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    • All HBS Web  (1,155)
      • Faculty Publications  (99)

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      • February 2023
      • Case

      Roblox: Virtual Commerce in the Metaverse

      By: Ayelet Israeli and Nicole Tempest Keller
      In 2022, Roblox had 58.8 million daily active users, including over half of all children and teens under the age of 16 in the United States. Roblox, a free-to-use “co-experience platform”, allowed users to come together in immersive 3D experiences to socialize, work,...  View Details
      Keywords: Entertainment; Games, Gaming, and Gambling; Market Design; Marketing; Brands and Branding; Marketing Channels; Marketing Strategy; Business Strategy; Economics; Economy; Economic Systems; Advertising; Advertising Campaigns; Digital Platforms; Markets; Price; Innovation and Management; Entertainment and Recreation Industry; Video Game Industry; Technology Industry; United States; California; North America; South America; Asia; Europe
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      Israeli, Ayelet, and Nicole Tempest Keller. "Roblox: Virtual Commerce in the Metaverse." Harvard Business School Case 523-028, February 2023.
      • February 2023 (Revised March 2023)
      • Case

      Hey, Insta & YouTube, Are You Watching TikTok?

      By: Felix Oberholzer-Gee
      In early 2023 the entertainment app TikTok reached close to 1 billion users globally, placing it 4th behind the leading social networks of Facebook, YouTube, and Instagram. Featuring a sophisticated recommendation engine, TikTok mastered the art of keeping users...  View Details
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      Oberholzer-Gee, Felix. "Hey, Insta & YouTube, Are You Watching TikTok?" Harvard Business School Case 723-426, February 2023. (Revised March 2023.)
      • January 2023
      • Teaching Note

      Duolingo: Teaching Languages to the Masses

      By: Youngme Moon
      At the time the case is written, Duolingo is the most popular language learning service in the world. The company has more than 40 million monthly active users, and the company’s total annual revenue has reached $250 million a year. Still, the sustainability of the...  View Details
      Keywords: Marketing; Marketing Strategy; Customer Relationship Management; Acquisition; Retention; Innovation and Invention
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      Moon, Youngme. "Duolingo: Teaching Languages to the Masses." Harvard Business School Teaching Note 323-070, January 2023.
      • 2022
      • Article

      OpenXAI: Towards a Transparent Evaluation of Model Explanations

      By: Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik and Himabindu Lakkaraju
      While several types of post hoc explanation methods have been proposed in recent literature, there is very little work on systematically benchmarking these methods. Here, we introduce OpenXAI, a comprehensive and extensible opensource framework for evaluating and...  View Details
      Keywords: Measurement and Metrics; Analytics and Data Science
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      Agarwal, Chirag, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, and Himabindu Lakkaraju. "OpenXAI: Towards a Transparent Evaluation of Model Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • Article

      Why Build in Web3

      By: Jad Esber and Scott Duke Kominers
      A major change is coming to the internet. While today’s dominant platforms have guarded their troves of user data and maintained an advantage through network effects, new companies—working in what they're calling a “Web3” model—are proposing a new value proposition to...  View Details
      Keywords: Blockchain; User Experience; Digital Platforms; Network Effects; Internet and the Web; Competition; Web Services Industry
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      Esber, Jad, and Scott Duke Kominers. "Why Build in Web3." Harvard Business Review Digital Articles (May 16, 2022).
      • May 2022 (Revised July 2022)
      • Case

      The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022

      By: David B. Yoffie and Daniel Fisher
      In 2022, after five years of pursuing a new "AI-first" strategy, Google had captured a sizeable share of the American and global markets for voice assistants. Google Assistant was used by hundreds of millions of users around the world, but Amazon retained the largest...  View Details
      Keywords: Strategy; Artificial Intelligence; Deep Learning; Voice Assistants; Smart Home; Market Share; Globalized Markets and Industries; Competitive Strategy; Digital Platforms; AI and Machine Learning; Technology Industry; United States
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      Yoffie, David B., and Daniel Fisher. "The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022." Harvard Business School Case 722-462, May 2022. (Revised July 2022.)
      • 2022
      • Working Paper

      The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

      By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
      As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how...  View Details
      Keywords: AI and Machine Learning; Analytics and Data Science; Mathematical Methods
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      Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
      • Article

      Pattern Detection in the Activation Space for Identifying Synthesized Content

      By: Celia Cintas, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III and Komminist Weldemariam
      Generative Adversarial Networks (GANs) have recently achieved unprecedented success in photo-realistic image synthesis from low-dimensional random noise. The ability to synthesize high-quality content at a large scale brings potential risks as the generated samples may...  View Details
      Keywords: Subset Scanning; Generative Models; Synthetic Content Detection
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      Cintas, Celia, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III, and Komminist Weldemariam. "Pattern Detection in the Activation Space for Identifying Synthesized Content." Pattern Recognition Letters 153 (January 2022): 207–213.
      • 2022
      • Working Paper

      TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations

      By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
      Practitioners increasingly use machine learning (ML) models, yet they have become more complex and harder to understand. To address this issue, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use explainability...  View Details
      Keywords: Natural Language Conversations; Predictive Models; AI and Machine Learning
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      Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations." Working Paper, 2022.
      • December 2021
      • Article

      Left- and Right-Leaning News Organizations Use Negative Emotional Content and Elicit User Engagement Similarly

      By: Andrea Bellovary, Nathaniel Young and Amit Goldenberg
      Negativity has historically dominated news content; however, little research has examined how news organizations use affect on social media, where content is generally positive. In the current project we ask a few questions: Do news organizations on Twitter use...  View Details
      Keywords: Negative Press; Twitter; Political Affiliation; Affect; News; Media; Internet and the Web; Emotions; Perspective; Social Media
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      Bellovary, Andrea, Nathaniel Young, and Amit Goldenberg. "Left- and Right-Leaning News Organizations Use Negative Emotional Content and Elicit User Engagement Similarly." Affective Science 2, no. 4 (December 2021): 391–396.
      • Article

      Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

      By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
      As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by...  View Details
      Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology
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      Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • November 2021
      • Article

      Ratings, Reviews, and the Marketing of New Products

      By: Itay P. Fainmesser, Dominique Olié Lauga and Elie Ofek
      We study how user-generated content (UGC) about new products impacts a firm's advertising and pricing decisions and the effect on profits and market dynamics. We construct a two-period model where consumers value quality and are heterogeneous in their taste for the new...  View Details
      Keywords: Online Reviews; Product Ratings; Social Networks; Word Of Mouth; Pricing; User-generated Content; Advertising; Product Marketing; Price; Consumer Behavior; Product Positioning; Social Media
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      Fainmesser, Itay P., Dominique Olié Lauga, and Elie Ofek. "Ratings, Reviews, and the Marketing of New Products." Management Science 67, no. 11 (November 2021): 7023–7045.
      • October 2021
      • Case

      (180) Days of Quibi

      By: David J. Collis and Terrence Shu
      Mobile streaming app Quibi was ready to take the entertainment world by storm at its April 2020 launch. Backed by $1.75 billion, influential investors from Hollywood to Wall Street eagerly anticipated early success for this brainchild of Meg Whitman, former CEO of...  View Details
      Keywords: Corporate Strategy; Strategy; Business Model; Business Startups; Mobile Technology
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      Collis, David J., and Terrence Shu. "(180) Days of Quibi." Harvard Business School Case 722-377, October 2021.
      • October 2021
      • Article

      Can Self-Regulation Save Digital Platforms?

      By: Michael A. Cusumano, Annabelle Gawer and David B. Yoffie
      This article explores some of the critical challenges facing self-regulation and the regulatory environment for digital platforms. We examine several historical examples of firms and industries that attempted self-regulation before the Internet. All dealt with similar...  View Details
      Keywords: Self-regulation; Government Regulation; Digital Platforms; Governing Rules, Regulations, and Reforms
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      Cusumano, Michael A., Annabelle Gawer, and David B. Yoffie. "Can Self-Regulation Save Digital Platforms?" Industrial and Corporate Change 30, no. 5 (October 2021): 1259–1285.
      • 2021
      • Working Paper

      The Value of Data and Its Impact on Competition

      By: Marco Iansiti
      Common regulatory perspective on the relationship between data, value, and competition in online platforms has increasingly centered on the volume of data accumulated by incumbent firms. This view posits the existence of "data network effects," where more data leads to...  View Details
      Keywords: Online Platforms; Data Network Effects; Analytics and Data Science; Value; Competition; Digital Platforms
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      Iansiti, Marco. "The Value of Data and Its Impact on Competition." Harvard Business School Working Paper, No. 22-002, July 2021.
      • Article

      Biosimilars and Follow-On Products in the United States: Adoption, Prices, and Users

      By: Ariel Dora Stern, Jacqueline L. Chen, Melissa Ouellet, Mark R. Trusheim, Zeid El-Kilani, Amber Jessup and Ernst R. Berndt
      Biologic drugs account for a disproportionate share of the increase in pharmaceutical spending in the U.S. and worldwide. Against this backdrop, many look to the expanding market for biosimilars—follow-on products to biologic drugs—as a vehicle for controlling...  View Details
      Keywords: Pharmaceuticals; Drug Spending; Drug Pricing; Health Care and Treatment; Spending; Price; Markets; Cost Management; United States
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      Stern, Ariel Dora, Jacqueline L. Chen, Melissa Ouellet, Mark R. Trusheim, Zeid El-Kilani, Amber Jessup, and Ernst R. Berndt. "Biosimilars and Follow-On Products in the United States: Adoption, Prices, and Users." Health Affairs 40, no. 6 (June 2021): 989–999.
      • May–June 2021
      • Article

      Capturing Value in Platform Business Models that Rely on User-Generated Content

      By: Hemang Subramanian, Sabyasachi Mitra and Sam Ransbotham
      Business models increasingly depend on inputs from outside traditional organizational boundaries. For example, platforms that generate revenue from advertising, subscription, or referral fees often rely on user-generated content (UGC). But there is considerable...  View Details
      Keywords: Business Model; Network Effects; Mergers and Acquisitions; Valuation; Risk and Uncertainty
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      Subramanian, Hemang, Sabyasachi Mitra, and Sam Ransbotham. "Capturing Value in Platform Business Models that Rely on User-Generated Content." Organization Science 32, no. 3 (May–June 2021): 804–823.
      • May 2021
      • Article

      Ideology and Composition Among an Online Crowd: Evidence From Wikipedians

      By: Shane Greenstein, Grace Gu and Feng Zhu
      Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that...  View Details
      Keywords: User Segregation; Online Community; Contested Knowledge; Collective Intelligence; Ideology; Bias; Wikipedia; Knowledge Sharing; Perspective; Government and Politics
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      Greenstein, Shane, Grace Gu, and Feng Zhu. "Ideology and Composition Among an Online Crowd: Evidence From Wikipedians." Management Science 67, no. 5 (May 2021): 3067–3086.
      • May 2021
      • Article

      Making Doctors Effective Managers and Leaders: A Matter of Health and Well-Being

      By: Lisa Rotenstein, Robert S. Huckman and Christine K. Cassel
      The COVID-19 crisis has forced physicians to make daily decisions that require knowledge and skills they did not acquire as part of their biomedical training. Physicians are being called upon to be both managers—able to set processes and structures—and leaders—capable...  View Details
      Keywords: Health Care and Treatment; Management; Leadership; Health Pandemics; Health Industry
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      Rotenstein, Lisa, Robert S. Huckman, and Christine K. Cassel. "Making Doctors Effective Managers and Leaders: A Matter of Health and Well-Being." Academic Medicine 96, no. 5 (May 2021).
      • 2021
      • Article

      Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring

      By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju
      Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the...  View Details
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      Sühr, Tom, Sophie Hilgard, and Himabindu Lakkaraju. "Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 4th (2021).
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