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(13,094)
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- Faculty Publications (2,488)
Show Results For
- All HBS Web
(13,094)
- People (70)
- News (4,035)
- Research (5,699)
- Events (60)
- Multimedia (96)
- Faculty Publications (2,488)
- 2014
- Working Paper
Modeling Money Market Spreads: What Do We Learn about Refinancing Risk?
By: Vincent Brousseau, Kleopatra Nikolaou and Huw Pill
Brousseau, Vincent, Kleopatra Nikolaou, and Huw Pill. "Modeling Money Market Spreads: What Do We Learn about Refinancing Risk?" Finance and Economics Discussion Series (Federal Reserve Board), No. 2014-112, November 2014.
- 2017
- Working Paper
Learning by Doing: The Value of Experience and the Origins of Skill for Mutual Fund Managers
By: Elisabeth Kempf, Alberto Manconi and Oliver Spalt
Learning by doing matters for professional investors. We develop a new methodology to show that mutual fund managers outperform in industries where they have obtained experience on the job. The key to our identification strategy is that we look "inside" funds and... View Details
Kempf, Elisabeth, Alberto Manconi, and Oliver Spalt. "Learning by Doing: The Value of Experience and the Origins of Skill for Mutual Fund Managers." SSRN Working Paper Series, No. 2124896, May 2017.
- 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.
- 09 Jun 2023
- Blog Post
Learning Curve
career in the field but instead found herself in quasi-retirement at age 35. “Life has a way of getting in the way,” she notes. Melcher’s first child, Katie, struggled in preschool with learning disabilities, and Melcher made the decision... View Details
- 27 Aug 2014
- Lessons from the Classroom
Learning From Japan’s Remarkable Disaster Recovery
idea to write their own cases, and Takeuchi readily agreed. He works with the small teams doing the work. "This allows HBS to make a difference by leaving best practices for future generations to study... View Details
- 07 Sep 2022
- News
Bored at Work? Learn to Manage It by Putting It to Work
- 2020
- Working Paper
Team Learning and Superior Firm Performance: A Meso-Level Perspective on Dynamic Capabilities
By: Jean-François Harvey, Henrik Bresman, Amy C. Edmondson and Gary P. Pisano
This paper proposes a team-based, meso-level perspective on dynamic capabilities. We argue that team-learning routines constitute a critical link between managerial cognition and organization-level processes of sensing, seizing, and reconfiguring. We draw from the... View Details
Keywords: Dynamic Capabilities; Innovation; Strategic Change; Teams; Team Learning; Groups and Teams; Learning; Innovation and Invention; Change; Performance
Harvey, Jean-François, Henrik Bresman, Amy C. Edmondson, and Gary P. Pisano. "Team Learning and Superior Firm Performance: A Meso-Level Perspective on Dynamic Capabilities." Harvard Business School Working Paper, No. 19-059, December 2018. (Revised January 2020.)
- December 1, 2021
- Article
Do You Know How Your Teams Get Work Done?
By: Rohan Narayana Murty, Rajath B. Das, Scott Duke Kominers, Arjun Narayan, Suraj Srinivasan, Tarun Khanna and Kartik Hosanagar
In a research study at four Fortune 500 companies, when managers were asked about their teams’ work, on average they either did not know or could not remember 60% of the work their teams do. This is a major problem because it can lead to unrealistic digital... View Details
Keywords: Leading Teams; Work Recall Gap; Machine Learning; Algorithms; Groups and Teams; Management; Technological Innovation
Murty, Rohan Narayana, Rajath B. Das, Scott Duke Kominers, Arjun Narayan, Suraj Srinivasan, Tarun Khanna, and Kartik Hosanagar. "Do You Know How Your Teams Get Work Done?" Harvard Business Review Digital Articles (December 1, 2021).
- July 2017
- Teaching Note
Designing Transformational Customer Experiences
By: Stefan Thomke
Keywords: Customer Experience; Design; Exercise; Learning By Doing; LEGO; Storytelling; Transformation
- 31 Mar 2011
- Working Paper Summaries
What Do CEOs Do?
- 27 Jun 2007
- Lessons from the Classroom
Learning to Make the Move to CEO
bring back what they've learned to their organizations? "Graduates walk a fine line," Simons remarks. "On the one hand, it's not wise to come back with the attitude that they know it all and are ready to save the company.... View Details
- Research Summary
Selective Attention and Learning
What do we notice, and how does this affect what we learn? Standard economic models of learning ignore memory by assuming that we remember everything. But there is growing recognition that memory is imperfect. Further, memory imperfections do not stem from limited... View Details
- 03 Feb 2016
- What Do You Think?
How Do You Hire an 'Impostor'?
the employment of “imposters,” a term, by the way, that was regarded as objectionable by many, most respondents implicitly rejected the notion. They pointed to the desirable qualities of imposters, people... View Details
Keywords: by James Heskett
- 17 Jan 2007
- Op-Ed
Learning from Private-Equity Boards
If Enron had been owned and controlled by a small group of private-equity investors, could the monitoring and control practices of a professionally run buyout shop have protected Enron's shareholders and employees from the problems that... View Details
- 31 Jul 2013
- Working Paper Summaries
Learning from Double-Digit Growth Experiences
Keywords: by Eric D. Werker
- 2020
- Working Paper
Machine Learning for Pattern Discovery in Management Research
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
- December 2023
- Article
Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency
By: Gunther Glenk, Philip Holler and Stefan Reichelstein
Widespread adoption of hydrogen as an energy carrier is widely believed to require continued advances in Power-to-Gas (PtG) technologies. Here we provide a comprehensive assessment of the dynamics of system prices and conversion efficiency for three currently prevalent... View Details
Keywords: Clean Technology; Green Hydrogen; Carbon Emissions; Decarbonization; Learning By Doing; Environment; Energy; Environmental Accounting; Environmental Management; Sustainable Cities; Cost Accounting; Innovation and Management; Technology Adoption; Energy Policy; Engineering; Green Technology; Energy Industry; Utilities Industry; Industrial Products Industry; Manufacturing Industry; Transportation Industry; North America; South America; Africa; Europe; Asia
Glenk, Gunther, Philip Holler, and Stefan Reichelstein. "Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency." Energy & Environmental Science 16, no. 12 (December 2023): 6058–6070.
- 15 Nov 2006
- Research & Ideas
Lessons Not Learned About Innovation
Every managerial generation rediscovers the need for innovation to drive growth but, decade after decade, "grand declarations about innovation are followed by mediocre execution that produces anemic results, and innovation groups are... View Details
Keywords: by Sean Silverthorne
- Research Summary
Making Machine Learning Models Fair
The goal of this research direction is to ensure that the machine learning models we build and deploy do not discriminate against individuals from minority groups. View Details
- 21 Nov 2019
- Research & Ideas
Do TV Debates Sway Voters?
the election don’t do it following TV debates. "We find that debates don’t have any effect on any group of voters." “There’s this perception that debates are this great democratic tool, where voters can find out what candidates... View Details
Keywords: by Danielle Kost