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(11,306)
- Faculty Publications (3,191)
- January 2024
- Technical Note
The ICARUS Principles: What It Takes to Tackle the World
By: Debora L. Spar and Julia M. Comeau
Over the course of the 20th century, most of the world’s major multinational corporations framed their mission around Milton Friedman’s famous mantra: that the sole purpose of the firm is to maximize its shareholders’ profits. Recently, however, growing numbers of... View Details
Keywords: Purpose; Mission; Social Business; Corporate Social Responsibility and Impact; Mission and Purpose; Social Enterprise; For-Profit Firms
Spar, Debora L., and Julia M. Comeau. "The ICARUS Principles: What It Takes to Tackle the World." Harvard Business School Technical Note 324-055, January 2024.
- January 2024 (Revised May 2024)
- Case
PortageBay and ESG Analytics
By: Vikram S. Gandhi and Radhika Kak
In 2023, sustainable investors faced several challenges. The first was the lack of access to standardized and vetted environmental, social, and governance (ESG) data, and equally, the interpretation of this data into investment-useful insights. Reducing reliance on... View Details
Keywords: ESG Ratings; Investment Funds; Governance; Environmental Sustainability; Corporate Social Responsibility and Impact
Gandhi, Vikram S., and Radhika Kak. "PortageBay and ESG Analytics." Harvard Business School Case 324-065, January 2024. (Revised May 2024.)
- 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
Keywords: Investor Relations; Forecasting; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Digital Transformation; Apparel and Accessories Industry; United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, 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... View Details
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.
- 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
Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.
- 2024
- Article
Technological Adoption and Taxation: The Case of China's Golden Tax Reform
By: Haichao Fan, Yu Liu, Nancy Qian and Jaya Y. Wen
This paper investigates the effect of Phase 2 of the Golden Tax Project on VAT in China. The reform introduced computer-generated invoices and electronic transaction linking. Using a difference-in-differences strategy, we show that the reform increased VAT by reducing... View Details
Keywords: Taxation; Governing Rules, Regulations, and Reforms; Technological Innovation; Economic Growth; China
Fan, Haichao, Yu Liu, Nancy Qian, and Jaya Y. Wen. "Technological Adoption and Taxation: The Case of China's Golden Tax Reform." Tax Policy and the Economy 38 (2024): 101–122.
- 2024
- Report
The Eco-Digital EraTM: The Dual Transition to a Sustainable and Digital Economy
By: Suraj Srinivasan, Andy Feinstein, Amol Khadikar, Jiani Zhang, Noémie Lauer, Hiral Shah, Sally Epstein, Jerome Buvat and Vaishnavee Ananth
Since the proliferation of smartphones and social media in the late 2000s, digital has captured an increasingly large portion of the economy. In this Capgemini Research Institute report, The Eco-Digital EraTM: The dual transition to a sustainable and... View Details
Srinivasan, Suraj, Andy Feinstein, Amol Khadikar, Jiani Zhang, Noémie Lauer, Hiral Shah, Sally Epstein, Jerome Buvat, and Vaishnavee Ananth. "The Eco-Digital EraTM: The Dual Transition to a Sustainable and Digital Economy." Report, Capgemini Research Institute, January 2024.
- 2024
- Book
The Everything Token: How NFTs and Web3 Will Transform the Way We Buy, Sell, and Create
By: Steve Kaczynski and Scott Duke Kominers
We demystify the coming digital revolution, showing how NFTs will transform our online and offline interactions.
NFTs aren’t just pictures on the internet, or a fad that has come and gone. Rather, they’re a new technology for creating digital assets and... View Details
NFTs aren’t just pictures on the internet, or a fad that has come and gone. Rather, they’re a new technology for creating digital assets and... View Details
Keywords: Economic Systems; Microeconomics; Entrepreneurship; Cultural Entrepreneurship; Information Technology; Innovation and Invention; Innovation Strategy; Digital Platforms; Digital Strategy; Digital Transformation; Internet and the Web; Technology Adoption; Marketing; Marketing Strategy; Product Marketing; Product Positioning; Markets; E-commerce; Market Design; Value; Customer Value and Value Chain; Collaborative Innovation and Invention; Innovation and Management; Organizational Structure; Customer Ownership; Ownership; Advertising Industry; Communications Industry; Computer Industry; Consumer Products Industry; Fashion Industry; Information Technology Industry; Media and Broadcasting Industry; Technology Industry; Web Services Industry
Kaczynski, Steve, and Scott Duke Kominers. The Everything Token: How NFTs and Web3 Will Transform the Way We Buy, Sell, and Create. Portfolio/Penguin, 2024.
- 2024
- Chapter
The Private Economy Under Party-State Capitalism
By: Margaret M. Pearson, Meg Rithmire and Kellee S. Tsai
This chapter addresses the evolution of China’s approach to the private sector from the early reform era until the beginning of Xi Jinping’s third term. It argues that China has evolved from a familiar form of state capitalism, in which economic growth is the primary... View Details
Keywords: Government Administration; International Relations; Economic Growth; Economic Sectors; Economic Systems; China
Pearson, Margaret M., Meg Rithmire, and Kellee S. Tsai. "The Private Economy Under Party-State Capitalism." Chap. 3 in Chinese Politics: The Xi Jinping Difference. 2nd edition edited by Stanley Rosen and Daniel C. Lynch, 67–82. Routledge, 2024.
- 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
Keywords: AI; Future Of Work; Labor Market; AI and Machine Learning; Labor; Value Creation; Performance Productivity; Technology Industry; United States
Stanton, Christopher, Matt Higgins, Shira Aronson, and Meg Shriber. "Generative AI and the Future of Work." Harvard Business School Case 824-130, December 2023. (Revised November 2024.)
- 2025
- Working Paper
Money, Time, and Grant Design
By: Kyle Myers and Wei Yang Tham
We conduct survey experiments to test how the design of scientific grants—
the money and time awarded—can be used to manage researchers. On average,
researchers are relatively unwilling to trade off money for time when choosing
among grants. However, there is... View Details
Myers, Kyle, and Wei Yang Tham. "Money, Time, and Grant Design." Harvard Business School Working Paper, No. 24-037, December 2023. (Revised June 2025.)
- December 2023 (Revised August 2024)
- Supplement
Microsoft Azure and the Cloud Wars (B)
By: Andy Wu and Matt Higgins
By 2023, the global market for cloud infrastructure had consolidated into a three-horse race. As of Q4 2022, Amazon, Microsoft, and Google collectively accounted for 66% of the global market. AWS had a market share of 33%, Microsoft Azure had 23%, and Google Cloud had... View Details
Keywords: Microsoft; Artificial Intelligence; AI; Competition; Information Infrastructure; Market Participation
Wu, Andy, and Matt Higgins. "Microsoft Azure and the Cloud Wars (B)." Harvard Business School Supplement 724-434, December 2023. (Revised August 2024.)
- 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
Keywords: Technological Innovation; AI and Machine Learning; Ethics; Governing Rules, Regulations, and Reforms; Technology Adoption; Corporate Social Responsibility and Impact; Technology Industry; United States; European Union; China
Healy, Paul M., and Debora L. Spar. "Monsters in the Machine? Tackling the Challenge of Responsible AI." Harvard Business School Case 324-062, December 2023. (Revised August 2024.)
- 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
Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (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.
- 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
Du, Wenxin, Benjamin Hebert, and Wenhao Li. "Intermediary Balance Sheets and the Treasury Yield Curve." Art. 103722. Journal of Financial Economics 150, no. 3 (December 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
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
Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
- 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).
- December 2023
- Article
Self-Orienting in Human and Machine Learning
By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum and T. Ullman
A current proposal for a computational notion of self is a representation of one’s body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientation, a challenging... View Details
De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum, and T. Ullman. "Self-Orienting in Human and Machine Learning." Nature Human Behaviour 7, no. 12 (December 2023): 2126–2139.