Publications
Publications
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- All HBS Web
(2,162)
- Faculty Publications (248)
- October 2024
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
- 2025
- Working Paper
Global Evidence on Gender Gaps and Generative AI
By: Nicholas G. Otis, Solène Delecourt, Katelynn Cranney and Rembrand Koning
Generative AI has the potential to transform productivity and reduce inequality, but only if adopted broadly. In this paper, we show that recently identified gender gaps in generative AI use are nearly universal. Synthesizing data from 18 studies covering more than... View Details
- 2024
- Article
Learning Under Random Distributional Shifts
By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host
countries has gained attention in recent years, with implementations in the U.S.
and Switzerland. These approaches use data on past arrivals to generate machine
learning models that can... View Details
- September–October 2024
- Article
Where Data-Driven Decision-Making Can Go Wrong
By: Michael Luca and Amy C. Edmondson
When considering internal data or the results of a study, often business leaders either take the evidence presented as gospel or dismiss it altogether. Both approaches are misguided. What leaders need to do instead is conduct rigorous discussions that assess any... View Details
- August 2024
- Case
The Walt Disney Company: Management Guidance
By: Joseph Pacelli and James Weber
In November 2023, financial analyst Aurora Fee was forecasting The Walt Disney Company’s earnings and stock price, with the goal of providing an investment recommendation to her clients. Disney, one of the world’s largest media and entertainment companies, had just... View Details
- August 2024
- Article
How Do Copayment Coupons Affect Branded Drug Prices and Quantities Purchased?
By: Leemore S. Dafny, Kate Ho and Edward Kong
Drug copayment coupons to reduce patient cost-sharing have become nearly ubiquitous for high-priced brand-name prescription drugs. Medicare bans such coupons on the grounds that they are kickbacks that induce utilization, but they are commonly used by... View Details
- July, 2024
- Article
Consumer Protection in an Online World: An Analysis of Occupational Licensing
By: Chiara Farronato, Andrey Fradkin, Bradley Larsen and Erik Brynjolfsson
We study the demand and supply implications of occupational licensing using transaction-level data from a large online platform for home improvement services. We find that demand is more responsive to a professional's reviews than to the professional's... View Details
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
- 2024
- Working Paper
Does the Case for Private Equity Still Hold?
By: Nori Gerardo Lietz and Philipp Chvanov
Private Equity (“PE”) received a 10-fold increase in capital flows since the Great Financial Crisis (“GFC”) Investors sought higher nominal returns relative to those they could obtain in the public capital markets. This paper questions the fundamental assumptions... View Details
- March–April 2024
- Article
Retailers and Health Systems Can Improve Care Together
By: Robert S. Huckman, Vivian S. Lee and Bradley R Staats
Health systems are struggling to address the many shortcomings of health care delivery: rapidly growing costs, inconsistent quality, and inadequate and unequal access to primary and other types of care. However, if retailers and health systems were to form strong... View Details
- March 2024 (Revised May 2024)
- Case
Amperity: First-Party Data at a Crossroads
By: Elie Ofek, Hema Yoganarasimhan and Alexis Lefort
In the summer of 2023, Amperity management was facing a critical decision on its future direction. Given the dramatic changes occurring within the digital advertising ecosystem, as concerns over consumer privacy placed limits on the ability to engage in third-party... View Details
- 2024
- Working Paper
The Cram Method for Efficient Simultaneous Learning and Evaluation
By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
- 2023
- Working Paper
New Facts and Data about Professors and Their Research
By: Kyle Myers, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural and Yilun Xu
We introduce a new survey of professors at roughly 150 of the most research-intensive institutions of higher education in the US. We document seven new features of how research-active professors are compensated, how they spend their time, and how they perceive their... View Details
- 2024
- Working Paper
Rapport in Organizations: Evidence from Fast Food
By: Achyuta Adhvaryu, Parker Howell, Anant Nyshadham and Jorge Tamayo
Common identity often provides a foundation for workplace rapport. Using personnel and productivity data from a large fast food chain in Colombia, we study whether mismatched gender identity across managers and workers affects the team’s ability to deal with demand... View Details
Keywords: Productivity; Workplace Relationships; Rapport; Managers; People Management; Labor Allocation; Staffing; Scheduling; Quick-serve Restaurants; Management; Relationships; Gender; Labor and Management Relations; Organizational Change and Adaptation; Employees; Food and Beverage Industry; Colombia
- December 4, 2023
- Comment
The Great Resignation, Employment, and Wages in Health Care
By: Amitabh Chandra and Louis-Jonas Heizlsperger
Notwithstanding concerns about staffing levels and burnout in health care, federal wage and employment data does not support the suggestion that a COVID-19 pandemic-related spike in quitting has had an enduring impact for hospitals or physician offices. Employment in... View Details
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
- 2023
- Book
Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow
By: Ken Huang, Yang Wang, Feng Zhu, Xi Chen and Chunxiao Xing
This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business... View Details
- December 2023
- Article
When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments
By: Christian Kaps, Simone Marinesi and Serguei Netessine
Globally, 1.5 billion people live off the grid, their only access to electricity often limited to operationally-expensive fossil fuel generators. Solar power has risen as a sustainable and less costly option, but its generation is variable during the day and... View Details
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
- 2024
- Working Paper
What Do Impact Investors Do Differently?
In recent years, impact investors—private investors who seek to generate simultaneously financial and social returns—have attracted intense interest and controversy. We introduce and analyze a novel, comprehensive data set of impact
and traditional investors to assess... View Details