Publications
Publications
Show Results For
- All HBS Web
(142)
- Faculty Publications (28)
Page 1 of 28
Results →
- 2025
- Working Paper
How to Choose Among Technologies with Learning Curves: Making Better Investment Decisions
By: Christian Kaps and Arielle Anderer
Learning curves, the fact that technologies improve as a function of cumulative experience or investment, are desirable-think inexpensive solar panels or higher performing semiconductors. But, for firms that need to pick one technology among several candidates, such as... View Details
- January–February 2025
- Article
The Double-Edged Sword of Exemplar Similarity
By: Majid Majzoubi, Eric Zhao, Tiona Zuzul and Greg Fisher
We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and... View Details
- October 2024
- Article
Canary Categories
By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
- 2023
- Working Paper
Targeting, Personalization, and Engagement in an Agricultural Advisory Service
By: Susan Athey, Shawn Cole, Shanjukta Nath and Jessica Zhu
ICT is increasingly used to deliver customized information in developing countries. We
examine whether individually targeting the timing of automated voice calls meaningfully
increases engagement in an agricultural advisory service. We define, estimate, and... View Details
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... 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
- 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
- 2021
- Article
Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation
By: Benjamin B. Lockwood, Afras Sial and Matthew C. Weinzierl
Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness—for the purposes of policymaking and evaluation—is to design policy that takes these... View Details
- January 2021
- Article
Turbulence, Firm Decentralization and Growth in Bad Times
By: Philippe Aghion, Nicholas Bloom, Brian Lucking, Raffaella Sadun and John Van Reenen
What is the optimal form of firm organization during “bad times”? We present a model of delegation within the firm to show that the effect is ambiguous. The greater turbulence following macro shocks may benefit decentralized firms because the value of local information... View Details
- Article
Robust and Stable Black Box Explanations
By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani
As machine learning black boxes are increasingly being deployed in real-world applications, there
has been a growing interest in developing post hoc explanations that summarize the behaviors
of these black boxes. However, existing algorithms for generating such... View Details
- 2020
- Working Paper
Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation
By: Benjami Lockwood, Afras Y. Sial and Matthew C. Weinzierl
Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness—for the purposes of policymaking and evaluation—is to design policy that takes these... View Details
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
- November 2018 (Revised May 2019)
- Case
California Closets: Organizing the Customer Experience
By: Boris Groysberg and Annelena Lobb
California Closets had used robust net promoter score (NPS) data, surveyed across its locations, to create a more consistent and satisfying customer experience. CEO Bill Barton wanted to further optimize the customer experience around best practices. He also wanted to... View Details
- 2018
- Working Paper
Opportunistic Returns and Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets
By: Chaithanya Bandi, Antonio Moreno, Donald Ngwe and Zhiji Xu
We investigate how dynamic pricing can lead to more product returns in the online retail industry. Using detailed sales data of more than two million transactions from the Indian online retail market, where price promotions are very common, we document two types of... View Details
- Article
Popular Acceptance of Inequality Due to Innate Brute Luck and Support for Classical Benefit-based Taxation
U.S. survey respondents' views on distributive justice differ in two specific, related ways from what is conventionally assumed in modern optimal tax research. When expressing their preferences over allocations in stylized, hypothetical scenarios meant to isolate key... View Details
- May 2017
- Article
Experimental Evidence of Pooling Outcomes Under Information Asymmetry
By: William Schmidt and Ryan W. Buell
Operational decisions under information asymmetry can signal a firm's prospects to less-informed parties, such as investors, customers, competitors, and regulators. Consequently, managers in these settings often face a tradeoff between making an optimal decision and... View Details
- 2018
- Working Paper
Opportunistic Returns and Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets
By: Chaithanya Bandi, Antonio Moreno, Donald Ngwe and Zhiji Xu
We investigate how dynamic pricing can lead to higher operational costs through more product returns in the online retail industry. Dynamic pricing has been widely applied by many online retailers. Research has shown that, in response to dynamic pricing, some customers... View Details