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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,...
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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
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?
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...
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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...
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- 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...
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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...
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Keywords:
Blockchain;
User Experience;
Digital Platforms;
Network Effects;
Internet and the Web;
Competition;
Web Services Industry
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...
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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
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...
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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...
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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...
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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...
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Keywords:
Negative Press;
Twitter;
Political Affiliation;
Affect;
News;
Media;
Internet and the Web;
Emotions;
Perspective;
Social Media
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...
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Keywords:
Black Box Explanations;
Bayesian Modeling;
Decision Making;
Risk and Uncertainty;
Information Technology
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...
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Keywords:
Online Reviews;
Product Ratings;
Social Networks;
Word Of Mouth;
Pricing;
User-generated Content;
Advertising;
Product Marketing;
Price;
Consumer Behavior;
Product Positioning;
Social Media
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...
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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...
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Keywords:
Self-regulation;
Government Regulation;
Digital Platforms;
Governing Rules, Regulations, and Reforms
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...
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Keywords:
Online Platforms;
Data Network Effects;
Analytics and Data Science;
Value;
Competition;
Digital Platforms
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...
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Keywords:
Pharmaceuticals;
Drug Spending;
Drug Pricing;
Health Care and Treatment;
Spending;
Price;
Markets;
Cost Management;
United States
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...
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Keywords:
Business Model;
Network Effects;
Mergers and Acquisitions;
Valuation;
Risk and Uncertainty
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...
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Keywords:
User Segregation;
Online Community;
Contested Knowledge;
Collective Intelligence;
Ideology;
Bias;
Wikipedia;
Knowledge Sharing;
Perspective;
Government and Politics
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...
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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...
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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).