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Mechanisms with Referrals: VCG Mechanisms and Multilevel Mechanisms

Authors: Joosung Lee; Joosung Lee;

Mechanisms with Referrals: VCG Mechanisms and Multilevel Mechanisms

Abstract

We study mechanisms for environments in which only some of the agents are directly connected to a mechanism designer and the other agents can participate in a mechanism only through the connected agents' referrals. In such environments, the mechanism designer and agents may have different interest in varying participants so that agents strategically manipulate their preference as well as their network connection to avoid competition or congestion; while the mechanism designer wants to elicit the agents' private information about both preferences and network connections. As a benchmark for an efficient mechanism, we re-define a VCG mechanism. It is incentive compatible and individually rational, but it generically runs a deficit as it requires too much compensation for referrals. Alternatively as a budget-surplus mechanism, we introduce a multilevel mechanism, in which each agent is compensated by the agents who would not be able to participate without her referrals. Under a multilevel mechanism, we show that fully referring one's acquaintances is a dominant strategy and agents have no incentive to under-report their preference if the social welfare is submodular.

Keywords

Mechanism Design, Multilevel Mechanism, Reward Scheme, Incentive Compatibility, Budget Feasibility, Referral Program, Research Methods/ Statistical Methods, VCG Mechanism

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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