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(840)
- News (77)
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- Faculty Publications (635)
Show Results For
- All HBS Web
(840)
- News (77)
- Research (639)
- Events (12)
- Multimedia (4)
- Faculty Publications (635)
- 2019
- Article
Ridesharing with Driver Location Preferences
By: Duncan Rheingans-Yoo, Scott Duke Kominers, Hongyao Ma and David C. Parkes
We study revenue-optimal pricing and driver compensation in ridesharing platforms when drivers have heterogeneous preferences over locations. If a platform ignores drivers' location preferences, it may make inefficient trip dispatches; moreover, drivers may strategize... View Details
Keywords: Ridesharing; Pricing; Compensation and Benefits; Geographic Location; Market Design; Mathematical Methods
Rheingans-Yoo, Duncan, Scott Duke Kominers, Hongyao Ma, and David C. Parkes. "Ridesharing with Driver Location Preferences." Proceedings of the International Joint Conference on Artificial Intelligence (2019): 557–564.
- June 2024
- Article
Redistributive Allocation Mechanisms
By: Mohammad Akbarpour, Piotr Dworczak and Scott Duke Kominers
Many scarce public resources are allocated at below-market-clearing prices, and sometimes for free. Such "non-market" mechanisms sacrifice some surplus, yet they can potentially improve equity. We develop a model of mechanism design with redistributive concerns. Agents... View Details
Akbarpour, Mohammad, Piotr Dworczak, and Scott Duke Kominers. "Redistributive Allocation Mechanisms." Journal of Political Economy 132, no. 6 (June 2024): 1831–1875. (Authors' names are in certified random order.)
- May 2010
- Teaching Note
Flare Fragrances Company, Inc.: Analyzing Growth Opportunities (Brief Case)
By: John A. Quelch and Lisa D. Donovan
Teaching note to case #4550 View Details
- February 2010
- Supplement
Marketing Analysis Toolkit: Breakeven Analysis (CW)
By: Thomas J. Steenburgh and Jill Avery
This Excel worksheet contains sample problems, prebuilt Excel models to run breakeven analyses, and charts and graphs which help visualize the results. It is designed to accompany "Marketing Analysis Toolkit: Breakeven Analysis." View Details
- June 2008
- Article
The Market for Mergers and the Boundaries of the Firm
By: Matthew Rhodes-Kropf and David Robinson
We relate the property rights theory of the firm to empirical regularities in the market for mergers and acquisitions. We first show that high market-to-book acquirers typically do not purchase low market-to-book targets. Instead, mergers pair together firms with... View Details
Rhodes-Kropf, Matthew, and David Robinson. "The Market for Mergers and the Boundaries of the Firm." Journal of Finance 63, no. 3 (June 2008): 1169–1211.
- 2008
- Working Paper
Taste Heterogeneity, IIA, and the Similarity Critique
By: Thomas J. Steenburgh and Andrew Ainslie
The purpose of this paper is to show that allowing for taste heterogeneity does not address the similarity critique of discrete-choice models. Although IIA may technically be broken in aggregate, the mixed logit model allows neither a given individual nor the... View Details
Steenburgh, Thomas J., and Andrew Ainslie. "Taste Heterogeneity, IIA, and the Similarity Critique." Harvard Business School Working Paper, No. 09-049, September 2008.
- Blog
When Generations Learn Together
continues to give me new insights just from the way he views a case here at HBS and when we discuss deals and operating improvement opportunities in my business. It's also a huge benefit to learn from the application of analytical tools that he has developed through... View Details
- 25 Aug 2022
- News
Labs Enable Large-scale Research
Professor of Computer Science and Applied Mathematics at the Harvard John A. Paulson School of Engineering & Applied Sciences REINVENTING THE FUTURE OF BUSINESS Harnessing the Tools of the Digital Age Understanding the Digital, Data, and... 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
Keywords: Model Persuasion; Analytics and Data Science; Forecasting and Prediction; Mathematical Methods; Framework
Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- May 2011
- Teaching Note
The Morrison Company (Brief Case)
By: Steven C. Wheelwright and Paul Meyers
Teaching Note for 4564. View Details
- October 2011
- Article
The Surprising Power of Age-Dependent Taxes
This article provides a new, empirically driven application of the dynamic Mirrleesian framework by studying a feasible and potentially powerful tax reform: age-dependent labor income taxation. I show analytically how age dependence improves policy on both the... View Details
Weinzierl, Matthew C. "The Surprising Power of Age-Dependent Taxes." Review of Economic Studies 78, no. 4 (October 2011): 1490–1518. (Also Harvard Business School Working Paper, No. 11-114, May 2011.)
- 2011
- Working Paper
Better-reply Dynamics in Deferred Acceptance Games
In this paper we address the question of learning in a two-sided matching mechanism that utilizes the deferred acceptance algorithm. We consider a repeated matching game where at each period agents observe their match and have the opportunity to revise their strategy... View Details
Keywords: Learning; Marketplace Matching; Outcome or Result; Game Theory; Mathematical Methods; Strategy
Haeringer, Guillaume, and Hanna Halaburda. "Better-reply Dynamics in Deferred Acceptance Games." Harvard Business School Working Paper, No. 11-126, June 2011.
- 2009
- Working Paper
Technology Innovation and Diffusion as Sources of Output and Asset Price Fluctuations
By: Diego A. Comin, Mark Gertler and Ana Maria Santacreu
We develop a model in which innovations in an economy's growth potential are an important driving force of the business cycle. The framework shares the emphasis of the recent "new shock" literature on revisions of beliefs about the future as a source of fluctuations,... View Details
Keywords: Business Cycles; Economic Growth; Asset Pricing; Technological Innovation; Mathematical Methods; System Shocks; Technology Adoption
Comin, Diego A., Mark Gertler, and Ana Maria Santacreu. "Technology Innovation and Diffusion as Sources of Output and Asset Price Fluctuations." Harvard Business School Working Paper, No. 09-134, May 2009. (Revise and Resubmit at the Journal of Political Economy.)
- 28 Mar 2018
- News
Fueling the Future
of Boston, she had a half dozen jobs (lawn mowing, farm stand, newspaper delivery) by the time she was 15. “Once I learned I could make money and have freedom, I was all about capitalizing on opportunities,” she observes. She attended Princeton, studying View Details
Keywords: Jill Radsken
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- October 1, 2021
- Article
An Evaluation of Cross-efficiency Methods: With an Application to Warehouse Performance.
By: B.M. Balk, M.R. De Koster, Christian Kaps and J.L. Zofio
Cross-efficiency measurement is an extension of Data Envelopment Analysis that allows for tie-breaking ranking of the Decision Making Units (DMUs) using all the peer evaluations. In this article we examine the theory of cross-efficiency measurement by comparing a... View Details
Keywords: Efficiency Analysis; Performance Benchmarking; Warehousing; Analytics and Data Science; Performance Evaluation; Measurement and Metrics; Mathematical Methods
Balk, B.M., M.R. De Koster, Christian Kaps, and J.L. Zofio. "An Evaluation of Cross-efficiency Methods: With an Application to Warehouse Performance." Art. 126261. Applied Mathematics and Computation 406 (October 1, 2021).
- 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
Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
- 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
Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).
- November–December 2018
- Article
Online Network Revenue Management Using Thompson Sampling
By: Kris J. Ferreira, David Simchi-Levi and He Wang
We consider a network revenue management problem where an online retailer aims to maximize revenue from multiple products with limited inventory constraints. As common in practice, the retailer does not know the consumer's purchase probability at each price and must... View Details
Keywords: Online Marketing; Revenue Management; Revenue; Management; Marketing; Internet and the Web; Price; Mathematical Methods
Ferreira, Kris J., David Simchi-Levi, and He Wang. "Online Network Revenue Management Using Thompson Sampling." Operations Research 66, no. 6 (November–December 2018): 1586–1602.