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- All HBS Web
(10,862)
- Faculty Publications (921)
- 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... View Details
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... View Details
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... View Details
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... View Details
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... View Details
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... View Details
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... View Details
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... View Details
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... View Details
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... View Details
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. (Revise and resubmit, Review of Financial Studies.)
- 2023
- Book
How the Harvard Business School Changed the Way We View Organizations
By: Jay W. Lorsch
The story of the field of organizational behavior (which overlaps considerably with the origin story of Harvard Business School) and how it created the “medical model” of systems thinking—anchored in the practices of listening, observing, testing, and only then... View Details
Keywords: Organizational Behavior; Systems Thinking; Medical Model; Organizations; Behavior; System; History
Lorsch, Jay W. How the Harvard Business School Changed the Way We View Organizations. Business Expert Press, 2023.
- November 2023 (Revised April 2024)
- Case
Khanmigo: Revolutionizing Learning with GenAI
By: William A. Sahlman, Allison M. Ciechanover and Emily Grandjean
Already a leader in the edtech space since its 2008 launch, Khan Academy was now one of the first edtech organizations to embrace generative artificial intelligence ("genAI"). In March 2023, Khan Academy began beta testing Khanmigo, a genAI “guide” and tutor built with... View Details
Keywords: Technology Adoption; Leading Change; Entrepreneurship; Risk and Uncertainty; Education; AI and Machine Learning; Corporate Social Responsibility and Impact; Education Industry; Technology Industry; United States; San Francisco
Sahlman, William A., Allison M. Ciechanover, and Emily Grandjean. "Khanmigo: Revolutionizing Learning with GenAI." Harvard Business School Case 824-059, November 2023. (Revised April 2024.)
- November 2023
- Case
Team Liquid: Fueling the Business of Fandom
By: Youngme Moon and Kerry Herman
In 2023, the co-CEOs of Team Liquid, one of the world's most prominent Esports organizations, are deciding whether and how to evolve their business model to include (1) a greater focus on enterprise revenue; and (2) more direct-to-consumer activity. Team Liquid has one... View Details
Keywords: Business Model; Customer Focus and Relationships; Games, Gaming, and Gambling; Revenue; Organizational Culture; Business and Community Relations; Video Game Industry
Moon, Youngme, and Kerry Herman. "Team Liquid: Fueling the Business of Fandom." Harvard Business School Case 324-041, November 2023.
- November–December 2023
- Article
Keep Your AI Projects on Track
By: Iavor Bojinov
AI—and especially its newest star, generative AI—is today a central theme in corporate boardrooms, leadership discussions, and casual exchanges among employees eager to supercharge their productivity. Sadly, beneath the aspirational headlines and tantalizing potential... View Details
Keywords: Generative Models; AI and Machine Learning; Success; Failure; Product Development; Technology Adoption
Bojinov, Iavor. "Keep Your AI Projects on Track." Harvard Business Review 101, no. 6 (November–December 2023): 53–59.
- 2023
- Working Paper
The Optimal Stock Valuation Ratio
By: Sebastian Hillenbrand and Odhrain McCarthy
Trailing price ratios, such as the price-dividend and the price-earnings ratio, scale prices by trailing cash flow measures. They theoretically contain expected returns, yet, their performance in predicting stock market returns is poor. This is because of an omitted... View Details
Keywords: Price; Investment Return; AI and Machine Learning; Valuation; Cash Flow; Forecasting and Prediction
Hillenbrand, Sebastian, and Odhrain McCarthy. "The Optimal Stock Valuation Ratio." Working Paper, November 2023.
- October 2023 (Revised January 2025)
- Case
Ӧzyeğin Social Investments: A Legacy of Giving
By: Christina R. Wing, Zeshan Gondal and Brittany L. Logan
This case explores the work of Özyeğin Social Investments, founded by Hüsnü Özyeğin, one of Turkey's most successful entrepreneurs. With a focus on education, health, gender equality, rural development, and disaster relief in Turkey, Özyeğin Social Investments and the... View Details
Keywords: Philanthropy and Charitable Giving; Family Business; Business Model; Social Entrepreneurship; Social Enterprise; Turkey
Wing, Christina R., Zeshan Gondal, and Brittany L. Logan. "Ӧzyeğin Social Investments: A Legacy of Giving." Harvard Business School Case 624-054, October 2023. (Revised January 2025.)
- 2023
- Working Paper
The Political Economy of a 'Miracle Cure': The Case of Nebulized Ibuprofen and Its Diffusion in Argentina
By: Sebastian Calónico, Rafael Di Tella and Juan Cruz Lopez Del Valle
We document the diffusion of nebulized ibuprofen in Argentina as a treatment for COVID-19. As the pandemic spread, this clinically unsupported drug reached thousands of patients, even some seriously ill, despite warnings by the regulator and medical societies. Detailed... View Details
Keywords: COVID-19; Health Care and Treatment; Health Pandemics; Adoption; Behavior; Governing Rules, Regulations, and Reforms; Learning
Calónico, Sebastian, Rafael Di Tella, and Juan Cruz Lopez Del Valle. "The Political Economy of a 'Miracle Cure': The Case of Nebulized Ibuprofen and Its Diffusion in Argentina." NBER Working Paper Series, No. 31781, October 2023.
- October 2023 (Revised January 2024)
- Case
McDonald's Board of Directors (A)
By: Lynn S. Paine and Will Hurwitz
In October 2019, the McDonald’s Corporation board of directors, chaired by Enrique Hernandez, Jr., gathered to learn the results of their outside counsel’s investigation into the conduct of the CEO. On the surface, the iconic fast-food chain was thriving as growing... View Details
Keywords: Board Of Directors; Board Chair; Board Decisions; Business Ethics; Corporate Boards; Fast Food; Franchising; Legal Aspects Of Business; Legal Battle; Legal Settlement; Misconduct; Regulation; Reorganization; Restaurant Industry; Sexual Harassment; Shareholders; Stakeholder Management; Strategy And Execution; Turnaround; Corporate Accountability; Corporate Governance; Culture; Executive Compensation; Leadership; Management; Ethics; Governing and Advisory Boards; Business and Stakeholder Relations; Food and Beverage Industry; Illinois; United States
Paine, Lynn S., and Will Hurwitz. "McDonald's Board of Directors (A)." Harvard Business School Case 324-044, October 2023. (Revised January 2024.)
- 2023
- Working Paper
Black-box Training Data Identification in GANs via Detector Networks
By: Lukman Olagoke, Salil Vadhan and Seth Neel
Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details
Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
- October 2023
- Article
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a U.S. Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
Keywords: Safety Regulations; Regulations; Regulatory Enforcement; Machine Learning Models; Safety; Operations; Service Operations; Production; Forecasting and Prediction; Decisions; United States
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." American Economic Journal: Applied Economics 15, no. 4 (October 2023): 30–67. (Profiled in the Regulatory Review.)