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- June 2024
- Teaching Note
Beamery: Using Skills and AI to Modernize HR
By: Boris Groysberg, David Lane, Susan Pinckney and Alexis Lefort
Teaching Note for HBS Case No. 424-004. Unicorn human relationships startup Beamery evaluates it growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management...
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Keywords:
Analysis;
Business Ventures;
Business Growth and Maturation;
Business Model;
Business Startups;
Business Plan;
Disruption;
Transformation;
Talent and Talent Management;
Decisions;
Diversity;
Ethnicity;
Gender;
Nationality;
Race;
Residency;
Education;
Higher Education;
Learning;
Entrepreneurship;
Fairness;
Cross-Cultural and Cross-Border Issues;
Global Strategy;
Growth and Development;
Information Technology;
AI and Machine Learning;
Digital Platforms;
Disruptive Innovation;
Technological Innovation;
Jobs and Positions;
Job Offer;
Job Search;
Knowledge Acquisition;
Knowledge Use and Leverage;
Product;
Mission and Purpose;
Strategic Planning;
Problems and Challenges;
Corporate Strategy;
Equality and Inequality;
Valuation;
Value Creation;
Employment Industry;
United Kingdom
- 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....
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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).
- June 2024
- Case
Driving Scale With Otto
By: Rebecca Karp, David Allen and Annelena Lobb
This case asks how startup founders make scaling decisions in light of their priorities for their business and for themselves. Otto was a technology company that applied artificial intelligence technology to sales. It deployed natural language processing to find sales...
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Keywords:
Artificial Intelligence;
Machine Learning;
Natural Language Processing;
B2B;
B2B Innovation;
Startups;
Scaling;
Scaling Tech Ventures;
Business Ventures;
Information Technology;
Finance;
Sales;
Strategy;
Information Technology Industry;
United States;
Cambridge;
New York (city, NY);
Spain
Karp, Rebecca, David Allen, and Annelena Lobb. "Driving Scale With Otto." Harvard Business School Case 724-407, June 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...
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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.
- 2024
- Working Paper
Don’t Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics
By: Katherine C. Kellogg, Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Frabrizio Dell'Acqua, Edward McFowland III, François Candelon and Karim R. Lakhani
The literature on communities of practice demonstrates that a proven way for senior professionals to upskill
themselves in the use of new technologies that undermine existing expertise is to learn from junior
professionals. It notes that juniors may be better able...
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Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Frabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. "Don’t Expect Juniors to Teach Senior Professionals to Use Generative AI: Emerging Technology Risks and Novice AI Risk Mitigation Tactics." Harvard Business School Working Paper, No. 24-074, 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...
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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.
- 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...
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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.
- May 2024
- Supplement
DRSi (A)
By: Richard S. Ruback and Royce Yudkoff
Pre-Abstract: Instructors should consider the timing of making videos available to students, as they may reveal key case details.
Abstract: In March of 2019, Jen Ransom Fuller purchased DRSi. DRSi, located in Bellevue, Washington, printed and reproduced...
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Keywords:
Acquisition;
Small Business;
Cost vs Benefits;
Decisions;
Business Education;
Corporate Entrepreneurship;
Leadership Style;
Leading Change;
Business or Company Management;
Problems and Challenges;
Health Pandemics;
Selection and Staffing;
Employee Relationship Management;
Production;
Logistics;
United States;
Washington (state, US)
Ruback, Richard S., and Royce Yudkoff. " DRSi (A)." Harvard Business School Multimedia/Video Supplement 224-717, May 2024.
- May 2024
- Supplement
DRSi (B)
By: Richard S. Ruback and Royce Yudkoff
Pre-Abstract: Instructors should consider the timing of making videos available to students, as they may reveal key case details.
Abstract: In March of 2019, Jen Ransom Fuller purchased DRSi. DRSi, located in Bellevue, Washington, printed and reproduced...
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Keywords:
Acquisition;
Small Business;
Cost vs Benefits;
Decisions;
Business Education;
Corporate Entrepreneurship;
Leadership Style;
Leading Change;
Business or Company Management;
Problems and Challenges;
Health Pandemics;
Selection and Staffing;
Employee Relationship Management;
Production;
Logistics;
Washington (state, US);
United States
Ruback, Richard S., and Royce Yudkoff. " DRSi (B)." Harvard Business School Multimedia/Video Supplement 224-718, May 2024.
- 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,...
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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
- Case
Pernod Ricard: Uncorking Digital Transformation
By: Iavor Bojinov, Edward McFowland III, François Candelon, Nikolina Jonsson and Emer Moloney
This case study explores the opportunities and challenges of the digital transformation journey of French wine and spirits company Pernod Ricard. As part of the transformation, the company launched four key digital programs (KDPs) aimed at using data and artificial...
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Keywords:
Business Organization;
Business Divisions;
Talent and Talent Management;
Global Strategy;
AI and Machine Learning;
Analytics and Data Science;
Digital Transformation;
Digital Strategy;
Marketing;
Advertising;
Sales;
Organizational Culture;
Product Development;
Food and Beverage Industry;
France;
Europe
Bojinov, Iavor, Edward McFowland III, François Candelon, Nikolina Jonsson, and Emer Moloney. "Pernod Ricard: Uncorking Digital Transformation." Harvard Business School Case 624-095, 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...
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Keywords:
Artificial Intelligence;
AI;
Customer Relationship Management;
CRM;
Chatbots;
Sales Management;
Generative Ai;
Software;
SaaS;
Marketing;
Sales;
AI and Machine Learning;
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...
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Keywords:
AI
- May 2024
- Teaching Note
AI21 Labs in 2023: Strategy for Generative AI
By: David Yoffie
Tel Aviv-based generative artificial intelligence company AI21 Labs considers how to build a competitive advantage versus the biggest players in the technology and AI arena.
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- 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...
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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.
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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.
- 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...
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Ghosh, Shikhar, and Shweta Bagai. "Anthropic: Building Safe AI." Harvard Business School Case 824-129, April 2024. (Revised May 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,...
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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),...
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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...
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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.