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- April 2025
- Article
Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile
By: Shunyuan Zhang, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar and Xupin Zhang
Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling... View Details
Keywords: Sharing Economy; Airbnb; Image Feature Extraction; Machine Learning; Facial Expressions; Prejudice and Bias; Nonverbal Communication; E-commerce; Consumer Behavior; Perception
Zhang, Shunyuan, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar, and Xupin Zhang. "Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile." Journal of Consumer Research 51, no. 6 (April 2025): 1073–1097.
- March 2025
- Case
Niramai: An AI Solution to Save Lives
By: Rembrand Koning, Maria P. Roche and Kairavi Dey
Founded in 2017, Niramai developed Thermalytix, a breast cancer screening tool. Thermalytix used a high-resolution thermal sensing device and machine learning algorithms to analyze thermal images and detect tumors. Its patented solution leveraged big data analytics,... View Details
- 2025
- Working Paper
The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise
By: Fabrizio Dell'Acqua, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub and Karim R. Lakhani
We examine how artificial intelligence transforms the core pillars of collaboration—
performance, expertise sharing, and social engagement—through a pre-registered field
experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods
company.... View Details
Keywords: Artificial Intelligence; Teamwork; Human-machine Interaction; Productivity; Skills; Innovation; Field Experiment; AI and Machine Learning; Groups and Teams; Competency and Skills; Performance Productivity; Collaborative Innovation and Invention; Product Development
Dell'Acqua, Fabrizio, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub, and Karim R. Lakhani. "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise." Harvard Business School Working Paper, No. 25-043, March 2025.
- March 2025
- Case
Xfund and Sam Altman: Finding Harvard’s Best Generative AI Founders
By: Suraj Srinivasan
On May 1, 2024, Xfund Managing Partners Patrick Chung and Brandon Farwell, hosted a high-stakes venture pitch session designed to select one startup for a minimum $100,000 investment. This “Xperiment Stake” competition, dedicated to startups in the Generative AI... View Details
- March 10, 2025
- Article
How Gen AI Could Change the Value of Expertise
By: Joseph Fuller, Matt Sigelman and Michael Fenlon
In the near future, gen AI is likely to affect some 50 million jobs, automating away elements of some jobs and augmenting workers’ abilities in others. The extent of those changes will compel companies to reshape their organizational structures and rethink their talent... View Details
Keywords: AI and Machine Learning; Job Cuts and Outsourcing; Organizational Structure; Talent and Talent Management; Personal Development and Career
Fuller, Joseph, Matt Sigelman, and Michael Fenlon. "How Gen AI Could Change the Value of Expertise." Harvard Business Review (website) (March 10, 2025).
- 2025
- Working Paper
Incentive-Compatible Recovery from Manipulated Signals, with Applications to Decentralized Physical Infrastructure
By: Jason Milionis, Jens Ernstberger, Joseph Bonneau, Scott Duke Kominers and Tim Roughgarden
We introduce the first formal model capturing the elicitation of unverifiable information from a party (the "source") with implicit signals derived by other players (the "observers"). Our model is motivated in part by applications in decentralized physical... View Details
Milionis, Jason, Jens Ernstberger, Joseph Bonneau, Scott Duke Kominers, and Tim Roughgarden. "Incentive-Compatible Recovery from Manipulated Signals, with Applications to Decentralized Physical Infrastructure." Working Paper, March 2025.
- 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
Keywords: Rank and Position; Competency and Skills; Technology Adoption; Experience and Expertise; AI and Machine Learning
Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. "Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures." Art. 100559. Information and Organization 35, no. 1 (March 2025).
- 2025
- Working Paper
Workplace Segregation Between College and Non-college Workers
By: Francis Dillon, Edward L. Glaeser and William Kerr
We measure the level and growth of education segregation in American workplaces from 2000 to 2020.
American workplaces show an educational segregation, measured by the degree to which the establishment
has mostly workers of similar education levels, that is... View Details
Dillon, Francis, Edward L. Glaeser, and William Kerr. "Workplace Segregation Between College and Non-college Workers." Harvard Business School Working Paper, No. 25-044, March 2025.
- February 2025
- Case
Fly, Fix, Fly at True Anomaly
By: Joshua Lev Krieger, Jim Matheson, Fiona Murray and David Allen
How should companies learn from failure? Founded by four U.S. Space Force warfighters, the tough tech startup True Anomaly wanted to compete with major defense contractors to supply the U.S. Department of Defense with satellites and software that could help protect... View Details
- 2025
- Working Paper
Is Love Blind? AI-Powered Trading with Emotional Dividends
By: Valeria Fedyk, Daniel Rabetti and Stella Kong
We leverage the non-fungible tokens (NFTs) setting to assess the valuation of emotional dividends (LOVE), a long-standing empirical challenge in private-value markets such as art, antiques, and collectibles. Having created and validated our proxy, we use deep learning... View Details
Keywords: AI and Machine Learning
Fedyk, Valeria, Daniel Rabetti, and Stella Kong. "Is Love Blind? AI-Powered Trading with Emotional Dividends." Working Paper, February 2025.
- February 2025
- Case
Institutional Neutrality, Restraint or Convenience?
By: Clayton S. Rose, Nicole Zelazko and Alexis Lefort
In the fall of 2023 and winter of 2024, college campuses across the U.S. experienced protests and encampments in the aftermath of the October 7, 2023 terrorist attack on Israel by the Islamist militant group Hamas, and Israel’s subsequent invasion of Gaza. These... View Details
Keywords: Change; Distribution; Decision Making; Cost vs Benefits; Ethics; Governance; Leadership; Management; Crisis Management; Risk Management; Organizations; Corporate Social Responsibility and Impact; Mission and Purpose; Organizational Change and Adaptation; Organizational Culture; Society; Civil Society or Community; Social Issues; Strategy; Adaptation
Rose, Clayton S., Nicole Zelazko, and Alexis Lefort. "Institutional Neutrality, Restraint or Convenience?" Harvard Business School Case 325-022, February 2025.
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.
- February 2025
- Article
Disclosure, Humanizing, and Contextual Vulnerability of Generative AI Chatbots
By: Julian De Freitas and I. Glenn Cohen
In the wake of recent advancements in generative AI, regulatory bodies are trying to keep pace. One key decision is whether to require app makers to disclose the use of generative AI-powered chatbots in their products. We suggest that some generative AI-based chatbots... View Details
Keywords: AI and Machine Learning; Governing Rules, Regulations, and Reforms; Applications and Software; Well-being
De Freitas, Julian, and I. Glenn Cohen. "Disclosure, Humanizing, and Contextual Vulnerability of Generative AI Chatbots." New England Journal of Medicine AI 2, no. 2 (February 2025).
- January 2025
- Teaching Plan
Knowledge Transfer: Toyota, NUMMI, and GM
By: Willy Shih
Teaching Plan for HBS Case No. 625-003. New United Motors Manufacturing, Inc. (NUMMI) was a joint venture between Toyota and General Motors. It was an opportunity for GM to learn about the Toyota Production System, which was quite different from the mass production... View Details
Keywords: Culture Change; Organizational Culture; Organizational Change and Adaptation; Factories, Labs, and Plants; Joint Ventures; Transformation; Selection and Staffing; Knowledge Acquisition; Knowledge Sharing; Labor Unions; Management Systems; Performance Improvement; Production; Labor and Management Relations; Auto Industry; Japan; United States
- January 2025
- Case
Colbún’s Angostura Dam Project (A)
By: James K. Sebenius and Nicolas Andrade
The A case describes Colbún Chile’s plans for the Angostura dam in the Bío Bío River, a hydroelectric construction venture with major challenges given the region’s history of indigenous resistance. This context was especially unfavorable given the highly contentious... View Details
- January 2025
- Supplement
Colbún’s Angostura Dam Project (B)
By: James K. Sebenius and Nicolas Andrade
The A case describes Colbún Chile’s plans for the Angostura dam in the Bío Bío River, a hydroelectric construction venture with major challenges given the region’s history of indigenous resistance. This context was especially unfavorable given the highly contentious... View Details
- January 2025
- Case
Hebbia: Redefining Productivity for Knowledge Workers Using AI
By: Suraj Srinivasan and Minoshka Narayan
In early 2025, George Sivulka, founder and CEO of Hebbia, reflected on the company’s rapid ascent as a pioneer in GenAI-powered productivity tools for knowledge workers. With its proprietary technology, Hebbia had redefined information retrieval and analysis and earned... View Details
- January 2025
- Case
Duolingo: On a 'Streak'
By: Jeffrey F. Rayport, Nicole Tempest Keller and Nicole Luo
In December 2024, Severin Hacker, Co-Founder and Chief Technology Officer of Duolingo, reflected on the remarkable evolution of the language-learning app he helped launch in 2011. As the #1 most downloaded education app in the world, Duolingo had over 100 million... View Details
Keywords: Learning; AI and Machine Learning; Growth and Development Strategy; Motivation and Incentives; Diversification; Technology Industry; Education Industry; United States
Rayport, Jeffrey F., Nicole Tempest Keller, and Nicole Luo. "Duolingo: On a 'Streak'." Harvard Business School Case 825-097, January 2025.
- January 2025 (Revised March 2025)
- Case
Gavi and the 'Next' Pandemic
By: Tarun Khanna and Kerry Herman
In 2025, CEO Dr. Sania Nishtar and her team consider the lessons the Global Alliance for Vaccine and Immunizations (GAVI) learned from the pandemic. GAVI successfully brought COVID-19 vaccines to large swaths of the undeveloped and under-developed world by pooling... View Details
Khanna, Tarun, and Kerry Herman. "Gavi and the 'Next' Pandemic." Harvard Business School Case 725-351, January 2025. (Revised March 2025.)
- January 2025
- Case
Summer Health: Raising an AI-First Company?
By: Jeffrey J. Bussgang, Sarah Mehta and Maxim Pike Harrell
In October 2023, Summer Health CEO Ellen DaSilva arrived at a defining juncture for her pediatric telehealth startup. Founded in 2021, Summer Health offered parents rapid access to licensed pediatricians via text message. DaSilva, an experienced telehealth executive,... View Details
Keywords: AI and Machine Learning; Technology Adoption; Entrepreneurship; Leadership; Health Industry; Telecommunications Industry; United States
Bussgang, Jeffrey J., Sarah Mehta, and Maxim Pike Harrell. "Summer Health: Raising an AI-First Company?" Harvard Business School Case 825-083, January 2025.