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- March 2025 (Revised April 2025)
- Case
Perplexity: Redefining Search
By: Suraj Srinivasan, Michelle Hu, Sriraghav Srinivasan and Radhika Kak
By early 2025, Perplexity had rapidly evolved from a modest startup into a popular "answer engine" valued at $9 billion. The company had boldly positioned itself as the disruptor to Google aiming to redefine search for the AI age. Through novel AI... View Details
Keywords: AI and Machine Learning; Venture Capital; Innovation Leadership; Technological Innovation; Internet and the Web; Business Startups; Competitive Strategy; Technology Industry; United States
Srinivasan, Suraj, Michelle Hu, Sriraghav Srinivasan, and Radhika Kak. "Perplexity: Redefining Search." Harvard Business School Case 125-093, March 2025. (Revised April 2025.)
- March 2025
- Case
Stagwell: AI and the Future of Marketing
By: Suraj Srinivasan and Radhika Kak
In early 2025, Mark Penn, Founder, CEO and Chairman of Stagwell, a global marketing company with a network of over 70+ agencies that served over 4000 blue-chip customers across 40 countries, was looking at ways that marketers should navigate the disruption emanating... 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
Keywords: Business Model; Ethics; AI and Machine Learning; Intellectual Property; Rights; Negotiation; Value; Motion Pictures and Video Industry; Technology Industry
Cullen, Zoë B., Shikhar Ghosh, and Shweta Bagai. "Metaphysic AI: Rethinking the Value of Human Expertise." Harvard Business School Case 825-146, March 2025.
- 2025
- Working Paper
How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions
By: Christian Kaps and Arielle Anderer
Learning curves, the fact that technologies improve as a function of cumulative experience or investment, are desirable-think inexpensive solar panels or higher performing semiconductors. But, for firms that need to pick one technology among several candidates, such as... View Details
Keywords: Learning Curve; Technology; Innovation; Batteries; Energy Storage; Sequential Decision Making; TELCO; Exploration; Exploitation; Problems and Challenges; Cost vs Benefits; Technology Adoption; Battery Industry
Kaps, Christian, and Arielle Anderer. "How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions." Working Paper, March 2025.
- March 2025 (Revised May 2025)
- Case
ING Türkiye: Flexible Work in a Competitive Banking Environment
By: Ashley Whillans and Nico Schaefer
This case explores ING Türkiye’s journey toward workplace flexibility within the traditionally conservative Turkish banking sector. Beginning with early remote work experiments in 2015 and culminating in the FlexING model, by 2024 ING Türkiye had positioned itself as a... View Details
- March 2025
- Case
The Changing Climate on Wall Street
By: Clayton S. Rose, Maxim Pike Harrell and Michael Norris
Increasing and conflicting regulatory requirements and political pressures regarding climate change tested the leaders of U.S. financial institutions, as they struggled to determine how best to comply while managing their business and its risks.
In October 2024,... View Details
Keywords: Change; Disruption; Competency and Skills; Decision Making; Cost vs Benefits; Ethics; Governance; Corporate Accountability; Leadership; 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; Banking Industry; Financial Services Industry; Insurance Industry; United States; Europe
- 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.
- February 2025 (Revised March 2025)
- Case
Accounting for Bitcoin at Block
By: Charles C.Y. Wang, Seil Kim and Sa-Pyung Sean Shin
Abstract: This case explores Block Inc.'s accounting practices for Bitcoin transactions and their impact on financial reporting. Following a 10% stock price drop after missing revenue estimates in Q3 2024, Block faced scrutiny over its Bitcoin-driven revenue model.... View Details
- February 2025
- Case
Doing Business in Casablanca, Morocco
By: Karen G. Mills, Ahmed Dahawy and Choetsow Tenzin
This case examines the challenges and opportunities of doing business in Morocco. The case explores the various historical, cultural, and social factors that impact the business environment. It also highlights Morocco’s unique economy where cash remains a dominant... View Details
- February 21, 2025
- Article
How a Company’s Ownership Model Shapes the Mistakes It Makes
By: Josh Baron
Why do some companies continue to thrive for decades and others die after an initial run of success? Like many kinds of accidents, company failure is generally the consequence of cascading effects that combine to overwhelm a previously effective strategy. But the... View Details
Baron, Josh. "How a Company’s Ownership Model Shapes the Mistakes It Makes." Harvard Business Review Digital Articles (February 21, 2025).
- February 2025
- Tutorial
Preparing Business Leaders for an Era of Climate Instability: Understanding and Managing Physical Climate Risk
By: Michael W. Toffel and Spencer Glendon
In this compelling video, Spencer Glendon, founder of Probable Futures and Executive Fellow at Harvard Business School, describes the profound implications of climate change for businesses, the economy, and societies around the world. Drawing from his background in... View Details
- 2025
- Working Paper
Is Love Blind? AI-Powered Trading with Emotional Dividends
By: De-Rong Kong and Daniel Rabetti
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
Kong, De-Rong, and Daniel Rabetti. "Is Love Blind? AI-Powered Trading with Emotional Dividends." Working Paper, February 2025.
- 2025
- Working Paper
Tax Planning, Illiquidity, and Credit Risks: Evidence from DeFi Lending
By: Lisa De Simone, Peiyi Jin and Daniel Rabetti
This study establishes a plausible causal link between tax-planning-induced illiquidity and credit risks in lending markets. Exploiting an exogenous tax shock imposed by the Internal Revenue Service (IRS) on cryptocurrency gains, along with millions of transactions in... View Details
Keywords: Cryptocurrency; Taxation; Financial Liquidity; Credit; Financing and Loans; Financial Markets
De Simone, Lisa, Peiyi Jin, and Daniel Rabetti. "Tax Planning, Illiquidity, and Credit Risks: Evidence from DeFi Lending." Working Paper, February 2025.
- February 2025
- Supplement
eBee: Affordable Mobility for Africa
By: Ramon Casadesus-Masanell, Gamze Yucaoglu and Jordan Mitchell
The case opens in March 2023, as Sten van der Ham and Jaap Maljers, CEO and co-founder of eBee, an electric bike (e-bike) company in Africa, are contemplating the different avenues for growth and path to profitability for the young and ambitious company. In 2023, the... View Details
- 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.
- 2025
- Working Paper
A Cognitive Theory of Reasoning and Choice
By: Pedro Bordalo, Nicola Gennaioli, Giacomo Lanzani and Andrei Shleifer
We present a theory of decisions in which attention to the features of choice options is determined by the decision maker's categorization of the current choice problem in a set of problems she solved in the past. Categorization depends on goal-relevant as well as... View Details
Bordalo, Pedro, Nicola Gennaioli, Giacomo Lanzani, and Andrei Shleifer. "A Cognitive Theory of Reasoning and Choice." NBER Working Paper Series, No. 33466, February 2025.
- 2025
- Working Paper
Climate Risk and the U.S. Insurance Gap: Measurement, Drivers and Implications
By: Pari Sastry, Therese Scharlemann, Ishita Sen and Ana-Maria Tenekedjieva
Despite rising climate-related property damage, the average American is under-insured. We study the homeowners insurance protection gap using nationwide state-of-the-art insurance, mortgage, and climate databases at a property level and exploiting quasi-exogenous... View Details
Keywords: Climate Change; Risk and Uncertainty; Insurance; Personal Finance; Consumer Behavior; Mortgages
Sastry, Pari, Therese Scharlemann, Ishita Sen, and Ana-Maria Tenekedjieva. "Climate Risk and the U.S. Insurance Gap: Measurement, Drivers and Implications." Harvard Business School Working Paper, No. 25-054, February 2025.
- January–March 2025
- Article
Transitioning from Responsible and Reactive to Deeply Responsible and Proactive International Business
By: Geoffrey G. Jones, Teresa da Silva Lopes, Pavida Pananond, Rob van Tulder, Noemi Sinkovics and Rudolf R. Sinkovics
This article aims to explore the role of multinational enterprises in addressing grand societal challenges, emphasizing the need for integrating environmental and social aspects into business models. It offers an analysis of how principles and values can guide engaged... View Details
Keywords: Corporate Social Responsibility and Impact; Business Model; Multinational Firms and Management
Jones, Geoffrey G., Teresa da Silva Lopes, Pavida Pananond, Rob van Tulder, Noemi Sinkovics, and Rudolf R. Sinkovics. "Transitioning from Responsible and Reactive to Deeply Responsible and Proactive International Business." Critical Perspectives on International Business 21, no. 2 (January–March 2025): 196–225.
- January 2025 (Revised April 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; Business Model; Market Entry and Exit; 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. (Revised April 2025.)
- January 2025
- Technical Note
AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix
By: Tsedal Neeley and Tim Englehart
This technical note introduces the confusion matrix as a foundational tool in artificial intelligence (AI) and large language models (LLMs) for assessing the performance of classification models, focusing on their reliability for decision-making. A confusion matrix... View Details
Keywords: Reliability; Confusion Matrix; AI and Machine Learning; Decision Making; Measurement and Metrics; Performance
Neeley, Tsedal, and Tim Englehart. "AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix." Harvard Business School Technical Note 425-049, January 2025.