crowdfunders. Based on the analysis of a large scale survey amongst project backers, this paper shows that in-crowd investors rely more on information about the project creator than out-crowd investors. Out-crowd investors do not seem to attach more importance to information about the crowdfunding project than in-crowd investors except for the case of donation-based crowdfunding. In the case of financial-return crowdfunding, financial information becomes less important once a strong relationship is established. Our study allows for targeting of specific audiences based on relationship strength across different types of crowdfunding.
Keywords: Crowdfunding, social networks, new ventures, entrepreneurial finance, information asymmetries *Corresponding author (firstname.lastname@example.org) Utrecht University School of Economics (USE), Sustainable Finance Lab (SFL), Kriekenpitplein 21-22, 3584 EC Impact Centre Erasmus (ICE), Erasmus School of Accounting and Assurance, Burgemeester Oudlaan 50, Rotterdam Utrecht University School of Economics (USE), Chair of Strategy, Organisation and Entrepreneurship, Kriekenpitplein 21-22, 3584 EC Introduction The funding of innovative start-ups has always been difficult due to lack of track record, collateral and technological uncertainty (Engel & Stiebale 2014; Hall 2002; Giudici & Paleari 2000). More generally, small and medium sized firms are more capital constrained than large firms, lacking access to market-based funding due to high fixed costs to issue equity and unwillingness of institutional investors to take small holdings, which leaves them highly dependent on bank credit, venture capital funds, angel investors and personal resources for their liquidity needs (Giudici & Paleari, 2000; Keasey & McGuinness, 1990). Of these, access to bank credit is often constrained due to lack of profitability and tangible assets, as well, and has become more so in recent decades due to increased centralization and computerized assessment of creditworthiness (Bhidé, 2010). This shift to transactional lending affects innovative small firms severely due to their disproportionate reliance on soft information in the lending process (Brancati, 2014;
Cosci, Meliciani, & Sabato, 2016). Additionally there is evidence that the financial crisis has limited the willingness of venture capitalists (VC) to fund ventures, in particular in follow-up rounds (Block & Sandner, 2009; Migendt, Schock, Täube, von Flotow, & Polzin, 2014).
The rise of crowdfunding in the past decade seems to fill this funding gap. Offering an alternative to traditional entrepreneurial finance channels, crowdfunding caters well to innovative, opaque small firms and makes use of social networks in its funding process.
It builds on and expands beyond the traditional ‘in-crowd’ finance niche of family, friends and fools by allowing both in- and out-crowd investors to provide financing through digital platforms (Bruton, Khavul, Siegel, & Wright, 2015). Crowdfunding has lowered the transaction costs for entrepreneurs to collect small investment amounts from a dispersed set of investors, and is becoming an increasingly sizable source of funding for start-ups and other bottom-up initiatives in the economy (Massolution, 2015).
In line with the growth of the crowdfunding industry, academic research directed at understanding the phenomenon of crowdfunding has emerged in recent years (Moritz & Block, 2016). Much of this literature is focused on success factors driving the crowdfunding campaign, such as the role of early contributions (Agrawal et al. 2015;
Cholakova and Clarysse 2015; Colombo et al. 2015). There is also considerable attention for the role of social networks in crowdfunding on the one hand (Agrawal et al., 2015;
Horvát, Uparna, & Uzzi, 2015; Hui, Gerber, & Gergle, 2014) and for ways in which informational asymmetries are overcome, on the other (Ahlers, Cumming, Günther, & Schweizer, 2015a; Lin, Prabhala, & Viswanathan, 2012; Vismara, 2015). A question that lacks attention until now bridges these two topics, namely how social networks affect the type of information used by investors in crowdfunding. Although there are suggestions regarding the information mechanisms that exist for crowdfunding and the role of social networks (Ter Wal, Alexy, Block, & Sandner, 2016), there is little empirical evidence available about the type of information that funders use to make investment decisions.
We add a novel perspective by focusing on the type of information used by in- and outcrowd funders to make their investment decision. In particular we want to know how relationships with the project creator affect the type of information that funders use. This study offers the first detailed empirical analysis on the heterogeneity in information use by crowdfunders, and how this is affected by their social networks. The ability to distinguish between investors based on their ties to the entrepreneur offers insights into the application of theories about information asymmetries and social networks in funding decisions, and serves as input for public policy for entrepreneurship and finance. Our main research question is: How does the type of information used by crowdfunders vary with the strength of their ties to project founders?
The remainder of this article is structured as follows: we first review the relevant literature and introduce the theoretical framework. Then the research design including the quantitative research approach and the data is presented. The subsequent section displays the results that form the basis for discussion and conclusion in the final sections.
Literature review and theoretical framework
Signalling in early-stage finance and information cascades The choice between various ways of obtaining capital at the formation of a new company has been shown to have important implications for future performance (Cassar, 2004).
The growth of start-ups is often constrained by the amount of finance available (Brancati, 2014; Carpenter & Petersen, 2002; Engel & Stiebale, 2014; Giudici & Paleari, 2000). In search for external finance, the relationship between entrepreneur and funder is characterised by agency due to a separation of ownership and management which leads to informational asymmetries, adverse selection and moral hazard (Denis, 2004; Jensen & Meckling, 1976; Parker, 2009).
To overcome these agency problems, scholars suggest signaling (Akerlof, 1970; Amit, Glosten, & Muller, 1990; Gompers, 1995; Myers & Majluf, 1984; Stiglitz & Weiss, 1981).
Signaling can take place using different kinds of information, for example through availability of patents and prototypes or through track record of entrepreneurial team (Audretsch, Bönte, & Mahagaonkar, 2012; Busenitz, Fiet, & Moesel, 2005; Gompers & Lerner, 2001; Spence, 1973). Within the signaling literature, many studies establish a positive relationship between early-stage investments and firm success (Bernstein et al.
2015a; Kerr et al. 2014; Kortum & Lerner 2000; Samila & Sorenson 2010) as well as linking entrepreneur’s characteristics such as highly skilled and specialized human capital to venture performance (Cooper, Gimeno-Gascon, & Woo, 1994; Ouimet & Zarutskie, 2014; Pukthuanthong, 2006).
Recently, crowdfunding1 emerged as a new form of seed finance that affects the relationship between investors and entrepreneurs (Bruton et al., 2015; Harrison, 2013).
Along with the growing interest in this new form of entrepreneurial finance, research into this phenomenon is emerging (for reviews see Kuppuswamy & Bayus 2015; Moritz & Block 2016). Crowdfunding combines features of a two-sided market platform with underlying networking technologies. The real-time, open and online insight into the commitment of previous funders as well as extensive targeted descriptions of the fundraising campaign are specific signals of crowdfunding (Bruton et al., 2015). The quality of these signals is questionable since the crowd might not have expertise on production, marketing and competition, nor are they likely to invest in due diligence due to high fixed costs (Belleflamme, Lambert, & Schwienbacher, 2013; Vismara, 2016). On the one hand, the crowd could represent launching customers, delivering knowledge about the market potential of the offering by signing up as funders. But they could also be free-riding on the – potentially unwise – funding decisions of others, and ‘herd’ without adding any new information to the decision process (Bikhchandani, Hirshleifer, & Welch, 1992).
Hornuf and Schwienbacher (2015) find that specific kinds of information, namely updates to the investors, significantly drives investments as investors update their preferences in the light of the assessment of the project. Moritz et al. (2015) examined investor communication in equity crowdfunding highlighting perceived sympathy, openness and trustworthiness in the relationship between venture and investor to reduce perceived information asymmetries. They also find that third-party communication influences the decision making process of crowdfunders. Furthermore, allowing crowdfunders to adjust privacy settings regarding information about their contribution deters some investors but increases average contribution size (Burtch, Ghose, & Wattal, 2015).
This suggests that some form of quality signalling between entrepreneur and crowdfunder occurs. This relates to the general notion of the ‘wisdom of the crowd’ in Following previous work we distinguish four types of crowdfunding (Ahlers, Cumming, Günther, & Schweizer, 2015a; Belleflamme, Lambert, & Schwienbacher, 2014; Mollick, 2014; Nesta, 2014): Purely donationbased crowdfunding exist, involving only intangible returns. Reward-based crowdfunding (or pre-ordering) consist of pledging an amount of money in exchange for future products. Lending-based crowdfunding can be compared to micro-loans, where the backer lends a certain amount of money to the project owner.
Equity-based crowdfunding call, shares of the company behind the call are distributed among the backers, according to the height of their contributions.
making funding decisions (Mollick & Nanda, 2015; Surowiecki, 2005). But how does the crowd gather its ‘wisdom’? Literature on investment processes suggest that this is facilitated by the social networks of both entrepreneur and investor (Alexy, Block, Sandner, & Ter Wal, 2012; Colombo et al., 2015; Ter Wal et al., 2016; Uzzi, 1999).
Ties that bind, ties that blind: Social networks and information Social networks strongly influence funding success of entrepreneurs as they provide access to resources such as finance, knowledge and partners (Davidsson & Honig, 2003;
Dubini & Aldrich, 1991; Huang & Knight, 2015; Kwon & Arenius, 2010; Shane & Cable, 2002). Sociological network theory provides a possible lens to study the role of information in the relationship between funder and venture (Granovetter, 1973; Hoang & Antoncic, 2003; Jack & Anderson, 2002; Kwon & Arenius, 2010; Uzzi, 1999). Granovetter (1973, p. 1361) defines the notion of ‘strength’ of interpersonal ties based on ‘a combination of the amount of time, the emotional intensity, the intimacy and the reciprocal services which characterize the tie’. Social networks, consisting of both strong and weak ties, can affect the type of information used in a financing decision through three mechanisms. First, funding decisions may be motivated by the wish to invest in the existing relationship with the entrepreneur, thereby lowering the information need about the project since the investment is not results-driven (Belleflamme, Lambert, & Schwienbacher, 2014; Shane & Cable, 2002). Secondly, dense ties develop and enforce common norms of behaviour through social reward and punishment, making free-rider behaviour of the entrepreneur in the form of moral hazard less likely (Bernstein, Giroud, et al., 2015; Granovetter, 2005; Uzzi, 1999) thereby lowering the risk profile of the investment. This may make obtaining information about the entrepreneur – thereby deepening ties - more attractive than information about the project, its objectives, risk and finance. Third, potential funders receive and disseminate quality signals through their ties with the entrepreneur, lowering informational asymmetries (Ter Wal et al., 2016). Both strong and weak ties play a role in information diffusion and adoption processes in entrepreneurial finance. Weak ties are expected to transmit more novel information than strong ties because networks of people who interact sporadically are more distant from each other’s networks and therefore contain more information they have not yet heard from someone else (Alexy et al., 2012; M. S. Granovetter, 1973; Ter Wal et al., 2016). However, when information contains decisions to be made under risk or uncertainty multiple sources of that information or more trustworthy and easily interpretable sources may be required, favouring overlapping and highly salient strong ties instead (Centola & Macy, 2007; Ter Wal et al., 2016).
Venture capitalists and angel investors mitigate information asymmetries by building relationships, which allow for screening and monitoring (Alexy et al., 2012; Gompers,
1995) as well as for syndication and staging their investments (Gompers & Lerner, 2001;
Yao-Wen, 2010). Ter Wal et al. (2016) highlight the flow and source of information between investors as a key determinant to venture success. They argue that syndicating investors with either open and specialised (strong ties) or closed and diverse networks (weak ties) facilitate the interpretation of new knowledge. These ties between investors are formed every time they are attracted to the same target company (Sorenson & Stuart, 2008; Ter Wal et al., 2016). Crowdfunding may classify as a new form of relationship-based financial intermediation, exploiting local knowledge and trust embedded in the social network of the entrepreneur to provide quality signals about the entrepreneur and their project. Several scholars (Agrawal et al., 2015; Belleflamme et al., 2014; Lin et al., 2012; Mollick, 2014; Ordanini, Miceli, Pizzetti, & Parasuraman, 2011; Vismara, 2016) show that the size of a founder’s social network is positively associated with the capital raised from a project and the subsequent success of the project in both reward-based and equity crowdfunding; this effect does not hold in a donation-based setting (Burtch, Ghose, & Wattal, 2013; Kuppuswamy & Bayus, 2015).
Vismara (2015) shows that social capital of the entrepreneur positively impacts funding success. Professional investors with industry experience and track-record enter relatively early in the campaign and by their public visibility attract other investors (Vismara, 2015). These mechanisms stems from other online market places (Dellarocas, 2003; Lin et al., 2012). Individual backers possess different levels of information, hence some investors have an advantage of others (Cumming, Leboeuf, & Schwienbacher, 2015).
This suggests that the quality indication process with crowdfunding is staged, with an incrowd to out-crowd sequence, using different types of information and levels of expertise to make a funding decision.
In-crowd information needs For a project to be carried out successfully, having insight into quality and intentions of the entrepreneur is highly relevant to overcome information asymmetries (Vismara, 2016). Bernstein et al. (2015b) examine venture/project attributes used to signal quality to investors, i.e. the team, track-record of the venture and identity of current investors.