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- 2023
- Working Paper
Using GPT for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have quickly become popular as labor-augmenting tools for programming, writing, and many other processes that benefit from quick text generation. In this paper we explore the uses and benefits of LLMs for marketing researchers and...
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Keywords:
Research;
AI and Machine Learning;
Analysis;
Customers;
Technology Industry;
Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using GPT for Market Research." Working Paper, March 2023.
- 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...
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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...
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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.
- 2022
- Working Paper
Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing
By: Kirk Bansak and Elisabeth Paulson
This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment...
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Bansak, Kirk, and Elisabeth Paulson. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing." Harvard Business School Working Paper, No. 23-048, January 2022.
- February 2023
- Supplement
Shanty Real Estate: Teaching Note Supplement
By: Michael Luca
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....
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- January 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...
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- 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.
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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 February 2023)
- Case
Akooda: Charging Toward Operational Intelligence
By: Christopher T. 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...
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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 T., and Mel Martin. "Akooda: Charging Toward Operational Intelligence." Harvard Business School Case 823-018, December 2022. (Revised February 2023.)
- 2022
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of tools...
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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.
- 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...
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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).
- 2022
- Working Paper
Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have “private” information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by...
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Keywords:
Cognitive Biases;
Algorithm Transparency;
Forecasting and Prediction;
Behavior;
AI and Machine Learning;
Analytics and Data Science;
Cognition and Thinking
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence." Working Paper, December 2022.
- 2022
- Working Paper
The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives
By: Ariel Dora Stern
For those who follow health and technology news, it is difficult to go more than a few days without reading about a compelling new application of Artificial Intelligence (AI) to health care. AI has myriad applications in medicine and its adjacent industries, with...
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Keywords:
AI and Machine Learning;
Health Care and Treatment;
Governing Rules, Regulations, and Reforms;
Technological Innovation;
Medical Devices and Supplies Industry
Stern, Ariel Dora. "The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives." NBER Working Paper Series, No. 30639, December 2022.
- November 2022 (Revised December 2022)
- 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...
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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 December 2022.)
- 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...
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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 January 2023)
- Case
Hugging Face: Serving AI on a Platform
By: Shane Greenstein, Daniel Yue, Kerry Herman and Sarah Gulick
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...
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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, Kerry Herman, and Sarah Gulick. "Hugging Face: Serving AI on a Platform." Harvard Business School Case 623-026, November 2022. (Revised January 2023.)
- 2022
- Article
A Human-Centric Take on Model Monitoring
By: Murtuza Shergadwala, Himabindu Lakkaraju and Krishnaram Kenthapadi
Predictive models are increasingly used to make various consequential decisions in high-stakes domains such as healthcare, finance, and policy. It becomes critical to ensure that these models make accurate predictions, are robust to shifts in the data, do not rely on...
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Shergadwala, Murtuza, Himabindu Lakkaraju, and Krishnaram Kenthapadi. "A Human-Centric Take on Model Monitoring." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (HCOMP) 10 (2022): 173–183.
- November 2022
- Article
A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups
By: Anjali M. Bhatt, Amir Goldberg and Sameer B. Srivastava
When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining...
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Keywords:
Culture;
Machine Learning;
Natural Language Processing;
Symbolic Boundaries;
Organizations;
Boundaries;
Social Psychology;
Interpersonal Communication;
Organizational Culture
Bhatt, Anjali M., Amir Goldberg, and Sameer B. Srivastava. "A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups." Sociological Methods & Research 51, no. 4 (November 2022): 1681–1720.
- November–December 2022
- Article
Can AI Really Help You Sell?
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...
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Dickie, Jim, Boris Groysberg, Benson P. Shapiro, and Barry Trailer. "Can AI Really Help You Sell?" Harvard Business Review (November–December 2022): 120–129.
- 2022
- Working Paper
Shared Models in Networks, Organizations, and Groups
By: Joshua Schwartzstein and Adi Sunderam
To understand new information, we exchange models or interpretations with others. This
paper provides a framework for thinking about such social exchanges of models. The key assumption is that people adopt the interpretation in their network that best explains the...
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Keywords:
Social Learning Theory;
Theory;
Social Issues;
Cognition and Thinking;
Social and Collaborative Networks;
Attitudes
Schwartzstein, Joshua, and Adi Sunderam. "Shared Models in Networks, Organizations, and Groups." NBER Working Paper Series, No. 30642, November 2022.
- 2022
- Working Paper
The Evolution of ESG Reports and the Role of Voluntary Standards
By: Ethan Rouen, Kunal Sachdeva and Aaron Yoon
We examine the evolution of ESG reports of S&P 500 firms from 2010 to 2021. The
percentage of firms releasing these voluntary disclosures increased from 35% to 86%
during this period, although the length of these documents experienced more modest
growth. Using a...
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Keywords:
Voluntary Disclosure;
Textual Analysis;
Modeling And Analysis;
Corporate Social Responsibility and Impact;
AI and Machine Learning;
Accounting
Rouen, Ethan, Kunal Sachdeva, and Aaron Yoon. "The Evolution of ESG Reports and the Role of Voluntary Standards." Harvard Business School Working Paper, No. 23-024, October 2022.