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Publications

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    • All HBS Web  (594)
      • Faculty Publications  (145)

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      • 2025
      • Working Paper

      Is Love Blind? AI-Powered Trading with Emotional Dividends

      By: De-Rong Kong and Daniel Rabetti
      We leverage the non-fungible tokens (NFTs) setting to assess the valuation of emotional dividends (LOVE), a long-standing empirical challenge in private-value markets such as art, antiques, and collectibles. Having created and validated our proxy, we use deep learning... View Details
      Keywords: NFTs; Non-fungible Tokens; AI and Machine Learning; Valuation; Financial Markets
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      Kong, De-Rong, and Daniel Rabetti. "Is Love Blind? AI-Powered Trading with Emotional Dividends." Working Paper, February 2025.
      • 2025
      • Article

      Emotion Regulation Contagion Drives Reduction in Negative Intergroup Emotions

      By: Michael Pinus, Yajun Cao, Eran Halperin, Alin Coman, James J. Gross and Amit Goldenberg
      When emotions occur in groups, they sometimes impact group behavior in undesired ways. Reducing group’s emotions with emotion regulation interventions can be helpful, but may also be a challenge, because treating every person in the group is often infeasible. One... View Details
      Keywords: Emotion Contagion; Emotion; Emotion Regulation; Groups and Teams; Emotions; Conflict and Resolution
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      Pinus, Michael, Yajun Cao, Eran Halperin, Alin Coman, James J. Gross, and Amit Goldenberg. "Emotion Regulation Contagion Drives Reduction in Negative Intergroup Emotions." Art. 1387. Nature Communications 16 (2025).
      • January 2025
      • Case

      A Tiger in the Tank: Exxon Sues Investors

      By: Clayton S. Rose, Sarah Sasso and James Weber
      In June 2024, investors were trying to make sense of ExxonMobil’s (Exxon) lawsuit against two impact investors, Arjuna Capital (Arjuna) and Follow This, that had just been dismissed by the U.S. District Court of Northern Texas. Exxon’s suit challenged the rights of two... View Details
      Keywords: Disruption; Talent and Talent Management; Customer Satisfaction; Decision Making; Demographics; Ethics; Corporate Accountability; Employees; Recruitment; Retention; Leadership; Crisis Management; Risk Management; Corporate Social Responsibility and Impact; Mission and Purpose; Organizational Change and Adaptation; Civil Society or Community; Social Issues; Adaptation; Investment Activism; Lawsuits and Litigation; Business and Shareholder Relations; Medical Devices and Supplies Industry; Health Industry; Energy Industry; United States; Netherlands; Norway
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      Rose, Clayton S., Sarah Sasso, and James Weber. "A Tiger in the Tank: Exxon Sues Investors." Harvard Business School Case 325-015, January 2025.
      • 2025
      • Article

      Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments

      By: Kosuke Imai and Michael Lingzhi Li
      Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
      Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science
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      Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
      • 2024
      • Working Paper

      The Real Effects of Bankruptcy Forum Shopping

      By: Samuel Antill and Aymeric Bellon
      Many non-Delaware firms strategically file for bankruptcy in Delaware. Should this "forum shopping" be allowed? This question has motivated six congressional bill proposals over decades of policy debate. Using a novel natural experiment and Census-Bureau microdata, we... View Details
      Keywords: Insolvency and Bankruptcy; Government Legislation; Policy; Geographic Location; Delaware
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      Antill, Samuel, and Aymeric Bellon. "The Real Effects of Bankruptcy Forum Shopping." Working Paper, December 2024.
      • 2024
      • Working Paper

      Scaling Core Earnings Measurement with Large Language Models

      By: Matthew Shaffer and Charles CY Wang
      We study the application of large language models (LLMs) to the estimation of core earnings, i.e., a firm's persistent profitability from its core business activities. This construct is central to investors' assessments of economic performance and valuations. However,... View Details
      Keywords: Large Language Models; AI and Machine Learning; Accounting; Profit; Corporate Disclosure; Analytics and Data Science; Measurement and Metrics
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      Shaffer, Matthew, and Charles CY Wang. "Scaling Core Earnings Measurement with Large Language Models." Working Paper, November 2024.
      • November 2024
      • Article

      Preference Externality Estimators: A Comparison of Border Approaches and IVs

      By: Xi Ling, Wesley R. Hartmann and Tomomichi Amano
      This paper compares two estimators—the Border Approach and an Instrumental Variable (IV) estimator—using a unified framework where identifying variation arises from “preference externalities,” following the intuition in Waldfogel (2003). We highlight two dimensions in... View Details
      Keywords: Econometrics; Casual Inference; Marketing; Economics; Advertising; Mathematical Methods
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      Ling, Xi, Wesley R. Hartmann, and Tomomichi Amano. "Preference Externality Estimators: A Comparison of Border Approaches and IVs." Management Science 70, no. 11 (November 2024): 7892–7910.
      • September–October 2024
      • Article

      Where Data-Driven Decision-Making Can Go Wrong

      By: Michael Luca and Amy C. Edmondson
      When considering internal data or the results of a study, often business leaders either take the evidence presented as gospel or dismiss it altogether. Both approaches are misguided. What leaders need to do instead is conduct rigorous discussions that assess any... View Details
      Keywords: Information; Analytics and Data Science; Analysis; Decision Making
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      Luca, Michael, and Amy C. Edmondson. "Where Data-Driven Decision-Making Can Go Wrong." Harvard Business Review 102, no. 5 (September–October 2024): 80–89.
      • 2024
      • Working Paper

      People, Practices, and Productivity: A Review of New Advances in Personnel Economics

      By: Mitchell Hoffman and Christopher T. Stanton
      This chapter surveys recent advances in personnel economics. We begin by presenting evidence showing substantial and persistent productivity variation among workers in the same roles. We discuss new research on incentives and compensation; hiring practices; the... View Details
      Keywords: Employees; Labor
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      Hoffman, Mitchell, and Christopher T. Stanton. "People, Practices, and Productivity: A Review of New Advances in Personnel Economics." NBER Working Paper Series, No. 32849, August 2024.
      • July 2024
      • Case

      Roja Garimella: Developing a Founder's Judgment

      By: Reza Satchu and Patrick Sanguineti
      Roja Garimella’s path to becoming a founder was anything but straight. Setting her sights on a career in medicine since childhood, she committed to medical school with her acceptance to college. And yet, throughout her studies, she continually explored alternative... View Details
      Keywords: Entrepreneurship; Personal Development and Career; Entrepreneurial Finance; Business Startups; Judgments; Financial Services Industry; Health Industry
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      Satchu, Reza, and Patrick Sanguineti. "Roja Garimella: Developing a Founder's Judgment." Harvard Business School Case 825-006, July 2024.
      • 2024
      • Working Paper

      The Value of Silence: The Effect of UMG’s Licensing Dispute with TikTok on Music Demand

      By: Mengjie (Magie) Cheng, Elie Ofek and Hema Yoganarasimhan
      Social media platforms like TikTok have transformed how music is discovered, consumed, and monetized. This study examines the implications of the dispute between TikTok and Universal Music Group (UMG), which resulted in UMG excluding its music from TikTok from... View Details
      Keywords: Demand And Consumers; Monetization; Social Media; Revenue; Conflict and Resolution; Music Industry
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      Cheng, Mengjie (Magie), Elie Ofek, and Hema Yoganarasimhan. "The Value of Silence: The Effect of UMG’s Licensing Dispute with TikTok on Music Demand." Harvard Business School Working Paper, No. 25-014, July 2024. (Revised October 2024.)
      • 2024
      • Working Paper

      Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization

      By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
      This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
      Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
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      Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
      • June 2024
      • Article

      The Monitoring Role of Social Media

      By: Jonas Heese and Joseph Pacelli
      In this study, we examine whether social media activity can reduce corporate misconduct. We use the staggered introduction of 3G mobile broadband access across the United States to identify exogenous increases in social media activity and test whether access to 3G... View Details
      Keywords: Corporate Misconduct; Twitter; Corporate Accountability; Mobile and Wireless Technology; Social and Collaborative Networks
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      Heese, Jonas, and Joseph Pacelli. "The Monitoring Role of Social Media." Review of Accounting Studies 29, no. 2 (June 2024): 1666–1706.
      • April 2024
      • Article

      A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification

      By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
      Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
      Keywords: Health Disorders; Health Testing and Trials; AI and Machine Learning; Health Industry
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      Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification." Journal of Pediatric Urology 20, no. 2 (April 2024): 271–278.
      • 2023
      • Working Paper

      An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

      By: Biyonka Liang and Iavor I. Bojinov
      Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
      Keywords: Analytics and Data Science; AI and Machine Learning; Mathematical Methods
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      Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
      • 2023
      • Working Paper

      Design-Based Inference for Multi-arm Bandits

      By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
      Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available... View Details
      Keywords: Analytics and Data Science; Mathematical Methods
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      Ham, Dae Woong, Iavor I. Bojinov, Michael Lindon, and Martin Tingley. "Design-Based Inference for Multi-arm Bandits." Harvard Business School Working Paper, No. 24-056, March 2024.
      • March 2024
      • Article

      Investigation of Divergent Thinking among Surgeons and Surgeon Trainees in Canada (IDEAS): A Mixed-methods Study

      By: Alex Thabane, Tyler McKechnie, Vikram Arora, Goran Calic, Jason W Busse, Ranil Sonnadara and Mohit Bhandari
      Objective: To assess the creative potential of surgeons and surgeon trainees, as measured by divergent thinking. The secondary objectives were to identify factors associated with divergent thinking, assess confidence in creative problem-solving and the perceived effect... View Details
      Keywords: Creativity; Cognition and Thinking; Surveys; Health Industry
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      Thabane, Alex, Tyler McKechnie, Vikram Arora, Goran Calic, Jason W Busse, Ranil Sonnadara, and Mohit Bhandari. "Investigation of Divergent Thinking among Surgeons and Surgeon Trainees in Canada (IDEAS): A Mixed-methods Study." BMJ Open 14, no. 3 (March 2024).
      • 2024
      • Chapter

      Managing for Organisational Integrity: My Take After Three Decades

      By: Lynn S. Paine
      This chapter revisits core ideas from my 1994 article “Managing for Organizational Integrity” and explores a critical issue not discussed in the article: the role of corporate boards. In the chapter, I first re-examine the article’s ideas about the origins of... View Details
      Keywords: Governing and Advisory Boards; Ethics; Corporate Governance
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      Paine, Lynn S. "Managing for Organisational Integrity: My Take After Three Decades." Chap. 2 in Research Handbook on Organisational Integrity, edited by Muel Kaptein, 8–23. Edward Elgar Publishing, 2024.
      • 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
      Keywords: Peer-to-peer Markets; Marketplace Matching; AI and Machine Learning; Demand and Consumers; Digital Platforms; Marketing
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      Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
      • October 2023 (Revised March 2024)
      • Case

      Fortinet: Cybersecurity Pioneer Ken Xie Considers the Long Game

      By: Tsedal Neeley, Jeff Huizinga and Emily Grandjean
      Ken Xie, cofounder of cybersecurity giant Fortinet, faced a critical decision that would validate his leadership. Fortinet became the industry’s second-largest pureplay cybersecurity firm by developing differentiated hardware and investing in R&D. However, after a... View Details
      Keywords: Leadership Development; Leadership Style; Marketing Strategy; Communication Strategy; Cybersecurity; Competitive Advantage; Information Technology Industry; United States; Sunnyvale
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      Neeley, Tsedal, Jeff Huizinga, and Emily Grandjean. "Fortinet: Cybersecurity Pioneer Ken Xie Considers the Long Game." Harvard Business School Case 424-016, October 2023. (Revised March 2024.)
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