A Dynamic Model of Crowdfunding

Crowdfunding is quickly emerging as an alternative to traditional methods of funding new products. In a crowdfunding campaign, a seller solicits financial contributions from a crowd, usually in the form of pre-buying an unrealized product, and commits to producing the product if the total amount pledged is above a certain threshold. We provide a model of crowdfunding in which consumers arrive sequentially and make decisions about whether to pledge or not. Pledging is not costless, and hence consumers would prefer not to pledge if they think the campaign will not succeed. This can lead to cascades where a campaign fails to raise the required amount even though there are enough consumers who want the product. The paper introduces a novel stochastic process -- anticipating random walks -- to analyze this problem. The analysis helps explain why some campaigns fail and some do not, and provides guidelines about how sellers should design their campaigns in order to maximize their chances of success.http://deepblue.lib.umich.edu/bitstream/2027.42/117507/1/1307_Mostagir.pd

Aiming for the Goal: Contribution Dynamics of Crowdfunding

We study reward-based crowdfunding campaigns, a new class of dynamic contribution games where consumption is exclusive. Two types of backers participate: buyers want to consume the product while donors just want the campaign to succeed. The key tension is one of coordination between buyers, instead of free-riding. Donors can alleviate this coordination risk. We analyze a dynamic model of crowdfunding and demonstrate that its predictions are consistent with high-frequency data collected from Kickstarter. We compare the Kickstarter mechanism to alternative platform designs and evaluate the value of dynamically arriving information. We extend the model to incorporate social learning about quality

Mutually Exciting Point Processes for Crowdfunding Platform Dynamics

Crowdfunding is a powerful tool for individuals or organizations seeking financial support from a vast audience. Despite widespread adoption, managers often lack information about dynamics of their platforms. Hawkes processes have been used to represent self-exciting behavior in a wide variety of empirical fields, but have not been applied to crowdfunding platforms in a way that could help managers understand the dynamics of users' engagement with the platform. In this paper, we extend the Hawkes process to capture important features of crowdfunding platform contributions and apply the model to analyze data from two donation-based platforms. For each user-item pair, the continuous-time conditional intensity is modeled as the superposition of a self-exciting baseline rate and a mutual excitation by preferential attachment, both depending on prior user engagement, and attenuated by a power law decay of user interest. The model is thus structured around two time-varying features -- contribution count and item popularity. We estimate parameters that govern the dynamics of contributions from 2,000 items and 164,000 users over several years. We identify a bottleneck in the user contribution pipeline, measure the force of item popularity, and characterize the decline in user interest over time. A contagion effect is introduced to assess the effect of item popularity on contribution rates. This mechanistic model lays the groundwork for enhanced crowdfunding platform monitoring based on evaluation of counterfactual scenarios and formulation of dynamics-aware recommendations

Rational Herding in Reward-Based Crowdfunding: An MTurk Experiment.

Crowdfunding is gaining popularity as a way of financing social sustainable initiatives. We performed a controlled economic experiment in MTurk by simulating a crowdfunding platform and developed a theoretical model that rationalizes herding behavior. The experiment was designed to test and quantify the causal effects of revealing specific information to prospective backers: (i) the number of early contributors already financing the project and (ii) positive opinions of other backers versus those of experts. The results show that early contributions to the campaign and positive opinions of peers act as a reinforcing signal to potential backers and affect backers' beliefs about the probability of success, increasing contributions to the campaign. Furthermore, we show that herding is rational and set expectations on when we should observe rational herding and when not. The theoretical model captures the rational herding, which may be the main information aggregation path in reward-based crowdfunding platforms, and can help managers increase the likelihood of success in crowdfunding campaigns

Innovative online platforms: Research opportunities

Economic growth in many countries is increasingly driven by successful startups that operate as online platforms. These success stories have motivated us to define and classify various online platforms according to their business models. This study discusses strategic and operational issues arising from five types of online platforms (resource sharing, matching, crowdsourcing, review, and crowdfunding) and presents some research opportunities for operations management scholars to explore