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      • July–August 2024
      • Article

      Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals

      By: Ta-Wei Huang and Eva Ascarza
      Firms are increasingly interested in developing targeted interventions for customers with the best response, which requires identifying differences in customer sensitivity, typically through the conditional average treatment effect (CATE) estimation. In theory, to... View Details
      Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
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      Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
      • July 2024
      • Article

      How Artificial Intelligence Constrains Human Experience

      By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
      Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
      Keywords: Large Language Model; User Experience; AI and Machine Learning; Consumer Behavior; Technology Adoption; Risk and Uncertainty; Cost vs Benefits
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      Valenzuela, A., S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino, and K. Wertenbroch. "How Artificial Intelligence Constrains Human Experience." Journal of the Association for Consumer Research 9, no. 3 (July 2024): 241–256.
      • July 2024
      • Case

      Replika AI: Alleviating Loneliness (A)

      By: Shikhar Ghosh and Shweta Bagai
      Eugenia Kuyda launched Replika AI in 2017 as an empathetic digital companion to combat loneliness and provide emotional support. The platform surged in popularity during the COVID-19 pandemic, offering non-judgmental support to isolated users. By 2023, Replika boasted... View Details
      Keywords: Entrepreneurship; Ethics; Health Pandemics; AI and Machine Learning; Well-being; Technology Industry
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      Ghosh, Shikhar, and Shweta Bagai. "Replika AI: Alleviating Loneliness (A)." Harvard Business School Case 824-088, July 2024.
      • June 2024
      • Teaching Note

      Numenta in 2020: The Future of AI

      By: David B. Yoffie
      In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This teaching note explores the challenges of building a... View Details
      Keywords: Artificial Intelligence; Monetization; Strategy; Intellectual Property; AI and Machine Learning; Business Model; Entrepreneurship; Technology Industry
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      Yoffie, David B. "Numenta in 2020: The Future of AI." Harvard Business School Teaching Note 724-496, June 2024.
      • June 2024 (Revised September 2024)
      • Case

      Driving Scale with Otto

      By: Rebecca Karp, David Allen and Annelena Lobb
      This case asks how startup founders make scaling decisions in light of their priorities for their business and for themselves. Otto was a technology company that applied artificial intelligence technology to sales. It deployed natural language processing to find sales... View Details
      Keywords: Artificial Intelligence; Natural Language Processing; B2B; B2B Innovation; Scaling; Scaling Tech Ventures; Business Startups; AI and Machine Learning; Finance; Sales; Business Strategy; Growth and Development Strategy; Entrepreneurship; Information Technology Industry; United States; Cambridge; New York (city, NY); Spain
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      Karp, Rebecca, David Allen, and Annelena Lobb. "Driving Scale with Otto." Harvard Business School Case 724-407, June 2024. (Revised September 2024.)
      • 2024
      • Working Paper

      Advancing Personalization: How to Experiment, Learn & Optimize

      By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
      Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details
      Keywords: Personalization; Targeting; Experiments; Observational Studies; Policy Implementation; Policy Evaluation; Customization and Personalization; Marketing Strategy; AI and Machine Learning
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      Lemmens, Aurelie, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela, and Oded Netzer. "Advancing Personalization: How to Experiment, Learn & Optimize." Working Paper, July 2024. (Revised March 2025.)
      • June 2024
      • Article

      Defining Who You Are by Whom You Serve? Strategies for Prosocial–Professional Identity Integration with Clients

      By: Lakshmi Ramarajan and Julie Yen
      Many professionals want to both achieve professional success and contribute to society. Yet, in some professional contexts, these aims are in tension because serving elite clients is considered the pinnacle of professional success, but professionals themselves may view... View Details
      Keywords: Identity; Experience and Expertise; Corporate Social Responsibility and Impact; Behavior; Social Entrepreneurship
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      Ramarajan, Lakshmi, and Julie Yen. "Defining Who You Are by Whom You Serve? Strategies for Prosocial–Professional Identity Integration with Clients." Administrative Science Quarterly 69, no. 2 (June 2024): 515–567.
      • 2024
      • Working Paper

      Health, Human Capital Development and the Longevity of Japanese Elites Since 710

      By: Tom Nicholas and Hiroshi Shimizu
      We examine the lifespan of over 40,000 elites in Japan born between 710 and 1912, including samurai warriors, feudal lords, business, political, cultural, and religious leaders at the apex of the social hierarchy. Japanese elites experienced increases in lifespan about... View Details
      Keywords: Life Expectancy; Status and Position; Health; History; Human Capital; Japan
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      Nicholas, Tom, and Hiroshi Shimizu. "Health, Human Capital Development and the Longevity of Japanese Elites Since 710." Working Paper, June 2024.
      • June 2024
      • Article

      Oral History and Business History in Emerging Markets

      By: Geoffrey Jones
      This article describes the motivation, structure and use of the Creating Emerging Markets (CEM) oral history-based project at the Harvard Business School. The project consists of lengthy interviews with business leaders from emerging markets. By June 2024 183... View Details
      Keywords: Emerging Economies; Oral History; Emerging Markets; Business History; Research
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      Jones, Geoffrey. "Oral History and Business History in Emerging Markets." Investigaciones de historia económica 20, no. 2 (June 2024): 1–4.
      • Summer 2024
      • Article

      The Business Revolution: Economy-Wide Impacts of Artificial Intelligence and Digital Platforms

      By: Hanna Halaburda, Jeffrey Prince, D. Daniel Sokol and Feng Zhu
      In this essay, we identify several themes of the digital business transformation, with a particular focus on the economy-wide impacts of artificial intelligence and digital platforms. In doing so, we highlight specific industries, beyond just the high-profile “Big... View Details
      Keywords: Digital Transformation; Digital Platforms; AI and Machine Learning
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      Halaburda, Hanna, Jeffrey Prince, D. Daniel Sokol, and Feng Zhu. "The Business Revolution: Economy-Wide Impacts of Artificial Intelligence and Digital Platforms." Journal of Economics & Management Strategy 33, no. 2 (Summer 2024): 269–275.
      • 2024
      • Working Paper

      The Value of AI Innovations

      By: Wilbur Xinyuan Chen, Terrence Tianshuo Shi and Suraj Srinivasan
      We study the value of AI innovations as it diffuses across general and application sectors, using the United States Patent and Trademark Office’s (USPTO) AI patent dataset. Investors value these innovations more than others, as AI patents exhibit a 9% value premium,... View Details
      Keywords: AI and Machine Learning; Valuation; Technological Innovation; Open Source Distribution; Patents; Policy; Knowledge Sharing; Technology Industry
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      Chen, Wilbur Xinyuan, Terrence Tianshuo Shi, and Suraj Srinivasan. "The Value of AI Innovations." Harvard Business School Working Paper, No. 24-069, May 2024.
      • May 2024
      • Case

      Pernod Ricard: Uncorking Digital Transformation

      By: Iavor Bojinov, Edward McFowland III, François Candelon, Nikolina Jonsson and Emer Moloney
      This case study explores the opportunities and challenges of the digital transformation journey of French wine and spirits company Pernod Ricard. As part of the transformation, the company launched four key digital programs (KDPs) aimed at using data and artificial... View Details
      Keywords: Business Organization; Business Divisions; Talent and Talent Management; Global Strategy; AI and Machine Learning; Analytics and Data Science; Digital Transformation; Digital Strategy; Advertising; Sales; Organizational Culture; Product Development; Decision Making; Technology Adoption; Alignment; Expansion; Food and Beverage Industry; France; Europe
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      Bojinov, Iavor, Edward McFowland III, François Candelon, Nikolina Jonsson, and Emer Moloney. "Pernod Ricard: Uncorking Digital Transformation." Harvard Business School Case 624-095, May 2024.
      • May 2024
      • Supplement

      HubSpot and Motion AI (B): Generative AI Opportunities

      By: Jill Avery
      The technologies driving artificial intelligence (AI) had progressed significantly since HubSpot’s acquisition of Motion AI in 2017. Generative AI was the newest major development. Software-as-a-service (SaaS) companies such as HubSpot were analyzing how generative AI... View Details
      Keywords: Artificial Intelligence; CRM; Chatbots; Sales Management; Generative Ai; SaaS; Marketing; Sales; AI and Machine Learning; Customer Relationship Management; Applications and Software; Technological Innovation; Competitive Advantage; Technology Industry; United States
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      Avery, Jill. "HubSpot and Motion AI (B): Generative AI Opportunities." Harvard Business School Supplement 524-088, May 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
      • Teaching Note

      AI21 Labs in 2023: Strategy for Generative AI

      By: David Yoffie
      Teaching Note for HBS Case 724-383. The case has 3 important teaching purposes: First, what are the advantages and disadvantages of imitation? (e.g., Should AI21 imitate OpenAI with a chatbot?) Second, what are the advantages and disadvantages of keeping new technology... View Details
      Keywords: AI; Generative Ai; Generative Models; AI and Machine Learning; Innovation Strategy; Growth and Development Strategy; Business Model; Business Startups; Open Source Distribution; Competitive Advantage; Technology Industry; Israel
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      Yoffie, David. "AI21 Labs in 2023: Strategy for Generative AI." Harvard Business School Teaching Note 724-461, 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.
      • 2024
      • Working Paper

      Old Moats for New Models: Openness, Control, and Competition in Generative AI

      By: Pierre Azoulay, Joshua L. Krieger and Abhishek Nagaraj
      Drawing insights from the field of innovation economics, we discuss the likely competitive environment shaping generative AI advances. Central to our analysis are the concepts of appropriability—whether firms in the industry are able to control the knowledge generated... View Details
      Keywords: Technological Innovation; AI and Machine Learning; Open Source Distribution; Policy
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      Azoulay, Pierre, Joshua L. Krieger, and Abhishek Nagaraj. "Old Moats for New Models: Openness, Control, and Competition in Generative AI." NBER Working Paper Series, No. 7442, May 2024.
      • May 2024
      • Article

      Relational Attributions for One’s Own Resilience Predict Compassion for Others

      By: Rachel Ruttan, Ting Zhang, Sivahn Barli and Katherine DeCelles
      Existing work on attribution theory distinguishes between external and internal attributions (i.e., “I overcame adversity due to luck” vs. “my own effort”). We introduce the construct of relational resilience attributions (i.e., “due to help from other people”) as a... View Details
      Keywords: Personal Characteristics; Forecasting and Prediction; Attitudes; Behavior
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      Ruttan, Rachel, Ting Zhang, Sivahn Barli, and Katherine DeCelles. "Relational Attributions for One’s Own Resilience Predict Compassion for Others." Journal of Personality and Social Psychology 126, no. 5 (May 2024): 818–840.
      • May 2024
      • Article

      The Health Risks of Generative AI-Based Wellness Apps

      By: Julian De Freitas and G. Cohen
      Artifcial intelligence (AI)-enabled chatbots are increasingly being used to help people manage their mental health. Chatbots for mental health and particularly ‘wellness’ applications currently exist in a regulatory ‘gray area’. Indeed, most generative AI-powered... View Details
      Keywords: AI and Machine Learning; Well-being; Governing Rules, Regulations, and Reforms; Applications and Software
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      De Freitas, Julian, and G. Cohen. "The Health Risks of Generative AI-Based Wellness Apps." Nature Medicine 30, no. 5 (May 2024): 1269–1275.
      • 2024
      • Working Paper

      What Is Newsworthy? Theory and Evidence

      By: Luis Armona, Matthew Gentzkow, Emir Kamenica and Jesse M. Shapiro
      We study newsworthiness in theory and practice. We focus on situations in which a news outlet observes the realization of a state of the world and must decide whether to report the realization to a consumer who pays an opportunity cost to consume the report. The... View Details
      Keywords: News; Mathematical Methods; Prejudice and Bias; Media and Broadcasting Industry
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      Armona, Luis, Matthew Gentzkow, Emir Kamenica, and Jesse M. Shapiro. "What Is Newsworthy? Theory and Evidence." NBER Working Paper Series, No. 32512, May 2024.
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