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  • August 2018 (Revised April 2019)
  • Supplement

Chateau Winery (B): Supervised Learning

By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
Keywords: Data Science; Clustering; Analytics and Data Science; Customers; Marketing; Analysis
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Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
  • 2011
  • Chapter

The Contribution of Teams to Organizational Learning

By: Kathryn S. Roloff, Anita W. Woolley and Amy C. Edmondson
Organizational learning theorists have proposed that teams play a critical role in organizational learning (Senge, 1990; Edmondson, 2002). Indeed, as organizations become increasingly more global, teams are formed to leverage knowledge, to increase efficiency, and to... View Details
Keywords: Organizational Change and Adaptation; Groups and Teams; Learning
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Roloff, Kathryn S., Anita W. Woolley, and Amy C. Edmondson. "The Contribution of Teams to Organizational Learning." In Handbook of Organizational Learning and Knowledge Management. 2nd ed. Edited by M. Easterby-Smith and M. Lyles, 249–272. London: John Wiley & Sons, 2011.
  • 08 Oct 2018
  • Working Paper Summaries

Developing Theory Using Machine Learning Methods

Keywords: by Prithwiraj Choudhury, Ryan Allen, and Michael G. Endres
  • July 2022
  • Supplement

Key Learnings about Turnarounds

By: Ranjay Gulati
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Gulati, Ranjay. "Key Learnings about Turnarounds." Harvard Business School Multimedia/Video Supplement 423-703, July 2022.
  • Article

Learning to Teach Negotiation

By: Michael A. Wheeler
Keywords: Negotiation; Pedagogy; Teaching; Training; Business Ecuation
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Wheeler, Michael A. "Learning to Teach Negotiation." Negotiation Journal 31, no. 4 (October 2015): 477–490.
  • April 2011
  • Article

Why Leaders Don't Learn from Success

By: Francesca Gino and Gary P. Pisano
We argue that for a variety of psychological reasons, it is often much harder for leaders and organizations to learn from success than to learn from failure. Success creates three kinds of traps that often impede deep learning. The first is attribution error or the... View Details
Keywords: Learning; Innovation and Management; Leadership; Failure; Success; Performance Evaluation; Prejudice and Bias
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Gino, Francesca, and Gary P. Pisano. "Why Leaders Don't Learn from Success." Harvard Business Review 89, no. 4 (April 2011): 68–74.
  • Research Summary

The Learning As BehaviorS (LABS) Model

The Learning As BehaviorS (LABS) Model of Expertise Development integrates research from management, cognitive psychology, educational psychology and neuroscience to describe the process of how a novice achieves expertise. Defining expertise as the ability to... View Details
  • October 2021
  • Article

Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

By: Nicolas Padilla and 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; Programs; Consumer Behavior; Analysis
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Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Journal of Marketing Research (JMR) 58, no. 5 (October 2021): 981–1006.
  • 17 Jan 2007
  • Op-Ed

Learning from Private-Equity Boards

quarterly earnings reports, reflecting the complexity of corporate restructurings and other long-term growth strategies. Lessons To Be Learned There are important implications of these differences for public company boards, even though... View Details
Keywords: by Malcolm Salter; Financial Services
  • 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
Keywords: Clustering; Data Science; Analytics and Data Science; Customers; Marketing; Analysis
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Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
  • 1 Jan 1994
  • Conference Presentation

Alliances as Learning Races

By: T. Khanna, R. Gulati and N. Nohria
Keywords: Alliances; Competition
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Khanna, T., R. Gulati, and N. Nohria. "Alliances as Learning Races." Paper presented at the Academy of Management Annual Meeting, January 01, 1994.
  • March 2000
  • Supplement

Types of Learning Processes

By: David A. Garvin and Jeffrey Berger
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Garvin, David A., and Jeffrey Berger. "Types of Learning Processes." Harvard Business School Supplement 300-124, March 2000.
  • 1998
  • Chapter

Trust and Organizational Learning

By: B. Moingeon and A. Edmondson
Keywords: Trust; Organizational Change and Adaptation
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Moingeon, B., and A. Edmondson. "Trust and Organizational Learning." In Trust, Learning and Economic Expectations, edited by N. Lazaric and E. Lorenz, 247–84. London: Edward Elgar Publishing, 1998.
  • 27 Aug 2014
  • Lessons from the Classroom

Learning From Japan’s Remarkable Disaster Recovery

leadership in mobilizing people and resources in highly dynamic situations.” Each winter, 900 HBS students dispatch around the world to see businesses up close, learn what they can about how they are run, and share their own knowledge... View Details
Keywords: by Sean Silverthorne; Energy; Utilities; Retail
  • 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
Keywords: Research and Development; Forecasting and Prediction; Valuation; Pharmaceutical Industry
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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.)
  • October 2001
  • Article

Speeding Up Team Learning

By: Amy C. Edmondson, Richard Bohmer and Gary P. Pisano
Keywords: Learning
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Edmondson, Amy C., Richard Bohmer, and Gary P. Pisano. "Speeding Up Team Learning." Harvard Business Review 79, no. 9 (October 2001): 125–134.
  • 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
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Latour, Kathryn A., and John A. Deighton. "Learning to Become a Taste Expert." Harvard Business School Working Paper, No. 18-107, June 2018.
  • 2019
  • Article

Fair Algorithms for Learning in Allocation Problems

By: Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael J Kearns, Seth Neel, Aaron Leon Roth and Zachary Schutzman
Settings such as lending and policing can be modeled by a centralized agent allocating a scarce resource (e.g. loans or police officers) amongst several groups, in order to maximize some objective (e.g. loans given that are repaid, or criminals that are apprehended).... View Details
Keywords: Allocation Problems; Algorithms; Fairness; Learning
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Elzayn, Hadi, Shahin Jabbari, Christopher Jung, Michael J Kearns, Seth Neel, Aaron Leon Roth, and Zachary Schutzman. "Fair Algorithms for Learning in Allocation Problems." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 170–179.
  • 1 Apr 1992
  • Conference Presentation

Motivation, Creativity, and Learning

By: R. Conti, Teresa M. Amabile and S. Pollack
Keywords: Motivation and Incentives; Creativity; Learning
Citation
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Conti, R., Teresa M. Amabile, and S. Pollack. "Motivation, Creativity, and Learning." Paper presented at the Eastern Psychological Association Meeting, Boston, MA, April 1, 1992.
  • February 2013
  • Article

Learning from Roger Fisher

By: James K. Sebenius
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
Keywords: Roger Fisher; Dispute Resolution; Bargaining; Negotiation
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Sebenius, James K. "Learning from Roger Fisher." Harvard Law Review 126, no. 4 (February 2013): 893–898.
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