Publications
Publications
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- 2025
- Working Paper
Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs
By: Mengjie Cheng, Elie Ofek and Hema Yoganarasimhan
We study how media firms can use LLMs to generate news content that aligns with multiple objectives—making content more engaging while maintaining a preferred level of polarization/slant consistent with the firm’s editorial policy. Using news articles from The New York... View Details
- 2025
- Working Paper
How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions
By: Christian Kaps and Arielle Anderer
Learning curves, the fact that technologies improve as a function of cumulative experience or investment, are desirable-think inexpensive solar panels or higher performing semiconductors. But, for firms that need to pick one technology among several candidates, such as... View Details
- 2025
- Working Paper
Residential Battery Storage - Reshaping the Way We Do Electricity
By: Christian Kaps and Serguei Netessine
In this paper, we aim to understand when private households invest in behind-the-meter battery storage next to rooftop solar and how those batteries impact households, the electricity market, and emissions. We answer three main research questions: 1) When do customers... View Details
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
- 2023
- Working Paper
The Complexity of Economic Decisions
By: Xavier Gabaix and Thomas Graeber
We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity... View Details
- April–June 2022
- Other Article
Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'
There has been a substantial discussion in various methodological and applied literatures around causal inference; especially in the use of machine learning and statistical models to understand heterogeneity in treatment effects and to make optimal decision... View Details
- 2020
- Working Paper
Targeting for Long-Term Outcomes
By: Jeremy Yang, Dean Eckles, Paramveer Dhillon and Sinan Aral
Decision makers often want to target interventions so as to maximize an outcome that is observed only in the long term. This typically requires delaying decisions until the outcome is observed or relying on simple short-term proxies for the long-term outcome. Here we... View Details
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
- June 2020
- Article
Understanding Different Approaches to Benefit-Based Taxation
By: Robert Scherf and Matthew C. Weinzierl
The normative principle of benefit-based taxation has exerted substantial influence on many areas of public finance, but it has been largely set aside in the modern theoretical approach to optimal income taxation, where welfarist objectives dominate. A prerequisite for... View Details
- Article
The Role of Interactivity in Local Differential Privacy
By: Matthew Joseph, Jieming Mao, Seth Neel and Aaron Leon Roth
We study the power of interactivity in local differential privacy. First, we focus on the difference between fully interactive and sequentially interactive protocols. Sequentially interactive protocols may query users adaptively in sequence, but they cannot return to... View Details
- October 2019 (Revised February 2023)
- Case
Gupta Media: Performance Marketing in the Digital Age
By: V. Kasturi Rangan and Courtney Han
Gupta Media is a Digital Marketing firm started in 2005 that places advertisements and marketing promotions for its clients in digital media, mainly social media such as Facebook and Google. Over the years it had built its expertise in promoting music labels, artists... View Details
- August 2019
- Article
When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation
By: Yicheng Song, Nachiketa Sahoo and Elie Ofek
Sometimes we desire change, a break from the same or an opportunity to fulfill different aspects of our needs. Noting that consumers seek variety, several approaches have been developed to diversify items recommended by personalized recommender systems. However,... View Details
- 2019
- Article
Time-Driven Activity-Based Cost Analysis for Outpatient Anticoagulation Therapy: Direct Costs in a Primary Care Setting with Optimal Performance
By: Robert S. Kaplan, Rohit A. Bobade, Richard A. Helmers, Thomas M. Jaeger, Laura J. Odell and Derek A. Haas
Objectives: To determine how overall cost of anticoagulation therapy for warfarin compares with that of Novel Oral Anticoagulants (NOACs). Also, to demonstrate a scientific, comprehensive, and an analytical approach to estimate direct costs involved in monitoring and... View Details
- 2019
- Working Paper
Understanding Different Approaches to Benefit-Based Taxation
By: Robert Scherf and Matthew C. Weinzierl
The normative principle of benefit-based taxation has exerted substantial influence on many areas of public finance, but it has been largely set aside in the modern theoretical approach to optimal income taxation, where welfarist objectives dominate. A prerequisite for... View Details
- 2019
- Working Paper
Large-Scale Demand Estimation with Search Data
By: Tomomichi Amano, Andrew Rhodes and Stephan Seiler
In many online markets, traditional methods of demand estimation are difficult to implement because assortments are very large and individual products are sold infrequently. At the same time, data on consumer search (i.e., browsing) behavior are often available and are... View Details
- February 2018
- Article
Retention Futility: Targeting High-Risk Customers Might Be Ineffective.
By: Eva Ascarza
Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details
- Article
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
By: Seth Neel and Aaron Leon Roth
Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated... View Details
- Article
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
- May 2017
- Article
Experimental Evidence of Pooling Outcomes Under Information Asymmetry
By: William Schmidt and Ryan W. Buell
Operational decisions under information asymmetry can signal a firm's prospects to less-informed parties, such as investors, customers, competitors, and regulators. Consequently, managers in these settings often face a tradeoff between making an optimal decision and... View Details
- 2018
- Working Paper
Opportunistic Returns and Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets
By: Chaithanya Bandi, Antonio Moreno, Donald Ngwe and Zhiji Xu
We investigate how dynamic pricing can lead to higher operational costs through more product returns in the online retail industry. Dynamic pricing has been widely applied by many online retailers. Research has shown that, in response to dynamic pricing, some customers... View Details