Publications
Publications
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- All HBS Web
(4,044)
- Faculty Publications (1,260)
- January–February 2023
- Article
Triadic Advocacy Work
By: Summer R. Jackson and Katherine C. Kellogg
Scholars of street-level bureaucracy and institutional research focus primarily on the relationships between advocates and their larger bureaucratic and social systems, assuming that advocates have little need to satisfy their beneficiaries. We find otherwise in our... View Details
- 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
- Working Paper
Diversification as an Adaptive Learning Process: An Empirical Study of General-Purpose and Market-Specific Technological Know-How in New Market Entry
By: Dominika Kinga Randle and Gary P. Pisano
An enduring trait of modern corporations is their propensity to diversify into multiple lines of business. Penrosian theories conceptualize diversification as a strategy to exploit a firm’s fungible, yet “untradeable,” resources and point to redeployment of... View Details
- 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
- 2022
- Article
Becoming a Learning Organization While Enhancing Performance: The Case of LEGO
By: Thomas Borup Kristensen, Henrik Saabye and Amy Edmondson
Purpose - The purpose of this study is to empirically test how problem-solving lean practices, along with
leaders as learning facilitators in an action learning approach, can be transferred from a production context to a
knowledge work context for the purpose... View Details
- 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
- December 2022
- Article
I Don't 'Recall': The Decision to Delay Innovation Launch to Avoid Costly Product Failure
By: Byungyeon Kim, Oded Koenigsberg and Elie Ofek
Innovations embody novel features or cutting-edge components aimed at delivering desired customer benefits.
Oftentimes, however, we observe the need to recall new products shortly after their introduction. Indeed, a firm
may rush an innovation to market in an attempt... View Details
- December 2022
- Article
The Task Bind: Explaining Gender Differences in Managerial Tasks and Performance
This multi-method study of managers in a grocery chain identifies a novel mechanism by which threats of gender stereotypes undermine women’s ability to be effective managers. I find that women managers face a task bind, a dilemma that managers experience as they try to... View Details
- 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
- 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
- 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... View Details
- 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... View Details
- 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
- 2024
- Working Paper
Sharing Models to Interpret Data
By: Joshua Schwartzstein and Adi Sunderam
To understand new data, we share models or interpretations with others. This paper studies such exchanges of models in a community. The key assumption is that people adopt the interpretation in their community that best explains the data, given their prior beliefs. An... View Details
- 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... View Details
- 13 Oct 2022
- Other Presentation
4 Business Ideas That Changed the World: Disruptive Innovation
By: Amy Bernstein, Rita McGrath, Felix Oberholzer-Gee and Derek van Bever
A roundtable conversation takes stock of Clayton Christensen’s influential theory. This first in a series of roundtable conversations assessing the origins and impact of four breakthrough ideas.
In the 1980s, Clayton Christensen cofounded a startup that... View Details
In the 1980s, Clayton Christensen cofounded a startup that... View Details
Keywords: Disruptive Innovation
- October 2022 (Revised December 2022)
- Case
SMART: AI and Machine Learning for Wildlife Conservation
By: Brian Trelstad and Bonnie Yining Cao
Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details
- 2022
- Working Paper
Communicating Corporate Culture in Labor Markets: Evidence from Job Postings
We examine how firms craft their job postings to convey information about their culture and
whether doing so helps attract employees. We utilize state-of-the-art machine learning methods to
develop a comprehensive dictionary of key corporate values across the near... View Details
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
- 2022
- Article
The Ordinary Concept of a Meaningful Life: The Role of Subjective and Objective Factors in Third-Person Attributions of Meaning
By: Michael Prinzing, Julian De Freitas and Barbara L. Fredrickson
The desire for a meaningful life is ubiquitous, yet the ordinary concept of a meaningful life is poorly understood. Across six experiments (total N = 2,539), we investigated whether third-person attributions of meaning depend on the psychological states an agent... View Details