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Show Results For
- All HBS Web
(10,856)
- People (64)
- News (3,419)
- Research (3,982)
- Events (30)
- Multimedia (61)
- Faculty Publications (1,445)
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- 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.
- June 10, 2022
- Article
What Top Executives Can Learn from Junior Employees
Having reached the pinnacle of their careers, many top executives think their learning days are over. Their role, as they see it, is to make pronouncements, define strategy and impart to others the benefits of their vast experience—that is, to tell the employees below... View Details
Kanter, Rosabeth Moss. "What Top Executives Can Learn from Junior Employees." Wall Street Journal (online) (June 10, 2022).
- 01 Sep 2021
- Op-Ed
How Women Can Learn from Even Biased Feedback
ask herself one question: “What can I learn that will make me better?” By staying focused on this question, she found she was able to avoid feeling strong emotions and reflect more thoughtfully on the... View Details
Keywords: by Francesca Gino
- 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
- 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
- 18 Mar 2018
- Working Paper Summaries
Thanks for Nothing: Expressing Gratitude Invites Exploitation by Competitors
- 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
- 22 Mar 2021
- Research & Ideas
How to Learn from the Big Mistake You Almost Make
psychological safety as opposed to near misses that are framed as successes,” she says. The ‘goldmine’ of avoided catastrophes By framing near misses as important learning opportunities, as well as View Details
- 21 Jan 2011
- Working Paper Summaries
Learning from Customers in Outsourcing: Individual and Organizational Effects
- 17 Feb 2003
- Research & Ideas
Rating Fund Managers by the Company They Keep
Many tools for rating the performance of mutual funds and their managers rely heavily on past performance. But what about the future? Now comes a system devised by Randolph B. Cohen and Joshua D. Coval of Harvard Business School, and... View Details
Keywords: by Ann Cullen
- 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).
- 2020
- Working Paper
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry
Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Harvard Business School Working Paper, No. 19-091, February 2019. (Revised May 2020. Accepted at the Journal of Marketing Research.)
- 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).
- 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
- 06 Dec 2017
- Working Paper Summaries
Trials and Terminations: Learning from Competitors' R&D Failures
Keywords: by Joshua Lev Krieger
- 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).)
- 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.
- 31 Oct 2004
- What Do You Think?
Should the Wisdom of Crowds Influence Our Thinking About Leadership?
the nature of leadership affirmed by the "wisdom of crowds" is clearly circumscribed, according to others. Jack Hughes, for example, says, "The Wisdom of Crowds has effectively shattered the narrow view that the right... View Details
Keywords: by James Heskett
- 17 Aug 2020
- Working Paper Summaries
Of Learning and Forgetting: Centrism, Populism, and the Legitimacy Crisis of Globalization
Keywords: by Rawi Abdelal
- 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