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(385)
- Faculty Publications (98)
- 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
Keywords: Pooling; Generalist Model; Specialist Model; Service Operations; Management; Financial Services Industry; United States
Shih, Willy C., and Antonio Moreno. "Vanguard Retail Operations (B)." Harvard Business School Supplement 620-105, June 2020. (Revised August 2020.)
- 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
Keywords: Analytics; Human Resource Management; Data; Workforce; Hiring; Talent Management; Forecasting; Predictive Analytics; Organizational Behavior; Recruiting; Analytics and Data Science; Forecasting and Prediction; Recruitment; Selection and Staffing; Talent and Talent Management
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (B)." Harvard Business School Supplement 420-086, March 2020.
- 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
Cui, Ruomeng, Santiago Gallino, Antonio Moreno, and Dennis J. Zhang. "The Operational Value of Social Media Information." Special Issue on Big Data in Supply Chain Management. Production and Operations Management 27, no. 10 (October 2018): 1749–1774.
- 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
Keywords: Data Science; Analytics and Data Science; Analysis; Customers; Household; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (B)." Harvard Business School Supplement 119-026, August 2018. (Revised September 2018.)
- 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
Keywords: Data Science; Data Analytics; Investing; Loans; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction; Business Model
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (A): Data Analytic Thinking (Abridged)." Harvard Business School Case 119-020, August 2018. (Revised September 2018.)
- 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.
... View Details
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Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (B): Decision Trees & Random Forests." Harvard Business School Supplement 119-021, August 2018. (Revised September 2018.)
- 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
Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (C): Gradient Boosting & Payoff Matrix." Harvard Business School Supplement 119-022, August 2018. (Revised September 2018.)
- 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
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (A)." Harvard Business School Case 418-013, February 2018. (Revised December 2020.)
- 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
Keywords: Forecasting; Stress Testing; Interest Rates; Forecasting and Prediction; Risk Management; United States
Engle, Robert F., Guillaume Roussellet, and Emil N. Siriwardane. "Scenario Generation for Long Run Interest Rate Risk Assessment." Special Issue on Theoretical and Financial Econometrics: Essays in Honor of C. Gourieroux. Journal of Econometrics 201, no. 2 (December 2017): 333–347.
- 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
Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States
Toffel, Michael W., Dan Levy, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (A)." Harvard Business School Case 618-019, October 2017. (Revised April 2018.)
- April 2017
- Article
Financing Risk and Innovation
By: Ramana Nanda and Matthew Rhodes-Kropf
We provide a model of investment into new ventures that demonstrates why some places, times, and industries should be associated with a greater degree of experimentation by investors. Investors respond to financing risk―a forecast of limited future funding―by modifying... View Details
Nanda, Ramana, and Matthew Rhodes-Kropf. "Financing Risk and Innovation." Management Science 63, no. 4 (April 2017): 901–918.
- 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
Siriwardane, Emil. "The Probability of Rare Disasters: Estimation and Implications." Harvard Business School Working Paper, No. 16-061, November 2015.
- 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
Keywords: Expected Returns; Discount Rates; Holding Period Returns; Fundamental Valuation; Present Value; Valuation; Investment Return
Lyle, Matthew R., and Charles C.Y. Wang. "The Cross Section of Expected Holding Period Returns and Their Dynamics: A Present Value Approach." Journal of Financial Economics 116, no. 3 (June 2015): 505–525.
- 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
Greenwood, Robin, and Samuel G. Hanson. "Waves in Ship Prices and Investment." Quarterly Journal of Economics 130, no. 1 (February 2015): 55–109.
- 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
Hammond, Janice H., and Aldo Sesia. "Caesars Entertainment." Harvard Business School Case 615-031, October 2014. (Revised August 2018.)
- 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
Keywords: Churn; Retention; Contractual Settings; Access Services; Hidden Markov Models; RFM; Latent Variable Models; Customer Value and Value Chain; Consumer Behavior
Ascarza, Eva, and Bruce G.S. Hardie. "A Joint Model of Usage and Churn in Contractual Settings." Marketing Science 32, no. 4 (July–August 2013): 570–590.
- 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
Turut, Ozge, and Elie Ofek. "Innovation Strategy and Entry Deterrence." Journal of Economics & Management Strategy 12, no. 3 (Fall 2012).
- June 2012
- Case
Innovating at AT&T: Partnering to Lead the Broadband Revolution
By: Lynda M. Applegate, Phillip Andrews and Kerry Herman
In 2010, the U.S. retail market value for next-generation non-handset wirelessly-enabled devices was just over $1 billion. By 2011 it had grown 1,141% to $13.2 billion and was forecast to reach $24.7 billion in 2015. At the same time, user demand for data was surging... View Details
Keywords: Innovation & Entrepreneurship; Team Leadership; Emerging Technologies; Business Models; Business To Business; Corporate Vision; Growth Strategy; Corporate Culture; Innovation and Invention; Corporate Entrepreneurship; Partners and Partnerships; Leadership; Mobile and Wireless Technology; Growth and Development Strategy; Globalized Firms and Management; Business Model; Technology Industry; United States
Applegate, Lynda M., Phillip Andrews, and Kerry Herman. "Innovating at AT&T: Partnering to Lead the Broadband Revolution." Harvard Business School Case 812-124, June 2012.