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Publications
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- June 2025
- Article
Ideation with Generative AI—In Consumer Research and Beyond
By: Julian De Freitas, G. Nave and Stefano Puntoni
The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing... View Details
- 2025
- Working Paper
Trade and Industrial Policy in Supply Chains: Directed Technological Change in Rare Earths
By: Laura Alfaro, Harald Fadinger, Jay Schymik and Gede Virananda
Trade and industrial policies, while primarily intended to support domestic industries, may unintentionally stimulate technological progress abroad. We document this mechanism in the case of rare earth elements (REEs)—critical inputs for manufacturing at the knowledge... View Details
- Working Paper
Shifting Work Patterns with Generative AI
By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton
We present evidence on how generative AI changes the work patterns of knowledge workers using
data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers
in the study received access to a generative AI tool integrated into the... View Details
- 2024
- Case
EPCorp: Convincing the C-Suite
By: Jacob M. Cook
In EPCorp: Convincing the C-Suite, Shivani Bahl is attempting to sell EPCorp's CEO, Debbie Sullivan, on her ideas for not only a new website upgrade but also a more expansive vision on how data and Generative AI can be used to grow the company. Debbie is understandably... View Details
- April 2025 (Revised May 2025)
- Case
Adobe: GenAI Opportunity or Threat?
By: Sunil Gupta, Rajiv Lal and Allison Ciechanover
In December 2022, Adobe CEO Shantanu Narayen faced a pivotal strategic decision due to the rapid rise of generative AI image models from OpenAI, Midjourney, and StabilityAI. Adobe, a leader in digital media and marketing software with a 40-year legacy of innovation and... View Details
- April 2025 (Revised April 2025)
- Case
JPMorganChase: Leadership in the Age of GenAI
By: Iavor I. Bojinov, Karim R. Lakhani and David Lane
This case study examines JPMorgan Chase's (JPMC) journey in adopting and implementing Generative AI (GenAI) following the release of ChatGPT. It outlines JPMC's initial cautious approach focused on data security, followed by strategic investments in internal platforms... View Details
Keywords: Banks and Banking; Governance Controls; Information Technology; AI and Machine Learning; Analytics and Data Science; Cybersecurity; Digital Platforms; Digital Transformation; Information Management; Information Infrastructure; Technology Adoption; Job Cuts and Outsourcing; Knowledge Management; Knowledge Sharing; Leading Change; Growth and Development Strategy; Marketing; Product Development; Performance Improvement; Customization and Personalization; Financial Services Industry; United States
- March–April 2025
- Article
Getting Value from Digital Technologies
By: Frank Cespedes and Georg Krentzel
Companies need digital technologies in an omni-channel buying world where online and in-person interactions are complements, not either/or substitutes. Multi-channel hybrid sales solutions are required, but what are the key requirements for using the available... View Details
- March 2025
- Case
Metaphysic AI: Rethinking the Value of Human Expertise
By: Zoë B. Cullen, Shikhar Ghosh and Shweta Bagai
In early 2025, Thomas Graham, CEO of Metaphysic, a leading AI generative video company confronted fundamental questions about who should control digital identity in a world where AI could perfectly recreate human likeness. Founded in 2021, Metaphysic first rose to fame... View Details
- March 2025
- Article
Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures
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
- 2025
- Working Paper
The Hidden Costs of Flexible Labor Models: How Working Multiple Jobs Affects Employees
By: Paige Tsai and Ryan W. Buell
As operations increasingly rely upon flexible labor models—such as gig, part-time, and remote work—it has become commonplace for individuals to work multiple jobs. Across three studies, relying on a combination of transaction-level data from 90,548 customers of a... View Details
- 2025
- Working Paper
Causes and Extent of Increasing Partisan Segregation in the U.S. – Evidence from Migration Patterns of 212 Million Voters
By: Jacob R. Brown, Enrico Cantoni, Vincent Pons and Emilie Sartre
Using data on the residential location and migration for every voter in U.S. states recording partisan registration between 2008–2020, we find that residential segregation between Democrats and Republicans has increased year over year at all geographic levels, from... View Details
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
- January–February 2025
- Article
Want Your Company to Get Better at Experimentation?: Learn Fast by Democratizing Testing
By: Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley
For years, online experimentation has fueled the innovations of leading tech companies, enabling them to rapidly test and refine new ideas, optimize product features, personalize user experiences, and maintain a competitive edge. The widespread availability and lower... View Details
- 2024
- Working Paper
Scaling Core Earnings Measurement with Large Language Models
By: Matthew Shaffer and Charles CY Wang
We study the application of large language models (LLMs) to the estimation of core earnings, i.e., a firm's persistent profitability from its core business activities. This construct is central to investors' assessments of economic performance and valuations. However,... View Details
- November 2024 (Revised January 2025)
- Case
MiDAS: Automating Unemployment Benefits
By: Shikhar Ghosh and Shweta Bagai
In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details
Keywords: Artificial Intelligence; AI; Machine Learning Models; Algorithmic Data; Automation; Benefits; Compensation; Cost Reduction; Government; Fraud; Government Technology; Public Sector; Systems; Systems Integration; Unemployment Insurance; Waste Heat Recovery; AI and Machine Learning; Government Administration; Insurance; Decision Making; Digital Transformation; Employment; Public Administration Industry; United States; Michigan
- 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
- 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