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Publications

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    • All HBS Web  (2,064)
      • Faculty Publications  (230)

      Field ExperimentsRemove Field Experiments →

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      • 2025
      • Working Paper

      The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise

      By: Fabrizio Dell'Acqua, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub and Karim R. Lakhani
      We examine how artificial intelligence transforms the core pillars of collaboration— performance, expertise sharing, and social engagement—through a pre-registered field experiment with 776 professionals at Procter & Gamble, a global consumer packaged goods company.... View Details
      Keywords: Artificial Intelligence; Teamwork; Human-machine Interaction; Productivity; Skills; Innovation; Field Experiment; AI and Machine Learning; Groups and Teams; Competency and Skills; Performance Productivity; Collaborative Innovation and Invention; Product Development
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      Dell'Acqua, Fabrizio, Charles Ayoubi, Hila Lifshitz, Raffaella Sadun, Ethan Mollick, Lilach Mollick, Yi Han, Jeff Goldman, Hari Nair, Stew Taub, and Karim R. Lakhani. "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise." Harvard Business School Working Paper, No. 25-043, March 2025.
      • March 2025
      • Article

      Does Communicating Measurable Diversity Goals Attract or Repel Historically Marginalized Job Applicants? Evidence from the Lab and Field

      By: Erika L. Kirgios, Ike Silver and Edward H. Chang
      Many organizations struggle to attract a demographically diverse workforce. How does adding a measurable goal to a public diversity commitment—for example, “We care about diversity” versus “We care about diversity and plan to hire at least one woman or racial minority... View Details
      Keywords: Selection and Staffing; Recruitment; Diversity; Goals and Objectives; Communication Intention and Meaning; Behavior
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      Kirgios, Erika L., Ike Silver, and Edward H. Chang. "Does Communicating Measurable Diversity Goals Attract or Repel Historically Marginalized Job Applicants? Evidence from the Lab and Field." Journal of Experimental Psychology: General 154, no. 3 (March 2025): 624–643.
      • 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).
      • February 2025
      • Article

      Improving Customer Compatibility with Tradeoff Transparency

      By: Ryan W. Buell and MoonSoo Choi
      Through a large-scale field experiment with 393,036 customers considering opening a credit card account with a nationwide retail bank, we investigate how providing transparency into an offering’s tradeoffs affects subsequent rates of customer acquisition and long-run... View Details
      Keywords: Transparency; Customer Selection; Customer Compatibility; Retention; Service Operations; Service Delivery; Marketing Strategy; Marketing Communications; Customer Focus and Relationships; Customer Satisfaction; Banking Industry; Australia
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      Buell, Ryan W., and MoonSoo Choi. "Improving Customer Compatibility with Tradeoff Transparency." Management Science 71, no. 2 (February 2025): 1335–1355.
      • January 24, 2025
      • Article

      Behaviorally Designed Training Leads to More Diverse Hiring

      By: Cansin Arslan, Edward H. Chang, Siri Chilazi, Iris Bohnet and Oliver P. Hauser
      Many organizations have shown interest in increasing the diversity of their workforces for various reasons. Collectively, they have spent millions of dollars and countless employee hours on diversity training. Yet, there is little empirical evidence that such training... View Details
      Keywords: Training; Diversity; Selection and Staffing; Behavior; Outcome or Result; Organizational Change and Adaptation
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      Arslan, Cansin, Edward H. Chang, Siri Chilazi, Iris Bohnet, and Oliver P. Hauser. "Behaviorally Designed Training Leads to More Diverse Hiring." Science 387, no. 6732 (January 24, 2025): 364–366.
      • October 2024
      • Article

      Canary Categories

      By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
      Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
      Keywords: Churn; Churn Management; Churn/retention; Assortment Planning; Retail; Retailing; Retailing Industry; Preference Heterogeneity; Assortment Optimization; Customers; Retention; Consumer Behavior; Forecasting and Prediction; Retail Industry
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      Anderson, Eric, Chaoqun Chen, Ayelet Israeli, and Duncan Simester. "Canary Categories." Journal of Marketing Research (JMR) 61, no. 5 (October 2024): 872–890.
      • 2024
      • Book

      Retiring: Creating a Life That Works for You

      By: Teresa M. Amabile, Lotte Bailyn, Marcy Crary, Douglas T. Hall and Kathy E. Kram
      Retirement, as a major life transition, can be both thrilling and challenging in unexpected ways. Written by acclaimed authors in the fields of business leadership, careers, and work, this book goes beyond the typical financial and health-related advice on retirement,... View Details
      Keywords: Retirement
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      Amabile, Teresa M., Lotte Bailyn, Marcy Crary, Douglas T. Hall, and Kathy E. Kram. Retiring: Creating a Life That Works for You. Routledge, 2024.
      • September 2024
      • Article

      A Potential Pitfall of Passion: Passion Is Associated with Performance Overconfidence

      By: Erica R. Bailey, Kai Krautter, Wen Wu, Adam D. Galinsky and Jon M. Jachimowicz
      Having passion is almost universally lauded. People strive to follow their passion at work, and organizations increasingly seek out passionate employees. Supporting the benefits of passion, prior research finds a robust relationship between passion and higher levels of... View Details
      Keywords: Interests; Personal Characteristics; Performance Evaluation
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      Bailey, Erica R., Kai Krautter, Wen Wu, Adam D. Galinsky, and Jon M. Jachimowicz. "A Potential Pitfall of Passion: Passion Is Associated with Performance Overconfidence." Social Psychological & Personality Science 15, no. 7 (September 2024): 769–779.
      • 2024
      • Working Paper

      The Wade Test: Generative AI and CEO Communication

      By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
      Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO communication? This study investigates whether AI can mimic a human CEO and whether employees’ perception of the communication’s source matter. In a field... View Details
      Keywords: Business or Company Management; AI and Machine Learning; Perception; Communication
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      Choudhury, Prithwiraj, Bart S. Vanneste, and Amirhossein Zohrehvand. "The Wade Test: Generative AI and CEO Communication." Harvard Business School Working Paper, No. 25-008, August 2024.
      • 2024
      • Working Paper

      The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations

      By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
      The rise of generative artificial intelligence (AI) is transforming creative problem-solving, necessitating new approaches for evaluating innovative solutions. This study explores how human-AI collaboration can enhance early-stage evaluations, focusing on the interplay... View Details
      Keywords: Large Language Models; AI and Machine Learning; Innovation and Invention; Decision Making
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      Lane, Jacqueline N., Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh, and Pei-Hsin Wang. "The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations." Harvard Business School Working Paper, No. 25-001, August 2024. (Revised August 2024.)
      • Working Paper

      The Returns to Skills During the Pandemic: Experimental Evidence from Uganda

      By: Livia Alfonsi, Vittorio Bassi, Imran Rasul and Elena Spadini
      The Covid-19 pandemic represents one of the most significant labor market shocks to the world economy in recent times. We present evidence from a field experiment to understand whether and why skilled and unskilled workers were differentially impacted by the shock, in... View Details
      Keywords: COVID-19 Pandemic; System Shocks; Labor; Competency and Skills; Development Economics; Uganda
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      Alfonsi, Livia, Vittorio Bassi, Imran Rasul, and Elena Spadini. "The Returns to Skills During the Pandemic: Experimental Evidence from Uganda." Harvard Business School Working Paper, No. 25-003, August 2024. (NBER Working Paper Series, No. 32785, August 2024.)
      • July 2024
      • Article

      Chatbots and Mental Health: Insights into the Safety of Generative AI

      By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
      Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
      Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics
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      De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
      • July–August 2024
      • Article

      Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals

      By: Ta-Wei Huang and Eva Ascarza
      Firms are increasingly interested in developing targeted interventions for customers with the best response, which requires identifying differences in customer sensitivity, typically through the conditional average treatment effect (CATE) estimation. In theory, to... View Details
      Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
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      Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
      • July 2024
      • Article

      Whether to Apply

      By: Katherine B. Coffman, Manuela Collis and Leena Kulkarni
      Labor market outcomes depend, in part, upon an individual’s willingness to put herself forward for different opportunities. We use a series of experiments to explore gender differences in willingness to apply for higher return, more challenging work. We find that, in... View Details
      Keywords: Beliefs; Recruitment; Job Search; Gender; Attitudes
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      Coffman, Katherine B., Manuela Collis, and Leena Kulkarni. "Whether to Apply." Management Science 70, no. 7 (July 2024): 4649–4669.
      • 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.
      • 2024
      • Working Paper

      Winner Take All: Exploiting Asymmetry in Factorial Designs

      By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
      Researchers and practitioners have embraced factorial experiments to simultaneously test multiple treatments, each with different levels. With the rise of technologies like Generative AI, factorial experimentation has become even more accessible: it is easier than ever... View Details
      Keywords: Factorial Designs; Fisher Randomizations; Rank Estimators; Employer Interventions; Causal Inference; Mathematical Methods; Performance Improvement
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      DosSantos DiSorbo, Matthew, Iavor I. Bojinov, and Fiammetta Menchetti. "Winner Take All: Exploiting Asymmetry in Factorial Designs." Harvard Business School Working Paper, No. 24-075, June 2024.
      • May–June 2024
      • Article

      Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs

      By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
      Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure... View Details
      Keywords: Prejudice and Bias; Gender; Training; Recruitment; Personal Development and Career
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      Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Organization Science 35, no. 3 (May–June 2024): 911–927.
      • 2024
      • Working Paper

      Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas

      By: Jacqueline N. Lane, Tianxi Cai, Michael Menietti, Griffin Weber and Eva C. Guinan
      Evaluation of novel projects is essential for scientific and technological advancement. However, evaluator bias toward a project’s potential can obscure its limitations. This study investigates evaluation formats by contrasting combined assessments of novelty and... View Details
      Keywords: Research; Performance Evaluation; Innovation and Invention; Prejudice and Bias
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      Lane, Jacqueline N., Tianxi Cai, Michael Menietti, Griffin Weber, and Eva C. Guinan. "Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas." Harvard Business School Working Paper, No. 24-064, March 2024.
      • 2024
      • Working Paper

      Platform Information Provision and Consumer Search: A Field Experiment

      By: Lu Fang, Yanyou Chen, Chiara Farronato, Zhe Yuan and Yitong Wang
      Despite substantial efforts to help consumers search in more intuitive ways, text search remains the predominant tool for product discovery online. In this paper, we explore the effects of visual and textual cues for search refinement on consumer search and purchasing... View Details
      Keywords: Consumer Behavior; E-commerce; Decision Choices and Conditions; Learning; Internet and the Web
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      Fang, Lu, Yanyou Chen, Chiara Farronato, Zhe Yuan, and Yitong Wang. "Platform Information Provision and Consumer Search: A Field Experiment." NBER Working Paper Series, No. 32099, February 2024.
      • 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).
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