| This dissertation studies the economics of electronic commerce and social networks. The first essay, "Market Mechanisms in Online Crowdfunding," systematically compares auctions with a platform-mandated posted-price mechanism in online crowdfunding. We exploit a regime change from auctions to platform-mandated posted prices on a debt-based crowdfunding platform. We develop a game-theoretic model that yields empirically testable hypotheses, then test them using detailed transactions data. Consistent with our hypotheses, we find that after the regime change, loans are funded with higher probability and higher interest rates. More important, all else equal, loans funded under the posted-price regime are more likely to default. While the posted prices may be faster than auctions that rely on the "crowd" to discover prices, auctions are not necessarily inferior in terms of overall social welfare.;The essay, "'Smart Money': Institutional Investors in Online Crowdfunding," studies institutional investors and their interactions with retail investors in online crowdfunding. Given their expertise, institutional investors are often referred to as "smart money" in financial markets, in the sense that these professional have selection ability and receive higher returns from their securities. We study whether institutional investors are indeed better able to screen borrowers in the marketplace than, and have any significant impacts on the behaviors of, retail investors. We find that although institutional investors indeed behave differently in terms of portfolio size and diversification strategies, their portfolios do not necessarily outperform those of retail investors. Institutional investors' bids have significant influence on the bidding strategies of retail investors, as well as final transaction outcomes. We find that this phenomenon is driven by the designation of "institutional investors" rather than just the size of their portfolios.;The last essay, "For Whom to Tweet? A Study of a Large-Scale Social Network," studies the effects of peer-groups sizes on individuals' contributions to public goods - tweets - in a large-scale and influential online social network. We attribute the highly-skewed distribution of tweets, which is observed from the network, to an individual's conflicting incentives of free-riding and maximizing social influence. We exploit the asymmetry of an individual's peer groups (followers and followees, groups of people following and being followed by the individual respectively) to disentangle these incentives, and devise empirical strategies to deal with the endogenous formation of one's peer groups. We find a larger group of followees leads an individual to tweet less, while a larger group of followers leads an individual to tweet more. With randomly generated 1% new links the total tweets will increase by 25% as the estimated follower effects dominate the followee effects. |
