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Show Results For
- All HBS Web
(1,272)
- People (20)
- News (195)
- Research (692)
- Events (6)
- Multimedia (11)
- Faculty Publications (308)
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- 22 Nov 2023
- Research & Ideas
Humans vs. Machines: Untangling the Tasks AI Can (and Can't) Handle
Knowing when to use artificial intelligence and when to rely on the human mind is a shifting fine line, one delineated by new research that shows considerable benefit and speed from generative AI—if it’s applied to the right tasks. What... View Details
- 2023
- Working Paper
Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill
In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides... View Details
Keywords: Causal Inference; Program Evaluation; Algorithms; Distributional Average Treatment Effect; Treatment Effect Subset Scan; Heterogeneous Treatment Effects
McFowland III, Edward, Sriram Somanchi, and Daniel B. Neill. "Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection." Working Paper, 2023.
- 2007
- Working Paper
Choice, Rationality and Welfare Measurement
By: Jerry R. Green and Daniel A. Hojman
We present a method for evaluating the welfare of a decision maker, based on observed choice data. Unlike the standard economic theory of revealed preference, our method can be used whether or not the observed choices are rational. Paralleling the standard theory we... View Details
Green, Jerry R., and Daniel A. Hojman. "Choice, Rationality and Welfare Measurement." HKS Faculty Research Working Paper Series, No. 2144, November 2007.
- October 2021
- Article
Board Design and Governance Failures at Peer Firms
By: Shelby Gai, J. Yo-Jud Cheng and Andy Wu
Our study introduces board committees as a crucial determinant of board actions. We examine how directors who structurally link different board committees—referred to as multi-committee directors (MCDs)—explain why some board actions are merely symbolic while others... View Details
Keywords: Board Committees; Board Monitoring; New Director Nomination; Peer Financial Restatements; Governing and Advisory Boards; Corporate Governance; Performance Effectiveness
Gai, Shelby, J. Yo-Jud Cheng, and Andy Wu. "Board Design and Governance Failures at Peer Firms." Strategic Management Journal 42, no. 10 (October 2021): 1909–1938.
- Article
Valuation of Bankrupt Firms
By: S. C. Gilson, E. S. Hotchkiss and R. S. Ruback
This study compares the market value of firms that reorganize in bankruptcy with estimates of value based on management's published cash flow projections. We estimate firm values using models that have been shown in other contexts to generate relatively precise... View Details
Gilson, S. C., E. S. Hotchkiss, and R. S. Ruback. "Valuation of Bankrupt Firms." Review of Financial Studies 13, no. 1 (Spring 2000): 43–74. (Abridged version reprinted in The Journal of Corporate Renewal 13, no. 7 (July 2000))
- June 2019
- Article
Learning to Become a Taste Expert
By: Kathryn A. Latour and John A. Deighton
Evidence suggests that consumers seek to become more expert about hedonic products to enhance their enjoyment of future consumption occasions. Current approaches to becoming expert center on cultivating an analytic mindset. In the present research the authors explore... View Details
Latour, Kathryn A., and John A. Deighton. "Learning to Become a Taste Expert." Journal of Consumer Research 46, no. 1 (June 2019): 1–19.
- Research Summary
Optimal Heteroskedasticity Autocorrelation Consistent Covariance Estimators for GMM Weighting Matrices
This paper considers the optimal bias-variance tradeoff for estimators of the long run covariance matrix used to generate GMM weighting matrices in time series contexts. Minimum MSE HAC estimators do not yield minimum MSE GMM estimators. Instead, achieving... View Details
- Fall 2021
- Article
When to Go and How to Go? Founder and Leader Transitions in Private Equity Firms
By: Josh Lerner and Diana Noble
Leadership transition in private equity firms is an understudied field, despite the important, albeit controversial, role such firms play in developed economies. We analyzed 260 firms in an empirical study, supplemented by qualitative interviews with a small sample of... View Details
Lerner, Josh, and Diana Noble. "When to Go and How to Go? Founder and Leader Transitions in Private Equity Firms." Journal of Alternative Investments 24, no. 2 (Fall 2021): 9–30.
- October 2013
- Case
Decision Making at the Top: The All-Star Sports eBusiness Division
By: David A. Garvin and Michael A. Roberto
Describes a senior management team's strategic decision-making process. The division president faces three options for redesigning the process to address several key concerns. The president has extensive quantitative and qualitative data about the process to guide him... View Details
Keywords: Decision Choices and Conditions; Management Teams; Performance Improvement; Planning; Mathematical Methods; Strategy
Garvin, David A., and Michael A. Roberto. "Decision Making at the Top: The All-Star Sports eBusiness Division." Harvard Business School Case 314-010, October 2013.
- 2009
- Working Paper
Performance Pressure as a Double-Edged Sword: Enhancing Team Motivation While Undermining the Use of Team Knowledge
By: Heidi K. Gardner
In this paper, I develop and empirically test the proposition that performance pressure acts as a double-edged sword for teams, providing positive effects by enhancing team motivation to achieve good results while simultaneously triggering process losses. I conducted a... View Details
Keywords: Experience and Expertise; Knowledge Use and Leverage; Performance Effectiveness; Performance Expectations; Groups and Teams
Gardner, Heidi K. "Performance Pressure as a Double-Edged Sword: Enhancing Team Motivation While Undermining the Use of Team Knowledge." Harvard Business School Working Paper, No. 09-126, April 2009. (Revised January 2012.)
- Article
Learning Models for Actionable Recourse
By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely... View Details
Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 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
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
- 2018
- Working Paper
Learning to Become a Taste Expert
By: Kathryn A. Latour and John A. Deighton
Evidence suggests that consumers seek to become more expert about hedonic products to enhance their enjoyment of future consumption occasions. Current approaches to becoming an expert center on cultivating an analytic mindset. In the present research the authors... View Details
Keywords: Hedonic; Wine; Expertise; Holistic; Analytic; Sensory; Taste; Learning; Experience and Expertise; Analysis; Perception
Latour, Kathryn A., and John A. Deighton. "Learning to Become a Taste Expert." Harvard Business School Working Paper, No. 18-107, June 2018.
- March 2022 (Revised March 2024)
- Case
Hometown Foods: Changing Price amid Inflation
During the early part of the 2021 Covid-19 pandemic, Hometown Foods, a large seller of flour-based products, thrived as consumers hoarded baked goods and took up baking to pass the time and find comfort. Then, amid growing shortages in commodities, a vaccine arrived,... View Details
Keywords: COVID-19 Pandemic; Consumer Behavior; Supply Chain; Inflation and Deflation; Spending; Price Bubble; Price; Volatility; Food and Beverage Industry
De Freitas, Julian, Jeremy Yang, and Das Narayandas. "Hometown Foods: Changing Price amid Inflation." Harvard Business School Case 522-087, March 2022. (Revised March 2024.)
- October 1997 (Revised May 1998)
- Case
Decision Making at the Top: The All-Star Sports Catalog Division
By: David A. Garvin and Michael Roberto
Describes a senior management team's strategic decision-making process. The division president faces three options for redesigning the process to address several key concerns. The president has extensive quantitative and qualitative data about the process to guide him... View Details
Keywords: Decision Choices and Conditions; Management Teams; Performance Improvement; Planning; Mathematical Methods; Strategy
Garvin, David A., and Michael Roberto. "Decision Making at the Top: The All-Star Sports Catalog Division." Harvard Business School Case 398-061, October 1997. (Revised May 1998.)
- 05 Jul 2006
- Working Paper Summaries
Measuring Consumer and Competitive Impact with Elasticity Decompositions
- Article
Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles
By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
Keywords: CEOs; Communication Style; Machine Learning; Spoken Communication; Nonverbal Communication; Personal Characteristics; Analysis; Performance
Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Strategic Management Journal 40, no. 11 (November 2019): 1705–1732.
- August 2020 (Revised December 2020)
- Background Note
A Note on Ethical Analysis
By: Nien-hê Hsieh
To engage in ethical analysis is to answer such questions as “What is the right thing to do?” “What does it mean to be a good person?” “How should I live my life?” Ethical analysis, on its own, is often not adequate for doing the right thing or being a good... View Details
Hsieh, Nien-hê. "A Note on Ethical Analysis." Harvard Business School Background Note 321-038, August 2020. (Revised December 2020.)
- Article
Assent-maximizing Social Choice
By: Katherine A. Baldiga and Jerry R. Green
We take a decision theoretic approach to the classic social choice problem, using data on the frequency of choice problems to compute social choice functions. We define a family of social choice rules that depend on the population's preferences and on the probability... View Details
Keywords: Decision Choices and Conditions; Theory; Measurement and Metrics; Mathematical Methods; Society
Baldiga, Katherine A., and Jerry R. Green. "Assent-maximizing Social Choice." Social Choice and Welfare 40, no. 2 (February 2013): 439–460.
- August 2023
- Article
Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.