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(3,063)
- Faculty Publications (604)
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
- March 2023 (Revised March 2025)
- Case
Accelerating AI Adoption in the U.S. Air Force
By: Maria P. Roche and Alexander Farrow
In August 2022, the Pentagon tasked U.S. Air Force Captain Victor Lopez to launch a new office for AFWERX, an Air Force innovation unit that leveraged commercial developers and military talent to acquire advanced technologies. This task was particularly arduous because... View Details
Keywords: Technological Innovation; Organizational Design; AI and Machine Learning; Adoption; Technology Adoption; United States
Roche, Maria P., and Alexander Farrow. "Accelerating AI Adoption in the U.S. Air Force." Harvard Business School Case 723-429, March 2023. (Revised March 2025.)
- March–April 2023
- Article
Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details
Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing
Aouad, Ali, Adam Elmachtoub, Kris J. Ferreira, and Ryan McNellis. "Market Segmentation Trees." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 648–667.
- 2023
- Working Paper
Translating Information into Action: A Public Health Experiment in Bangladesh
By: Reshmaan Hussam, Kailash Pandey, Abu Shonchoy and Chikako Yamauchi
While models of technology adoption posit learning as the basis of behavior change, information campaigns in public health frequently fail to change behavior. We design an information campaign embedding hand-hygiene edutainment within popular dramas using mobile... View Details
Hussam, Reshmaan, Kailash Pandey, Abu Shonchoy, and Chikako Yamauchi. "Translating Information into Action: A Public Health Experiment in Bangladesh." Working Paper, February 2023.
- 2023
- Working Paper
Sending Signals: Strategic Displays of Warmth and Competence
By: Bushra S. Guenoun and Julian J. Zlatev
Using a combination of exploratory and confirmatory approaches, this research examines how
people signal important information about themselves to others. We first train machine learning
models to assess the use of warmth and competence impression management... View Details
Keywords: AI and Machine Learning; Personal Characteristics; Perception; Interpersonal Communication
Guenoun, Bushra S., and Julian J. Zlatev. "Sending Signals: Strategic Displays of Warmth and Competence." Harvard Business School Working Paper, No. 23-051, February 2023.
- February 2023 (Revised March 2024)
- Supplement
Shanty Real Estate: Teaching Note Supplement
By: Michael Luca and Jesse M. Shapiro
Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
- January–February 2023
- Article
Forecasting COVID-19 and Analyzing the Effect of Government Interventions
By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details
Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction
Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
- January 2023 (Revised April 2023)
- Case
Cobalt Robotics: Scaling Workplace Robotics
By: Jeffrey F. Rayport, Nicole Tempest Keller and Kyung Keun Park
Founded in 2016, Cobalt Robotics, based in Fremont, California, was a Robot-as-a-Service (RaaS) company that built autonomous workplace robots that were designed to replace or supplement human security guards. Outfitted with over 60 sensors, Cobalt robots patrolled... View Details
Keywords: Information Infrastructure; Disruptive Innovation; Innovation and Invention; Marketing Strategy; Marketing Channels; Customers; Technology Industry; United States; California
Rayport, Jeffrey F., Nicole Tempest Keller, and Kyung Keun Park. "Cobalt Robotics: Scaling Workplace Robotics." Harvard Business School Case 823-096, January 2023. (Revised April 2023.)
- January 2023 (Revised June 2023)
- Case
Replika: Embodying AI
By: Shikhar Ghosh, Shweta Bagai and Marilyn Morgan Westner
Replika was a virtual AI companion that provided a way for people to process their emotions, build connections in a safe environment, and get through periods of loneliness. The chatbot fulfilled a user's need for a friend, romantic partner, or purely an emotional... View Details
Ghosh, Shikhar, Shweta Bagai, and Marilyn Morgan Westner. "Replika: Embodying AI." Harvard Business School Case 823-090, January 2023. (Revised June 2023.)
- 8 Sep 2023
- Conference Presentation
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, K. Uguralp, Z. Uguralp and Stefano Puntoni
De Freitas, Julian, K. Uguralp, Z. Uguralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Paper presented at the Business & Generative AI Workshop, Wharton School, AI at Wharton, San Francisco, CA, United States, September 8, 2023.
- January–February 2023
- Article
Data-Driven COVID-19 Vaccine Development for Janssen
By: Dimitris Bertsimas, Michael Lingzhi Li, Xinggang Liu, Jennings Xu and Najat Khan
The COVID-19 pandemic has spurred extensive vaccine research worldwide. One crucial part of vaccine development is the phase III clinical trial that assesses the vaccine for safety and efficacy in the prevention of COVID-19. In this work, we enumerate the first... View Details
Keywords: COVID-19; Health Testing and Trials; Forecasting and Prediction; AI and Machine Learning; Research; Pharmaceutical Industry
Bertsimas, Dimitris, Michael Lingzhi Li, Xinggang Liu, Jennings Xu, and Najat Khan. "Data-Driven COVID-19 Vaccine Development for Janssen." INFORMS Journal on Applied Analytics 53, no. 1 (January–February 2023): 70–84.
- 2023
- Article
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
- January–February 2023
- Article
The Overlooked Key to a Successful Scale-Up
By: Jeffrey F. Rayport, Davide Sola and Martin Kupp
Many start-ups experience enormous popularity and runaway growth, but only a few go on to become stable giants. What separates them from the pack? They all go through a developmental stage called extrapolation, say three business school professors.
View Details
Keywords: Entrepreneurship And Strategy; Scalability; Business Startups; Growth and Development Strategy; Entrepreneurship
Rayport, Jeffrey F., Davide Sola, and Martin Kupp. "The Overlooked Key to a Successful Scale-Up." Harvard Business Review (January–February 2023): 56–65.
- December 2022 (Revised January 2025)
- Case
Akooda: Charging Toward Operational Intelligence
By: Christopher Stanton and Mel Martin
The Akooda case describes the challenges confronting founder and CEO Yuval Gonczarowski (MBA ‘17) in 2022 as he attempts to boost sales. Launched in November 2020, Akooda was an AI company that mined 20 different sources of digital data, from tools like Slack, Google... View Details
Keywords: Data Mining; Productivity; Monitoring; Data Analysis; AI and Machine Learning; Knowledge Management; Operations; Problems and Challenges; Employee Relationship Management; Information Technology Industry; Technology Industry; Information Industry; Boston; Israel
Stanton, Christopher, and Mel Martin. "Akooda: Charging Toward Operational Intelligence." Harvard Business School Case 823-018, December 2022. (Revised January 2025.)
- 2023
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial
intelligence and machine learning business applications. Although prior discussions
highlight advances in methods (along the dimensions of data, computing power, and
algorithms)... View Details
Keywords: Analytics and Data Science
Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
- 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
Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
- November 2022 (Revised March 2024)
- Case
Replika AI: Monetizing a Chatbot
By: Julian De Freitas and Nicole Tempest Keller
In early 2018, Eugenia Kuyda, co-founder and CEO of San Francisco-based chatbot Replika AI, was deciding how to monetize the app she had built. Launched in 2017, Replika was a consumer AI “companion app” developed by a team of AI software engineers originally based in... View Details
Keywords: Mental Health; Subscriber Models; TAM; Monetization Strategy; Marketing Strategy; Product Marketing; AI and Machine Learning; Applications and Software; Product Positioning; Health Disorders; Technology Industry
De Freitas, Julian, and Nicole Tempest Keller. "Replika AI: Monetizing a Chatbot." Harvard Business School Case 523-016, November 2022. (Revised March 2024.)
- November 2022
- Background Note
The Future of E-Commerce: Lessons from the Livestream Wars in China
By: Ayelet Israeli, Jeremy Yang and Billy Chan
This note explores the emerging multi-billion dollar commerce trend of livestream commerce. Livestream commerce is the sale of goods or services directly to consumers via live shows on digital platforms (such as social media or e-commerce platforms). It is a form of... View Details
Keywords: Retail; Retailing; E-commerce; E-Commerce Strategy; Ecommerce; Channels Of Distribution; Marketing Communication; Livestream Commerce; Marketing; Marketing Channels; Marketing Strategy; Advertising; Brands and Branding; Media; Consumer Behavior; Social Media; Retail Industry; Consumer Products Industry; Advertising Industry; China; United States; United Kingdom
Israeli, Ayelet, Jeremy Yang, and Billy Chan. "The Future of E-Commerce: Lessons from the Livestream Wars in China." Harvard Business School Background Note 523-055, November 2022.
- November 2022 (Revised December 2024)
- Case
Hugging Face (A): Serving AI on a Platform
By: Shane Greenstein, Daniel Yue, Sarah Gulick and Kerry Herman
It is fall 2022, and open-source AI model company Hugging Face is considering its three areas of priorities: platform development, supporting the open-source community, and pursuing cutting-edge scientific research. As it expands services for enterprise clients, which... View Details
Keywords: Community; Open-source; AI and Machine Learning; Product Development; Networks; Service Delivery; Research; Governance; Business and Stakeholder Relations; Information Industry; Technology Industry; United States
Greenstein, Shane, Daniel Yue, Sarah Gulick, and Kerry Herman. "Hugging Face (A): Serving AI on a Platform." Harvard Business School Case 623-026, November 2022. (Revised December 2024.)