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- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in...
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Keywords:
Empirical Methods;
Empirical Operations;
Statistical Methods And Machine Learning;
Statistical Interferences;
Research Analysts;
Analytics and Data Science;
Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- September–October 2024
- Article
How AI Can Power Brand Management
By: Julian De Freitas and Elie Ofek
Marketers have begun experimenting with AI to improve their brand-management efforts. But unlike other marketing tasks, brand management involves more than just repeatedly executing one specialized function. Long considered the exclusive domain of creative talent, it...
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Keywords:
Creativity;
AI and Machine Learning;
Brands and Branding;
Product Positioning;
Customer Focus and Relationships
De Freitas, Julian, and Elie Ofek. "How AI Can Power Brand Management." Harvard Business Review 102, no. 5 (September–October 2024): 108–114.
- 2024
- Article
Learning Under Random Distributional Shifts
By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host
countries has gained attention in recent years, with implementations in the U.S.
and Switzerland. These approaches use data on past arrivals to generate machine
learning models that can...
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Bansak, Kirk, Elisabeth Paulson, and Dominik Rothenhäusler. "Learning Under Random Distributional Shifts." Proceedings of the 27th International Conference on Artificial Intelligence and Statistics 238 (2024).
- 2024
- Working Paper
The Wade Test: Generative AI and CEO Communication
By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO
communication? This study investigates whether AI can mimic a human CEO and whether employees’
perception of the communication’s source matter. In a field...
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Choudhury, Prithwiraj, Bart S. Vanneste, and Amirhossein Zohrehvand. "The Wade Test: Generative AI and CEO Communication." Harvard Business School Working Paper, No. 25-008, August 2024.
- August 2024
- Background Note
Mitigating Climate Change with Machine Learning
By: Michael W. Toffel, Kelsey Carter, Amy Chambers, Avery Park and Susan Pinckney
This note highlights how machine learning is being used to decarbonize (reduce GHG emissions) several key sectors including electricity, transportation, building, industrial processes, and agriculture -- and how machine learning is being used to accelerate efforts to...
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Toffel, Michael W., Kelsey Carter, Amy Chambers, Avery Park, and Susan Pinckney. "Mitigating Climate Change with Machine Learning." Harvard Business School Background Note 625-014, August 2024.
- 2024
- Working Paper
The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations
By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
The rise of generative artificial intelligence (AI) is transforming creative problem-solving, necessitating new approaches for evaluating innovative solutions. This study explores how human-AI collaboration can enhance early-stage evaluations, focusing on the interplay...
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Lane, Jacqueline N., Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh, and Pei-Hsin Wang. "The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations." Harvard Business School Working Paper, No. 25-001, August 2024. (Revised August 2024.)
- 2024
- Book
Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity
By: Karen G. Mills
The second edition of Fintech, Small Business & the American Dream, builds on the groundbreaking 2019 book with new insights on how technology and artificial intelligence are transforming small business lending. This ambitious view covers the significance of...
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Keywords:
Fintech;
AI;
AI and Machine Learning;
Small Business;
Economy;
Technology Adoption;
Credit;
Financing and Loans;
Analytics and Data Science
Mills, Karen G. Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity. 2nd Edition New York City, NY: Palgrave Macmillan, 2024.
- 2024
- Article
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
By: Michael Lingzhi Li and Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across...
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Li, Michael Lingzhi, and Kosuke Imai. "Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules." Journal of Causal Inference 12, no. 1 (2024).
- July 2024
- Article
AI, ROI, and Sales Productivity
Artificial intelligence (AI) is now a loose term for many different things and at the peak of its hype curve. So managers hitch-their-pitch to the term in arguing for resources. But like any technology, its business value depends upon actionable use cases embraced by...
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Cespedes, Frank V. "AI, ROI, and Sales Productivity." Top Sales Magazine (July 2024), 12–13.
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety...
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Keywords:
Autonomy;
Chatbots;
New Technology;
Brand Crises;
Mental Health;
Large Language Model;
AI and Machine Learning;
Behavior;
Well-being;
Technological Innovation;
Ethics
De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
- July 2024
- Article
How Artificial Intelligence Constrains Human Experience
By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language...
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Keywords:
Large Language Model;
User Experience;
AI and Machine Learning;
Consumer Behavior;
Technology Adoption;
Risk and Uncertainty;
Cost vs Benefits
Valenzuela, A., S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino, and K. Wertenbroch. "How Artificial Intelligence Constrains Human Experience." Journal of the Association for Consumer Research 9, no. 3 (July 2024): 241–256.
- 2024
- Working Paper
AI Companions Reduce Loneliness
By: Julian De Freitas, Ahmet K Uguralp, Zeliha O Uguralp and Puntoni Stefano
Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are...
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De Freitas, Julian, Ahmet K Uguralp, Zeliha O Uguralp, and Puntoni Stefano. "AI Companions Reduce Loneliness." Harvard Business School Working Paper, No. 24-078, June 2024.
- June 2024
- Teaching Note
Numenta in 2020: The Future of AI
By: David B. Yoffie
In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This teaching note explores the challenges of building a...
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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 Growth and Maturation;
Business Model;
Business Startups;
Business Plan;
Disruption;
Transformation;
Talent and Talent Management;
Decisions;
Diversity;
Ethnicity;
Gender;
Nationality;
Race;
Residency;
Higher Education;
Learning;
Entrepreneurship;
Fairness;
Cross-Cultural and Cross-Border Issues;
Global Strategy;
Growth and Development;
AI and Machine Learning;
Digital Platforms;
Disruptive Innovation;
Technological Innovation;
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
- 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;
Natural Language Processing;
B2B;
B2B Innovation;
Scaling;
Scaling Tech Ventures;
Business Startups;
AI and Machine Learning;
Finance;
Sales;
Business Strategy;
Growth and Development Strategy;
Entrepreneurship;
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
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.
- 2024
- Working Paper
Personalization and Targeting: How to Experiment, Learn & Optimize
By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic...
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Keywords:
Personalization;
Targeting;
Experiments;
Observational Studies;
Policy Implementation;
Policy Evaluation;
Customization and Personalization;
Marketing Strategy;
AI and Machine Learning
Lemmens, Aurelie, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela, and Oded Netzer. "Personalization and Targeting: How to Experiment, Learn & Optimize." Working Paper, June 2024.
- 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.
- 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.