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- 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
- 2024
- 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 used broadly. In this paper, we show that recently identified gender gaps in AI use are nearly universal. Synthesizing evidence from 16 studies that surveyed 100,000... 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
- September–October 2024
- Article
Working Around the Clock: Temporal Distance, Intrafirm Communication, and Time Shifting of the Employee Workday
By: Jasmina Chauvin, Prithwiraj Choudhury and Tommy Pan Fang
This paper examines the effects of temporal distance generated by time zone separation on communication in geographically distributed organizations. We build on prior research, which highlights time zone separation as a significant challenge, but argue that employees... 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
- 2024
- Working Paper
The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations
By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
The rise of generative artificial intelligence (AI) is transforming creative problem-solving, necessitating new approaches for evaluating innovative solutions. This study explores how human-AI collaboration can enhance early-stage evaluations, focusing on the interplay... 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
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
Don’t Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics
By: Katherine C. Kellogg, Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon and Karim R. Lakhani
The literature on communities of practice demonstrates that a proven way for senior professionals to upskill
themselves in the use of new technologies that undermine existing expertise is to learn from junior
professionals. It notes that juniors may be better able... 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
- March 7, 2024
- Article
Integrating Digital Tools into Every Stage of Your Sales Strategy
By: Frank V. Cespedes and Georg Krentzel
In their growth and customer-acquisition activities, most companies now face twin challenges: understanding and responding to omni-channel buying behavior and doing that without inadvertently decreasing sales productivity. Thirty years ago, Peter Drucker noted that... View Details
- 2024
- Working Paper
Who Values Democracy?
By: Max Miller
This paper tests the conventional view that redistribution is central to the democratization process using data from stock markets. Consistent with this view, democratizations have a large, negative impact on asset valuations driven by a rise in redistribution risk.... View Details
- 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
- 2023
- 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. Though gender is perhaps the most frequently studied dimension of identity among workers, little is known about how gender match between managers and their workers might affect team performance. Using... View Details
- 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