Filter Results:
(2,885)
Show Results For
- All HBS Web
(2,885)
- News (476)
- Research (2,212)
- Events (43)
- Multimedia (14)
- Faculty Publications (1,428)
Show Results For
- All HBS Web
(2,885)
- News (476)
- Research (2,212)
- Events (43)
- Multimedia (14)
- Faculty Publications (1,428)
- January–February 2023
- Article
Forecasting COVID-19 and Analyzing the Effect of Government Interventions
By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details
Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction
Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
- 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.
- April 2024
- Article
Loneliness and Emotion Regulation in Daily Life
By: Lameese Eldesouky, Amit Goldenberg and Kate Ellis
There is a growing understanding that emotion regulation (ER) abilities can be an important buffer for loneliness. However, most of this research is cross-sectional. Thus, it is unknown whether loneliness is associated with ER in momentary evaluations and can predict... View Details
Eldesouky, Lameese, Amit Goldenberg, and Kate Ellis. "Loneliness and Emotion Regulation in Daily Life." Art. 112566. Personality and Individual Differences 221 (April 2024).
Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers
1. Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to... View Details
- October 2000
- Article
The Equity Share in New Issues and Aggregate Stock Returns
By: Malcolm Baker and Jeffrey Wurgler
The share of equity issues in total new equity and debt issues is a strong predictor of U.S. stock market returns between 1928 and 1997. In particular, firms issue more equity than debt just before periods of low market returns. The equity share in new issues has... View Details
Keywords: Equity; Borrowing and Debt; Stocks; Markets; Debt Securities; Forecasting and Prediction; Accounting Industry; United States
Baker, Malcolm, and Jeffrey Wurgler. "The Equity Share in New Issues and Aggregate Stock Returns." Journal of Finance 55, no. 5 (October 2000): 2219–57.
Ashley V. Whillans
Ashley Whillans is the Volpert Family Associate Professor of Business Administration at the Harvard Business School, where she teaches the Motivation and Incentives course to MBA students. Professor Whillans earned her PhD in Social Psychology from the University of... View Details
- 2009
- Article
Compelled to Help: Effects of Direct and Indirect Exchange on Perceived Obligation in Professional Networks
By: Roy Y.J. Chua, Billian Sullivan and Michael W. Morris
This research examines felt obligation to help others in employees' and managers' professional networks using a social exchange perspective. We hypothesize that obligation toward others would follow the norms of both direct and indirect reciprocity. Direct reciprocity... View Details
Keywords: Perspective; Conflict of Interests; Research; Surveys; Networks; Forecasting and Prediction; Social Issues
Chua, Roy Y.J., Billian Sullivan, and Michael W. Morris. "Compelled to Help: Effects of Direct and Indirect Exchange on Perceived Obligation in Professional Networks." Academy of Management Annual Meeting Proceedings (2009).
- 18 Nov 2015
- News
The internet of things will bring makers closer to customers
- 03 Jan 2014
- News
Book Review: 'Fortune Tellers' by Walter Friedman
- August 2003
- Article
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." Quarterly Journal of Economics 118, no. 3 (August 2003): 969–1006.
- 07 Jun 2019
- Working Paper Summaries
Reflexivity in Credit Markets
- 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.)
- December 2023
- Article
Save More Today or Tomorrow: The Role of Urgency in Precommitment Design
By: Joseph Reiff, Hengchen Dai, John Beshears, Katherine L. Milkman and Shlomo Benartzi
To encourage farsighted behaviors, past research suggests that marketers may be wise to invite consumers to pre-commit to adopt them “later.” However, the authors propose that people will draw different inferences from different types of pre-commitment offers, and that... View Details
Reiff, Joseph, Hengchen Dai, John Beshears, Katherine L. Milkman, and Shlomo Benartzi. "Save More Today or Tomorrow: The Role of Urgency in Precommitment Design." Journal of Marketing Research (JMR) 60, no. 6 (December 2023): 1095–1113.
- 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.
- October 2016 (Revised April 2018)
- Case
DataXu: Selling Ad Tech
By: Frank V. Cespedes, John Deighton, Lisa Cox and Olivia Hull
DataXu served marketers by buying digital advertising for brands using its demand-side platform. It sought a way to build a more predictable revenue stream in the very transactional media marketplace, and hoped that two new marketing analytics products would give it a... View Details
Keywords: Sales Management; Pricing; Programmatic Ad Buying; ＂Marketing Analytics＂; Advertising Technology; Sales; Digital Marketing; Marketing Strategy; Advertising Campaigns; Product Launch; Product Positioning; Media; Technology Industry; Advertising Industry; Boston; Massachusetts
Cespedes, Frank V., John Deighton, Lisa Cox, and Olivia Hull. "DataXu: Selling Ad Tech." Harvard Business School Case 817-012, October 2016. (Revised April 2018.)
- Article
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to... View Details
Keywords: Machine Learning; Marketing Applications; Knowledge; Technological Innovation; Core Relationships; Marketing; Applications and Software
Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Marketing Letters 31, no. 4 (December 2020): 393–404.
- 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.
- fall 2007
- Article
The Design of Patent Pools: The Determinants of Licensing Rules
By: Josh Lerner, Marcin Strojwas and Jean Tirole
Patent pools are an important but little-studied economic institution. In this paper, we first make a set of predictions about the licensing terms associated with patent pools. The theoretical framework predicts that (a) pools consisting of complementary patents are... View Details
Keywords: Governing Rules, Regulations, and Reforms; Collaborative Innovation and Invention; Patents; Rights
Lerner, Josh, Marcin Strojwas, and Jean Tirole. "The Design of Patent Pools: The Determinants of Licensing Rules." RAND Journal of Economics 38, no. 3 (fall 2007): 610–625. (Earlier version distributed as National Bureau of Economic Research Working Paper No. 9680.)
- March 2002 (Revised December 2002)
- Background Note
A Note on Corporate Venturing and New Business Creation
By: David A. Garvin
Presents an introduction and overview of corporate venturing. Describes the need for companies to create new businesses, the stages in the process, predictable problems and challenges, the strengths and weaknesses of alternative approaches such as internal venture... View Details
Keywords: Business Plan; Business Startups; Forecasting and Prediction; Venture Capital; Problems and Challenges
Garvin, David A. "A Note on Corporate Venturing and New Business Creation." Harvard Business School Background Note 302-091, March 2002. (Revised December 2002.)