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A defining feature of digital goods is that replication and degradation are costless: once a high-quality good is produced, low-quality versions can be created and distributed at no additional cost. This paper studies quality-based…

Theoretical Economics · Economics 2026-03-10 Pietro Dall'Ara , Elia Sartori

Fairness in advertising is a topic of particular concern motivated by theoretical and empirical observations in both the computer science and economics literature. We examine the problem of fairness in advertising for general purpose…

Computer Science and Game Theory · Computer Science 2019-08-30 Shuchi Chawla , Christina Ilvento , Meena Jagadeesan

This paper presents the Sequential Rationality Hypothesis, which argues that consumers are better able to make utility-maximizing decisions when products appear in sequential pairwise comparisons rather than in simultaneous multi-option…

Theoretical Economics · Economics 2026-01-23 Dipankar Das

We investigate the relationship between product offerings, information dissemination, and consumer decision-making in a monopolistic screening environment in which consumers lack information about their valuation of quality-differentiated…

Theoretical Economics · Economics 2026-04-13 Panagiotis Kyriazis , Edmund Lou

In consumer search, there is a set of items. An agent has a prior over her value for each item and can pay a cost to learn the instantiation of her value. After exploring a subset of items, the agent chooses one and obtains a payoff equal…

Computer Science and Game Theory · Computer Science 2019-05-15 Nicole Immorlica , Jieming Mao , Christos Tzamos

Ranking algorithms are deployed widely to order a set of items in applications such as search engines, news feeds, and recommendation systems. Recent studies, however, have shown that, left unchecked, the output of ranking algorithms can…

Data Structures and Algorithms · Computer Science 2018-07-31 L. Elisa Celis , Damian Straszak , Nisheeth K. Vishnoi

We explore the fundamental problem of sorting through the lens of learning-augmented algorithms, where algorithms can leverage possibly erroneous predictions to improve their efficiency. We consider two different settings: In the first…

Data Structures and Algorithms · Computer Science 2023-11-03 Xingjian Bai , Christian Coester

We analyze a nonlinear pricing model where the seller controls both product pricing (screening) and buyer information about their own values (persuasion). We prove that the optimal mechanism always consists of finitely many signals and…

Theoretical Economics · Economics 2025-03-11 Dirk Bergemann , Tibor Heumann , Stephen Morris

We solve for the equilibrium dynamics of information sharing in a large population. Each agent is endowed with signals regarding the likely outcome of a random variable of common concern. Individuals choose the effort with which they search…

Probability · Mathematics 2008-11-20 Darrell Duffie , Semyon Malamud , Gustavo Manso

We study optimal monopoly pricing over consumer networks governed by general nonlinear utilities. In our framework, a consumer's utility is jointly determined by an individualized price and the consumption choices of their peers, propagated…

Statistics Theory · Mathematics 2026-05-15 Daniele Bracale , George Michailidis

Consumers in many markets are uncertain about firms' qualities and costs, so buy based on both the price and the quality inferred from it. Optimal pricing depends on consumer heterogeneity only when firms with higher quality have higher…

Theoretical Economics · Economics 2019-04-12 Sander Heinsalu

The paper explores a consumer search setting where the sellers have asymmetries. The model is an extension of the popular Stahl Model, which is widely used in the literature. The extension introduces sellers with heterogeneous stores…

Computer Science and Game Theory · Computer Science 2015-03-20 Sergey Kuniavsky

Machine learning models play a key role for service providers looking to gain market share in consumer markets. However, traditional learning approaches do not take into account the existence of additional providers, who compete with each…

Machine Learning · Computer Science 2025-08-15 Ohad Einav , Nir Rosenfeld

A user faces a list returned by a search system, ordered by a noisy proxy for relevance, and decides sequentially whether to pay a fixed cost to inspect another item or stop with the best she has uncovered. She does not enter the page…

Information Retrieval · Computer Science 2026-05-26 Shichao Ma

When designing product rankings, online retailers and platforms choose which outcome to maximize: revenues from commissions or markups, the number of transactions, or consumer welfare. These objectives need not align, creating potential…

General Economics · Economics 2026-03-26 Rafael P. Greminger

Dynamic, risk-based pricing can systematically exclude vulnerable consumer groups from essential resources such as health insurance and consumer credit. We show that a regulator can realign private incentives with social objectives through…

Artificial Intelligence · Computer Science 2025-06-05 Jesse Thibodeau , Hadi Nekoei , Afaf Taïk , Janarthanan Rajendran , Golnoosh Farnadi

We analyze a reversed-supervision strategy that searches over labelings of a large unlabeled set \(B\) to minimize error on a small labeled set \(A\). The search space is \(2^n\), and the resulting complexity remains exponential even under…

Machine Learning · Computer Science 2025-12-19 Masoud Makrehchi

In many online platforms, customers' decisions are substantially influenced by product rankings as most customers only examine a few top-ranked products. Concurrently, such platforms also use the same data corresponding to customers'…

Machine Learning · Computer Science 2020-09-14 Negin Golrezaei , Vahideh Manshadi , Jon Schneider , Shreyas Sekar

An informed seller designs a dynamic mechanism to sell an experience good. The seller has partial information about the product match, which affects the buyer's private consumption experience. We characterize equilibrium mechanisms of this…

Theoretical Economics · Economics 2025-06-24 Tan Gan , Nicholas Wu

Traditionally, recommender systems operate by returning a user a set of items, ranked in order of estimated relevance to that user. In recent years, methods relying on stochastic ordering have been developed to create "fairer" rankings that…

Information Retrieval · Computer Science 2022-09-13 Amanda Bower , Kristian Lum , Tomo Lazovich , Kyra Yee , Luca Belli
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