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Publications

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      • April 2025
      • Case

      Techint: Strategic Choices for Community Impact

      By: Lauren Cohen, Virak Prum, Kenneth Charman, Pedro Levindo and Mariana Cal
      In early 2024 Erika Bienek, Chief Community Relations Officer at Techint, had to decide whether to invest in a new company-owned and operated technical school in Veracruz, Mexico, or invest instead in strengthening the city’s public education system. Techint, a global... View Details
      Keywords: Technical Institutes; Community Relations; Social Impact; Argentina; Mexico; Brazil; Conglomerate; Stakeholder Management; Government And Business; Community Impact; Philanthropy; Business Conglomerates; Business Subsidiaries; Business Headquarters; Family Business; Decision Making; Private Sector; Public Sector; Education; Curriculum and Courses; Middle School Education; Secondary Education; Teaching; Training; Learning; Energy; Engineering; Construction; Values and Beliefs; Geography; Global Range; Local Range; Cross-Cultural and Cross-Border Issues; Globalized Firms and Management; Government Legislation; Recruitment; Innovation and Invention; Disruptive Innovation; Knowledge; Resource Allocation; Industry Clusters; Infrastructure; Family Ownership; Philanthropy and Charitable Giving; Business and Community Relations; Business and Stakeholder Relations; Business and Government Relations; Creativity; Reputation; Social and Collaborative Networks; Civil Society or Community; Social Issues; Poverty; Strategy; Construction Industry; Education Industry; Energy Industry; Industrial Products Industry; Manufacturing Industry; Steel Industry; Europe; Italy; Latin America; North and Central America; Mexico; North America; United States; South America; Argentina; Buenos Aires; Brazil
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      Cohen, Lauren, Virak Prum, Kenneth Charman, Pedro Levindo, and Mariana Cal. "Techint: Strategic Choices for Community Impact." Harvard Business School Case 825-058, April 2025.
      • March 2025 (Revised April 2025)
      • Case

      Perplexity: Redefining Search

      By: Suraj Srinivasan, Michelle Hu, Sriraghav Srinivasan and Radhika Kak
      By early 2025, Perplexity had rapidly evolved from a modest startup into a popular "answer engine" valued at $9 billion. The company had boldly positioned itself as the disruptor to Google aiming to redefine search for the AI age. Through novel AI... View Details
      Keywords: AI and Machine Learning; Venture Capital; Innovation Leadership; Technological Innovation; Internet and the Web; Business Startups; Competitive Strategy; Technology Industry; United States
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      Srinivasan, Suraj, Michelle Hu, Sriraghav Srinivasan, and Radhika Kak. "Perplexity: Redefining Search." Harvard Business School Case 125-093, March 2025. (Revised April 2025.)
      • March 2025
      • Article

      Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures

      By: Katherine C. Kellogg, Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon and Karim R. Lakhani
      The literature on communities of practice demonstrates that a proven way for senior professionals to upskill themselves in the use of new technologies that undermine existing expertise is to learn from junior professionals. It notes that juniors may be better able... View Details
      Keywords: Rank and Position; Competency and Skills; Technology Adoption; Experience and Expertise; AI and Machine Learning
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      Kellogg, Katherine C., Hila Lifshitz-Assaf, Steven Randazzo, Ethan Mollick, Fabrizio Dell'Acqua, Edward McFowland III, François Candelon, and Karim R. Lakhani. "Novice Risk Work: How Juniors Coaching Seniors on Emerging Technologies Such as Generative AI Can Lead to Learning Failures." Art. 100559. Information and Organization 35, no. 1 (March 2025).
      • 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.
      • February 2025 (Revised April 2025)
      • Case

      Institutional Neutrality, Restraint or Convenience?

      By: Clayton S. Rose, Nicole Zelazko and Alexis Lefort
      In the fall of 2023 and winter of 2024, college campuses across the U.S. experienced protests and encampments in the aftermath of the October 7, 2023 terrorist attack on Israel by the Islamist militant group Hamas, and Israel’s subsequent invasion of Gaza. These... View Details
      Keywords: Distribution; Cost vs Benefits; Ethics; Governance; Leadership; Crisis Management; Risk Management; Corporate Social Responsibility and Impact; Mission and Purpose; Organizational Change and Adaptation; Organizational Culture; Civil Society or Community; Social Issues; Adaptation; Disruption; Communication Strategy; Higher Education; United States
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      Rose, Clayton S., Nicole Zelazko, and Alexis Lefort. "Institutional Neutrality, Restraint or Convenience?" Harvard Business School Case 325-022, February 2025. (Revised April 2025.)
      • 2025
      • Working Paper

      Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning

      By: Liangzong Ma, Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
      Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships between customer states, company actions, and long-term value. However, its practical implementation often faces significant challenges.... View Details
      Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
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      Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.
      • November 2024
      • Supplement

      AlphaGo (C): Birth of a New Intelligence

      By: Shikhar Ghosh and Shweta Bagai
      This case, the final of a three-part series, explores DeepMind's pivotal transition from mastering games to solving real-world scientific challenges. In December 2020, DeepMind's AI system AlphaFold 2 achieved a breakthrough by solving protein folding—a 50-year-old... View Details
      Keywords: Autonomy; Deep Learning; Drug Discovery; Healthcare Innovation; Neural Networks; Scientific Research; Technology Startup; AI and Machine Learning; Technological Innovation; Research and Development; Business Model; Business Strategy; Open Source Distribution; Technology Industry; United States
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      Ghosh, Shikhar, and Shweta Bagai. "AlphaGo (C): Birth of a New Intelligence." Harvard Business School Supplement 825-075, November 2024.
      • September 2024
      • Case

      Xendit: Hiring for Growth

      By: Jeffrey F. Rayport, Steve Castano, Quoc Anh Nguyen and Claire Wu
      In 2019, Xendit, a growth-stage Southeast Asia (SEA) fintech venture based in Jakarta, was looking to hire a Head of Sales and Head of Product to lead its next phase of growth. Founded by Moses Lo and Tessa Wijaya, Xendit provided payment infrastructure, modeling... View Details
      Keywords: Fintech; Financing and Loans; Entrepreneurship; Jobs and Positions; Sales; Product; Growth and Development; Selection and Staffing; Organizational Culture; Expansion; Financial Services Industry; Technology Industry; Southeast Asia; Indonesia; Philippines
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      Rayport, Jeffrey F., Steve Castano, Quoc Anh Nguyen, and Claire Wu. "Xendit: Hiring for Growth." Harvard Business School Case 825-046, September 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.
      • 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).
      • 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.
      • 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.
      • 18 Jul 2023
      • Interview

      Jeffrey Rayport on Product Market Fit, Profit Market Fit and Whiplash, and More

      By: Jeffrey F. Rayport and Doug Levin
      This episode of "Lessons from Startup Life" podcast features Jeffrey Rayport, Senior Lecturer of Business Administration at the Harvard Business School. Jeffrey specializes in teaching and researching growth-stage technology ventures and their scalability. Prior to... View Details
      Keywords: Scaling And Growth; Start-up; Diversity; Equity; Inclusion; Technology; Business Startups; Product Marketing; Business Growth and Maturation
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      "Jeffrey Rayport on Product Market Fit, Profit Market Fit and Whiplash, and More." Lessons from a Startup Life (podcast), July 18, 2023.
      • March 2023 (Revised January 2024)
      • Case

      Nigeria: Africa's Giant

      By: Marlous van Waijenburg
      "Nigeria: Africa’s Giant" delves into the economic development and state building record of Africa’s most populous country. Despite being one of the continent’s largest oil-exporters, Nigeria’s economy has been struggling, and poverty is widespread. The country’s... View Details
      Keywords: Crime and Corruption; Developing Countries and Economies; Government Administration; Poverty; Africa; Nigeria
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      van Waijenburg, Marlous. "Nigeria: Africa's Giant." Harvard Business School Case 723-056, March 2023. (Revised January 2024.)
      • 2022
      • Article

      Efficiently Training Low-Curvature Neural Networks

      By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
      Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details
      Keywords: AI and Machine Learning
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      Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
      • November–December 2022
      • Article

      Can AI Really Help You Sell?: It Can, Depending on When and How You Implement It

      By: Jim Dickie, Boris Groysberg, Benson P. Shapiro and Barry Trailer
      Many salespeople today are struggling; only 57% of them make their annual quotas, surveys show. One problem is that buying processes have evolved faster than selling processes, and buyers today can access a wide range of online resources that let them evaluate products... View Details
      Keywords: Sales; AI and Machine Learning; Customers
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      Dickie, Jim, Boris Groysberg, Benson P. Shapiro, and Barry Trailer. "Can AI Really Help You Sell? It Can, Depending on When and How You Implement It." Harvard Business Review 100, no. 6 (November–December 2022): 120–129.
      • August 2022
      • Article

      What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features

      By: Shunyuan Zhang, Dokyun Lee, Param Vir Singh and Kannan Srinivasan
      We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel dataset... View Details
      Keywords: Sharing Economy; Airbnb; Property Demand; Computer Vision; Deep Learning; Image Feature Extraction; Content Engineering; Property; Marketing; Demand and Consumers
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      Zhang, Shunyuan, Dokyun Lee, Param Vir Singh, and Kannan Srinivasan. "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features." Management Science 68, no. 8 (August 2022): 5644–5666.
      • May 2022 (Revised July 2022)
      • Case

      The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022

      By: David B. Yoffie and Daniel Fisher
      In 2022, after five years of pursuing a new "AI-first" strategy, Google had captured a sizeable share of the American and global markets for voice assistants. Google Assistant was used by hundreds of millions of users around the world, but Amazon retained the largest... View Details
      Keywords: Strategy; Artificial Intelligence; Deep Learning; Voice Assistants; Smart Home; Market Share; Globalized Markets and Industries; Competitive Strategy; Digital Platforms; AI and Machine Learning; Technology Industry; United States
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      Yoffie, David B., and Daniel Fisher. "The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022." Harvard Business School Case 722-462, May 2022. (Revised July 2022.)
      • February 2022 (Revised September 2022)
      • Case

      InstaDeep: AI Innovation Born in Africa (A)

      By: Shikhar Ghosh and Esel Çekin
      Karim Beguir and Zohra Slim were the co-founders of InstaDeep, a deep tech startup focusing on artificial intelligence (AI) solutions. Instadeep was one of the few companies globally that were partnering with DeepMind, an AI subsidiary of Google [Alphabet Inc.].... View Details
      Keywords: AI; Artificial Intelligence; Entrepreneurship; Operations; Business Subsidiaries; Brands and Branding; Innovation and Invention; Growth and Development Strategy; AI and Machine Learning; Technology Industry; Africa
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      Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (A)." Harvard Business School Case 822-104, February 2022. (Revised September 2022.)
      • February 2022 (Revised July 2022)
      • Supplement

      InstaDeep: AI Innovation Born in Africa (B)

      By: Shikhar Ghosh and Esel Çekin
      Karim Beguir and Zohra Slim were the co-founders of InstaDeep, a deep tech startup focusing on artificial intelligence (AI) solutions. Instadeep was one of the few companies globally that were partnering with DeepMind, an AI subsidiary of Google [Alphabet Inc.].... View Details
      Keywords: AI; Artificial Intelligence; Entrepreneurship; Operations; Business Subsidiaries; Brands and Branding; Innovation and Invention; Growth and Development Strategy; AI and Machine Learning; Technology Industry; Africa
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      Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (B)." Harvard Business School Supplement 822-105, February 2022. (Revised July 2022.)
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