Filter Results:
(3,798)
Show Results For
- All HBS Web
(11,269)
- People (74)
- News (2,855)
- Research (3,798)
- Events (45)
- Multimedia (238)
- Faculty Publications (2,360)
Show Results For
- All HBS Web
(11,269)
- People (74)
- News (2,855)
- Research (3,798)
- Events (45)
- Multimedia (238)
- Faculty Publications (2,360)
Sort by
- 26 Feb 2008
- Working Paper Summaries
Long-Run Stockholder Consumption Risk and Asset Returns
- June 2024
- Article
Inflation with COVID Consumption Baskets
By: Alberto Cavallo
The Covid-19 pandemic led to changes in expenditure patterns that introduced significant bias in the measurement of Consumer Price Index (CPI) inflation. Using publicly-available data on card transactions, I updated the official CPI weights and re-calculated inflation... View Details
Keywords: COVID; Consumer Expenditures; CPI; Inflation; Consumer Behavior; Inflation and Deflation; Health Pandemics
Cavallo, Alberto. "Inflation with COVID Consumption Baskets." Special Issue on The Global Economy: Looking Back, Moving Forward, Part II. IMF Economic Review 72, no. 2 (June 2024): 902–917.
- January 2022 (Revised November 2023)
- Case
Expanding the Culture of Learning at Kraft Heinz
By: Ashley V. Whillans and Carolyn Watson
The Kraft Heinz Company (KHC) was an American food company formed in 2015 by the merger of Kraft Foods Group, Inc and the H.J. Heinz Company. The company sold food products like Heinz Ketchup, Kraft Mac & Cheese, Kool-Aid, and Philadelphia cream cheese to supermarkets,... View Details
Keywords: Learning; Culture; Work Culture; Workplace Practices; Mergers; Mergers and Acquisitions; Competitive Advantage; Human Capital; Training; Performance Evaluation; Growth and Development; Personal Development and Career; Employee Relationship Management; Organizational Change and Adaptation; Organizational Culture; Food and Beverage Industry
Whillans, Ashley V., and Carolyn Watson. "Expanding the Culture of Learning at Kraft Heinz." Harvard Business School Case 922-036, January 2022. (Revised November 2023.)
- December 1982
- Article
Determinants of Food Consumption in American Households
By: D. Schmalensee and J. Quelch
Schmalensee, D., and J. Quelch. "Determinants of Food Consumption in American Households." Marketing Science Institute, Report (December 1982). (Cambridge, Mass., Report 82:112.)
- September 2002
- Article
Pricing and the Psychology of Consumption
By: John Gourville and Dilip Soman
Gourville, John, and Dilip Soman. "Pricing and the Psychology of Consumption." Harvard Business Review 80, no. 9 (September 2002).
- 2008
- Working Paper
Long-Run Stockholder Consumption Risk and Asset Returns
By: Christopher J. Malloy, Tobias J. Moskowitz and Annette Vissing-Jorgensen
We provide new evidence on the success of long-run risks in asset pricing by focusing on the risks borne by stockholders. Exploiting micro-level household consumption data, we show that long-run stockholder consumption risk better captures cross-sectional... View Details
Malloy, Christopher J., Tobias J. Moskowitz, and Annette Vissing-Jorgensen. "Long-Run Stockholder Consumption Risk and Asset Returns." Harvard Business School Working Paper, No. 08-060, January 2008.
- 2023
- Working Paper
The Effects of Cryptocurrency Wealth on Household Consumption and Investment
By: Darren Aiello, Scott R. Baker, Tetyana Balyuk, Marco Di Maggio, Mark J. Johnson and Jason Kotter
This paper uses transaction-level data across millions of accounts to identify cryptocurrency investors and evaluate how fluctuations in individual crypto wealth affect household consumption, equity investment, and local real estate markets. We estimate an MPC out of... View Details
Keywords: Cryptocurrency; Marginal Propensity To Consume; Household Balance Sheet; Real Estate; Etherium; Bitcoin; Investment; Housing; Spending
Aiello, Darren, Scott R. Baker, Tetyana Balyuk, Marco Di Maggio, Mark J. Johnson, and Jason Kotter. "The Effects of Cryptocurrency Wealth on Household Consumption and Investment." Harvard Business School Working Paper, No. 23-077, June 2023.
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
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; AI and Machine Learning
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- Article
Learning Models for Actionable Recourse
By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely... View Details
Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- Article
The Effects of Increased Serving Sizes on Consumption
By: Chris Hydock, Anne Wilson and Karthik Easwar
Hydock, Chris, Anne Wilson, and Karthik Easwar. "The Effects of Increased Serving Sizes on Consumption." Appetite 101 (June 2016): 71–79.
- 18 Nov 2016
- Conference Presentation
Rawlsian Fairness for Machine Learning
By: Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
Motivated by concerns that automated decision-making procedures can unintentionally lead to discriminatory behavior, we study a technical definition of fairness modeled after John Rawls' notion of "fair equality of opportunity". In the context of a simple model of... View Details
Joseph, Matthew, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Rawlsian Fairness for Machine Learning." Paper presented at the 3rd Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), November 18, 2016.
- 2010
- Chapter
Consumer Policy: Business and the Politics of Consumption
By: Gunnar Trumbull
Trumbull, Gunnar. "Consumer Policy: Business and the Politics of Consumption." Chap. 27 in The Oxford Handbook of Business and Government, edited by David Coen, Wyn Grant, and Graham Wilson, 622–642. Oxford: Oxford University Press, 2010.
- June 2017
- Article
Conspicuous Consumption of Time: When Busyness and Lack of Leisure Time Become a Status Symbol
By: Silvia Bellezza, Neeru Paharia and Anat Keinan
While research on conspicuous consumption has typically analyzed how people spend money on products that signal status, we investigate conspicuous consumption in relation to time. We argue that a busy and overworked lifestyle, rather than a leisurely lifestyle, has... View Details
Bellezza, Silvia, Neeru Paharia, and Anat Keinan. "Conspicuous Consumption of Time: When Busyness and Lack of Leisure Time Become a Status Symbol." Journal of Consumer Research 44, no. 1 (June 2017): 118–138.
- June 2015 (Revised November 2016)
- Case
2012 Obama Campaign: Learning in the Field
By: Leonard A. Schlesinger and Jason Gray
The development and utilization of an intentional Field learning strategy developed for the Obama for President campaign in 2012 following an after action Review calling for it after the 2008 elections View Details
Keywords: Training; Political Campaigns; Learning Organizations; Learning; Political Elections; Organizational Change and Adaptation; United States
Schlesinger, Leonard A., and Jason Gray. "2012 Obama Campaign: Learning in the Field." Harvard Business School Case 315-127, June 2015. (Revised November 2016.)
- Teaching Interest
Big Data Analytics and Machine Learning
Big data in the context of marketing, management, and innovation strategy. Machine Learning algorithms and tools.
View Details
View Details
- Article
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
- July–September 2020
- Article
Innovation Contest: Effect of Perceived Support for Learning on Participation
By: Olivia Jung, Andrea Blasco and Karim R. Lakhani
Background: Frontline staff are well positioned to conceive improvement opportunities based on first-hand knowledge of what works and does not work. The innovation contest may be a relevant and useful vehicle to elicit staff ideas. However, the success of the... View Details
Keywords: Contest; Innovation; Employee Engagement; Organizational Learning; Health Care; Health Care Delivery; Innovation and Invention; Organizations; Learning; Employees; Perception; Health Care and Treatment
Jung, Olivia, Andrea Blasco, and Karim R. Lakhani. "Innovation Contest: Effect of Perceived Support for Learning on Participation." Health Care Management Review 45, no. 3 (July–September 2020): 255–266.
- 2021
- Working Paper
Deep Learning for Two-Sided Matching
By: Sai Srivatsa Ravindranatha, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers and David Parkes
We initiate the use of a multi-layer neural network to model two-sided matching and to explore the design space between strategy-proofness and stability. It is well known that both properties cannot be achieved simultaneously but the efficient frontier in this design... View Details
Keywords: Strategy-proofness; Deep Learning; Two-Sided Platforms; Marketplace Matching; Balance and Stability
Srivatsa Ravindranatha, Sai, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers, and David Parkes. "Deep Learning for Two-Sided Matching." Working Paper, July 2021.
- December 2019
- Article
Invest in Information or Wing It? A Model of Dynamic Pricing with Seller Learning
By: Guofang Huang, Hong Luo and Jing Xia
Pricing idiosyncratic products is often challenging because the seller, ex ante, lacks information about the demand for individual items. This paper develops a model of dynamic pricing for idiosyncratic products that features the optimal stopping structure and a seller... View Details
Keywords: Dynamic Pricing; Idiosyncratic Products; Item-specific Demand; Demand Uncertainty; Active Seller Learning; The Value Of Information; Price; Information; Value; Learning
Huang, Guofang, Hong Luo, and Jing Xia. "Invest in Information or Wing It? A Model of Dynamic Pricing with Seller Learning." Management Science 65, no. 12 (December 2019): 5556–5583.