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Publications

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      • Faculty Publications  (104)

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      • April 2025
      • Case

      Techint: Strategic Choices for Community Impact

      By: Lauren Cohen, Virak Prum, Kenneth Charman, Pedro Levindo and Mariana Cal
      In early 2024 Erika Bienek, Chief Community Relations Officer at Techint, had to decide whether to invest in a new company-owned and operated technical school in Veracruz, Mexico, or invest instead in strengthening the city’s public education system. Techint, a global... View Details
      Keywords: Technical Institutes; Community Relations; Social Impact; Argentina; Mexico; Brazil; Conglomerate; Stakeholder Management; Government And Business; Community Impact; Philanthropy; Business Conglomerates; Business Subsidiaries; Business Headquarters; Family Business; Decision Making; Private Sector; Public Sector; Education; Curriculum and Courses; Middle School Education; Secondary Education; Teaching; Training; Learning; Energy; Engineering; Construction; Values and Beliefs; Geography; Global Range; Local Range; Cross-Cultural and Cross-Border Issues; Globalized Firms and Management; Government Legislation; Recruitment; Innovation and Invention; Disruptive Innovation; Knowledge; Resource Allocation; Industry Clusters; Infrastructure; Family Ownership; Philanthropy and Charitable Giving; Business and Community Relations; Business and Stakeholder Relations; Business and Government Relations; Creativity; Reputation; Social and Collaborative Networks; Civil Society or Community; Social Issues; Poverty; Strategy; Construction Industry; Education Industry; Energy Industry; Industrial Products Industry; Manufacturing Industry; Steel Industry; Europe; Italy; Latin America; North and Central America; Mexico; North America; United States; South America; Argentina; Buenos Aires; Brazil
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      Cohen, Lauren, Virak Prum, Kenneth Charman, Pedro Levindo, and Mariana Cal. "Techint: Strategic Choices for Community Impact." Harvard Business School Case 825-058, 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
      • Case

      Index and Active Investing: Vanguard and the New Frontier of Active ETFs

      By: Marco Sammon, Luis M. Viceira and Jonathan Kanagasabai
      This case explores Vanguard’s strategic decision-making process as it considers entering the growing market for actively managed exchange-traded funds (ETFs). Set in 2024, the case places students in the position of Rodney Comegys, Vanguard’s global head of the Equity... View Details
      Keywords: Asset Management; Financial Strategy; Investment Funds; Investment Portfolio; Financial Services Industry
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      Sammon, Marco, Luis M. Viceira, and Jonathan Kanagasabai. "Index and Active Investing: Vanguard and the New Frontier of Active ETFs." Harvard Business School Case 225-056, January 2025.
      • 2025
      • Working Paper

      Generative AI and the Nature of Work

      By: Manuel Hoffmann, Sam Boysel, Frank Nagle, Sida Peng and Kevin Xu
      Recent advances in artificial intelligence (AI) technology demonstrate a considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid... View Details
      Keywords: Generative Ai; Digital Work; Open Source Software; Knowledge Economy; AI and Machine Learning; Open Source Distribution; Organizational Structure; Performance Productivity; Labor
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      Hoffmann, Manuel, Sam Boysel, Frank Nagle, Sida Peng, and Kevin Xu. "Generative AI and the Nature of Work." Harvard Business School Working Paper, No. 25-021, October 2024. (Revised April 2025.)
      • 2025
      • Working Paper

      Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships

      By: Julian De Freitas, Noah Castelo, Ahmet K. Uğuralp and Zeliha O. Uğuralp
      As consumers increasingly interact with AI applications specialized for social relationships, what is the nature and depth of these relationships among actual users, and can company actions influence these dynamics? We find that active users of the US-based AI... View Details
      Keywords: AI and Machine Learning; Welfare; Loss; Well-being; Identity; Perception; Relationships
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      De Freitas, Julian, Noah Castelo, Ahmet K. Uğuralp, and Zeliha O. Uğuralp. "Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships." Harvard Business School Working Paper, No. 25-018, October 2024. (Revised May 2025.)
      • September–October 2024
      • Article

      How AI Can Power Brand Management

      By: Julian De Freitas and Elie Ofek
      Marketers have begun experimenting with AI to improve their brand-management efforts. But unlike other marketing tasks, brand management involves more than just repeatedly executing one specialized function. Long considered the exclusive domain of creative talent, it... View Details
      Keywords: Creativity; AI and Machine Learning; Brands and Branding; Product Positioning; Customer Focus and Relationships
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      De Freitas, Julian, and Elie Ofek. "How AI Can Power Brand Management." Harvard Business Review 102, no. 5 (September–October 2024): 108–114.
      • 2024
      • Working Paper

      AI Companions Reduce Loneliness

      By: Julian De Freitas, Ahmet K. Uğuralp, Zeliha O. Uğuralp and Stefano Puntoni
      Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details
      Keywords: AI and Machine Learning; Technological Innovation; Behavior; Well-being
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      De Freitas, Julian, Ahmet K. Uğuralp, Zeliha O. Uğuralp, and Stefano Puntoni. "AI Companions Reduce Loneliness." Harvard Business School Working Paper, No. 24-078, June 2024.
      • May 2024
      • Teaching Note

      AI Wars

      By: Andy Wu and Matt Higgins
      Teaching Note for HBS Case No. 723-434. In 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI popularized over... View Details
      Keywords: AI; Trends; AI and Machine Learning; Public Opinion; Technological Innovation; Competitive Advantage; Technology Industry
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      Wu, Andy, and Matt Higgins. "AI Wars." Harvard Business School Teaching Note 724-482, May 2024.
      • May 2024
      • Article

      Financial Innovation in the 21st Century: Evidence from U.S. Patents

      By: Josh Lerner, Amit Seru, Nick Short and Yuan Sun
      We develop a unique dataset of 24 thousand U.S. finance patents granted over the last two decades to explore the evolution and production of financial innovation. We use machine learning to identify the financial patents and extensively audit the results to ensure... View Details
      Keywords: Banking; Investment Banks; Information Technology; Regulation; Patents; Innovation and Invention; Trends
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      Lerner, Josh, Amit Seru, Nick Short, and Yuan Sun. "Financial Innovation in the 21st Century: Evidence from U.S. Patents." Journal of Political Economy 132, no. 5 (May 2024): 1391–1449.
      • April 2024
      • Article

      Detecting Routines: Applications to Ridesharing CRM

      By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
      Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
      Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
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      Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
      • 2024
      • Working Paper

      Platform Information Provision and Consumer Search: A Field Experiment

      By: Lu Fang, Yanyou Chen, Chiara Farronato, Zhe Yuan and Yitong Wang
      Despite substantial efforts to help consumers search in more intuitive ways, text search remains the predominant tool for product discovery online. In this paper, we explore the effects of visual and textual cues for search refinement on consumer search and purchasing... View Details
      Keywords: Consumer Behavior; E-commerce; Decision Choices and Conditions; Learning; Internet and the Web
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      Fang, Lu, Yanyou Chen, Chiara Farronato, Zhe Yuan, and Yitong Wang. "Platform Information Provision and Consumer Search: A Field Experiment." NBER Working Paper Series, No. 32099, February 2024.
      • November 2023
      • Case

      Open Source Machine Learning at Google

      By: Shane Greenstein, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue and James Barnett
      Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts... View Details
      Keywords: Decision Choices and Conditions; Technological Innovation; Open Source Distribution; Strategy; AI and Machine Learning; Applications and Software; Technology Industry; United States
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      Greenstein, Shane, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue, and James Barnett. "Open Source Machine Learning at Google." Harvard Business School Case 624-015, November 2023.
      • 2023
      • Working Paper

      Learning by Investing: Entrepreneurial Spillovers from Venture Capital

      By: Josh Lerner, Jinlin Li and Tong Liu
      This paper studies how investing in venture capital (VC) affects the entrepreneurial outcomes of individual limited partners (LPs). Using comprehensive administrative data on entrepreneurial activities and VC fundraising and investments in China, we first document that... View Details
      Keywords: Partners and Partnerships; Entrepreneurship; Venture Capital; Investment; China
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      Lerner, Josh, Jinlin Li, and Tong Liu. "Learning by Investing: Entrepreneurial Spillovers from Venture Capital." Harvard Business School Working Paper, No. 24-029, November 2023.
      • November 2023
      • Case

      Apple Inc. in 2023

      By: David B. Yoffie and Sarah von Bargen
      Under CEO Tim Cook, Apple became the first trillion dollar market cap company, the first two trillion dollar company, and the first three trillion dollar company. Since the COVID pandemic, Apple gained over 20% of the world smartphone market and 50% of the U.S. market,... View Details
      Keywords: Competitive Advantage; Product Positioning; Emerging Markets; Competitive Strategy; Technological Innovation; Revenue; Technology Industry
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      Yoffie, David B., and Sarah von Bargen. "Apple Inc. in 2023." Harvard Business School Case 724-419, November 2023.
      • 2023
      • Working Paper

      Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality

      By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
      The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine... View Details
      Keywords: Large Language Model; AI and Machine Learning; Performance Efficiency; Performance Improvement
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      Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
      • September 2023
      • Article

      The Dynamics of Team Learning: Harmony and Rhythm in Teamwork Arrangements for Innovation

      By: Jean-François Harvey, Johnathan R. Cromwell, Kevin J. Johnson and Amy C. Edmondson
      Innovation teams must navigate inherent tensions between different learning activities to produce high levels of performance. Yet, we know little about how teams combine these activities—notably reflexive, experimental, vicarious, and contextual learning—most... View Details
      Keywords: Groups and Teams; Learning; Performance Effectiveness; Collaborative Innovation and Invention
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      Harvey, Jean-François, Johnathan R. Cromwell, Kevin J. Johnson, and Amy C. Edmondson. "The Dynamics of Team Learning: Harmony and Rhythm in Teamwork Arrangements for Innovation." Administrative Science Quarterly 68, no. 3 (September 2023): 601–647.
      • 2023
      • Working Paper

      Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate

      By: Mengxia Zhang and Isamar Troncoso
      3D virtual tours (VTs) have become a popular digital tool in real estate platforms, enabling potential buyers to virtually walk through the houses they search for online. In this paper, we study home sellers’ adoption of VTs and the VTs’ relative benefits compared to... View Details
      Keywords: Marketing; AI and Machine Learning; Technology Adoption; Real Estate Industry
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      Zhang, Mengxia, and Isamar Troncoso. "Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate." Harvard Business School Working Paper, No. 24-003, July 2023.
      • 2023
      • Working Paper

      Learning to Use: Stack Overflow and Technology Adoption

      By: Daniel Jay Brown and Maria P. Roche
      In this paper, we examine the potential impact of Q&A websites on the adoption of technologies. Using data from Stack Overflow – one of the most popular Q&A websites worldwide – and implementing an instrumental-variable approach, we find that users whose questions... View Details
      Keywords: Technology Adoption; Knowledge Sharing
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      Brown, Daniel Jay, and Maria P. Roche. "Learning to Use: Stack Overflow and Technology Adoption." Harvard Business School Working Paper, No. 24-001, July 2023.
      • April 2023 (Revised February 2024)
      • Case

      AI Wars

      By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
      In February 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI. Over a year ago, OpenAI released ChatGPT, a... View Details
      Keywords: AI; Artificial Intelligence; AI and Machine Learning; Technology Adoption; Competitive Strategy; Technological Innovation
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      Wu, Andy, Matt Higgins, Miaomiao Zhang, and Hang Jiang. "AI Wars." Harvard Business School Case 723-434, April 2023. (Revised February 2024.)
      • March–April 2023
      • Article

      Pricing for Heterogeneous Products: Analytics for Ticket Reselling

      By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
      Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
      Keywords: Price; Demand and Consumers; AI and Machine Learning; Investment Return; Entertainment and Recreation Industry; Sports Industry
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      Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
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