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      • July 2024
      • Article

      Chatbots and Mental Health: Insights into the Safety of Generative AI

      By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
      Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
      Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics
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      De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
      • 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.
      • 2024
      • Working Paper

      Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations

      By: Raviv Murciano-Goroff, Ran Zhuo and Shane Greenstein
      How prevalent are severe software vulnerabilities, how fast do software users respond to the availability of secure versions, and what determines the variance in the installation distribution? Using the largest dataset ever assembled on user updates, tracking server... View Details
      Keywords: Cybersecurity; Applications and Software; Technology Adoption; Consumer Behavior
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      Murciano-Goroff, Raviv, Ran Zhuo, and Shane Greenstein. "Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations." NBER Working Paper Series, No. 32696, July 2024.
      • 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

      Dirk Nowitzki: Changing the Game

      By: Boris Groysberg, Katherine Connolly Baden and Robin Abrahams
      Teaching Note for HBS Case No. 420-031. NBA Superstar Dirk Nowitzki was unsure whether the 2018-19 season would be his last as an NBA player. He had not faced such uncertainty since 1998, when he had navigated a difficult decision regarding the timing of his move to... View Details
      Keywords: Problems and Challenges; Practice; Retirement; Work-Life Balance; Success; Knowledge Acquisition; Knowledge Sharing; Knowledge Use and Leverage; Growth and Development; Philanthropy and Charitable Giving; Performance; Sports Industry; United States
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      Groysberg, Boris, Katherine Connolly Baden, and Robin Abrahams. "Dirk Nowitzki: Changing the Game." Harvard Business School Teaching Note 424-100, June 2024.
      • June 2024 (Revised August 2024)
      • Case

      Revlon India's Turnaround: Navigating Online-Offline Decisions Using a Balanced Scorecard

      By: Tatiana Sandino and Samuel Grad
      Revlon India was founded as a joint venture in 1995, pairing the industrial conglomerate UMG with the global beauty brand Revlon, Inc. to bring international color cosmetics to India. After growing rapidly and pioneering the Beauty Advisor (BA) model in India, the... View Details
      Keywords: Balanced Scorecard; Restructuring; Training; Supply Chain Management; Distribution; E-commerce; Business Model; Business Plan; Decision Choices and Conditions; Marketing Strategy; Alignment; Brands and Branding; Negotiation; Joint Ventures; Strategic Planning; Salesforce Management; Competition; Retail Industry; Consumer Products Industry; Beauty and Cosmetics Industry; India
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      Sandino, Tatiana, and Samuel Grad. "Revlon India's Turnaround: Navigating Online-Offline Decisions Using a Balanced Scorecard." Harvard Business School Case 124-107, June 2024. (Revised August 2024.)
      • July 2024
      • Article

      Mass General Brigham’s Patient-Reported Outcomes Measurement System: A Decade of Learnings

      By: Jason B. Liu, Robert S. Kaplan, David W. Bates, Mario O. Edelen, Rachel C. Sisodia and Andrea L. Pusic
      This article describes the strategies that leaders at the Mass General Brigham (MGB) health system have used in launching a standardized patient-reported outcome measure (PROM) collection program in 2012, a major step in the value-based transformation of health care.... View Details
      Keywords: Patient-reported Outcomes; Value Based Health Care; Health Care and Treatment; Transformation; Outcome or Result; Organizational Change and Adaptation; Performance Improvement; Health Industry
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      Liu, Jason B., Robert S. Kaplan, David W. Bates, Mario O. Edelen, Rachel C. Sisodia, and Andrea L. Pusic. "Mass General Brigham’s Patient-Reported Outcomes Measurement System: A Decade of Learnings." NEJM Catalyst Innovations in Care Delivery 5, no. 7 (July 2024).
      • 2024
      • Working Paper

      Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization

      By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
      This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
      Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
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      Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, 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.
      • June 2024
      • Article

      Rationalizing Outcomes: Interdependent Learning in Competitive Markets

      By: Anoop R. Menon and Dennis Yao
      In this article we use simulation models to explore interdependent learning in competitive markets. Such interactions require attention to both the mental representations held by the management of the focal firm as well as the beliefs of that management about the... View Details
      Keywords: Mental Models; Strategic Interactions; Rationalization; Explanation-based View; Competition
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      Menon, Anoop R., and Dennis Yao. "Rationalizing Outcomes: Interdependent Learning in Competitive Markets." Strategy Science 9, no. 2 (June 2024): 97–117.
      • 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
      • Case

      EPCorp: Sell on Amazon or Invest in Our Data?

      By: Jacob M. Cook
      Amidst a history of exponential growth, Electronic Products Company (EPCorp) finds itself at a crossroads as its once thriving retail presence faces a downturn, despite hefty investments into a promising new direct-to-consumer e-commerce platform. Shivani, EPCorp s... View Details
      Keywords: E-commerce; Technology Adoption; Cost vs Benefits; Organizational Culture; Retail Industry
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      Cook, Jacob M. "EPCorp: Sell on Amazon or Invest in Our Data?" Harvard Business Publishing Case, 2024. (Quick Case.)
      • 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
      • 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–June 2024
      • Article

      Should Your Brand Hire a Virtual Influencer?

      By: Serim Hwang, Shunyuan Zhang, Xiao Liu and Kannan Srinivasan
      Followers respond more favorably to sponsored posts by virtual influencers versus those by humans, costs are lower, and creating an influencer from scratch allows marketers to introduce more diversity. View Details
      Keywords: Social Media; AI and Machine Learning; Brands and Branding; Power and Influence
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      Hwang, Serim, Shunyuan Zhang, Xiao Liu, and Kannan Srinivasan. "Should Your Brand Hire a Virtual Influencer?" Harvard Business Review 102, no. 3 (May–June 2024): 56–60.
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