Publications
Publications
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- All HBS Web
(390)
- Faculty Publications (96)
- 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
- June 2020 (Revised May 2022)
- Case
Vanguard Retail Operations (A)
By: Willy C. Shih and Antonio Moreno
The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or... View Details
- June 2020 (Revised August 2020)
- Supplement
Vanguard Retail Operations (B)
By: Willy C. Shih and Antonio Moreno
The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or... View Details
- March 2020
- Supplement
People Analytics at Teach For America (B)
By: Jeffrey T. Polzer and Julia Kelley
This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, situated one year after the A case, Managing Director Michael Metzger must decide how to apply his team's predictive models generated from the previous year’s data. View Details
- October 2018
- Article
The Operational Value of Social Media Information
By: Ruomeng Cui, Santiago Gallino, Antonio Moreno and Dennis J. Zhang
While the value of using social media information has been established in multiple business contexts, the field of operations and supply chain management have not yet explored the possibilities it offers in improving firms' operational decisions. This study attempts to... View Details
- August 2018 (Revised September 2018)
- Supplement
Predicting Purchasing Behavior at PriceMart (B)
By: Srikant M. Datar and Caitlin N. Bowler
Supplements the (A) case. In this case, Wehunt and Morse are concerned about the logistic regression model overfitting to the training data, so they explore two methods for reducing the sensitivity of the model to the data by regularizing the coefficients of the... View Details
- August 2018 (Revised September 2018)
- Case
LendingClub (A): Data Analytic Thinking (Abridged)
By: Srikant M. Datar and Caitlin N. Bowler
LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
- August 2018 (Revised September 2018)
- Supplement
LendingClub (B): Decision Trees & Random Forests
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) case. In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan.
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- August 2018 (Revised September 2018)
- Supplement
LendingClub (C): Gradient Boosting & Payoff Matrix
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details
- February 2018 (Revised December 2020)
- Case
People Analytics at Teach For America (A)
By: Jeffrey T. Polzer and Julia Kelley
As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization's strategy, including recruitment and selection. A few months earlier, former... View Details
- Article
Scenario Generation for Long Run Interest Rate Risk Assessment
By: Robert F. Engle, Guillaume Roussellet and Emil N. Siriwardane
We propose a statistical model of the term structure of U.S. treasury yields tailored for long-term probability-based scenario generation and forecasts. Our model is easy to estimate and is able to simultaneously reproduce the positivity, persistence, and factor... View Details
- October 2017 (Revised April 2018)
- Case
Improving Worker Safety in the Era of Machine Learning (A)
By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson
Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details
- 2015
- Working Paper
The Probability of Rare Disasters: Estimation and Implications
By: Emil Siriwardane
I analyze a rare disasters economy that yields a measure of the risk neutral probability of a macroeconomic disaster, p*t. A large panel of options data provides strong evidence that p*t is the single factor driving option-implied jump risk measures in the cross... View Details
- June 2015
- Supplement
Generating Higher Value at IBM (A): EPS Forecasting Model
By: Benjamin C. Esty and Scott Mayfield
This case analyzes IBM's financial performance and its capital allocation decisions over a 10-year period from 2004-2013, during which IBM returned more than $140B to shareholders through a combination of dividends and share repurchases. During this time, CEO Sam... View Details
- Article
The Cross Section of Expected Holding Period Returns and Their Dynamics: A Present Value Approach
By: Matthew R. Lyle and Charles C.Y. Wang
We provide a tractable model of firm-level expected holding period returns using two firm fundamentals—book-to-market ratio and ROE—and study the cross-sectional properties of the model-implied expected returns. We find that 1) firm-level expected returns and expected... View Details
- Article
Waves in Ship Prices and Investment
By: Robin Greenwood and Samuel G. Hanson
We study the link between investment boom and bust cycles and returns on capital in the dry bulk shipping industry. We show that high current ship earnings are associated with high used ship prices and heightened industry investment in new ships, but forecast low... View Details
- October 2014 (Revised August 2018)
- Case
Caesars Entertainment
By: Janice H. Hammond and Aldo Sesia
This case describes the introduction of a regression analysis model for forecasting guest arrivals to Caesars Palace hotel in Las Vegas, Nevada. The company will use the forecast to staff the front desk in the hotel. The staff is unionized and the company has little... View Details
Keywords: Forecasting; Staffing; Gaming; Gaming Industry; Hotel Industry; Decision Making; Forecasting and Prediction; Human Resources; Selection and Staffing; Entertainment; Games, Gaming, and Gambling; Operations; Service Delivery; Service Operations; Accommodations Industry; Travel Industry; Tourism Industry; Food and Beverage Industry; Las Vegas
- July–August 2013
- Article
A Joint Model of Usage and Churn in Contractual Settings
By: Eva Ascarza and Bruce G.S. Hardie
As firms become more customer-centric, concepts such as customer equity come to the fore. Any serious attempt to quantify customer equity requires modeling techniques that can provide accurate multiperiod forecasts of customer behavior. Although a number of researchers... View Details
- May 2013
- Teaching Note
Coca-Cola: Residual Income Valuation
By: Suraj Srinivasan and Edward J. Riedl
Teaching note for a case of the same title that introduces students to the residual income (also known as the abnormal earnings) valuation model using the firm Coca-Cola. Students are provided with the primary financial statements (through fiscal 2010) and forecast... View Details
- Fall 2012
- Article
Innovation Strategy and Entry Deterrence
By: Ozge Turut and Elie Ofek
We model an incumbent's decision to pursue radical or incremental innovation when facing a rival entrant. The radical innovation may yield lucrative financial returns but entails significant technological and market-related uncertainties. It is also particularly... View Details