Sequential Fundraising and Social Insurance

05/21/2020
by   Amir Ban, et al.
0

Seed fundraising for ventures often takes place by sequentially approaching potential contributors, whose decisions are observed by other contributors. The fundraising succeeds when a target number of investments is reached. When a single investment suffices, this setting resembles the classic information cascades model. However, when more than one investment is needed, the solution is radically different and exhibits surprising complexities. We analyze a setting where contributors' levels of information are i.i.d. draws from a known distribution, and find strategies in equilibrium for all. We show that participants rely on social insurance, i.e., invest despite having unfavorable private information, relying on future player strategies to protect them from loss. Delegation is an extreme form of social insurance where a contributor will unconditionally invest, effectively delegating the decision to future players. In a typical fundraising, early contributors will invest unconditionally, stopping when the target is "close enough", thus de facto delegating the business of determining fundraising success or failure to the last contributors.

READ FULL TEXT
research
05/05/2018

Modelling Competitive marketing strategies in Social Networks

In a competitive marketing, there are a large number of players which pr...
research
12/13/2022

Target Defense against Sequentially Arriving Intruders

We consider a variant of the target defense problem where a single defen...
research
06/07/2020

Sharp Thresholds of the Information Cascade Fragility Under a Mismatched Model

We analyze a sequential decision making model in which decision makers (...
research
03/07/2022

Identifying the Deviator

A group of players are supposed to follow a prescribed profile of strate...
research
03/16/2020

Timing uncertainty in collective risk dilemmas encourages group reciprocation and polarization

Human social dilemmas are often shaped by actions involving uncertain go...
research
03/04/2016

Analyzing Games with Ambiguous Player Types using the MINthenMAX Decision Model

In many common interactive scenarios, participants lack information abou...

Please sign up or login with your details

Forgot password? Click here to reset