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- Faculty Publications (141)
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- All HBS Web (316)
- Faculty Publications (141)
- 9 AM – 10 AM EST, 09 Jan 2019
- HBS Online
HBS Online Business Analytics
Develop a data mindset and the analytical skills to interpret and communicate data. This course will demystify data analysis and equip you with concrete skills to apply in your work or further studies.
Program Dates: January 9, 2019 - March 6, 2019 View Details
- 9 AM – 10 AM EDT, 07 Aug 2019
- HBS Online
HBS Online Business Analytics
Develop a data mindset and the analytical skills to interpret and communicate data. This course will demystify data analysis and equip you with concrete skills to apply in your work or further studies.
Program Dates: August 7, 2019 - October 2, 2019 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
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (A)." Harvard Business School Case 418-013, February 2018. (Revised December 2020.)
- August 2018 (Revised September 2018)
- Case
Predicting Purchasing Behavior at PriceMart (A)
By: Srikant M. Datar and Caitlin N. Bowler
This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details
Keywords: Data Science; Analytics and Data Science; Analysis; Consumer Behavior; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (A)." Harvard Business School Case 119-025, August 2018. (Revised September 2018.)
- January 2022
- Technical Note
Introduction to Capital Structure Analytics
By: Samuel Antill and Ted Berk
This technical note provides an overview of key analytical approaches that are useful in assessing the appropriateness of a firm’s capital structure and funding plan. This note introduces basic quantitative tools and metrics that are commonly used as inputs to this... View Details
Keywords: Budgets and Budgeting; Business Plan; Forecasting and Prediction; Borrowing and Debt; Corporate Finance; Capital Structure; Cash Flow; Financial Liquidity; Financial Management; Financing and Loans
Antill, Samuel, and Ted Berk. "Introduction to Capital Structure Analytics." Harvard Business School Technical Note 222-061, January 2022.
- August 2008
- Article
Economic Links and Predictable Returns
By: Lauren Cohen and Andrea Frazzini
This paper finds evidence of return predictability across economically linked firms. We test the hypothesis that in the presence of investors subject to attention constraints, stock prices do not promptly incorporate news about economically related firms, generating... View Details
Keywords: Economics; Price; Assets; Analytics and Data Science; Customers; Stocks; Equity; Strategy; Investment Return; Forecasting and Prediction
Cohen, Lauren, and Andrea Frazzini. "Economic Links and Predictable Returns." Journal of Finance 63, no. 4 (August 2008). (Winner of Smith Breeden Prize for the Best Paper Published in the Journal of Finance in Asset Pricing (Distinguished Paper) 2008. Winner of Chicago Quantitative Alliance Academic Paper Competition. First Prize presented by Chicago Quantitative Alliance. Winner of BSI Gamma Foundation Research Grant presented by BSI Gamma Foundation.)
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
- March 2022 (Revised July 2022)
- Technical Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised July 2022.)
- 2009
- Case
What People Want (and How to Predict It)
By: Thomas H. Davenport and Jeanne G. Harris
Historically, neither the creators nor the distributors of cultural products such as books or movies have used analytics -- data, statistics, predictive modeling -- to determine the likely success of their offerings. Instead, companies relied on the brilliance of... View Details
Keywords: Product Development; Creativity; Customer Satisfaction; Forecasting and Prediction; Markets; Business Model; Publishing Industry; Motion Pictures and Video Industry
Davenport, Thomas H., and Jeanne G. Harris. "What People Want (and How to Predict It)." 2009.
- Web
Online Business Analytics Course | HBS Online
throughout the course. Learn about bringing this course to your organization . Learner Stories 92% strengthened analytical skills I'm using regression analysis and other statistical concepts from Business View Details
- June 2021
- Article
From Predictions to Prescriptions: A Data-driven Response to COVID-19
By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details
Keywords: COVID-19; Health Pandemics; AI and Machine Learning; Forecasting and Prediction; Analytics and Data Science
Bertsimas, Dimitris, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg, and Cynthia Zeng. "From Predictions to Prescriptions: A Data-driven Response to COVID-19." Health Care Management Science 24, no. 2 (June 2021): 253–272.
- 09 Feb 2007
- Working Paper Summaries
Do Corporate Social Responsibility Ratings Predict Corporate Social Performance?
- 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.)
- July 2019
- Article
'Forward Flow': A New Measure to Quantify Free Thought and Predict Creativity
By: Kurt Gray, Stephen Anderson, Eric Evan Chen, John Michael Kelly, Michael S. Christian, John Patrick, Laura Huang, Yoed N. Kenett and Kevin Lewis
When the human mind is free to roam, its subjective experience is characterized by a continuously evolving stream of thought. Although there is a technique that captures people’s streams of free thought—free association—its utility for scientific research is undermined... View Details
Gray, Kurt, Stephen Anderson, Eric Evan Chen, John Michael Kelly, Michael S. Christian, John Patrick, Laura Huang, Yoed N. Kenett, and Kevin Lewis. "'Forward Flow': A New Measure to Quantify Free Thought and Predict Creativity." American Psychologist 74, no. 5 (July 2019): 539–554.
- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
- Article
Algorithms Need Managers, Too
By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan
Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on... View Details
Keywords: Machine Learning; Algorithms; Predictive Analytics; Management; Big Data; Analytics and Data Science
Luca, Michael, Jon Kleinberg, and Sendhil Mullainathan. "Algorithms Need Managers, Too." Harvard Business Review 94, nos. 1/2 (January–February 2016): 96–101.
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing... View Details
- August 2022
- Article
What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features
By: Shunyuan Zhang, Dokyun Lee, Param Vir Singh and Kannan Srinivasan
We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel dataset... View Details
Keywords: Sharing Economy; Airbnb; Property Demand; Computer Vision; Deep Learning; Image Feature Extraction; Content Engineering; Property; Marketing; Demand and Consumers
Zhang, Shunyuan, Dokyun Lee, Param Vir Singh, and Kannan Srinivasan. "What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features." Management Science 68, no. 8 (August 2022): 5644–5666.
- 2023
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial
intelligence and machine learning business applications. Although prior discussions
highlight advances in methods (along the dimensions of data, computing power, and
algorithms)... View Details
Keywords: Analytics and Data Science
Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
- Article
Consumer Neuroscience: Advances in Understanding Consumer Psychology
By: Uma R. Karmarkar and Carolyn Yoon
While the study of consumer behavior has been enriched by improved abilities to generate new insights, many of the mechanisms underlying judgments and decision making remain difficult to investigate. In this review, we highlight some of the ways in which our... View Details
Keywords: Consumer Neuroscience; Neuroscience; Neuroeconomics; Consumer Psychology; Customer Behavior; Predictive Analytics; Neural Prediction; Neuroimaging; fMRI; Eye-tracking; Consumer Behavior; Marketing
Karmarkar, Uma R., and Carolyn Yoon. "Consumer Neuroscience: Advances in Understanding Consumer Psychology." Current Opinion in Psychology 10 (August 2016): 160–165.