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Show Results For
- All HBS Web
(10,693)
- People (64)
- News (3,257)
- Research (3,905)
- Events (24)
- Multimedia (60)
- Faculty Publications (1,368)
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- August 2018 (Revised April 2019)
- Case
Chateau Winery (A): Unsupervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers’ purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups... View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
- 27 May 2008
- Sharpening Your Skills
Sharpening Your Skills: Thinking About Global
Sharpening Your Skills dives into the HBS Working Knowledge archives to bring together articles on ways to improve your business skills. Questions To Be Answered Are global brands effective? How should I think about strategy in a flat... View Details
- 2018
- Working Paper
Learning to Become a Taste Expert
By: Kathryn A. Latour and John A. Deighton
Evidence suggests that consumers seek to become more expert about hedonic products to enhance their enjoyment of future consumption occasions. Current approaches to becoming an expert center on cultivating an analytic mindset. In the present research the authors... View Details
Keywords: Hedonic; Wine; Expertise; Holistic; Analytic; Sensory; Taste; Learning; Experience and Expertise; Analysis; Perception
Latour, Kathryn A., and John A. Deighton. "Learning to Become a Taste Expert." Harvard Business School Working Paper, No. 18-107, June 2018.
- 2023
- Working Paper
Evaluation and Learning in R&D Investment
By: Alexander P. Frankel, Joshua L. Krieger, Danielle Li and Dimitris Papanikolaou
We examine the role of spillover learning in shaping the value of exploratory versus incremental
R&D. Using data from drug development, we show that novel drug candidates generate more
knowledge spillovers than incremental ones. Despite being less likely to reach... View Details
Frankel, Alexander P., Joshua L. Krieger, Danielle Li, and Dimitris Papanikolaou. "Evaluation and Learning in R&D Investment." Harvard Business School Working Paper, No. 23-074, May 2023. (NBER Working Paper Series, No. 31290, May 2023.)
- February 2013
- Article
Learning from Roger Fisher
Roger Fisher's career and writings not only offer lessons about negotiation but also about how an academic, especially in a professional school such as law or business, can make an important, positive difference in the world. By his relentless engagement in vexing... View Details
Sebenius, James K. "Learning from Roger Fisher." Harvard Law Review 126, no. 4 (February 2013): 893–898.
- February 26, 2024
- Article
Making Workplaces Safer Through Machine Learning
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
Machine learning algorithms can dramatically improve regulatory effectiveness. This short article describes the authors' scholarly work that shows how the U.S. Occupational Safety and Health Administration (OSHA) could have reduced nearly twice as many occupational... View Details
Keywords: Government Experimentation; Auditing; Inspection; Evaluation; Process Improvement; Government Administration; AI and Machine Learning; Safety; Governing Rules, Regulations, and Reforms
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Making Workplaces Safer Through Machine Learning." Regulatory Review (February 26, 2024).
- October 2018
- Case
Learning How to Honnold
By: Eugene F. Soltes, Sara Hess and Dutch Leonard
Alex Honnold is the world’s most accomplished free climber. To many, climbing sheer vertical faces of rock—like the famed El Capitan—without a rope is viewed as not simply risky but reckless. Honnold contrasts this sentiment by presenting his perspective on risk taking... View Details
Soltes, Eugene F., Sara Hess, and Dutch Leonard. "Learning How to Honnold." Harvard Business School Case 119-043, October 2018.
- July–August 2023
- Article
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
Problem Definition: We consider the problem of demand learning and pricing for retailers who offer assortments of substitutable products that change frequently, e.g., due to limited inventory, perishable or time-sensitive products, or the retailer’s desire to... View Details
Keywords: Experiments; Pricing And Revenue Management; Retailing; Demand Estimation; Pricing Algorithm; Marketing; Price; Demand and Consumers; Mathematical Methods
Ferreira, Kris, and Emily Mower. "Demand Learning and Pricing for Varying Assortments." Manufacturing & Service Operations Management 25, no. 4 (July–August 2023): 1227–1244. (Finalist, Practice-Based Research Competition, MSOM (2021) and Finalist, Revenue Management & Pricing Section Practice Award, INFORMS (2019).)
- 18 Mar 2018
- Working Paper Summaries
Thanks for Nothing: Expressing Gratitude Invites Exploitation by Competitors
- 21 Aug 2019
- Research & Ideas
What Machine Learning Teaches Us about CEO Leadership Style
is a writer based in the Boston area. [Image: ConceptCafe] Related Reading: Will Machine Learning Make You a Better Manager? The Better Way to Forecast the Future Working Paper: CEO Behavior and Firm Performance What do you View Details
Keywords: by Michael Blanding
- June 2024
- Article
Rationalizing Outcomes: Interdependent Learning in Competitive Markets
By: Anoop R. Menon and Dennis Yao
In this article we use simulation models to explore interdependent learning in competitive markets. Such interactions require attention to both the mental representations held by the management of the focal firm as well as the beliefs of that management about the... View Details
Keywords: Mental Models; Strategic Interactions; Rationalization; Explanation-based View; Competition
Menon, Anoop R., and Dennis Yao. "Rationalizing Outcomes: Interdependent Learning in Competitive Markets." Strategy Science 9, no. 2 (June 2024): 97–117.
- Article
Active World Model Learning with Progress Curiosity
By: Kuno Kim, Megumi Sano, Julian De Freitas, Nick Haber and Daniel Yamins
World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact abstractions of high bandwidth sensory inputs, the ability to plan across long temporal... View Details
Kim, Kuno, Megumi Sano, Julian De Freitas, Nick Haber, and Daniel Yamins. "Active World Model Learning with Progress Curiosity." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
- 21 Jan 2011
- Working Paper Summaries
Learning from Customers in Outsourcing: Individual and Organizational Effects
- Research Summary
Making Machine Learning Robust to Adversarial Attacks
The goal of this research is to ensure that machine learning models that we build and deploy are not easily susceptible to attacks by adversarial or malicious entities. View Details
- 13 Jun 2005
- Research & Ideas
From Turf Wars to Learning Curves: How Hospitals Adopt New Technology
influential
, PTCA has been used less frequently than in hospitals with less influential surgeons." And even if PTCA and other innovations make it past initial gatekeepers, it's a long road to adoption because of learning curves... View Details
- January 2008
- Article
Learning the Fine Art of Collaboration
By: Alan MacCormack and Theodore Forbath
Innovations are increasingly brought to the market by networks of firms, selected for their unique capabilities and operating in a coordinated manner. This collaborative model demands that firms develop different skills, yet despite this need, there is little guidance... View Details
Keywords: Digital Platforms
MacCormack, Alan, and Theodore Forbath. "Learning the Fine Art of Collaboration." Forethought. Special Issue on HBS Centennial. Harvard Business Review 86, no. 1 (January 2008): 10–11.
- 08 Sep 2009
- Research & Ideas
The Height Tax, and Other New Ways to Think about Taxation
reforms seem unlikely, but we are missing a large opportunity by avoiding them. In general, I hesitate to pass judgment on our tax system as a whole. My intuition is that tax theorists have as much or more to View Details
Keywords: by Martha Lagace
- 10 Apr 2008
- Working Paper Summaries
Where Does it Go? Spending by the Financially Constrained
- 06 Dec 2017
- Working Paper Summaries
Trials and Terminations: Learning from Competitors' R&D Failures
Keywords: by Joshua Lev Krieger
- 24 Sep 2014
- Op-Ed
Stop Thinking of Climate Change as a Religious or Political Issue
You sometimes hear people say things like, "I believe in global warming" or "I don't believe in climate change." It seems odd to approach climate change in this way, as though it were a question of belief, like religion. Most of the time when we confront uncertainty in... View Details