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Publications

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      • Faculty Publications  (178)

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      • Working Paper

      Shifting Work Patterns with Generative AI

      By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton
      We present evidence on how generative AI changes the work patterns of knowledge workers using data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers in the study received access to a generative AI tool integrated into the... View Details
      Keywords: AI and Machine Learning; Behavior; Time Management
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      Dillon, Eleanor W., Sonia Jaffe, Nicole Immorlica, and Christopher T. Stanton. "Shifting Work Patterns with Generative AI." NBER Working Paper Series, No. 33795, May 2025.
      • April 2025
      • Article

      Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile

      By: Shunyuan Zhang, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar and Xupin Zhang
      Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling... View Details
      Keywords: Sharing Economy; Airbnb; Image Feature Extraction; Machine Learning; Facial Expressions; Prejudice and Bias; Nonverbal Communication; E-commerce; Consumer Behavior; Perception
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      Zhang, Shunyuan, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar, and Xupin Zhang. "Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile." Journal of Consumer Research 51, no. 6 (April 2025): 1073–1097.
      • 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.
      • Working Paper

      AI in Disguise—How AI-generated Ads' Visual Cues Shape Consumer Perception and Performance

      By: Yannick Exner, Jochen Hartmann, Oded Netzer and Shunyuan Zhang
      Generative AI’s recent advancements in creating content have offered vast potential to transform the advertising industry. This research investigates the impact of generative AI-enabled visual ad creation on real-world advertising effectiveness. For this purpose, we... View Details
      Keywords: Digital Marketing; AI and Machine Learning; Advertising; Consumer Behavior; Advertising Industry
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      Exner, Yannick, Jochen Hartmann, Oded Netzer, and Shunyuan Zhang. "AI in Disguise—How AI-generated Ads' Visual Cues Shape Consumer Perception and Performance." SSRN Working Paper Series, No. 5096969.
      • January 2025
      • Case

      AI Meets VC: The Data-Driven Revolution at Quantum Light Capital

      By: Lauren Cohen, Grace Headinger and Sophia Pan
      Ilya Kondrashov, CEO of Quantum Light Capital, was driven to harness AI for identifying high-potential scale-ups. Collaborating with Nik Storonsky, founder of Revolut, the duo observed that most venture capital (VC) decisions were heavily influenced by emotion, with... View Details
      Keywords: Artificial Intelligence; Business Finance; Data Analysis; Angel Investors; Cognitive Biases; Scale; Venture Capital; Investment; Business Model; Forecasting and Prediction; Technological Innovation; Innovation Strategy; Behavior; Cognition and Thinking; Public Opinion; Private Sector; Business Strategy; Competitive Advantage; Business Earnings; Behavioral Finance; AI and Machine Learning; Analytics and Data Science; Business Startups; Financial Services Industry; London; United Kingdom
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      Cohen, Lauren, Grace Headinger, and Sophia Pan. "AI Meets VC: The Data-Driven Revolution at Quantum Light Capital." Harvard Business School Case 225-053, January 2025.
      • 2025
      • Working Paper

      Why Most Resist AI Companions

      By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp and Stefano Puntoni
      AI companion applications—designed to serve as synthetic interaction partners—have recently become capable enough to reduce loneliness, a growing public health concern. However, behavioral research has yet to fully explain the barriers to adoption of such AI and... View Details
      Keywords: Generative Ai; Chatbots; Artificial Intelligence; Algorithmic Aversion; Lonelines; Technology Adoption; AI and Machine Learning; Well-being; Emotions
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      De Freitas, Julian, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp, and Stefano Puntoni. "Why Most Resist AI Companions." Harvard Business School Working Paper, No. 25-030, December 2024. (Revised May 2025.)
      • 2025
      • Working Paper

      Global Evidence on Gender Gaps and Generative AI

      By: Nicholas G. Otis, Solène Delecourt, Katelynn Cranney and Rembrand Koning
      Generative AI has the potential to transform productivity and reduce inequality, but only if adopted broadly. In this paper, we show that recently identified gender gaps in generative AI use are nearly universal. Synthesizing data from 18 studies covering more than... View Details
      Keywords: AI and Machine Learning; Gender; Equality and Inequality; Technology Adoption; Behavior
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      Otis, Nicholas G., Solène Delecourt, Katelynn Cranney, and Rembrand Koning. "Global Evidence on Gender Gaps and Generative AI." Harvard Business School Working Paper, No. 25-023, October 2024. (Revised January 2025.)
      • July 2024 (Revised January 2025)
      • Case

      Dynamic Pricing at Wendy's: Where's the Beef?

      By: Elie Ofek, Alicia Dadlani and Martha Hostetter
      In early 2024, Wendy’s new CEO announced on an earnings call that the company would install digital menus in its US locations so it could begin testing dynamic pricing—changing prices up or down in response to shifts in supply and demand – as well as allow engaging in... View Details
      Keywords: Dynamic Pricing; Marketing Strategy; Price; Technology Adoption; Consumer Behavior; AI and Machine Learning; Customer Focus and Relationships; Policy; Food and Beverage Industry
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      Ofek, Elie, Alicia Dadlani, and Martha Hostetter. "Dynamic Pricing at Wendy's: Where's the Beef?" Harvard Business School Case 525-010, July 2024. (Revised January 2025.)
      • 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

      How Artificial Intelligence Constrains Human Experience

      By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
      Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
      Keywords: Large Language Model; User Experience; AI and Machine Learning; Consumer Behavior; Technology Adoption; Risk and Uncertainty; Cost vs Benefits
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      Valenzuela, A., S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino, and K. Wertenbroch. "How Artificial Intelligence Constrains Human Experience." Journal of the Association for Consumer Research 9, no. 3 (July 2024): 241–256.
      • April 2024
      • Article

      Detecting Routines: Applications to Ridesharing CRM

      By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
      Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
      Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
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      Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
      • 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.
      • 2024
      • Working Paper

      Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift

      By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong
      Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... View Details
      Keywords: AI and Machine Learning; Decision Choices and Conditions
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      DosSantos DiSorbo, Matthew, Kris Ferreira, Maya Balakrishnan, and Jordan Tong. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
      • January 2024
      • Supplement

      Winning Business at Russell Reynolds

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting—and... View Details
      Keywords: Restructuring; Talent and Talent Management; Compensation and Benefits; Growth and Development Strategy; Organizational Change and Adaptation; Organizational Culture; Performance Evaluation; Motivation and Incentives; Consulting Industry
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      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds." Harvard Business School Multimedia/Video Supplement 424-704, January 2024.
      • 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 Political Economy of a 'Miracle Cure': The Case of Nebulized Ibuprofen and Its Diffusion in Argentina

      By: Sebastian Calónico, Rafael Di Tella and Juan Cruz Lopez Del Valle
      We document the diffusion of nebulized ibuprofen in Argentina as a treatment for COVID-19. As the pandemic spread, this clinically unsupported drug reached thousands of patients, even some seriously ill, despite warnings by the regulator and medical societies. Detailed... View Details
      Keywords: COVID-19; Health Care and Treatment; Health Pandemics; Adoption; Behavior; Governing Rules, Regulations, and Reforms; Learning
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      Calónico, Sebastian, Rafael Di Tella, and Juan Cruz Lopez Del Valle. "The Political Economy of a 'Miracle Cure': The Case of Nebulized Ibuprofen and Its Diffusion in Argentina." NBER Working Paper Series, No. 31781, October 2023.
      • 2023
      • Working Paper

      The Customer Journey as a Source of Information

      By: Nicolas Padilla, Eva Ascarza and Oded Netzer
      In the face of heightened data privacy concerns and diminishing third-party data access, firms are placing increased emphasis on first-party data (1PD) for marketing decisions. However, in environments with infrequent purchases, reliance on past purchases 1PD... View Details
      Keywords: Customer Journey; Privacy; Consumer Behavior; Analytics and Data Science; AI and Machine Learning; Customer Focus and Relationships
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      Padilla, Nicolas, Eva Ascarza, and Oded Netzer. "The Customer Journey as a Source of Information." Harvard Business School Working Paper, No. 24-035, October 2023. (Revised October 2023.)
      • 2023
      • Working Paper

      Evaluation and Learning in R&D Investment

      By: Alexander P. Frankel, Joshua L. Krieger, Danielle Li and Dimitris Papanikolaou
      We examine the role of spillover learning in shaping the value of exploratory versus incremental R&D. Using data from drug development, we show that novel drug candidates generate more knowledge spillovers than incremental ones. Despite being less likely to reach... View Details
      Keywords: Research and Development; Forecasting and Prediction; Valuation; Pharmaceutical Industry
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      Frankel, Alexander P., Joshua L. Krieger, Danielle Li, and Dimitris Papanikolaou. "Evaluation and Learning in R&D Investment." Harvard Business School Working Paper, No. 23-074, May 2023. (NBER Working Paper Series, No. 31290, May 2023.)
      • April 12, 2023
      • Article

      Using AI to Adjust Your Marketing and Sales in a Volatile World

      By: Das Narayandas and Arijit Sengupta
      Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer... View Details
      Keywords: Forecasting and Prediction; AI and Machine Learning; Consumer Behavior; Technology Adoption; Competitive Advantage
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      Narayandas, Das, and Arijit Sengupta. "Using AI to Adjust Your Marketing and Sales in a Volatile World." Harvard Business Review Digital Articles (April 12, 2023).
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