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      • 2024
      • Working Paper

      The Impact of Culture Consistency on Subunit Outcomes

      By: Jasmijn Bol, Robert Grasser, Serena Loftus and Tatiana Sandino
      We examine the association between subunit culture consistency—defined as the congruence between the organizational values espoused by top management and those perceived and practiced by subunit employees—and subunit outcomes. Using data from 235 subunits of a... View Details
      Keywords: Organizational Culture; Employees; Creativity; Satisfaction
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      Bol, Jasmijn, Robert Grasser, Serena Loftus, and Tatiana Sandino. "The Impact of Culture Consistency on Subunit Outcomes." Working Paper, December 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.
      • 2023
      • Working Paper

      Money, Time, and Grant Design

      By: Kyle Myers and Wei Yang Tham
      The design of research grants has been hypothesized to be a useful tool for influencing researchers and their science. We test this by conducting two thought experiments in a nationally representative survey of academic researchers. First, we offer participants a... 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.
      • 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... View Details
      Keywords: Health Care and Treatment; Employee Relationship Management; Knowledge Dissemination; Knowledge Management; Management Practices and Processes; Organizational Design; Organizational Structure; Groups and Teams; Learning; Health Industry; Netherlands
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      Bernstein, Ethan, and Tatiana Sandino. "Buurtzorg." Harvard Business School Teaching Note 124-059, December 2023.
      • 2025
      • Working Paper

      Enhancing Treatment Effect Prediction on Privacy-Protected Data: An Honest Post-Processing Approach

      By: Ta-Wei Huang and Eva Ascarza
      As firms increasingly rely on customer data for personalization, concerns over privacy and regulatory compliance have grown. Local Differential Privacy (LDP) offers strong individual-level protection by injecting noise into data before collection. While... View Details
      Keywords: Targeted Intervention; Conditional Average Treatment Effect Estimation; Differential Privacy; Honest Estimation; Post-processing; Analytics and Data Science; Consumer Behavior; Marketing
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      Huang, Ta-Wei, and Eva Ascarza. "Enhancing Treatment Effect Prediction on Privacy-Protected Data: An Honest Post-Processing Approach." Harvard Business School Working Paper, No. 24-034, December 2023. (Revised March 2025.)
      • December 2023
      • Article

      Association of Hospital System Affiliation with COVID-19 Capacity Burden

      By: Zachary Levin, Pinar Karaca-Mandic, Richard J. Boxer and Regina E. Herzlinger
      What is the message? The COVID-19 pandemic exposed the highly variable and uncoordinated responses by hospitals. The authors found that while the non-top ten system affiliated hospitals had a larger COVID-19 share index relative to independent hospitals, top-ten system... View Details
      Keywords: COVID-19 Pandemic; Resource Allocation; Health Pandemics; Demographics; Health Care and Treatment; Health Industry
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      Levin, Zachary, Pinar Karaca-Mandic, Richard J. Boxer, and Regina E. Herzlinger. "Association of Hospital System Affiliation with COVID-19 Capacity Burden." Health Management, Policy and Innovation 8, no. 3 (December 2023).
      • 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
      Keywords: Product Launch; Mathematical Methods; Product Development
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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
      • 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

      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
      Keywords: Motivation and Incentives; Behavior; Moral Sensibility; Employees
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      Kwon, Mijeong, Julia Lee Cunningham, and Jon M. Jachimowicz. "Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work." Academy of Management Journal 66, no. 6 (December 2023): 1625–1650.
      • 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

      Recover, Explore, Practice: The Transformative Potential of Sabbaticals

      By: Kira Schabram, Matt Bloom and DJ DiDonna
      Sabbaticals have seen an exponential growth in adoption over the last two decades and are ascribed extensive benefits by employers and employees alike. Little is known, however, about how individuals spend their time or how their experiences impact them after they... View Details
      Keywords: Sabbatical; Personal Development and Career; Employees
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      Schabram, Kira, Matt Bloom, and DJ DiDonna. "Recover, Explore, Practice: The Transformative Potential of Sabbaticals." Academy of Management Discoveries 9, no. 4 (December 2023): 441–468.
      • 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
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      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).
      • November 22, 2023
      • Article

      Unifying Your Company Around a Moral Goal

      By: Ranjay Gulati
      In turbulent times, companies need a reliable anchor to guide decision-making. When organizations become moral communities, underpinned by purpose, they provide that stability for stakeholders as well as a reassuring sense of hope, solidarity, agency, and meaning.... View Details
      Keywords: Mission and Purpose; Organizational Culture; Corporate Strategy; Leadership
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      Gulati, Ranjay. "Unifying Your Company Around a Moral Goal." Harvard Business Review Digital Articles (November 22, 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
      Keywords: AI and Machine Learning; Mathematical Methods
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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).
      • December 2023
      • Article

      What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data

      By: Alberto Cavallo and Oleksiy Kryvtsov
      We use a detailed micro dataset on product availability and stockouts to construct a direct high-frequency measure of consumer product shortages during the 2020-2022 pandemic. We document a widespread multi-fold rise in stockouts in nearly all sectors early in the... View Details
      Keywords: Prices; Stockouts; Inventories; Supply Disruptions; COVID-19 Pandemic; Supply Chain; Product; Demand and Consumers
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      Cavallo, Alberto, and Oleksiy Kryvtsov. "What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data." Journal of International Economics 146 (December 2023).
      • December 2023
      • Article

      When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments

      By: Christian Kaps, Simone Marinesi and Serguei Netessine
      Globally, 1.5 billion people live off the grid, their only access to electricity often limited to operationally-expensive fossil fuel generators. Solar power has risen as a sustainable and less costly option, but its generation is variable during the day and... View Details
      Keywords: Energy; Renewable Energy
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      Kaps, Christian, Simone Marinesi, and Serguei Netessine. "When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments." Management Science 69, no. 12 (December 2023): 7633–7650.
      • 2023
      • Article

      Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness

      By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
      One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
      Keywords: AI and Machine Learning; Mathematical Methods
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      Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
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