• 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.

• 2023
• Working Paper

New Facts and Data about Professors and Their Research

By: Kyle Myers, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural and Yilun Xu

We introduce a new survey of professors at roughly 150 of the most research-intensive institutions of higher education in the US. We document seven new features of how research-active professors are compensated, how they spend their time, and how they perceive their... View Details

Keywords: Research; Higher Education; Compensation and Benefits; Measurement and Metrics; Equality and Inequality; Performance Productivity

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Myers, Kyle, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural, and Yilun Xu. "New Facts and Data about Professors and Their Research." Harvard Business School Working Paper, No. 24-036, December 2023.

• December 2023
• Case

TikTok: The Algorithm Will See You Now

By: Shikhar Ghosh and Shweta Bagai

In a world where attention is a scarce commodity, this case explores the meteoric rise of TikTok—an app that transformed from a niche platform for teens into the most visited domain by 2021—surpassing even Google. Its algorithm was a sophisticated mechanism for... View Details

Keywords: Social Media; Applications and Software; Disruptive Innovation; Business and Government Relations; International Relations; Cybersecurity; Culture; Technology Industry; China; United States; India

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Ghosh, Shikhar, and Shweta Bagai. "TikTok: The Algorithm Will See You Now." Harvard Business School Case 824-125, 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.)

• 2023
• Working Paper

Rapport in Organizations: Evidence from Fast Food

By: Achyuta Adhvaryu, Parker Howell, Anant Nyshadham and Jorge Tamayo

Common identity often provides a foundation for workplace rapport. Though gender is perhaps the most frequently studied dimension of identity among workers, little is known about how gender match between managers and their workers might affect team performance. Using... View Details

Keywords: Management; Relationships; Gender; Labor and Management Relations; Organizational Change and Adaptation; Employees; Food and Beverage Industry; Colombia

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Adhvaryu, Achyuta, Parker Howell, Anant Nyshadham, and Jorge Tamayo. "Rapport in Organizations: Evidence from Fast Food." Harvard Business School Working Paper, No. 24-032, November 2023.

• December 12, 2023
• Article

Prices for Common Services at Quaternary vs Nonquaternary Hospitals

By: Brandon W. Yan, Maximilian J. Pany and Leemore S. Dafny

Using commercial health insurance claims data from 2017-2019, we assessed whether quaternary hospitals charged higher prices for common, unspecialized services also offered by nonquaternary hospitals. We found quaternary-hospital price premiums of 8.2 percent, on... View Details

Keywords: Price; Health Care and Treatment; Insurance; Markets; Health Industry

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Yan, Brandon W., Maximilian J. Pany, and Leemore S. Dafny. "Prices for Common Services at Quaternary vs Nonquaternary Hospitals." JAMA, the Journal of the American Medical Association 330, no. 22 (December 12, 2023): 2211–2213.

• 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

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.

• September 2023
• Article

Customer Churn and Intangible Capital

By: Scott R. Baker, Brian Baugh and Marco Sammon

Intangible capital is a crucial and growing piece of firms’ capital structure, but many of its distinct components are difficult to measure. We develop and make available several new firm-level metrics regarding a key component of intangible capital – firms’ customer... View Details

Keywords: Customer Base; Transaction Data; Customer Churn; Intangible Capital; Capital Structure; Measurement and Metrics; Customers

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Baker, Scott R., Brian Baugh, and Marco Sammon. "Customer Churn and Intangible Capital." Journal of Political Economy Macroeconomics 1, no. 3 (September 2023): 447–505.

• 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
• 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).