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All HBS Web
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- Faculty Publications (895)
- January 2024 (Revised February 2024)
- Case
TPG Rise Climate: Deploying 'Climate Capital'
By: Vikram S. Gandhi, David Allen, Sarah Mehta and Shannon Roche
This case is about TPG Rise Climate, a $7.3 billion climate impact fund launched in 2021 by alternative asset manager TPG. Climate investing is a complex, capital-intensive endeavor; entering it has forced TPG to think and act differently. Relative to other funds, Rise...
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Keywords:
Energy;
Environmental Management;
Ownership;
Science;
Value;
Asset Management;
Investment Funds;
Investment Portfolio;
Financial Markets;
Financial Services Industry;
California;
San Francisco;
New York (city, NY)
Gandhi, Vikram S., David Allen, Sarah Mehta, and Shannon Roche. "TPG Rise Climate: Deploying 'Climate Capital'." Harvard Business School Case 824-077, January 2024. (Revised February 2024.)
- January 2024 (Revised February 2024)
- Case
OpenAI: Idealism Meets Capitalism
By: Shikhar Ghosh and Shweta Bagai
In November 2023, the board of OpenAI, one of the most successful companies in the history of technology, decided to fire Sam Altman, its charismatic and influential CEO. Their decision shocked the corporate world and had people wondering why OpenAI had designed a...
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Keywords:
AI;
AI and Machine Learning;
Governing and Advisory Boards;
Ethics;
Strategy;
Technological Innovation;
Leadership
Ghosh, Shikhar, and Shweta Bagai. "OpenAI: Idealism Meets Capitalism." Harvard Business School Case 824-134, January 2024. (Revised February 2024.)
- 2024
- Working Paper
Lost in Transmission
By: Thomas Graeber, Shakked Noy and Christopher Roth
For many decisions, people rely on information received from others by word of mouth. How does the process of verbal transmission distort economic information? In our experiments, participants listen to audio recordings containing economic forecasts and are paid to...
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Keywords:
Information Trnasmission;
Word Of Mouth;
Word-of-Mouth;
Narratives;
Reliability;
Knowledge Sharing;
Spoken Communication;
Cognition and Thinking
Graeber, Thomas, Shakked Noy, and Christopher Roth. "Lost in Transmission." Harvard Business School Working Paper, No. 24-047, January 2024.
- December 2023 (Revised February 2024)
- Case
Generative AI and the Future of Work
By: Christopher Stanton and Matt Higgins
Generative AI seemed poised to reshape the world of work, including the higher-wage, white-collar jobs typically pursued by MBA graduates. Informed by the latest research, this case explores generative AI's potential impacts on work, productivity, value creation, and...
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Keywords:
AI;
Future Of Work;
Labor Market;
AI and Machine Learning;
Labor;
Value Creation;
Performance Productivity;
Technology Industry;
United States
Stanton, Christopher, and Matt Higgins. "Generative AI and the Future of Work." Harvard Business School Case 824-130, December 2023. (Revised February 2024.)
- December 2023
- Case
Robert McNamara: Changing the World
By: Robert Simons and Shirley Sun
This case traces the life of Robert McNamara from Harvard Business School to Ford Motor Company to the U.S. Department of Defense. McNamara excelled in every job along the way: becoming the youngest-ever professor at Harvard Business School, the first non-family...
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Keywords:
Performance Measurement;
Military;
Leadership Development;
Values and Beliefs;
Personal Characteristics;
Leadership Style;
Success;
Business and Government Relations;
Power and Influence;
Business Education;
War
Simons, Robert, and Shirley Sun. "Robert McNamara: Changing the World." Harvard Business School Case 124-036, December 2023.
- December 2023
- Teaching Note
Buurtzorg
By: Ethan Bernstein and Tatiana Sandino
Teaching Note for HBS Case No. 122-101. As co-founders of home nursing company Buurtzorg, Jos de Blok and Gonnie Kronenberg prized both self-management and organizational learning. Buurtzorg’s 10,000 nurses across 950 neighborhood nursing teams in the Netherlands were...
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- 2023
- Working Paper
Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach
By: Ta-Wei Huang and Eva Ascarza
Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes
by utilizing individual-level data from experiments. A key element of this process is the estimation
of Conditional Average Treatment Effects (CATE), which...
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Huang, Ta-Wei, and Eva Ascarza. "Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach." Harvard Business School Working Paper, No. 24-034, December 2023.
- December 2023
- Case
Davivienda Bank's Upskilling and Reskilling Strategy in Colombia
By: Jorge Tamayo, Raffaella Sadun and Jenyfeer Martinez Buitrago
Set in 2022, this case describes the digital transformation strategy of Davivienda— a leading player in Colombia’s commercial banking and one of the companies belonging to Grupo Bolívar, a major Colombian financial conglomerate—and the bank’s upskilling and reskilling...
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Keywords:
Change Management;
Transformation;
Decision Choices and Conditions;
Digital Strategy;
Digital Transformation;
Internet and the Web;
Mobile and Wireless Technology;
Innovation and Management;
Innovation Strategy;
Growth and Development Strategy;
Business Strategy;
Corporate Strategy;
Organizational Culture;
Talent and Talent Management;
Training;
Banking Industry;
Latin America;
Central America;
South America;
Colombia
Tamayo, Jorge, Raffaella Sadun, and Jenyfeer Martinez Buitrago. "Davivienda Bank's Upskilling and Reskilling Strategy in Colombia." Harvard Business School Case 724-425, December 2023.
- December 2023
- Case
Food & Life Companies
By: Forest L. Reinhardt and Akiko Saito
Founded in 1984 in Japan, Food & Life Companies Ltd. (F&LC) operated Sushiro, the largest conveyor belt sushi restaurant chain in Japan, and other types of restaurants that offered sushi and fish cuisine. F&LC was committed to offering high-quality sushi at an...
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Keywords:
Growth and Development Strategy;
Market Entry and Exit;
Expansion;
Food and Beverage Industry;
Japan;
Asia;
United States
Reinhardt, Forest L., and Akiko Saito. "Food & Life Companies." Harvard Business School Case 724-015, December 2023.
- December 2023 (Revised August 2024)
- Case
Monsters in the Machine? Tackling the Challenge of Responsible AI
By: Paul M. Healy and Debora L. Spar
In November of 2022, the small tech company OpenAI released ChatGPT, an artificial intelligence chatbot which quickly captured the public’s imagination—becoming the world’s fastest-growing consumer application within months of its release. Though observers from across...
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- 2023
- Article
Balancing Risk and Reward: An Automated Phased Release Strategy
By: Yufan Li, Jialiang Mao and Iavor Bojinov
Phased releases are a common strategy in the technology industry for gradually releasing new products or updates through a sequence of A/B tests in which the number of treated units gradually grows until full deployment or deprecation. Performing phased releases in a...
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Li, Yufan, Jialiang Mao, and Iavor Bojinov. "Balancing Risk and Reward: An Automated Phased Release Strategy." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Book
Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow
By: Ken Huang, Yang Wang, Feng Zhu, Xi Chen and Chunxiao Xing
This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business...
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Huang, Ken, Yang Wang, Feng Zhu, Xi Chen, and Chunxiao Xing, eds. Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow. Springer, 2023.
- 2023
- Article
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models
By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong
While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for...
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Keywords:
AI and Machine Learning
Lakkaraju, Himabindu, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, and Haoyi Xiong. "M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance...
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Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Other Article
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers and Stuart Shieber
Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Though the impact and novelty of innovations expressed in patent data are difficult...
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Keywords:
USPTO;
Natural Language Processing;
Classification;
Summarization;
Patent Novelty;
Patent Trolls;
Patent Enforceability;
Patents;
Innovation and Invention;
Intellectual Property;
AI and Machine Learning;
Analytics and Data Science
Suzgun, Mirac, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers, and Stuart Shieber. "The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- 2023
- Working Paper
The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks
By: Isamar Troncoso, Minkyung Kim, Ishita Chakraborty and SooHyun Kim
The US has seen a rise in union movements, but their effects on service industry marketing outcomes like customer satisfaction and perceptions of service quality remain understudied. In this paper, we empirically study the impact on customer satisfaction and...
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Keywords:
Labor Unions;
Customer Satisfaction;
Perception;
Public Opinion;
Employees;
Food and Beverage Industry
Troncoso, Isamar, Minkyung Kim, Ishita Chakraborty, and SooHyun Kim. "The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks." Working Paper, 2023.
- 2024
- Working Paper
The Uneven Impact of Generative AI on Entrepreneurial Performance
By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning
Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make...
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Keywords:
AI and Machine Learning;
Performance Improvement;
Small Business;
Decision Choices and Conditions;
Kenya
Otis, Nicholas G., Rowan Clarke, Solène Delecourt, David Holtz, and Rembrand Koning. "The Uneven Impact of Generative AI on Entrepreneurial Performance." Harvard Business School Working Paper, No. 24-042, December 2023.
- 2023
- Article
Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju
With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to...
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Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- November 2023
- Case
Open Source Machine Learning at Google
Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts...
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Keywords:
Decision Choices and Conditions;
Technological Innovation;
Open Source Distribution;
Strategy;
AI and Machine Learning;
Applications and Software;
Technology Industry;
United States
Greenstein, Shane, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue, and James Barnett. "Open Source Machine Learning at Google." Harvard Business School Case 624-015, November 2023.
- 2023
- Working Paper
Learning by Investing: Entrepreneurial Spillovers from Venture Capital
By: Josh Lerner, Jinlin Li and Tong Liu
This paper studies how investing in venture capital (VC) affects the entrepreneurial outcomes of individual limited partners (LPs). Using comprehensive administrative data on entrepreneurial activities and VC fundraising and investments in China, we first document that...
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Lerner, Josh, Jinlin Li, and Tong Liu. "Learning by Investing: Entrepreneurial Spillovers from Venture Capital." Harvard Business School Working Paper, No. 24-029, November 2023.