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- All HBS Web
(2,965)
- News (476)
- Research (2,199)
- Events (43)
- Multimedia (14)
- Faculty Publications (1,429)
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- 20 Oct 2011
- Research & Ideas
Getting the Marketing Mix Right
their FSL model, however, the results provided much greater detail about the potential effects of different marketing investments. For example, the model predicted that sales gains from DTCA and M&E would come primarily through... View Details
Keywords: by Dina Gerdeman
- 2014
- Chapter
Appetite, Consumption, and Choice in the Human Brain
By: Brian Knutson and Uma R. Karmarkar
Although linked, researchers have long distinguished appetitive from consummatory phases of reward processing. Recent improvements in the spatial and temporal resolution of neuroimaging techniques have allowed researchers to separately visualize different stages of... View Details
Knutson, Brian, and Uma R. Karmarkar. "Appetite, Consumption, and Choice in the Human Brain." Chap. 9 in The Interdisciplinary Science of Consumption, edited by Stephanie D. Preston, Morten L. Kringelbach, and Brian Knutson, 163–184. Cambridge, MA: MIT Press, 2014.
- 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... View Details
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).
- 25 Oct 2004
- Research & Ideas
Planning for Surprises
The train wreck that was Enron's collapse is only one big, blatant example of how some disasters catch us unawares—but shouldn't. In fact, according to Max H. Bazerman and Michael D. Watkins, many surprises in all types and sizes of organizations are View Details
Keywords: by Martha Lagace
- 07 Apr 2003
- Research & Ideas
Three Steps for Crisis Prevention
to actually mobilizing the resources required to stop it. We term this the "RPM process": recognition, prioritization, mobilization. Failure at any of these three stages will leave a company vulnerable to potentially devastating View Details
Keywords: by Michael D. Watkins & Max H. Bazerman
- December 2015
- Article
What Is Disruptive Innovation?
By: Clayton M. Christensen, Michael Raynor and Rory McDonald
For the past 20 years, the theory of disruptive innovation has been enormously influential in business circles and a powerful tool for predicting which industry entrants will succeed. Unfortunately, the theory has also been widely misunderstood, and the "disruptive"... View Details
Christensen, Clayton M., Michael Raynor, and Rory McDonald. "What Is Disruptive Innovation?" Harvard Business Review 93, no. 12 (December 2015): 44–53.
- December 1970 (Revised September 2006)
- Case
Harmon Foods, Inc.
Prediction and shipment has been a scheduling and budgetary problem. Multiple regression is suggested as a solution. Evaluation of regression coefficients leads to better understanding of trend, seasonality, and promotion effectiveness. View Details
Keywords: Demand and Consumers; Production; Forecasting and Prediction; Budgets and Budgeting; Manufacturing Industry; Food and Beverage Industry
Whiston, William B. "Harmon Foods, Inc." Harvard Business School Case 171-248, December 1970. (Revised September 2006.)
- Article
Can Analysts Assess Fundamental Risk and Valuation Uncertainty? An Empirical Analysis of Scenario-Based Value Estimates
By: Peter R. Joos, Joseph D. Piotroski and Suraj Srinivasan
We use a dataset of sell-side analysts' scenario-based valuation estimates to examine whether analysts reliably assess the risk surrounding a firm's fundamental value. We find that the spread in analysts' state-side contingent valuations captures the riskiness of... View Details
Keywords: Analyst Forecasts; Scenarios; Uncertainty; Risk and Uncertainty; Valuation; Forecasting and Prediction
Joos, Peter R., Joseph D. Piotroski, and Suraj Srinivasan. "Can Analysts Assess Fundamental Risk and Valuation Uncertainty? An Empirical Analysis of Scenario-Based Value Estimates." Journal of Financial Economics 121, no. 3 (September 2016): 645–663.
- 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... View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
- Research Summary
Making Machine Learning Models Interpretable
I work on developing various tools and methodologies which can help decision makers (e.g., doctors, managers) to better understand the predictions of machine learning models. View Details
- October 2019
- Article
Making Sense of Recommendations
By: Michael Yeomans, Anuj Shah, Sendhil Mullainathan and Jon Kleinberg
Computer algorithms are increasingly being used to predict people's preferences and make recommendations. Although people frequently encounter these algorithms because they are cheap to scale, we do not know how they compare to human judgment. Here, we compare computer... View Details
Keywords: Recommender Systems; Artificial Intelligence; Interpretability; Information Technology; Forecasting and Prediction; Decision Making; Attitudes
Yeomans, Michael, Anuj Shah, Sendhil Mullainathan, and Jon Kleinberg. "Making Sense of Recommendations." Journal of Behavioral Decision Making 32, no. 4 (October 2019): 403–414.
- 03 Mar 2014
- Research & Ideas
Facebook’s Future
Editor's note: Now 10 years old, Facebook's growth is starting to slow. That's one reason it purchased What'sApp last month in a jaw-dropping deal valued at $19 billion. What might the next decade be like? Harvard Business School Associate Professor Mikolaj Piskorski,... View Details
Keywords: by Mikolaj Piskorski
- 14 Mar 2023
- Cold Call Podcast
Can AI and Machine Learning Help Park Rangers Prevent Poaching?
- December 2020 (Revised March 2022)
- Teaching Note
Forecasting ClimaCell
By: Joshua Lev Krieger, Christopher Stanton and James Barnett
A weather technology startup, ClimaCell considers the R&D trade-offs and financing implications of pursuing a proposed contract with a major automobile maker, rather than continuing its focus on building a scalable, all-purpose weather prediction engine. View Details
- 2001
- Working Paper
When Does the Market Matter? Stock Prices and the Investment of Equity Dependent Firms
By: Malcolm Baker, Jeremy Stein and Jeffrey Wurgler
We use a simple model of corporate investment to determine when investment will be sensitive to non-fundamental movements in stock prices. The key cross-sectional prediction of the model is that stock prices will have a stronger impact on the investment of firms that... View Details
Baker, Malcolm, Jeremy Stein, and Jeffrey Wurgler. "When Does the Market Matter? Stock Prices and the Investment of Equity Dependent Firms." NBER Working Paper Series, No. 8750, December 2001. (First draft in 2001.)
- August 1998
- Background Note
Selling Books Online in Mid-1998
By: Jeffrey F. Rayport, Carin-Isabel Knoop and Cate Reavis
Provides an overview of the trends and predictions for the online book retail industry as of August 1998 and the current status of Amazon.com, BarnesandNoble.com, and other main players' online ventures. View Details
Rayport, Jeffrey F., Carin-Isabel Knoop, and Cate Reavis. "Selling Books Online in Mid-1998." Harvard Business School Background Note 899-038, August 1998.
- February 2024
- Article
Representation and Extrapolation: Evidence from Clinical Trials
By: Marcella Alsan, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein and Heidi L. Williams
This article examines the consequences and causes of low enrollment of Black patients in clinical
trials. We develop a simple model of similarity-based extrapolation that predicts that evidence is
more relevant for decision-making by physicians and patients when it... View Details
Keywords: Representation; Racial Disparity; Health Testing and Trials; Race; Equality and Inequality; Innovation and Invention; Pharmaceutical Industry
Alsan, Marcella, Maya Durvasula, Harsh Gupta, Joshua Schwartzstein, and Heidi L. Williams. "Representation and Extrapolation: Evidence from Clinical Trials." Quarterly Journal of Economics 139, no. 1 (February 2024): 575–635.
- 17 Dec 2020
- Research & Ideas
The 10 Most Popular Stories of 2020
about the most interesting business trends of the year, and your predictions for 2021. Top 10 most popular stories Merck CEO Ken Frazier Discusses a COVID Cure, Racism, and Why Leaders Need to Walk the Talk Ken Frazier, one of only four... View Details
Keywords: by Dina Gerdeman
- 2024
- Working Paper
Finance Without Exotic Risk
By: Pedro Bordalo, Nicola Gennaioli, Rafael La Porta and Andrei Shleifer
We address the joint hypothesis problem in cross-sectional asset pricing by using measured analyst expectations of earnings growth. We construct a firm-level measure of Expectations Based Returns (EBRs) that uses analyst forecast errors and revisions and shuts down any... View Details
Bordalo, Pedro, Nicola Gennaioli, Rafael La Porta, and Andrei Shleifer. "Finance Without Exotic Risk." NBER Working Paper Series, No. 33004, September 2024.
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.