Publications
Publications
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- All HBS Web
(5,546)
- Faculty Publications (1,087)
- January 2023
- Supplement
Apple: Privacy vs. Safety (B)
By: Henry McGee, Nien-hê Hsieh and Christian Godwin
In 2020, as the COVID-19 pandemic swept across the globe, Apple and Google partnered to develop a contact tracing application that would collect information about users infected with the disease and notify those who they had been in contact with. While Apple/Google’s... View Details
Keywords: Iphone; Encryption; Data Privacy; Customers; Customer Focus and Relationships; Decision Making; Ethics; Values and Beliefs; Globalized Firms and Management; Government and Politics; Health; Health Pandemics; Leadership; Markets; Safety; Social Issues; Information Technology; Telecommunications Industry; Technology Industry; Consumer Products Industry; Electronics Industry; Health Industry; United States; Europe
- January 2023 (Revised June 2023)
- Case
Replika: Embodying AI
By: Shikhar Ghosh, Shweta Bagai and Marilyn Morgan Westner
Replika was a virtual AI companion that provided a way for people to process their emotions, build connections in a safe environment, and get through periods of loneliness. The chatbot fulfilled a user's need for a friend, romantic partner, or purely an emotional... View Details
- January 2023 (Revised August 2023)
- Case
Veeva Systems and the Transformation to a Public Benefit Corporation
By: Ranjay Gulati and Allison M. Ciechanover
Peter Gassner, the co-founder and CEO of Veeva Systems, steered the company through rapid scaling from its launch in 2007 to 2022. Year after year, the company had exceeded expectations, with its market capitalization reaching $50 billion at its peak. By 2022, the... View Details
- January 2023
- Case
Proday: Calling the Right Play
By: Lindsay N. Hyde, Thomas R. Eisenmann and Tom Quinn
Sarah Kunst knew the elements of a successful startup from her tenure at venture capital firms. In April 2018, however, her own app – Proday, a home fitness platform featuring exercises filmed by professional sports stars – was floundering. Kunst theorized that... View Details
- 2 Mar 2023 - 4 Mar 2023
- Conference Presentation
Ethical Risks of Autonomous Products: The Case of Mental Health Crises on AI Companion Applications
By: Julian De Freitas, K. Uguralp and Z. Oguz
- 2023
- Article
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
- 2 Mar 2023 - 4 Mar 2023
- Conference Presentation
Stigma Against AI Companion Applications
By: Julian De Freitas, A. Ragnhildstveit, K. Uguralp and Z. Oguz
- December 2022 (Revised September 2024)
- Case
Sword Health
By: Regina E. Herzlinger, Annelena Lobb and Carin-Isabel Knoop
Virgilio “V” Bento, CEO of Sword Health—a startup that provided virtual physical therapy to patients in self-insured firms via AI and sensor technology with supervision by a physical therapist with a doctorate—considered how to increase its U.S. market share. To do so,... View Details
- December 2022 (Revised February 2023)
- Case
Akooda: Charging Toward Operational Intelligence
By: Christopher T. Stanton and Mel Martin
The Akooda case describes the challenges confronting founder and CEO Yuval Gonczarowski (MBA ‘17) in 2022 as he attempts to boost sales. Launched in November 2020, Akooda was an AI company that mined 20 different sources of digital data, from tools like Slack, Google... View Details
- Working Paper
Diversification as an Adaptive Learning Process: An Empirical Study of General-Purpose and Market-Specific Technological Know-How in New Market Entry
By: Dominika Kinga Randle and Gary P. Pisano
An enduring trait of modern corporations is their propensity to diversify into multiple lines of business. Penrosian theories conceptualize diversification as a strategy to exploit a firm’s fungible, yet “untradeable,” resources and point to redeployment of... View Details
- 2023
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial
intelligence and machine learning business applications. Although prior discussions
highlight advances in methods (along the dimensions of data, computing power, and
algorithms)... View Details
Keywords: Analytics and Data Science
- December 2022 (Revised August 2023)
- Case
Circles.Life at a Crossroads of Growth
By: Juan Alcácer and Adina Wong
In June 2022, the founders of Singapore mobile operator Circles.Life had a crucial decision to make. Circles.Life developed a new business model in mobile telecommunications—a digital telco—built around its proprietary operating system. After expanding its brand in... View Details
- 2022
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
We empirically analyze how managerial overrides to a commercial algorithm that forecasts demand and schedules labor affect store performance. We analyze administrative data from a large grocery retailer that utilizes a commercial algorithm to forecast demand and... View Details
- 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
- November 2022 (Revised March 2024)
- Case
Replika AI: Monetizing a Chatbot
By: Julian De Freitas and Nicole Tempest Keller
In early 2018, Eugenia Kuyda, co-founder and CEO of San Francisco-based chatbot Replika AI, was deciding how to monetize the app she had built. Launched in 2017, Replika was a consumer AI “companion app” developed by a team of AI software engineers originally based in... View Details
- November 2022
- Case
Para: Pay Transparency and Gig Drivers' Rights
By: Christopher Stanton and George Gonzalez
The case presents the founding vision and early days of a young startup that seeks to empower delivery drivers with tools and transparency. The company's flagship mobile app has been taken up by tens of thousands of delivery drivers across major U.S. cities who use it... View Details
- October 2022 (Revised December 2022)
- Case
SMART: AI and Machine Learning for Wildlife Conservation
By: Brian Trelstad and Bonnie Yining Cao
Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details
- October 2022 (Revised August 2023)
- Case
Founders First Capital Partners: An Approach to Capital Access Equity
By: Brian Trelstad, Mel Martin and Amy Klopfenstein
In June 2021, Kim T. Folsom, the founder and CEO of revenue-based financing firm Founders First Capital Partners (FFCP), must decide whether to issue another loan to OnShore Technology Group, an up-and-coming software validation company. FFCP provided revenue-based... View Details
- October 17, 2022
- Article
Relational Diversity in Social Portfolios Predicts Well-Being
By: Hanne K. Collins, Serena F. Hagerty, Jordi Quoidbach, Michael I. Norton and Alison Wood Brooks
We document a link between the relational diversity of one’s social portfolio—the richness and evenness of relationship types across one’s social interactions—and well-being. Across four distinct samples, respondents from the United States who completed a preregistered... View Details
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details