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- Faculty Publications (904)
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- All HBS Web
(10,692)
- Faculty Publications (904)
- 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
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
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
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
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
Menon, Anoop R., and Dennis Yao. "Rationalizing Outcomes: Interdependent Learning in Competitive Markets." Strategy Science 9, no. 2 (June 2024): 97–117.
- May 2024
- Case
Naked Wines: The Profit vs. Growth Decision
By: Benjamin C. Esty and Edward A. Meyer
Nick Devlin faced a difficult strategic decision in October 2022. As the CEO of a UK-based subscription business connecting wine drinkers in the US, UK, and Australia with winemakers from around the world (which one journalist called the “Netflix of Wine”), he had to... View Details
Keywords: Profit Vs. Growth; Platform Business; Economies Of Scale; Subscription Business; Wine; Scaling; Racing; Value Creation; Network Effects; Business Startups; Small Business; Financial Management; Financial Strategy; Growth Management; Business Strategy; Competitive Advantage; Expansion; Profit; E-commerce; Growth and Development Strategy; Agriculture and Agribusiness Industry; Food and Beverage Industry; United States; Australia; United Kingdom
- 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
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
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
- 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
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
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
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.
- May 2024
- Article
The Effect of Configural Processing on Mentalization
By: Katrina Fincher, Ting Zhang, Asteya Percaya, Adam Galinsky and Michael W. Morris
Eight studies (N = 2,561) reveal that how we perceptually process a person’s face affects our capacity to understand their mind. Studies 1A and B indicate this relationship functions via two separate pathways: (a) indirectly by increasing our sensitivity to the... View Details
Fincher, Katrina, Ting Zhang, Asteya Percaya, Adam Galinsky, and Michael W. Morris. "The Effect of Configural Processing on Mentalization." Journal of Personality and Social Psychology 126, no. 5 (May 2024): 758–778.
- 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
De Freitas, Julian, and G. Cohen. "The Health Risks of Generative AI-Based Wellness Apps." Nature Medicine 30, no. 5 (May 2024): 1269–1275.
- April 2024 (Revised May 2024)
- Case
Anthropic: Building Safe AI
By: Shikhar Ghosh and Shweta Bagai
In March 2024, Anthropic, a leading AI safety and research company, made headlines with the launch of Claude 3, its most advanced AI model. This marked Anthropic’s bold entry into the multimodal GenAI domain, showcasing capabilities extending to both image and text... View Details
Keywords: AI and Machine Learning; Corporate Accountability; Corporate Social Responsibility and Impact; Business Growth and Maturation; Corporate Strategy; Technology Industry; United States
Ghosh, Shikhar, and Shweta Bagai. "Anthropic: Building Safe AI." Harvard Business School Case 824-129, April 2024. (Revised May 2024.)
- April 2024
- Case
Managing AI Risks in Consumer Banking
By: Suraj Srinivasan, Satish Tadikonda, Paul Dongha, Manoj Saxena and Radhika Kak
In early 2024, Ruth Jones, head of digital banking at Signa Bank, a (fictitious) European consumer bank, was thinking about how to best incorporate GenAI capabilities to improve efficiencies and create new ways to improve the customer experience. Where were the biggest... View Details
Keywords: Customer Relationship Management; AI and Machine Learning; Risk Management; Opportunities; Customization and Personalization; Banking Industry; Europe
Srinivasan, Suraj, Satish Tadikonda, Paul Dongha, Manoj Saxena, and Radhika Kak. "Managing AI Risks in Consumer Banking." Harvard Business School Case 124-093, April 2024.
- 2024
- Working Paper
Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions
By: Caleb Kwon, Ananth Raman and Jorge Tamayo
We investigate whether corporate officers should grant managers discretion to override AI-driven demand forecasts and labor scheduling tools. Analyzing five years of administrative data from a large grocery retailer using such an AI tool, encompassing over 500 stores,... View Details
Keywords: AI and Machine Learning; Forecasting and Prediction; Working Conditions; Performance Productivity
Kwon, Caleb, Ananth Raman, and Jorge Tamayo. "Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions." Working Paper, April 2024.
- April 2024
- Article
A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification
By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification." Journal of Pediatric Urology 20, no. 2 (April 2024): 271–278.
- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
- April 2024
- Supplement
RHI Magnesita (B): Brick by Brick—Diversification?
By: Ramon Casadesus-Masanell, David M Wagner, Oliver Gassmann and Jordan Mitchell
In Part A, as of April 2017, Austria’s RHI, a backward integrated refractory company is still within the midst of merging with the next biggest competitor, Brazil’s Magnesita, while weighing options for future growth. Should the company pursue organic growth options... View Details
Casadesus-Masanell, Ramon, David M Wagner, Oliver Gassmann, and Jordan Mitchell. "RHI Magnesita (B): Brick by Brick—Diversification?" Harvard Business School Supplement 724-438, April 2024.
- March 2024 (Revised April 2024)
- Case
Coursera's Foray into GenAI
By: Suraj Srinivasan, Michael Parzen and Radhika Kak
In early 2023, Maggioncalda, CEO of US EdTech firm Coursera, launched Project Genesis to develop a strategy for incorporating GenAI capabilities into the firm's offerings, asking his teams to focus on value to the firm and cost of implementation. The team identified... View Details
Keywords: Business Model; AI and Machine Learning; Brands and Branding; Business Strategy; Competitive Advantage; Technological Innovation; Education Industry; Technology Industry; United States
Srinivasan, Suraj, Michael Parzen, and Radhika Kak. "Coursera's Foray into GenAI." Harvard Business School Case 124-089, March 2024. (Revised April 2024.)