Filter Results:
(838)
Show Results For
- All HBS Web
(838)
- News (77)
- Research (639)
- Events (11)
- Multimedia (4)
- Faculty Publications (636)
Show Results For
- All HBS Web
(838)
- News (77)
- Research (639)
- Events (11)
- Multimedia (4)
- Faculty Publications (636)
- 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.
- 01 Dec 2017
- News
Ink: Alumni Book Recommendations
understanding of human psychology, without the acceptance that we are all crazy, irrational, impulsive, emotionally driven animals, all the raw intelligence and mathematical logic in the world is little help in the fraught, shifting... View Details
- 01 Jun 2000
- News
Professors Fox, Mace Remembered
established the Bertrand Fox Publication Fund to support the dissemination of research studies and other faculty manuscripts. A native of Wisconsin, Fox earned his AB in mathematics and astronomy in 1929 from Northwestern University,... View Details
- November 1990
- Case
Chemplan Corp.: Paint-Rite Division
By: Paul A. Vatter
An exercise with data that allows a discussion of regression analysis as a tool for forecasting and understanding structure. View Details
Vatter, Paul A. "Chemplan Corp.: Paint-Rite Division." Harvard Business School Case 191-090, November 1990.
- 1979
- Chapter
Research Methods and Data Analysis: The Challenge of Knowing How to Do What About Why
By: T. M. Amabile and W. DeJong
- 2017
- Working Paper
Minimizing Justified Envy in School Choice: The Design of New Orleans' OneApp
By: Atila Abdulkadiroglu, Yeon-Koo Che, Parag A. Pathak, Alvin E. Roth and Oliver Tercieux
In 2012, New Orleans Recovery School District (RSD) became the first U.S. district to unify charter and traditional public school admissions in a single-offer assignment mechanism known as OneApp. The RSD also became the first district to use a mechanism based on Top... View Details
Keywords: Education; Decision Choices and Conditions; Marketplace Matching; Mathematical Methods; Design
Abdulkadiroglu, Atila, Yeon-Koo Che, Parag A. Pathak, Alvin E. Roth, and Oliver Tercieux. "Minimizing Justified Envy in School Choice: The Design of New Orleans' OneApp." NBER Working Paper Series, No. 23265, March 2017.
- Article
Assent-maximizing Social Choice
By: Katherine A. Baldiga and Jerry R. Green
We take a decision theoretic approach to the classic social choice problem, using data on the frequency of choice problems to compute social choice functions. We define a family of social choice rules that depend on the population's preferences and on the probability... View Details
Keywords: Decision Choices and Conditions; Theory; Measurement and Metrics; Mathematical Methods; Society
Baldiga, Katherine A., and Jerry R. Green. "Assent-maximizing Social Choice." Social Choice and Welfare 40, no. 2 (February 2013): 439–460.
- August 1983
- Background Note
Balance of Payments: Accounting and Presentation
By: David B. Yoffie
Provides an overview of balance of payments accounting and analytical presentation of balance of payments data. Includes sample transactions to illustrate the application of the basic accounting principles and definitions of the standard balances. View Details
Yoffie, David B. "Balance of Payments: Accounting and Presentation." Harvard Business School Background Note 384-005, August 1983.
- 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
Keywords: COVID-19; Forecasting and Prediction; Health Pandemics; Mathematical Methods; Partners and Partnerships
Cramer, Estee Y., Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li, and et al. "Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States." e2113561119. Proceedings of the National Academy of Sciences 119, no. 15 (April 12, 2022). (See full author list here.)
- 2019
- Working Paper
Intelligent Artificiality: Algorithmic Microfoundations for Strategic Problem Solving
By: Mihnea Moldoveanu
This paper introduces algorithmic micro-foundations for formulating and solving strategic problems. It shows how the languages and disciplines of theoretical computer science, “artificial intelligence,” and computational complexity theory can be used to devise a set of... View Details
Keywords: Problems and Challenges; Analysis; Strategy; Framework; Management Analysis, Tools, and Techniques; Mathematical Methods
Moldoveanu, Mihnea. "Intelligent Artificiality: Algorithmic Microfoundations for Strategic Problem Solving." Harvard Business School Working Paper, No. 19-072, January 2019. (Revised February 2019.)
- October 2005 (Revised February 2010)
- Background Note
Calculating Free Cash Flows
By: Robin Greenwood and David S. Scharfstein
Outlines the mechanics of calculating free cash flows from historical and proforma financial statements. Focuses on the mechanical process of transforming numbers from financial forecasts into cash flows. View Details
Greenwood, Robin, and David S. Scharfstein. "Calculating Free Cash Flows." Harvard Business School Background Note 206-028, October 2005. (Revised February 2010.)
- 05 Jun 2015
- Blog Post
The HBS Investment
simple equation for what the cost amounts to from a career or personal growth perspective. Simply having two years to take time and reflect is unreal and shouldn’t be subject to mathematical analysis. Add to this, you get these two years... View Details
- 01 Jan 2008
- News
Jeffrey R. Immelt, MBA 1982
Chairman & CEO, GE Return to Alumni Achievement Awards main page EARLIER EUDUCATION Dartmouth College, 1978 B.A., Applied Mathematics LESSONS FROM HBS “Understanding the difference between knowledge and intelligence.” ADVICE TO STUDENTS... 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.
- 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
Han, Tessa, Suraj Srinivas, and Himabindu Lakkaraju. "Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022). (Best Paper Award, International Conference on Machine Learning (ICML) Workshop on Interpretable ML in Healthcare.)
- 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
Dai, Jessica, Sohini Upadhyay, Ulrich Aivodji, Stephen Bach, and Himabindu Lakkaraju. "Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 203–214.