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Show Results For
- All HBS Web
(12,551)
- People (75)
- News (2,866)
- Research (3,663)
- Events (32)
- Multimedia (331)
- Faculty Publications (2,349)
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- 27 Dec 2018
- Working Paper Summaries
Team Learning Capabilities: A Meso Model of Sustained Innovation and Superior Firm Performance
- Working Paper
Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application
By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
Keywords: Peer-to-peer Markets; Marketplace Matching; AI and Machine Learning; Demand and Consumers; Digital Platforms; Marketing
Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
- August 4, 2016
- Article
The Right Thing To Do: Why More U.S. Firms Need to Learn from JP Morgan Chase
By: Joseph B. Fuller and Matthew Sigelman
Fuller, Joseph B., and Matthew Sigelman. "The Right Thing To Do: Why More U.S. Firms Need to Learn from JP Morgan Chase." The Hill (August 4, 2016).
- July 2024
- Article
Mass General Brigham’s Patient-Reported Outcomes Measurement System: A Decade of Learnings
By: Jason B. Liu, Robert S. Kaplan, David W. Bates, Mario O. Edelen, Rachel C. Sisodia and Andrea L. Pusic
This article describes the strategies that leaders at the Mass General Brigham (MGB) health system have used in launching a standardized patient-reported outcome measure (PROM) collection program in 2012, a major step in the value-based transformation of health care.... View Details
Keywords: Patient-reported Outcomes; Value Based Health Care; Health Care and Treatment; Transformation; Outcome or Result; Organizational Change and Adaptation; Performance Improvement; Health Industry
Liu, Jason B., Robert S. Kaplan, David W. Bates, Mario O. Edelen, Rachel C. Sisodia, and Andrea L. Pusic. "Mass General Brigham’s Patient-Reported Outcomes Measurement System: A Decade of Learnings." NEJM Catalyst Innovations in Care Delivery 5, no. 7 (July 2024).
- April 17, 2012
- Blog Post
Learning and the Disappearing Association between Governance and Returns
By: Lucian A. Bebchuk, Alma Cohen and Charles CY Wang
Bebchuk, Lucian A., Alma Cohen, and Charles CY Wang. "Learning and the Disappearing Association between Governance and Returns." Harvard Law School Forum on Corporate Governance (April 17, 2012). https://corpgov.law.harvard.edu/2012/04/17/learning-and-the-disappearing-association-between-governance-and-returns/.
- Article
Productivity and Selection of Human Capital with Machine Learning
By: Aaron Chalfin, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig and Sendhil Mullainathan
Keywords: Analytics and Data Science; Selection and Staffing; Performance Productivity; Mathematical Methods; Policy
Chalfin, Aaron, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig, and Sendhil Mullainathan. "Productivity and Selection of Human Capital with Machine Learning." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 124–127.
- October 2003 (Revised May 2004)
- Teaching Note
Learning from LeapFrog: Creating Business and Educational Value (TN)
By: Lynda M. Applegate and Christopher Dede
Teaching Note for (9-804-062). View Details
- 1995
- Working Paper
Developing an Organization Capable of Implementing Strategy and Learning
By: Michael Beer
- Article
Simulation, Learning and R&D Performance: Evidence from Automotive Development
By: S. Thomke
Thomke, S. "Simulation, Learning and R&D Performance: Evidence from Automotive Development." Research Policy 27, no. 1 (May 1998): 55–74.
- 2003
- Article
Temporal Specificity of Perceptual Learning in an Auditory Discrimination Task
By: Uma R. Karmarkar and Dean V. Buonomano
Karmarkar, Uma R., and Dean V. Buonomano. "Temporal Specificity of Perceptual Learning in an Auditory Discrimination Task." Learning & Memory 10 (2003): 141–147.
- Article
Why Hospitals Don't Learn from Failures: Organizational and Psychological Dynamics That Inhibit System Change
By: A. Tucker and A. Edmondson
The importance of hospitals learning from their failures hardly needs to be stated. Not only are matters of life and death at stake on a daily basis, but also an increasing number of U.S. hospitals are operating in the red. This article reports on in-depth qualitative... View Details
Tucker, A., and A. Edmondson. "Why Hospitals Don't Learn from Failures: Organizational and Psychological Dynamics That Inhibit System Change." California Management Review 45, no. 2 (Winter 2003). (Winner of Accenture Award For the article published in the California Management Review that has made the most important contribution to improving the practice of management.)
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
- November 12, 2020
- Article
What We Can Learn About Unity from Hostile Takeovers
In the wake of the recent election, the United States faces a fraught, difficult transfer of power. What we know about hostile takeovers in business can provide help in finding a path forward. Leaders on the winning side of the more successful acquisitions emphasized... View Details
Kanter, Rosabeth Moss. "What We Can Learn About Unity from Hostile Takeovers." Harvard Business Review Digital Articles (November 12, 2020).
- May 20, 2021
- Article
How to Build a Life: What Introverts and Extroverts Can Learn from Each Other
By: Arthur C. Brooks
Brooks, Arthur C. "How to Build a Life: What Introverts and Extroverts Can Learn from Each Other." The Atlantic (May 20, 2021).
- 2018
- Working Paper
Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning
By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck
Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details
Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets
Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
- January – February 2012
- Article
What Business Schools Can Learn from the Medical Profession
By: Nitin Nohria
Nohria, Nitin. "What Business Schools Can Learn from the Medical Profession." Harvard Business Review 90, nos. 1-2 (January–February 2012).
- May 2007
- Article
Multi-agent Learning and the Descriptive Value of Simple Models
By: Ido Erev and Alvin E. Roth
Keywords: Value
Erev, Ido, and Alvin E. Roth. "Multi-agent Learning and the Descriptive Value of Simple Models." Special Issue on Foundations of Multi-Agent Learning. Artificial Intelligence 171, no. 7 (May 2007): 423–428.
- 2003
- Chapter
Management in Perspective: Lessons Learned from Harvard Business School
By: D. Quinn Mills and Franziska Zellweger
Keywords: Management