Publications
Publications
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- Faculty Publications (78)
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- September 2024
- Case
Open Door Legal: Universal Legal Access
By: Brian Trelstad, Taylor Greenthal and Sarah Mehta
This case is about Open Door Legal (ODL), a San Francisco-based civil legal aid nonprofit. CEO Adrian Tirtanadi founded the organization in 2012 with a mission to achieve universal access to legal representation for all city residents. By 2024, ODL had opened four... View Details
- September 2024
- Supplement
National Public Broadcasting (B)
By: Richard S. Ruback and Royce Yudkoff
Pre-abstract: Instructors should consider the timing of making videos available to students, as they may reveal key case details.
Abstract: This (B) case supplement is designed for use by faculty only to support classroom instruction in conjunction with "National... View Details
- September 2024
- Article
Activist Directors: Determinants and Consequences
By: Ian D. Gow, Sa-Pyung Sean Shin and Suraj Srinivasan
This paper examines determinants and consequences of hedge fund activism, focusing on activist directors, i.e., directors appointed in response to activist demands. Using a sample of 3,259 activism events from 2004 to 2016, we identify 1,623 activist directors.... View Details
- 2024
- Working Paper
The New Digital Divide
By: Mayana Pereira, Shane Greenstein, Raffaella Sadun, Prasanna Tambe, Lucia Ronchi Darre, Tammy Glazer, Allen Kim, Rahul Dodhia and Juan Lavista Ferres
We build and analyze new metrics of digital usage that leverage telemetry data collected by Microsoft during operating system updates across forty million Windows devices in U.S. households. These measures of US household digital usage are much more comprehensive than... View Details
- 2024
- Working Paper
Voting Rules, Turnout, and Economic Policies
By: Enrico Cantoni, Vincent Pons and Jérôme Schäfer
In recent years, voter ID laws and convenience voting have generated heated partisan debates. To shed light on these policy issues, we survey the recent evidence on the institutional determinants and effects of voter turnout and broaden the perspective beyond the most... View Details
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
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
- June 2024
- Article
Rationalizing Outcomes: Interdependent Learning in Competitive Markets
By: Anoop R. Menon and Dennis Yao
In this article we use simulation models to explore interdependent learning in competitive markets. Such interactions require attention to both the mental representations held by the management of the focal firm as well as the beliefs of that management about the... View Details
- April 2024
- Article
An Integrative Model of Hybrid Governance: The Role of Boards in Helping Sustain Organizational Hybridity
By: Anne-Claire Pache, Julie Battilana and Channing Spencer
Hybrid organizations must sustainably attend to multiple goals embedded in different institutional spheres. Past research has highlighted the value for hybrids in recruiting board members representing different logics to avoid attentional drifts; yet, diverse boards... View Details
- February 2024
- Article
Representation and Extrapolation: Evidence from Clinical Trials
By: Marcella Alsan, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein and Heidi L. Williams
This article examines the consequences and causes of low enrollment of Black patients in clinical
trials. We develop a simple model of similarity-based extrapolation that predicts that evidence is
more relevant for decision-making by physicians and patients when it... View Details
- 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
- August 2023 (Revised February 2024)
- Case
DexAI
By: Jo Tango and Christina Wallace
During a challenging fundraising environment, the DexAI founders received two term sheets with nearly identical economic terms but very different legal ones. The entrepreneurs had to navigate: representations and warranties (their personal guarantees that the company's... View Details
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
- December 2022
- Article
Entry Points: Gaining Momentum in Early-Stage Cross-Boundary Collaborations
By: Eva Flavia Martínez Orbegozo, Jorrit de Jong, Hannah Riley Bowles, Amy Edmondson, Anahide Nahhal and Lisa Cox
To address complex social challenges, it is widely recognized that leaders from public, for-profit, and civic organizations should join forces. Yet, well-intended collaborators often struggle to achieve alignment and fail to gain traction in their joint efforts. This... View Details
- December 2022
- Article
Two Representations of Information Structures and Their Comparisons
By: Jerry R. Green and Nancy L. Stokey
This paper compares two representations of informativeness. View Details
- October 2022
- Case
Single.Earth
By: Rembrand Koning and Emer Moloney
Estonian greentech company Single.Earth is launching a nature-backed token that is linked to and funds the protection of a specific plot fo land. The first landowners had been onboarded to the company's Digital Twin, a virtual representation of the planet's natural... View Details
Keywords: Alternative Assets; Business Startups; Entrepreneurship; Climate Change; Environmental Sustainability; Green Technology; Natural Resources; Pollution; Analytics and Data Science; Marketing; Product Marketing; Product Launch; Product Positioning; Markets; Market Timing; Strategy; Green Technology Industry; Estonia
- 2022
- Working Paper
Racial Diversity in Private Capital Fundraising
By: Johan Cassel, Josh Lerner and Emmanuel Yimfor
Black- and Hispanic-owned funds control a very modest share of assets in the private capital
industry. We find that the sensitivity of follow-on fundraising to fund performance
is greater for minority-owned groups, particularly for underperforming groups. We... View Details
- 2022
- Working Paper
Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments
By: Fanglin Chen, Xiao Liu, Davide Proserpio and Isamar Troncoso
We propose a method, Product2Vec, based on representation learning, that can automatically learn latent product attributes that drive consumer choices, to study product-level competition when the number of products is large. We demonstrate Product2Vec’s... View Details
- Article
Behavioral and Neural Representations en route to Intuitive Action Understanding
By: Leyla Tarhan, Julian De Freitas and Talia Konkle
When we observe another person’s actions, we process many kinds of information—from how their body moves to the intention behind their movements. What kinds of information underlie our intuitive understanding about how similar actions are to each other? To address this... View Details
- September 2021
- Article
Shaking Things Up: Disruptive Events and Inequality
By: Letian Zhang
This paper develops a theory of how disruptive events could reduce racial and gender inequality in organizations. Despite pressure from regulators and advocates, racial and gender inequality in the workplace remains high. I theorize that because such inequality is... View Details
- 2021
- Chapter
Towards a Unified Framework for Fair and Stable Graph Representation Learning
By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details