Information Design in Crowdfunding under Thresholding Policies
September 12, 2017 Β· Declared Dead Β· π Adaptive Agents and Multi-Agent Systems
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Authors
Wen Shen, Jacob W. Crandall, Ke Yan, Cristina V. Lopes
arXiv ID
1709.04049
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CY,
cs.MA
Citations
15
Venue
Adaptive Agents and Multi-Agent Systems
Last Checked
4 months ago
Abstract
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.
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