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    • All HBS Web  (2,141)
      • Faculty Publications  (294)

      Large Language ModelsRemove Large Language Models →

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      • 2025
      • Working Paper

      New Economic Forces Behind the Value Distribution of Innovation

      By: Timothy F. Bresnahan, Shane Greenstein and Pai-Ling Yin
      Advances in a general-purpose technology (GPT) enable many firms to invent complementary inventions, or co-inventions, making the GPT more valuable. This study examines the empirical implications of a straightforward model in which firms choose either incremental or... View Details
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      Bresnahan, Timothy F., Shane Greenstein, and Pai-Ling Yin. "New Economic Forces Behind the Value Distribution of Innovation." NBER Working Paper Series, No. 34090, August 2025.
      • Article

      Using Gen AI for Early-Stage Market Research

      By: James Brand, Ayelet Israeli and Donald Ngwe
      Generative AI, particularly large language models (LLMs), offers a promising new tool for early-stage market research by simulating customer responses to product concepts. This can allow companies to draw conclusions similar to those they’d obtain by surveying... View Details
      Keywords: Large Language Models; Large Language Model; Generative Ai; Artificial Intelligence; Market Research; Research; Marketing; AI and Machine Learning; Analytics and Data Science; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry
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      Brand, James, Ayelet Israeli, and Donald Ngwe. "Using Gen AI for Early-Stage Market Research." Harvard Business Review (website) (July 18, 2025).
      • 2025
      • Working Paper

      Rethinking Volume

      By: Philippe van der Beck, Lorenzo Bretscher and Zhiyu Julie Fu
      Gross trading volumes in financial markets are large and far exceed return volatility. In contrast, “net volume”—trading from persistent portfolio reallocations—is substantially lower, as it excludes transitory round-trip trades. This observation reveals a fundamental... View Details
      Keywords: Financial Markets; Investment Return; Asset Pricing; Volatility
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      van der Beck, Philippe, Lorenzo Bretscher, and Zhiyu Julie Fu. "Rethinking Volume." Harvard Business School Working Paper, No. 26-003, July 2025.
      • June 2025
      • Case

      From Single Stock to Diversified Portfolio: Mastercard Foundation's $42 Billion Asset Management Launch

      By: Luis M. Viceira and Justin Cohen
      This case examines the decision of the Mastercard Foundation in 2023 to divest its holdings of Mastercard stock, its only asset since inception in 2006 and worth $42 billion in early 2024, and to invest the proceeds in a newly designed diversified portfolio. To this... View Details
      Keywords: Asset Management; Financial Liquidity; Financial Strategy; Investment Portfolio; Corporate Governance; Selection and Staffing; Risk Management; Organizational Culture; Organizational Structure; Motivation and Incentives
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      Viceira, Luis M., and Justin Cohen. "From Single Stock to Diversified Portfolio: Mastercard Foundation's $42 Billion Asset Management Launch." Harvard Business School Case 225-096, June 2025.
      • June 2025
      • Case

      Accounting for OpenAI at Microsoft

      By: Jonas Heese, Joseph Pacelli, Nicole Zelazko and Michael Norris
      In early 2025, Microsoft was evaluating the impact of its $14 billion investment in OpenAI. As OpenAI’s computing needs expanded, Microsoft positioned Azure as the exclusive provider for training and inference of their large language models. Despite the scale of the... View Details
      Keywords: Accounting; Financial Reporting; Revenue Recognition; Corporate Finance; Capital; Investment; Revenue; AI and Machine Learning; Valuation; Governance; Technology Industry; Financial Services Industry; Web Services Industry; Information Technology Industry; United States
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      Heese, Jonas, Joseph Pacelli, Nicole Zelazko, and Michael Norris. "Accounting for OpenAI at Microsoft." Harvard Business School Case 125-118, June 2025.
      • 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
      Keywords: Large Language Model; AI and Machine Learning; Creativity; Innovation Strategy
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      De Freitas, Julian, G. Nave, and Stefano Puntoni. "Ideation with Generative AI—In Consumer Research and Beyond." Journal of Consumer Research 51, no. 1 (June 2025): 18–31.
      • June 2025
      • Article

      Unregulated Emotional Risks of AI Wellness Apps

      By: Julian De Freitas and Glenn Cohen
      We propose that AI-driven wellness apps powered by large language models can foster extreme emotional attachments and dependencies akin to human relationships—posing risks like ambiguous loss and dysfunctional dependence—that challenge current regulatory frameworks and... View Details
      Keywords: AI and Machine Learning; Well-being; Emotions; Governing Rules, Regulations, and Reforms
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      De Freitas, Julian, and Glenn Cohen. "Unregulated Emotional Risks of AI Wellness Apps." Nature Machine Intelligence 7, no. 6 (June 2025): 813–815.
      • 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
      Keywords: Industrial Policy; Global Value Chains; Directed Technological Change; Input-output Linkages; Innovation; Trade; Metals and Minerals; Technological Innovation; Supply Chain; Technology Industry
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      Alfaro, Laura, Harald Fadinger, Jay Schymik, and Gede Virananda. "Trade and Industrial Policy in Supply Chains: Directed Technological Change in Rare Earths." Harvard Business School Working Paper, No. 25-059, May 2025.
      • May 2025 (Revised May 2025)
      • Case

      Humana Commits to Value-Based Care

      By: V.G. Narayanan, Henry Eyring and David Lane
      In late 2023, CEO Bruce Broussard reviewed health insurer Humana’s transformation into a value-based care ecosystem. Under its CenterWell brand, the several millions of members in Humana Medicare Advantage plans now had access to Humana-provided primary care, home... View Details
      Keywords: Business Model; Business Units; Financing and Loans; Innovation Strategy; Growth and Development Strategy; Service Operations; Mergers and Acquisitions; Insurance; Health Care and Treatment; Partners and Partnerships; Health Industry; Insurance Industry; United States
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      Narayanan, V.G., Henry Eyring, and David Lane. "Humana Commits to Value-Based Care." Harvard Business School Case 125-013, May 2025. (Revised May 2025.)
      • May–June 2025
      • Article

      Branch-and-Price for Prescriptive Contagion Analytics

      By: Alexandre Jacquillat, Michael Lingzhi Li, Martin Ramé and Kai Wang
      Contagion models are ubiquitous in epidemiology, social sciences, engineering, and management. This paper formulates a prescriptive contagion analytics model where a decision maker allocates shared resources across multiple segments of a population, each governed by... View Details
      Keywords: COVID-19; Mathematical Methods
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      Jacquillat, Alexandre, Michael Lingzhi Li, Martin Ramé, and Kai Wang. "Branch-and-Price for Prescriptive Contagion Analytics." Operations Research 73, no. 3 (May–June 2025): 1558–1580.
      • 2025
      • Working Paper

      Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha

      By: Mark Bradshaw, Chenyang Ma, Benjamin Yost and Yuan Zou
      We study the use of generative AI for firm-specific financial analysis on the Seeking Alpha platform. We find that, after the initial launch of ChatGPT in November 2022, the share of AI-generated articles rose sharply to 13.4% of all articles, then declined in late... View Details
      Keywords: Generative Ai; Seeking Alpha; Equity Research; Large Language Models; Gpt; AI and Machine Learning; Information Publishing; Financial Markets
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      Bradshaw, Mark, Chenyang Ma, Benjamin Yost, and Yuan Zou. "Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha." Harvard Business School Working Paper, No. 25-055, April 2025.
      • 2025
      • Working Paper

      Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs

      By: Mengjie Cheng, Elie Ofek and Hema Yoganarasimhan
      We study how media firms can use LLMs to generate news content that aligns with multiple objectives—making content more engaging while maintaining a preferred level of polarization/slant consistent with the firm’s editorial policy. Using news articles from The New York... View Details
      Keywords: Large Language Models; Content Creation; Media; Polarization; Generative Ai; Direct Preference Optimization; AI and Machine Learning; News; Perspective; Digital Marketing; Policy; Media and Broadcasting Industry
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      Cheng, Mengjie, Elie Ofek, and Hema Yoganarasimhan. "Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs." Harvard Business School Working Paper, No. 25-051, April 2025.
      • 2025
      • Working Paper

      Extractive Taxation and the French Revolution

      By: Tommaso Giommoni, Gabriel Loumeau and Marco Tabellini
      We study the fiscal determinants of the French Revolution, exploiting plausibly exogenous variation in the salt tax—a large source of royal revenues and one of the most extractive forms of taxation of the Ancien Régime. Implementing a Regression Discontinuity... View Details
      Keywords: Extractive Taxation; Regime Change; French Revolution; State Capacity; Taxation; History; Government Administration; Attitudes; Public Opinion
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      Giommoni, Tommaso, Gabriel Loumeau, and Marco Tabellini. "Extractive Taxation and the French Revolution." Harvard Business School Working Paper, No. 25-047, April 2025. (Featured at VoxEU and HBS Working Knowledge.)
      • 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; Business Model; Technology Industry; United States
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      Srinivasan, Suraj, Michelle Hu, Sriraghav Srinivasan, and Radhika Kak. "Perplexity: Redefining Search." Harvard Business School Case 125-093, March 2025. (Revised April 2025.)
      • 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
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      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
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      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.
      • January 2025
      • Teaching Note

      Vytal: Packaging-as-a-Service

      By: George Serafeim, Michael W. Toffel and Stacy Straaberg
      Teaching Note for HBS Case No. 124-007. The Germany-based startup Vytal operated the largest digital-native reusable packaging-as-a-service network globally, having raised nearly €15 million, established a large network of restaurant partners, and prevented the use of... View Details
      Keywords: Environmental Sustainability; Innovation and Invention; Business Growth and Maturation; Growth and Development Strategy; Business Startups; Resource Allocation; Risk Management; Adoption; Strategy; Performance Productivity; Service Delivery; Service Operations; Supply Chain; Distribution; Entrepreneurship; Climate Change; Business Model; Governing Rules, Regulations, and Reforms; Profit; Financing and Loans; Expansion; Green Technology Industry; Service Industry; Retail Industry; Germany; Europe
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      Serafeim, George, Michael W. Toffel, and Stacy Straaberg. "Vytal: Packaging-as-a-Service." Harvard Business School Teaching Note 125-003, January 2025.
      • January 2025
      • Case

      Redwood & Strong: The Value of a Consulting Engagement

      By: David G. Fubini and Patrick Sanguineti
      The board of Redwood & Strong LLP (R&S), the American branch of a large global law firm, is meeting to review the findings of a recent strategic initiative designed to identify potential merger candidates. The request for the engagement originated from Daniel Crawford,... View Details
      Keywords: Client Service; Professional Service Firm; Professional Services; Consulting; Mergers and Acquisitions; Governing and Advisory Boards; Reports; Strategic Planning; Value; Consulting Industry; Legal Services Industry; United States
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      Fubini, David G., and Patrick Sanguineti. "Redwood & Strong: The Value of a Consulting Engagement." Harvard Business School Case 425-070, January 2025.
      • January–February 2025
      • Article

      The Double-Edged Sword of Exemplar Similarity

      By: Majid Majzoubi, Eric Zhao, Tiona Zuzul and Greg Fisher
      We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and... View Details
      Keywords: Natural Language Processing; Analytics and Data Science; Performance Evaluation
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      Majzoubi, Majid, Eric Zhao, Tiona Zuzul, and Greg Fisher. "The Double-Edged Sword of Exemplar Similarity." Organization Science 36, no. 1 (January–February 2025): 121–144.
      • 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
      Keywords: Large Language Models; AI and Machine Learning; Accounting; Profit; Corporate Disclosure; Analytics and Data Science; Measurement and Metrics
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      Shaffer, Matthew, and Charles CY Wang. "Scaling Core Earnings Measurement with Large Language Models." Working Paper, November 2024.
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