Publications
Publications
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- All HBS Web
(1,026)
- Faculty Publications (218)
- 2022
- Working Paper
Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15... View Details
- April 12, 2022
- Article
Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States
By: Estee Y. Cramer, Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li and et al.
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models... View Details
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
- March 2022
- Article
Where to Locate COVID-19 Mass Vaccination Facilities?
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
- 2022
- Working Paper
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details
- January 10, 2022
- Article
The Link Between Income, Income Inequality, and Prosocial Behavior Around the World: A Multiverse Approach
By: Lucia Macchia and Ashley V. Whillans
The questions of whether high-income individuals are more prosocial than low-income individuals and whether income inequality moderates this effect have received extensive attention. We shed new light on this topic by analyzing a large-scale dataset with a... View Details
- 2022
- Working Paper
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet they have become more complex and harder to understand. To address this issue, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use explainability... View Details
- Article
Counterfactual Explanations Can Be Manipulated
By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... 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
- October 2021
- Article
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Nicolas Padilla and Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
- 2021
- Working Paper
Salience
By: Pedro Bordalo, Nicola Gennaioli and Andrei Shleifer
We review the fast-growing work on salience and economic behavior. Psychological research shows that salient stimuli attract human attention “bottom up” due to their high contrast with surroundings, their surprising nature relative to recalled experiences, or their... View Details
- August 2021 (Revised February 2024)
- Case
Data Science at the Warriors
By: Iavor I. Bojinov and Michael Parzen
The case explores the development and early growth of a data science team at the Golden State Warriors, an NBA team based in San Francisco. The case begins by explaining the initial rationale for investing in data science, then covers a debate on the appropriate team... View Details
- August 2021
- Supplement
Coats: Supply Chain Challenges: Spreadsheet Supplement
By: Willy C. Shih
Coats, the largest thread maker in the world, transformed its business to digital colour measurement so that it could respond better to customer demand in the garment industry for rapid product cycles and more fragmented colour choices. Its embrace of digital colour... View Details
- 2021
- Working Paper
Multiple Team Membership, Turnover, and On-Time Delivery: Evidence from Construction Services
By: Hise O. Gibson, Bradely R. Staats and Ananth Raman
Firms who want to compete in dynamic markets are finding that they must build more agile operations to ensure success. One way for a firm to increase organizational agility is to allocate employees to multiple project teams, simultaneously—a practice known as multiple... 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
- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical... View Details
- 2021
- Working Paper
Equilibrium Effects of Pay Transparency
By: Zoë B. Cullen and Bobak Pakzad-Hurson
The public discourse around pay transparency has focused on the direct effect: how workers seek
to rectify newly-disclosed pay inequities through renegotiations. The question of how wage-setting
and hiring practices of the firm respond in equilibrium has received... View Details
- May 2021
- Article
Choice Architecture in Physician–patient Communication: A Mixed-methods Assessment of Physicians' Competency
By: J. Hart, K. Yadav, S. Szymanski, A. Summer, A. Tannenbaum, J. Zlatev, D. Daniels and S.D. Halpern
Background: Clinicians’ use of choice architecture, or how they present options, systematically influences the choices made by patients and their surrogate decision makers. However, clinicians may incompletely understand this influence.... View Details
- 2021
- Working Paper
Property Rights and Urban Form
By: Simeon Djankov, Edward L. Glaeser, Valeria Perotti and Andrei Shleifer
How do the different elements in the standard bundle of property rights, including those of possession and transfer, influence the shape of cities? This paper incorporates insecure property rights into a standard model of urban land prices and density, and makes... View Details
- April 2021
- Case
Distinct Software
By: Das Narayandas, Arijit Sengupta and Jonathan Wray
Distinct Software (disguised name), a global enterprise software company, is at an important point in its growth trajectory where the luster of its mantra of “grow and win at any cost” has dimmed with increasing competition and margin pressures. To help navigate its... View Details