Publications

December 2024
Article

Respect for Improvements and Comparative Statics in Matching Markets

By: Scott Duke Kominers

One of the oldest results in the theory of two-sided matching is the entry comparative static, which shows that under the Gale–Shapley deferred acceptance algorithm, adding a new agent to one side of the market makes all the agents on the other side weakly... View Details

Keywords: Market Entry and Exit; Marketplace Matching; Mathematical Methods; Market Design

2024
Working Paper

Why Most Resist AI Companions

By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp and Stefano Puntoni

Chatbots are now able to form emotional relationships with people and alleviate loneliness—a growing public health concern. Behavioral research provides little insight into whether everyday people are likely to use these applications and why. We address this question... View Details

Keywords: Generative Ai; Chatbots; Artificial Intelligence; Algorithmic Aversion; Lonelines; Technology Adoption; AI and Machine Learning; Well-being; Emotions

2024
Working Paper

Does Private Equity Have Any Business Being in the Health Care Business?

By: Nori Gerardo Lietz and Zirui Song

Private Equity (“PE”) has come under increased scrutiny by the press, academics, and policymakers, as well as the public, for its investments in health care delivery. This scrutiny has been exacerbated by recent high profile hospital bankruptcies following PE... View Details

Keywords: Private Equity; Government Administration; Acquisition; Health Industry

July 2024
Article

Chatbots and Mental Health: Insights into the Safety of Generative AI

By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni

Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details

Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics

2024
Working Paper

Digital Platforms 2.0: Learnings, Opportunities, and Challenges

By: Shrabastee Banerjee, Ishita Chakraborty, Hana Choi, Hannes Datta, Remi Daviet, Chiara Farronato, Minkyung Kim, Anja Lambrecht, Puneet Manchanda, Aniko Oery, Ananya Sen, Marshall W Van Alstyne, Prasad Vana, Kenneth C Wilbur, Xu Zhang and Bobby Zhou

Platform-based digital ecosystems form the backbone of our interactions with the Internet. Over the past decade, digital ecosystems have witnessed significant growth, both in terms of industry footprint and academic research. Yet, the challenges associated with their... View Details

Keywords: Digital Platforms; Technology Adoption; E-commerce; Market Design

2024
Working Paper

Webmunk: A New Tool for Studying Online Behavior and Digital Platforms

By: Chiara Farronato, Andrey Fradkin and Chris Karr

Understanding the behavior of users online is important for researchers, policymakers, and private companies alike. But observing online behavior and conducting experiments is difficult without direct access to the user base and software of technology companies. We... View Details

Keywords: Policy; Technology Adoption; Behavior; Research; Consumer Behavior; Internet and the Web

Find at Harvard

2024
Working Paper

AI Companions Reduce Loneliness

By: Julian De Freitas, Ahmet K. Uğuralp, Zeliha O. Uğuralp and Stefano Puntoni

Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details

Keywords: AI and Machine Learning; Technological Innovation; Behavior; Well-being

2024
Working Paper

Winner Take All: Exploiting Asymmetry in Factorial Designs

By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti

Researchers and practitioners have embraced factorial experiments to simultaneously test multiple treatments, each with different levels. With the rise of technologies like Generative AI, factorial experimentation has become even more accessible: it is easier than ever... View Details

Keywords: Factorial Designs; Fisher Randomizations; Rank Estimators; Employer Interventions; Causal Inference; Mathematical Methods; Performance Improvement

2024
Working Paper

Advancing Personalization: How to Experiment, Learn & Optimize

By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer

Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details

Keywords: Personalization; Targeting; Experiments; Observational Studies; Policy Implementation; Policy Evaluation; Customization and Personalization; Marketing Strategy; AI and Machine Learning

June 2024
Article

Redistributive Allocation Mechanisms

By: Mohammad Akbarpour, Piotr Dworczak and Scott Duke Kominers

Many scarce public resources are allocated at below-market-clearing prices, and sometimes for free. Such "non-market" mechanisms sacrifice some surplus, yet they can potentially improve equity. We develop a model of mechanism design with redistributive concerns. Agents... View Details

Keywords: Equality and Inequality; Welfare; Mathematical Methods; Market Design; Cost vs Benefits

2023
Working Paper

An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

By: Biyonka Liang and Iavor I. Bojinov

Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details

Keywords: Analytics and Data Science; AI and Machine Learning; Mathematical Methods

2024
Working Paper

Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference

By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov

Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details

Keywords: Mathematical Methods; Analytics and Data Science

2024
Working Paper

Design of Panel Experiments with Spatial and Temporal Interference

By: Tu Ni, Iavor Bojinov and Jinglong Zhao

One of the main practical challenges companies face when running experiments (or A/B tests) over a panel is interference, the setting where one experimental unit's treatment assignment at one time period impacts another's outcomes, possibly at the following time... View Details

Keywords: Research

March 2024
Module Note

Module Note on the Structuring of Collaborative Work

By: Ethan Bernstein

This module note for instructors describes the organizational structure module of the Managing Human Capital course that integrates insights from research on workplace connectivity (who gets to communicate with whom) and workplace transparency (who gets to observe... View Details

Keywords: Human Resources; Management; Organizational Design; Organizational Structure; Human Capital

Purchase

February 2024 (Revised March 2024)
Teaching Note

X: The Foghorn Decision

By: Kyle Myers and Walter Frick

Teaching Note for HBS Case No. 618-060. View Details