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Show Results For
- All HBS Web
(11,290)
- People (74)
- News (2,859)
- Research (3,807)
- Events (45)
- Multimedia (240)
- Faculty Publications (2,370)
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- March – April 2002
- Article
The Local and Variegated Nature of Learning in Organizations: A Group-Level Perspective
By: Amy C. Edmondson
Edmondson, Amy C. "The Local and Variegated Nature of Learning in Organizations: A Group-Level Perspective." Organization Science 13, no. 2 (March–April 2002): 128–146.
- June, 2021
- Article
Learning from Deregulation: The Asymmetric Impact of Lockdown and Reopening on Risky Behavior During COVID-19
By: Edward L. Glaeser, Ginger Zhe Jin, Benjamin T. Leyden and Michael Luca
During the COVID-19 pandemic, states issued and then rescinded stay-at-home orders that restricted mobility. We develop a model of learning by deregulation, which predicts that lifting stay-at-home orders can signal that going out has become safer. Using restaurant... View Details
Keywords: COVID-19; Lockdown; Reopening; Impact; Coronavirus; Public Health Measures; Mobility; Health Pandemics; Governing Rules, Regulations, and Reforms; Consumer Behavior
Glaeser, Edward L., Ginger Zhe Jin, Benjamin T. Leyden, and Michael Luca. "Learning from Deregulation: The Asymmetric Impact of Lockdown and Reopening on Risky Behavior During COVID-19." Journal of Regional Science 61, no. 4 (June, 2021): 696–709.
- November 2023
- Case
Open Source Machine Learning at Google
Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts... View Details
Keywords: Decision Choices and Conditions; Technological Innovation; Open Source Distribution; Strategy; AI and Machine Learning; Applications and Software; Technology Industry; United States
Greenstein, Shane, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue, and James Barnett. "Open Source Machine Learning at Google." Harvard Business School Case 624-015, November 2023.
- February 2009
- Article
Learning in a New Cardiac Surgical Center: An Analysis of Precursor Events
By: Daniel R. Wong, Imtiaz S. Ali, David F. Torchiana, Arvind K. Agnihotri, Richard Bohmer and Thomas J. Vander Salm
Wong, Daniel R., Imtiaz S. Ali, David F. Torchiana, Arvind K. Agnihotri, Richard Bohmer, and Thomas J. Vander Salm. "Learning in a New Cardiac Surgical Center: An Analysis of Precursor Events." Surgery 145, no. 2 (February 2009): 131–137.
- June 1996 (Revised January 2000)
- Case
McKinsey & Co.: Managing Knowledge and Learning
Describes the development of McKinsey & Co. as a worldwide management consulting firm from 1926 to 1996. In particular, it focuses on the way in which McKinsey has developed structures, systems, processes, and practices to help it develop, transfer, and disseminate... View Details
Keywords: Management; Managerial Roles; Management Practices and Processes; Competitive Advantage; Global Range; Knowledge Dissemination; Business Processes; Consulting Industry
Bartlett, Christopher A. "McKinsey & Co.: Managing Knowledge and Learning." Harvard Business School Case 396-357, June 1996. (Revised January 2000.)
- 2005
- Working Paper
Team Learning Trade-Offs: When Improving One Critical Dimension of Performance Inhibits Another
By: Richard M.J. Bohmer, Ann B. Winslow, Amy C. Edmondson and Gary P. Pisano
Bohmer, Richard M.J., Ann B. Winslow, Amy C. Edmondson, and Gary P. Pisano. "Team Learning Trade-Offs: When Improving One Critical Dimension of Performance Inhibits Another." Harvard Business School Working Paper, No. 05-047, January 2005.
- September 1992
- Case
Star Cablevision Group (F): Lessons Learned
Last case in a series of six cases. This case describes the company as it reflects back to lessons learned. View Details
Keywords: Learning
Sahlman, William A. "Star Cablevision Group (F): Lessons Learned." Harvard Business School Case 293-041, September 1992.
- 25 Apr 2005
- Research & Ideas
New Learning at American Home Products
1931 of John Wyeth & Brothers. In prescription drugs, the company's initial learning base emerged with the purchase in 1931 of John Wyeth & Brothers, a respected... View Details
- Guest Column
Is Your Company Encouraging Employees to Share What They Know?
By: Christopher G. Myers
Is your company encouraging employees to share what they know? Too much expertise is going to waste. Many of the things we need to know to be successful—to innovate, collaborate, solve problems, and identify new opportunities—aren't learned simply through schooling,... View Details
Keywords: Vicarious Learning; Learning And Development; Learning Organizations; Knowledge Sharing; Organizations; Employees; Learning
Myers, Christopher G. "Is Your Company Encouraging Employees to Share What They Know?" Harvard Business Review (website) (November 6, 2015).
- September 1999
- Background Note
Learning from Projects: Note on Conducting a Postmortem Analysis
By: Stefan H. Thomke and Steven Sinofsky
Describes how firms can learn from projects through postmortem analysis. Focuses on the step-by-step process of preparing and running a postmortem meeting as it is done at Microsoft and other software developers. View Details
Keywords: Conferences; Management Analysis, Tools, and Techniques; Projects; Software; Information Technology Industry
Thomke, Stefan H., and Steven Sinofsky. "Learning from Projects: Note on Conducting a Postmortem Analysis." Harvard Business School Background Note 600-021, September 1999.
- 2020
- Working Paper
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing... View Details
Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Decision-making; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Harvard Business School Working Paper, No. 21-073, October 2020. (Revised September 2021.)
- 21 Jan 2011
- Working Paper Summaries
Learning from Customers in Outsourcing: Individual and Organizational Effects
- Mar 2020
- Conference Presentation
A New Analysis of Differential Privacy's Generalization Guarantees
By: Christopher Jung, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Moshe Shenfeld
We give a new proof of the "transfer theorem" underlying adaptive data analysis: that any mechanism for answering adaptively chosen statistical queries that is differentially private and sample-accurate is also accurate out-of-sample. Our new proof is elementary and... View Details
Jung, Christopher, Katrina Ligett, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, and Moshe Shenfeld. "A New Analysis of Differential Privacy's Generalization Guarantees." Paper presented at the 11th Innovations in Theoretical Computer Science Conference, Seattle, March 2020.
- March 2023
- Article
Learning to Successfully Hire in Online Labor Markets
By: Marios Kokkodis and Sam Ransbotham
Hiring in online labor markets involves considerable uncertainty: which hiring choices are more likely to yield successful outcomes and how do employers adjust their hiring behaviors to make such choices? We argue that employers will initially explore the value of... View Details
Kokkodis, Marios, and Sam Ransbotham. "Learning to Successfully Hire in Online Labor Markets." Management Science 69, no. 3 (March 2023): 1597–1614.
- Article
Overcoming the Winner's Curse: An Adaptive Learning Perspective
By: Yoella Bereby-Meyer and Brit Grosskopf
The winner's curse phenomenon refers to the fact that the winner in a common value auction, in order to actually win the auction, is likely to have overestimated the item's value and consequently is likely to gain less than expected and may even lose (i.e., it is said... View Details
Bereby-Meyer, Yoella, and Brit Grosskopf. "Overcoming the Winner's Curse: An Adaptive Learning Perspective." Journal of Behavioral Decision Making 21, no. 1 (January 2008): 15–27.
- 08 Dec 2006
- Working Paper Summaries
When Learning and Performance are at Odds: Confronting the Tension
Keywords: by Sara J. Singer & Amy C. Edmondson
- 17 Jun 2019
- Research & Ideas
What Hospitals Must Learn to Compete
Harvard Business School professors Raffaella Sadun and Leemore Dafny are both economists who have studied hospitals extensively—Sadun’s research has looked at the economics of management, while Dafny’s examines interactions between health... View Details
- 05 Dec 2017
- Research & Ideas
What We've Learned from 101 Entrepreneurs in Emerging Markets
studied at Harvard Business School. Credit: Bartosz Hadyniak For perspectives on what has been learned so far, HBS Working Knowledge conducted an email interview with four of the key drivers View Details
Keywords: by Sean Silverthorne
- 14 Mar 2023
- Cold Call Podcast
Can AI and Machine Learning Help Park Rangers Prevent Poaching?
- Forthcoming
- Article
Advancing Personalization: How to Experiment, Learn & Optimize
By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details
Keywords: Targeting; Experiments; Observational Studies; Policy Implementation; Policy Evaluation; Customization and Personalization; Marketing Strategy; Customer Focus and Relationships; Research
Lemmens, Aurelie, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela, and Oded Netzer. "Advancing Personalization: How to Experiment, Learn & Optimize." International Journal of Research in Marketing (forthcoming).