Management, as well as seminar participants at the Fox School of Business at Temple University for useful suggestions. They also thank Ashish Agarwal, Avi Goldfarb, Yili Hong, Pei-yu Chen and Evan Polman for providing helpful comments. Anindya Ghose acknowledges funding from the WCAI (Wharton Customer Analytics Institute) and NSF CAREER Award IIS-0643847.

We examine how the entry of gig-economy platforms influences local entrepreneurial activity. On one hand, such platforms may reduce entrepreneurial activity by offering stable employment for the un-and under-employed. On the other hand, such platforms may enable entrepreneurial activity by offering work flexibility that allows the entrepreneur to redeploy resources strategically in order to pursue her nascent venture. To resolve this tension we exploit a set of natural experiments, the entry of the ride-sharing platform Uber X and the on-demand delivery platform Postmates into local areas. We examine the effect of each on crowdfunding campaign launches at Kickstarter, the world's largest reward-based crowdfunding platform. Results indicate a negative and significant effect on crowdfunding campaign launches, and thus local entrepreneurial activity, after entry of Uber X or Postmates. Strikingly, the effect appears to accrue primarily to unfunded and under-funded projects, suggesting that gig-economy platforms predominantly reduce lower quality entrepreneurial activity by offering viable employment for the un-and under-employed.

In this paper, we analyze patterns of transaction between individuals using data drawn from Kiva.org, a global online crowdfunding platform that facilitates prosocial, peer-to-peer lending. Our analysis, which employs an aggregate dataset of country-to-country lending volumes based on more than three million individual lending transactions that took place between 2005 and 2010, considers the dual roles of geographic distance and cultural differences on lenders' decisions about which borrowers to support. While cultural differences have seen extensive study in the Information Systems literature as sources of friction in extended interactions, here, we argue and demonstrate their role in individuals' selection of a transaction partner. We present evidence that lenders do prefer culturally similar and geographically proximate borrowers. An analysis of the marginal effects indicates that an increase of one standard deviation in the cultural differences between lender and borrower countries is associated with 30 fewer lending actions, while an increase of one standard deviation in physical distance is associated with 0.23 fewer lending actions. We also identify a substitution effect between cultural differences and physical distance, such that a 50 percent increase in physical distance is associated with an approximate 30 percent decline in the effect of cultural differences. Considering approaches to overcoming the observed cultural effect, we offer some empirical evidence of the potential of IT-based trust mechanisms, focusing on Kiva's reputation rating system for microfinance intermediaries. We discuss the implications of our findings for pro-social lending, online crowdfunding, and electronic markets more broadly.

In hopes of motivating consumers to provide larger volumes of useful reviews, many retailers offer financial incentives. Here, we explore an alternative approach, social norms. We inform individuals about the volume of reviews authored by peers. We test the effectiveness of using financial incentives, social norms, and a combination of both strategies in motivating consumers. In two randomized experiments, one in the field conducted in partnership with a large online clothing retailer based in China and a second on Amazon Mechanical Turk, we compare the effectiveness of each strategy in stimulating online reviews in larger numbers and of greater length. We find that financial incentives are more effective at inducing larger volumes of reviews, but the reviews that result are not particularly lengthy, whereas social norms have a greater effect on the length of reviews. Importantly, we show that the combination of financial incentives and social norms yields the greatest overall benefit by motivating reviews in greater numbers and of greater length. We further assess treatment-induced self-selection and sentiment bias by triangulating the experimental results with findings from an observational study.

This study examines how social network integration (i.e., integration of online platforms with other social media services, for example, with Facebook or Twitter) can affect the characteristics of user-generated content (volume and linguistic features) in the context of online reviews. Building on the social presence theory, we propose a number of hypotheses on how social network integration affects review volume and linguistic features of review text. We consider two natural experiments at leading online review platforms (Yelp.com and TripAdvisor.com), wherein each implemented a social network integration with Facebook. Constructing a unique panel dataset of online reviews for a matched set of restaurants across the two review sites, we estimate a difference-indifferences (DID) model to assess the impact of social network integration. We find that integration with Facebook increased the production of user-generated content and positive emotion in review text, while simultaneously decreasing cognitive language, negative emotion, and expressions of disagreement (negations) in review text. Our findings demonstrate that social network integration works as a doubleedged sword. On the one hand, integration provides benefits in terms of increased review quantity. On the other hand, these benefits appear to come at the cost of reduced review quality, given past research which has found that positive, emotional reviews are perceived by users to be less helpful. We discuss the implications of these results as they relate to the creation of sustainable online social platforms for user content generation.