Publications
Publications
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- All HBS Web
(1,960)
- Faculty Publications (567)
- 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
- August 2021
- Article
Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders
By: Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett
This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories Project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British... View Details
- August 2021
- Article
Multiple Imputation Using Gaussian Copulas
By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky
Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use... View Details
- August 2021
- Article
The Undervalued Power of Self-relevant Research: The Case of Researching Retirement While Retiring
By: Teresa M. Amabile and Douglas T. (Tim) Hall
For decades, training in management research has emphasized objectivity, typically viewed as an arm’s length distance between the topic of the research and the interests of the researcher. This emphasis has led most scholars to avoid research topics of deep personal... 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
- 2021
- Article
Nudging the Commute: Using Behaviorally-Informed Interventions to Promote Sustainable Transportation
By: Ashley Whillans, Joseph Sherlock, Jessica Roberts, Shibeal O'Flaherty, Lyndsay Gavin, Holly Dykstra and Michael Daly
Dramatic reductions in carbon emissions must take place immediately. A human-centric method of reducing environmental impacts is to “nudge” employees away from single-occupancy vehicles (SOVs) toward more sustainable commuting options. While an abundance of research... 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
Population Interference in Panel Experiments
By: Iavor I Bojinov, Kevin Wu Han and Guillaume Basse
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in... View Details
- Mar 2021
- Conference Presentation
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
By: Seth Neel, Aaron Leon Roth and Saeed Sharifi-Malvajerdi
We study the data deletion problem for convex models. By leveraging techniques from convex optimization and reservoir sampling, we give the first data deletion algorithms that are able to handle an arbitrarily long sequence of adversarial updates while promising both... View Details
- 2021
- Working Paper
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the... View Details
- Article
Manage the Suppliers That Could Harm Your Brand: Know When to Avoid, Engage, or Drop Them
By: Jodi L Short and Michael W. Toffel
The pandemic has placed a new spotlight on working conditions in factories that supply global companies. To avert problems, firms often impose codes of conduct on their suppliers and perform audits to assess compliance. Do these measures help identify unethical... View Details
Keywords: Auditing; Agency Cost; Quality And Safety; Quality Management System; Quality Management; Unions; Environmental Management; Globalization; Goods and Commodities; Governance; Labor; Labor Unions; Wages; Working Conditions; Operations; Supply Chain; Safety; Quality; China; Bangladesh; Asia; Pakistan
- February 2021
- Tutorial
What is AI?
By: Tsedal Neeley
This video explores the elements that constitute artificial intelligence (AI). From its mathematical basis to current advances in AI, this video introduces students to data, tools, and statistical models that make a computer 'intelligent.' Through an explanation of... View Details
- February 2021
- Article
A Dynamic Theory of Multiple Borrowing
By: Daniel Green and Ernest Liu
Multiple borrowing—a borrower obtains overlapping loans from multiple lenders—is a common phenomenon in many credit markets. We build a highly tractable, dynamic model of multiple borrowing and show that, because overlapping creditors may impose default externalities... View Details
- 2021
- Article
Fundraising for Stigmatized Groups: A Text Message Donation Experiment
By: Katerina Linos, Laura Jakli and Melissa Carlson
As government welfare programming contracts and NGOs increasingly assume core aid functions, they must address a long-standing challenge—that people in need often belong to stigmatized groups. To study other-regarding behavior, we fielded an experiment through a... View Details
- 2021
- Article
Prisoners, Rooms, and Lightswitches
By: Daniel M. Kane and Scott Duke Kominers
We examine a new variant of the classic prisoners and lightswitches puzzle: A warden leads his n prisoners in and out of r rooms, one at a time, in some order, with each prisoner eventually visiting every room an arbitrarily large number of times. The... View Details
Keywords: Mathematical Methods
- 2021
- Article
Fair Algorithms for Infinite and Contextual Bandits
By: Matthew Joseph, Michael J Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
We study fairness in linear bandit problems. Starting from the notion of meritocratic fairness introduced in Joseph et al. [2016], we carry out a more refined analysis of a more general problem, achieving better performance guarantees with fewer modelling assumptions... View Details
- 2021
- Book
Harvard Business Review Family Business Handbook: How to Build and Sustain a Successful, Enduring Enterprise
By: Josh Baron and Rob Lachenauer
Navigate the complex decisions and critical relationships necessary to create and sustain a healthy family business--and business family. Though "family business" may sound like it refers only to mom-and-pop shops, businesses owned by families are among the most... View Details
- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details
- January 2021
- Article
Using Models to Persuade
By: Joshua Schwartzstein and Adi Sunderam
We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model... View Details
- Article
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to... View Details