Publications
Publications
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- All HBS Web
(5,466)
- Faculty Publications (878)
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
- March 2023
- Article
Not from Concentrate: Collusion in Collaborative Industries
By: Jordan M. Barry, John William Hatfield, Scott Duke Kominers and Richard Lowery
The chief principle of antitrust law and theory is that reducing market concentration—having more, smaller firms instead of fewer, bigger ones—reduces anticompetitive behavior. We demonstrate that this principle is fundamentally incomplete.
In many... View Details
In many... View Details
Keywords: Antitrust; Antitrust Law; Antitrust Theory; Law And Economics; Collusion; Collaboration; Collaborative Industries; Regulation; ＂Repeated Games＂; IPOs; Initial Public Offerings; Underwriters; Real Estate; Real Estate Agents; Realtors; Syndicated Markets; Syndication; Brokers; Market Concentration; Competition; Law; Economics; Collaborative Innovation and Invention; Governing Rules, Regulations, and Reforms; Game Theory; Initial Public Offering
- February 2023 (Revised February 2024)
- Case
Doing Business in Helsinki, Finland
By: Martin A. Sinozich, Lena Duchene, Tonia Labruyere and Daniela Beyersdorfer
This case examines the challenges and opportunities of doing business in Finland. It highlights Finland's economic transformation in the decades leading up to 2024 in the context of its history, culture, and politics. The case gives an overview of some of the main... View Details
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
- Working Paper
Group Fairness in Dynamic Refugee Assignment
By: Daniel Freund, Thodoris Lykouris, Elisabeth Paulson, Bradley Sturt and Wentao Weng
Ensuring that refugees and asylum seekers thrive (e.g., find employment) in their host countries is a profound humanitarian goal, and a primary driver of employment is the geographic
location within a host country to which the refugee or asylum seeker is... View Details
- January 2023
- Case
Year Up: Measuring and Scaling Impact
Year Up, a non-profit that provides training and practical work experience to low-income young people, has for years prioritized impact measurement. By 2022, it had built a robust body of evidence demonstrating that its program yields higher earnings for participants.... View Details
- January 2023
- Case
Cleave Therapeutics: Taking a Risk on Oncology Drug Discovery
By: Regina Herzlinger and Brian Walker
What should a successful executive (HBS Baker Scholar) assess as her next move as the CEO of a firm with a promising and yet uncertain new drug? Amy Burroughs’ mandate to successfully commercialize Cleave Therapeutics’ drug for a cancer with no current successful... View Details
- December 2022 (Revised June 2023)
- Case
Hacking the U.S. Election: Russia's Misinformation Campaign
By: Shikhar Ghosh
The case discusses the relatively low technology approach used by Russia to influence the U.S. Presidential Election in 2016. Although political parties manipulating the media was not a new phenomenon, the Russians ran a broad, well-financed, and sophisticated social... View Details
- 2022
- Article
Becoming a Learning Organization While Enhancing Performance: The Case of LEGO
By: Thomas Borup Kristensen, Henrik Saabye and Amy Edmondson
Purpose - The purpose of this study is to empirically test how problem-solving lean practices, along with
leaders as learning facilitators in an action learning approach, can be transferred from a production context to a
knowledge work context for the purpose... View Details
- December 2022
- Article
The Contribution of Price Growth to Pharmaceutical Revenue Growth in the United States: Evidence from Medicines Sold in Retail Pharmacies
By: Pragya Kakani, Michael Chernew and Amitabh Chandra
Context: To what extent does pharmaceutical revenue growth depend on new medicines versus increasing prices for existing medicines? Moreover, does using list prices, as is commonly done, instead of prices net of confidential rebates offered by manufacturers, which are... View Details
- December 2022
- Article
The Rise of People Analytics and the Future of Organizational Research
By: Jeff Polzer
Organizations are transforming as they adopt new technologies and use new sources of data, changing the experiences of employees and pushing organizational researchers to respond. As employees perform their daily activities, they generate vast digital data. These data,... View Details
- 2022
- Article
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations
By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju
A critical problem in the field of post hoc explainability is the lack of a common foundational goal among methods. For example, some methods are motivated by function approximation, some by game theoretic notions, and some by obtaining clean visualizations. This... View Details
- November 2022
- Article
Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings
By: Kristin Blesch, Oliver P. Hauser and Jon M. Jachimowicz
Prior research has found mixed results on how economic inequality is related to various outcomes. These contradicting findings may in part stem from a predominant focus on the Gini coefficient, which only narrowly captures inequality. Here, we conceptualize the... View Details
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
- 2022
- Book
Healthy Buildings: How Indoor Spaces Can Make You Sick—or Keep You Well
By: Joseph G. Allen and John D. Macomber
For too long we’ve designed buildings that haven’t focused on the people inside—their health, their ability to work effectively, and what that means for the bottom line. An authoritative introduction to a movement whose vital importance is now all too clear, Healthy... View Details
- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats... View Details
- 2022
- Article
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations
By: Jessica Dai, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach and Himabindu Lakkaraju
As post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to ensure that the quality of the resulting explanations is consistently high across all subgroups of a population. For instance, it... View Details
- 2022
- Article
Nonparametric Subset Scanning for Detection of Heteroscedasticity
By: Charles R. Doss and Edward McFowland III
We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning... View Details
- 2022
- Article
Towards Robust Off-Policy Evaluation via Human Inputs
By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset... View Details
- June 2022
- Article
The Use and Misuse of Patent Data: Issues for Finance and Beyond
By: Josh Lerner and Amit Seru
Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing... View Details