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- 2025
- Working Paper
Markups and Cost Pass-through Along the Supply Chain
By: Santiago E. Alvarez-Blaser, Alberto Cavallo, Alexander MacKay and Paolo Mengano
We study markups and pricing strategies along the supply chain. Our unique dataset combines detailed price and cost information from a large global manufacturer with matched retail prices collected online for the period July 2018 through June 2023. We show that total... 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
- August 2024
- Article
Partisans neither Expect nor Receive Reputational Rewards for Sharing Falsehoods over Truth Online.
By: Isaias Ghezae, Jillian J. Jordan, Izzy Gainsburg, Mohsen Mosleh, Gordon Pennycook, Robb Willer and David Rand
A frequently invoked explanation for the sharing of false over true political information is that partisans are motivated by their reputations. In particular, it is often argued that by indiscriminately sharing news that is favorable to one’s political party,... View Details
- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine... 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
- 2024
- Working Paper
Using LLMs for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity 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 researchers and
practitioners... View Details
- 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
- 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
- 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
- 2022
- White Paper
The American Opportunity Index: A Corporate Scorecard of Worker Advancement
By: Matt Sigelman, Joseph Fuller, Nik Dawson and Gad Levanon
The American Opportunity Index: A Corporate Scorecard of Worker Advancement is a new effort to give companies and other stakeholders a set of robust tools that measure how well major employers are doing in fostering economic mobility for workers and how they could do... View Details
- September 2022
- Article
Loneliness Versus Distress: A Comparison of Emotion Regulation Profiles
By: Alyssa J. Tan, Vincent Mancini, James J. Gross, Amit Goldenberg, Johanna C. Badcock, Michelle H. Lim, Rodrigo Becerra, Ben Jackson and David A. Preece
Loneliness, a negative emotion stemming from the perception of unmet social needs, is a major public health concern. Current interventions often target social domains but produce small effects and are not as effective as established emotion regulation (ER)-based... View Details
Keywords: Emotions
- 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
- May 2022
- Article
Variance Analysis: New Insights from Health Care Applications
By: Robert S. Kaplan and Susanna Gallani
We use a health care application to illustrate how variance analysis can be used to benchmark costs across similar service delivery sites. Variances for personnel costs, typically the largest cost component in service organizations, are calculated for price, quantity,... View Details
- May 2022
- Article
When Harry Fired Sally: The Double Standard in Punishing Misconduct
By: Mark Egan, Gregor Matvos and Amit Seru
We examine gender differences in misconduct punishment in the financial advisory industry. We find evidence of a “gender punishment gap”: following an incident of misconduct, female advisers are 20% more likely to lose their jobs and 30% less likely to find new jobs... View Details
- March 2022
- Article
Sensitivity Analysis of Agent-based Models: A New Protocol
By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow
Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such... 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
- 2021
- Working Paper
The Great Unequalizer: Initial Health Effects of COVID-19 in the United States
By: Marcella Alsan, Amitabh Chandra and Kosali I. Simon
We measure inequities from the COVID-19 pandemic on mortality and hospitalizations in the United States during the early months of the outbreak. We discuss challenges in measuring health outcomes and health inequality, some of which are specific to COVID-19 and others... View Details
- April 2021 (Revised July 2021)
- Case
StockX: The Stock Market of Things (Abridged)
By: Chiara Farronato, John J. Horton, Annelena Lobb and Julia Kelley
Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust... View Details
Keywords: Markets; Auctions; Bids and Bidding; Demand and Consumers; Consumer Behavior; Analytics and Data Science; Market Design; Digital Platforms; Market Transactions; Marketplace Matching; Supply and Industry; Analysis; Price; Product Marketing; Product Launch; Apparel and Accessories Industry; Fashion Industry; North and Central America; United States; Michigan; Detroit
- 2020
- Working Paper
EMEs and COVID-19: Shutting Down in a World of Informal and Tiny Firms
By: Laura Alfaro, Oscar Becerra and Marcela Eslava
Emerging economies are characterized by an extremely high prevalence of informality, small-firm employment and jobs not fit for working from home. These features factor into how the COVID-19 crisis has affected the economy. We develop a framework that, based on... View Details
- 2020
- Working Paper
Anchors Aweigh: Analysis of Anchor Limited Partner Investors in Impact Investment Funds
By: Shawn A. Cole, T. Robert Zochowski, Fanele Mashwama and Heather McPherson
This note describes results from a survey of “anchor investors” in impact funds. Anchor investors
are described as “generally the first investor to make a substantial capital commitment to a fund,”
(according to the Global Impact Investing Network, “GIIN”) and their... View Details