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      • 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.
      • 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.)
      • December 2023
      • Case

      Davivienda Bank's Upskilling and Reskilling Strategy in Colombia

      By: Jorge Tamayo, Raffaella Sadun and Jenyfeer Martinez Buitrago
      Set in 2022, this case describes the digital transformation strategy of Davivienda— a leading player in Colombia’s commercial banking and one of the companies belonging to Grupo Bolívar, a major Colombian financial conglomerate—and the bank’s upskilling and reskilling... View Details
      Keywords: Change Management; Transformation; Decision Choices and Conditions; Digital Strategy; Digital Transformation; Internet and the Web; Mobile and Wireless Technology; Innovation and Management; Innovation Strategy; Growth and Development Strategy; Business Strategy; Corporate Strategy; Organizational Culture; Talent and Talent Management; Training; Banking Industry; Latin America; Central America; South America; Colombia
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      Tamayo, Jorge, Raffaella Sadun, and Jenyfeer Martinez Buitrago. "Davivienda Bank's Upskilling and Reskilling Strategy in Colombia." Harvard Business School Case 724-425, December 2023.
      • 2023
      • Working Paper

      Estimating Productivity in the Presence of Spillovers: Firm-Level Evidence from the U.S. Production Network

      By: Ebehi Iyoha
      This paper examines the extent to which productivity gains are transmitted across U.S. firms through buyer-supplier relationships. Many empirical studies measure firm-to-firm spillovers using firm-level productivity estimates derived from control function approaches.... View Details
      Keywords: Supply and Industry; Partners and Partnerships; Production
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      Iyoha, Ebehi. "Estimating Productivity in the Presence of Spillovers: Firm-Level Evidence from the U.S. Production Network." Harvard Business School Working Paper, No. 24-033, December 2023. (Winner of the Young Economists' Essay Award at the 2021 Annual Conference of the European Association for Research in Industrial Economics (EARIE))
      • December 2023 (Revised February 2024)
      • Case

      21Seeds: Taking Shots at Breakout Growth

      By: Elie Ofek, Julian De Freitas, Michael Moynihan and Nicole Tempest Keller
      21Seeds, a female-founded flavor-infused tequila startup launched in 2019, had made inroads into the alcoholic beverage industry by focusing on an underserved consumer segment in spirits—women, primarily in their 30s and 40s, many of whom were moms—and by following a... View Details
      Keywords: Mergers and Acquisitions; Business Startups; Growth and Development Strategy; Brands and Branding; Product Positioning; Distribution Channels; Sales; Food and Beverage Industry
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      Ofek, Elie, Julian De Freitas, Michael Moynihan, and Nicole Tempest Keller. "21Seeds: Taking Shots at Breakout Growth." Harvard Business School Case 524-008, December 2023. (Revised February 2024.)
      • December 2023 (Revised July 2024)
      • Case

      Boortmalt: The Master Maltster

      By: Forest Reinhardt, Jose B Alvarez, Damien McLoughlin, Lena Duchene and Emer Moloney
      By May 2023, Boortmalt was the world’s leading producer of malt, with a production capacity of 3 million tonnes, 15% of global market share, and 27 malting plants across five continents. It had recently acquired a major competitor and had sustained an EBITDA growth of... View Details
      Keywords: Plant-Based Agribusiness; Mergers and Acquisitions; Talent and Talent Management; Customer Focus and Relationships; Values and Beliefs; Financing and Loans; Employee Relationship Management; Collaborative Innovation and Invention; Innovation Leadership; Knowledge Sharing; Leadership Style; Business or Company Management; Growth and Development Strategy; Growth Management; Management Style; Resource Allocation; Corporate Social Responsibility and Impact; Strategic Planning; Environmental Sustainability; Organizational Culture; Agriculture and Agribusiness Industry; Belgium; Europe
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      Reinhardt, Forest, Jose B Alvarez, Damien McLoughlin, Lena Duchene, and Emer Moloney. "Boortmalt: The Master Maltster." Harvard Business School Case 724-021, December 2023. (Revised July 2024.)
      • 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).
      • December 2023
      • Case

      Gabriela Santana Goldstein

      By: Leslie Perlow and Hannah Weisman
      Gabriela Santana Goldstein was pursuing her passion, working as the Head of Business for a telehealth startup, when her father went into sudden cardiac arrest and family duty called. The case discusses Goldstein’s difficult decision to leave her dream job, and her path... View Details
      Keywords: Personal Development and Career; Well-being; Work-Life Balance; Family and Family Relationships; Decisions; Health Industry; United States; Boston; New York (city, NY)
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      Perlow, Leslie, and Hannah Weisman. "Gabriela Santana Goldstein." Harvard Business School Case 424-021, 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).
      • 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).
      • 2023
      • Working Paper

      The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks

      By: Isamar Troncoso, Minkyung Kim, Ishita Chakraborty and SooHyun Kim
      The US has seen a rise in union movements, but their effects on service industry marketing outcomes like customer satisfaction and perceptions of service quality remain understudied. In this paper, we empirically study the impact on customer satisfaction and... View Details
      Keywords: Labor Unions; Customer Satisfaction; Perception; Public Opinion; Employees; Food and Beverage Industry
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      Troncoso, Isamar, Minkyung Kim, Ishita Chakraborty, and SooHyun Kim. "The Impact of Unionization on Consumer Perceptions of Service Quality: Evidence from Starbucks." Working Paper, 2023.
      • December 2023
      • Teaching Note

      The Rise and Fall of FTX

      By: Jonas Heese, Aiyesha Dey and Joseph Pacelli
      Teaching Note for HBS Case No. 124-014. View Details
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      Heese, Jonas, Aiyesha Dey, and Joseph Pacelli. "The Rise and Fall of FTX." Harvard Business School Teaching Note 124-046, December 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

      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).
      • November 2023 (Revised October 2024)
      • Supplement

      Accounting Outages at Plug Power? (C)

      By: Jonas Heese, Joseph Pacelli and James Barnett
      Set in June 2023, the C case explores Plug Power’s recovery from its financial restatements, how it benefited from government subsidies, and new strategic alliances. View Details
      Keywords: Environmental Accounting; Financial Reporting; Ethics; Finance; Management; Social Enterprise; Energy Industry; Green Technology Industry; United States; Europe
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      Heese, Jonas, Joseph Pacelli, and James Barnett. "Accounting Outages at Plug Power? (C)." Harvard Business School Supplement 124-019, November 2023. (Revised October 2024.)
      • November 2023
      • Case

      Open Source Machine Learning at Google

      By: Shane Greenstein, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue and James Barnett
      Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts... View Details
      Keywords: Decision Choices and Conditions; Technological Innovation; Open Source Distribution; Strategy; AI and Machine Learning; Applications and Software; Technology Industry; United States
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      Greenstein, Shane, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue, and James Barnett. "Open Source Machine Learning at Google." Harvard Business School Case 624-015, November 2023.
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