On Three-Layer Data Markets
CoRR(2024)
摘要
We study a three-layer data market comprising users (data owners), platforms,
and a data buyer. Each user benefits from platform services in exchange for
data, incurring privacy loss when their data, albeit noisily, is shared with
the buyer. The user chooses platforms to share data with, while platforms
decide on data noise levels and pricing before selling to the buyer. The buyer
selects platforms to purchase data from. We model these interactions via a
multi-stage game, focusing on the subgame Nash equilibrium. We find that when
the buyer places a high value on user data (and platforms can command high
prices), all platforms offer services to the user who joins and shares data
with every platform. Conversely, when the buyer's valuation of user data is
low, only large platforms with low service costs can afford to serve users. In
this scenario, users exclusively join and share data with these low-cost
platforms. Interestingly, increased competition benefits the buyer, not the
user: as the number of platforms increases, the user utility does not improve
while the buyer utility improves. However, increasing the competition improves
the overall utilitarian welfare. Building on our analysis, we then study
regulations to improve the user utility. We discover that banning data sharing
maximizes user utility only when all platforms are low-cost. In mixed markets
of high- and low-cost platforms, users prefer a minimum noise mandate over a
sharing ban. Imposing this mandate on high-cost platforms and banning data
sharing for low-cost ones further enhances user utility.
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