Information Design in Crowdfunding under Thresholding Policies
This work addresses the challenge of incomplete information in crowdfunding for entrepreneurs, though it is incremental as it builds on existing thresholding policy frameworks.
The paper tackles the problem of optimizing revenue for entrepreneurs in crowdfunding by designing dynamic information-disclosure policies, showing that immediate disclosure is suboptimal and that their heuristic algorithm achieves competitive results.
Crowdfunding has emerged as a prominent way for entrepreneurs to secure funding without sophisticated intermediation. In crowdfunding, an entrepreneur often has to decide how to disclose the campaign status in order to collect as many contributions as possible. Such decisions are difficult to make primarily due to incomplete information. We propose information design as a tool to help the entrepreneur to improve revenue by influencing backers' beliefs. We introduce a heuristic algorithm to dynamically compute information-disclosure policies for the entrepreneur, followed by an empirical evaluation to demonstrate its competitiveness over the widely-adopted immediate-disclosure policy. Our results demonstrate that the immediate-disclosure policy is not optimal when backers follow thresholding policies despite its ease of implementation. With appropriate heuristics, an entrepreneur can benefit from dynamic information disclosure. Our work sheds light on information design in a dynamic setting where agents make decisions using thresholding policies.