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- Faculty Publications (215)
- September 26, 2018
- Article
Ownership and Power Structure: Together at Last
By: Laura Alfaro, Nicholas Bloom, Paola Conconi, Harald Fadinger, Patrick Legros, Andrew Newman, Raffaella Sadun and John Van Reenen
Economists have largely ignored the deep interdependency between integration and delegation. This column describes a new theory of integration and delegation choices aimed at shedding light on how these distinct elements of organizational design interact. Contrary to...
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Alfaro, Laura, Nicholas Bloom, Paola Conconi, Harald Fadinger, Patrick Legros, Andrew Newman, Raffaella Sadun, and John Van Reenen. "Ownership and Power Structure: Together at Last." Vox, CEPR Policy Portal (September 26, 2018).
- 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...
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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 April 2019)
- Supplement
Chateau Winery (B): Supervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those...
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Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
- 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...
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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.
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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...
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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.)
- August 2018
- Article
Extrapolation and Bubbles
By: Nicholas Barberis, Robin Greenwood, Lawrence Jin and Andrei Shleifer
We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals: an average of the asset’s past price changes and the asset’s degree of overvaluation. The two signals are in conflict, and investors...
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Barberis, Nicholas, Robin Greenwood, Lawrence Jin, and Andrei Shleifer. "Extrapolation and Bubbles." Journal of Financial Economics 129, no. 2 (August 2018): 203–227.
- June 2018
- Article
The Power of Workplace Rewards: Using Self-Determination Theory to Understand Why Reward Satisfaction Matters for Workers Around the World
By: Anais Thibault Landry and A.V. Whillans
How can workplace rewards promote employee well-being and engagement? To answer these questions, we utilized self-determination theory to examine whether reward satisfaction predicted employee well-being, job satisfaction, intrinsic motivation, and affective...
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Keywords:
Workplace;
Rewards;
Motivation;
Employees;
Satisfaction;
Motivation and Incentives;
Welfare
Landry, Anais Thibault, and A.V. Whillans. "The Power of Workplace Rewards: Using Self-Determination Theory to Understand Why Reward Satisfaction Matters for Workers Around the World." Compensation & Benefits Review 50, no. 3 (June 2018): 123–148.
- 2018
- Working Paper
Channeled Attention and Stable Errors -- Previous Working Version
A common critique of models of mistaken beliefs is that people should recognize their error after observations they thought were unlikely. This paper develops a framework for assessing when a given error is likely to be discovered, in the sense that the error-maker...
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Gagnon-Bartsch, Tristan, Matthew Rabin, and Joshua Schwartzstein. "Channeled Attention and Stable Errors -- Previous Working Version." Harvard Business School Working Paper, No. 18-108, June 2018.
- May 2018
- Article
Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing...
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Keywords:
Forecasting Models;
Simulation Methods;
Regional Economic Activity: Growth, Development, Environmental Issues, And Changes;
Geographic Location;
Local Range;
Transition;
Analytics and Data Science;
Measurement and Metrics;
Economic Growth;
Forecasting and Prediction
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
- April 2018
- Article
Compromised Ethics in Hiring Processes? How Referrers' Power Affects Employees' Reactions to Referral Practices
By: Rellie Derfler-Rozin, Bradford Baker and F. Gino
In this paper, we explore referral-based hiring practices and show how a referrer’s power (relative to the hiring manager) influences other organizational members’ support (or lack thereof) for who is hired through perceptions of the hiring manager’s motives and...
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Derfler-Rozin, Rellie, Bradford Baker, and F. Gino. "Compromised Ethics in Hiring Processes? How Referrers' Power Affects Employees' Reactions to Referral Practices." Academy of Management Journal 61, no. 2 (April 2018): 615–636.
- February 2018
- Case
EmQuest: Travel Distribution in the Digital Era
By: Karim R. Lakhani and Gamze Yucaoglu
EmQuest, Emirates Group’s travel distribution company, must decide what to do with its contract with the global distribution system it uses, Sabre. Since its founding in 1988, EmQuest was servicing travel agents in the MENA region by providing a connection to over 400...
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Keywords:
UAE;
Decision;
Business Model;
Competitive Strategy;
Growth and Development Strategy;
Decision Choices and Conditions;
Business Strategy;
Value Creation;
Change Management;
Emerging Markets;
For-Profit Firms;
Competitive Advantage;
Travel Industry;
United Arab Emirates
Lakhani, Karim R., and Gamze Yucaoglu. "EmQuest: Travel Distribution in the Digital Era." Harvard Business School Case 618-040, February 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...
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Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (A)." Harvard Business School Case 418-013, February 2018. (Revised December 2020.)
- February 2018
- Article
Retention Futility: Targeting High-Risk Customers Might Be Ineffective.
By: Eva Ascarza
Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models...
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Keywords:
Retention/churn;
Proactive Churn Management;
Field Experiments;
Heterogeneous Treatment Effect;
Machine Learning;
Customer Relationship Management;
Risk Management
Ascarza, Eva. "Retention Futility: Targeting High-Risk Customers Might Be Ineffective." Journal of Marketing Research (JMR) 55, no. 1 (February 2018): 80–98.
- 2017
- Working Paper
Investment Timing with Costly Search for Financing
By: Samuel Antill
I develop a dynamic model of investment timing in which firms must first choose when to search for external financing. Search is costly and the arrival of investors is uncertain, leading to delay in financing and investment. Depending on parameters, my model can...
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Keywords:
Real Options;
Search And Bargaining;
Time-varying Financial Conditions;
Investment;
Venture Capital;
Mathematical Methods
Antill, Samuel. "Investment Timing with Costly Search for Financing." Working Paper, December 2017.
- 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...
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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 November 2017)
- Case
NYC311
By: Constantine E. Kontokosta, Mitchell Weiss, Christine Snively and Sarah Gulick
Joe Morrisroe, executive director for NYC311, had some gut instincts but no definitive answer to the question he was just asked by one of the mayor’s deputies: “Are some communities being underserved by 311? How do we know we are hearing from the right people?” Founded...
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Keywords:
New York City;
NYC;
311;
NYC311;
Big Data;
Equal Access;
Bias;
Data Analysis;
Public Entrepreneurship;
Urban Informatics;
Predictive Analytics;
Chief Data Officer;
Data Analytics;
Cities;
City Leadership;
Analytics and Data Science;
Analysis;
Prejudice and Bias;
Entrepreneurship;
Public Sector;
City;
Public Administration Industry;
New York (city, NY)
- 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...
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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.)
- 2017
- Working Paper
Biased Beliefs About Random Samples: Evidence from Two Integrated Experiments
By: Daniel J. Benjamin, Don A. Moore and Matthew Rabin
This paper describes results of a pair of incentivized experiments on biases in judgments about random samples. Consistent with the Law of Small Numbers (LSN), participants exaggerated the likelihood that short sequences and random subsets of coin flips would be...
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Benjamin, Daniel J., Don A. Moore, and Matthew Rabin. "Biased Beliefs About Random Samples: Evidence from Two Integrated Experiments." NBER Working Paper Series, No. 23927, October 2017.
- 2017
- Working Paper
Tort Reform and Innovation
By: Alberto Galasso and Hong Luo
Current academic and policy debates focus on the impact of tort reforms on physicians’ behavior and medical costs. This paper examines whether these reforms also affect incentives to develop new technologies. We develop a theoretical model which predicts that the...
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Keywords:
Lawsuits and Litigation;
Laws and Statutes;
Innovation and Invention;
Medical Devices and Supplies Industry
Galasso, Alberto, and Hong Luo. "Tort Reform and Innovation." Working Paper, August 2017. (Accepted for publication in Journal of Law and Economics.)