Research

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We develop a model that classifies platforms in the “creator economy”-e.g. Youtube, Patreon, and Twitch-into three broad business models: pure discovery mode (providing recommendations and helping consumers search for creators); pure membership mode (enabling individual creators to monetize their viewers through direct transactions and collecting commissions from the transactions); and a hybrid mode which combines both. Creators respond to platforms’ decisions by individually choosing to supply content designed along a broad-niche spectrum, which involves a trade-off between viewership size and per-viewer revenue. These design changes create a trade-off between advertising revenue and transaction commission revenue for the platform. In a monopoly platform benchmark moving from pure discovery to hybrid always increases platform revenue while making content weakly more niche. However, moving from pure membership to hybrid may reduce platform revenue if providing advertising is not sufficiently lucrative. In a duopoly setup these trade-offs can be reversed, depending on the level of platform competition and homing behavior of creators and consumers.

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Market platforms must decide how much effort to put into screening out low-quality sellers. Increasing quality of the sellers on a market increases consumer confidence and participation, but other factors may reduce the incentive to screen. This article explores why market platforms do not screen out low-quality sellers when screening costs are minimal. Consumers must search for a seller whose product is a good match. The presence of low-quality sellers reduces search intensity, softening competition between sellers, increasing equilibrium price and hence the platform’s revenue per sale. If sellers compete with sufficient intensity then the platform admits some low-quality sellers. This might initially seem contradictory to the practice of platform recommendations, but recommending a high-quality seller and search obfuscation are complementary strategies. The low-quality sellers enable the recommended seller to attract many consumers at a high price and the effect of the recommendation is strengthened as low-quality sellers become more adept at imitating high-quality sellers.

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In many search environments, searchers are learning about the distribution of offers in the market. I conduct an experiment exploring a broad class of search problems with learning about the distribution of payoffs. My results support the prediction that learning results in declining reservation values, providing evidence that learning may be an explanation for recall. Theory predicts a “one step” reservation value strategy, but many subjects instead choose to set a high reservation value in order to learn about the distribution before adjusting based on their observations. Under-searching in search experiments may stem from a reinforcement heuristic and lack of negative feedback after using sub-optimal strategies.

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We show that adding a disutility term in education choice models is equivalent to assuming a relationship between wealth, risk, and education decisions. Utility gains from education are increasing in the riskiness of future consumption, implying that a riskier environment will lead agents to choose human capital investment options which maximize future income. If the degree of risk increases heterogeneously across human capital investment options, then risk aversion and the precautionary savings motive can compound or negate each other depending which option has a greater increase in risk.

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What are the unintended effects of policies that reduce the cost of disintermediating from market platforms? I show that it may be profitable for a platform to reduce the intensity with which it screens sellers while simultaneously offering a robust refund policy to insure consumers against possible transactions with low-quality sellers. This reduces the incentive to disintermediate by shrinking consumer confidence in sellers who steer consumers to direct transactions, reducing consumers’ willingness to pay for off-platform transactions. The refund policy encourages low-quality sellers to only offer direct transactions while maintaining consumer willingness to pay for products sold through the platform. Introducing a rival platform increases seller welfare and eliminates this unintended effect by deterring platforms from allowing low-quality sellers to join their marketplaces for fear of losing consumers to their rival.

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What are the welfare consequences of privacy regulation when a media platform offers both an ad-supported free version and a premium subscription? We present a model where privacy regulation lowers advertiser willingness to pay for advertising on the platform. The platform will drive more consumers toward its premium subscription by lowering the price while increasing the advertising load imposed on free viewers. The overall welfare consequence is that low-income consumers—who are more price sensitive and less advertising-averse and therefore consume the ad-supported version—are harmed by the privacy regulation while high-income consumers are better off. In extensions, we consider cases where wealthier consumers are more valuable to advertisers and where consumers have intrinsic preferences for privacy and provide conditions under which our main qualitative results still hold.

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