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(1,226)
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- Faculty Publications (309)
Show Results For
- All HBS Web
(1,226)
- People (20)
- News (193)
- Research (699)
- Events (5)
- Multimedia (11)
- Faculty Publications (309)
- 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.
- 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.
- 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.
- 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
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. (Revised April 2023.)
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... View Details
- 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).
- 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.)
- August 2015 (Revised January 2017)
- Technical Note
From Correlation to Causation
By: Feng Zhu and Karim R. Lakhani
To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details
Zhu, Feng, and Karim R. Lakhani. "From Correlation to Causation." Harvard Business School Technical Note 616-009, August 2015. (Revised January 2017.)
- 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.)
- 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.
- 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.
- Article
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by... View Details
Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology
Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 19 Sep 2023
- HBS Case
How Will the Tech Titans Behind ChatGPT, Bard, and LLaMA Make Money?
The dizzying explosion of generative artificial intelligence platforms has been the big business story of the past year, but how they’ll make money and how smart companies can use them wisely are the questions that will dominate the next... View Details
- 05 Jul 2006
- Working Paper Summaries
Measuring Consumer and Competitive Impact with Elasticity Decompositions
- 2019
- Article
Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading
By: Iavor I Bojinov and Neil Shephard
We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. Our approach allows the estimation of a broad class of these estimands and exact randomization based p-values for testing causal... View Details
Bojinov, Iavor I., and Neil Shephard. "Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading." Journal of the American Statistical Association 114, no. 528 (2019): 1665–1682.
- 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.