Publications
Publications
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- All HBS Web
(4,160)
- Faculty Publications (1,266)
- 2024
- Working Paper
Corporate Culture Homogeneity and Top Executive Incentive Design: Evidence from CEO Compensation Contracts
By: Dennis Campbell, Ruidi Shang and Zhifang Zhang
We examine how corporate cultures characterized by high degrees of homogeneity in the underlying values and beliefs of organizational members are related to the design of CEO incentive compensation contracts. We argue that culture homogeneity within firms lowers... View Details
- February 2024
- Article
Diversification as an Adaptive Learning Process: An Empirical Study of General-Purpose and Market-Specific Technological Know-How in New Market Entry
By: Dominika Kinga Randle and Gary P. Pisano
An enduring trait of modern corporations is their propensity to diversify into multiple lines of business. Penrosian theories conceptualize diversification as a strategy to exploit a firm’s fungible, yet “untradeable”, resources and point to redeployment of... View Details
- February 2024
- Article
Pricing Power in Advertising Markets: Theory and Evidence
By: Matthew Gentzkow, Jesse M. Shapiro, Frank Yang and Ali Yurukoglu
Existing theories of media competition imply that advertisers will pay a lower price in equilibrium to reach consumers who multi-home across competing outlets. We generalize, extend, and test this prediction. We find that television outlets whose viewers watch more... View Details
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
- 2025
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers
By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to make... View Details
- January 2024 (Revised January 2025)
- Case
Huawei: Resilience amid Autarky and Adversity
By: William C. Kirby and Daniel Fu
In September 2023, Huawei made a dramatic return to the global smartphone space with the launch of its Mate 60 Pro smartphone, equipped with an indigenously designed, 7nm chip. This came despite a myriad of export controls and restrictions imposed against the company... View Details
Keywords: International Strategy; Semiconductors; Smartphone; Government And Politics; Government And Business; Digital Infrastructure; 5G; Political Risk; Business and Government Relations; Global Strategy; Multinational Firms and Management; Governing Rules, Regulations, and Reforms; AI and Machine Learning; Mobile and Wireless Technology; Leadership; Retirement; Corporate Strategy; Technology Industry; China; United States; Europe; Asia; Middle East
- January 2024
- Case
The Financial Times (FT) and Generative AI
By: Andrew Rashbass, Ramon Casadesus-Masanell and Jordan Mitchell
In September 2023, John Ridding, CEO of the Financial Times, was considering the possible impact of Generative AI on the industry and his business. Having navigated successfully the seismic shift from print to digital, and reporting record results, the company... View Details
- 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... View Details
- January 2024 (Revised February 2024)
- Case
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its... View Details
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM... View Details
- January–February 2024
- Article
The Challenge of Maintaining Passion for Work over Time: A Daily Perspective on Passion and Emotional Exhaustion
By: Joy Bredehorst, Kai Krautter, Jirs Meuris and Jon M. Jachimowicz
Passion for work is highly coveted, but many employees report struggling to maintain their passion over time. In the current research, we explain the challenge of pursuing passion by conceptualizing passion as an attribute with temporal variation. Viewed through a... View Details
- December 2023 (Revised November 2024)
- Case
Generative AI and the Future of Work
By: Christopher Stanton, Matt Higgins, Shira Aronson and Meg Shriber
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... View Details
- 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... View Details
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
- 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
- December 2023
- Article
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work
By: Mijeong Kwon, Julia Lee Cunningham and Jon M. Jachimowicz
Intrinsic motivation has received widespread attention as a predictor of positive work outcomes, including employees’ prosocial behavior. In the current research, we offer a more nuanced view by proposing that intrinsic motivation does not uniformly increase prosocial... View Details
- December 2023
- Article
Intermediary Balance Sheets and the Treasury Yield Curve
By: Wenxin Du, Benjamin Hebert and Wenhao Li
We document a regime change in the Treasury market post-Global Financial Crisis (GFC): dealers switched from net short to net long Treasury bonds. We construct “net-long” and “net-short” curves that account for balance sheet and financing costs, and show that actual... View Details
- 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
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
- 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