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      • 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
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      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
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      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
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      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
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      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
      Keywords: Large Language Model; AI and Machine Learning
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      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
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      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
      Keywords: Technology Adoption; Digital Transformation; Environmental Sustainability; Trends
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      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
      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
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      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
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      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
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      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
      Keywords: Research; Power and Influence; Money
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      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
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      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
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      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
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      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
      Keywords: Generative Ai; AI and Machine Learning; Ethics; Technology Adoption
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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.
      • 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
      Keywords: Bonds; Financial Markets; Financial Crisis; Asset Pricing
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      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
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      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
      Keywords: Large Language Model; AI and Machine Learning; Cybersecurity
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      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
      Keywords: AI and Machine Learning; Performance Effectiveness
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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).
      • 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
      Keywords: AI and Machine Learning; Behavior; Learning
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      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.
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