SIGECOM

This is the ninth annual collection of profiles of the junior faculty job market candidates of the SIGecom community. The twenty seven candidates for 2024 are listed alphabetically and indexed by research areas that define the interests of the community. ...

Inspired by the SIGecom Exchanges' annual survey of job market candidates,¹ this is the fourth annual collection of profiles of the junior faculty job market candidates of the market design community. The eleven candidates are listed alphabetically. ...

The fourth annual ACM SIGecom Winter Meeting took place on February 15, 2024. Organized by Sigal Oren and Ran Shorrer, this year's meeting brought together researchers from economics, computer science, and adjacent fields to focus behavioral models. The ...

I argue that further integration between Decision Theory and the methods of quantifying complexity and evaluating performance in Computer Science is valuable. I review [Lanzani 2024] as an illustration of this combination.

This letter provides an overview of our recent work on COVID-19 testing mechanisms that appeared at EC'23. Large-scale testing is crucial in pandemics but resources are often prohibitively constrained. We study a scenario in which a population under ...

Customers can access hundreds of reviews for a single product in online marketplaces. Buyers often use reviews from other customers that share their type---such as height for clothing or skin type for skincare products---to estimate their values, which ...

Policymakers are often concerned about inequalities in the markets they control. In this letter, I argue that mechanism design has not responded sufficiently to the need for a comprehensive theory of inequality-aware market design. I review some of my ...

Traditionally, AI has been modeled within economics as a technology that impacts payoffs by reducing costs or refining information for human agents. Our position is that, in light of recent advances in generative AI, it is increasingly useful to model AI ...

We provide an overview of research on causal inference in the presence of strategic agents. Work in this area uses tools from econometrics, statistics, machine learning, and game theory to infer causal relationships between treatments and outcomes of ...

The study of peer selection mechanisms presents a unique opportunity to understand and improve the practice of a group selecting its best members, despite each member of that group wanting to be selected. A prime example of such a setting is academic ...

Which varieties or brands of a product should a retailer stock on its shelf? Carrying a large variety caters to more customers' needs, but could cannibalize the sales of high-end brands and also cause an inventory nightmare. Assortment optimization aims ...

This note provides a survey for the Economics and Computation community of some recent trends in the field of information elicitation. At its core, the field concerns the design of incentives for strategic agents to provide accurate and truthful ...

Matching, capturing allocation of items to unit-demand buyers, or tasks to workers, or pairs of collaborators, is a central problem in economics. Indeed, the growing prevalence of matching-based markets, many of which online in nature, has motivated much ...

In this survey, we summarize recent developments in research fueled by the growing adoption of automated bidding strategies in online advertising. We explore the challenges and opportunities that have arisen as markets embrace this autobidding and cover ...