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Show Results For
- All HBS Web
(10,667)
- People (74)
- News (2,858)
- Research (3,823)
- Events (45)
- Multimedia (239)
- Faculty Publications (2,360)
- February 2014
- Article
Learning by Supplying
By: Juan Alcacer and Joanne Oxley
Learning processes lie at the heart of our understanding of how firms build capabilities to generate and sustain competitive advantage: learning by doing, learning by exporting, learning from competitors, users, and alliance partners. In this paper we focus attention... View Details
Alcacer, Juan, and Joanne Oxley. "Learning by Supplying." Strategic Management Journal 35, no. 2 (February 2014): 204–223.
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.
- Article
Inviting Consumers to Downsize Fast-Food Portions Significantly Reduces Calorie Consumption
By: Janet Schwartz, Jason Riis, Brian Elbel and Dan Ariely
Policies that mandate calorie labeling in fast-food and chain restaurants have had little or no observable impact on calorie consumption to date. In three field experiments, we tested an alternative approach: activating consumers' self-control by having servers ask... View Details
Keywords: Food; Labels; Consumer Behavior; Interpersonal Communication; Motivation and Incentives; Health Industry; Food and Beverage Industry
Schwartz, Janet, Jason Riis, Brian Elbel, and Dan Ariely. "Inviting Consumers to Downsize Fast-Food Portions Significantly Reduces Calorie Consumption." Health Affairs 31, no. 2 (February 2012): 2399–2407.
- July 2022
- Article
A Strategic View of Team Learning in Organizations
By: Jean-François Harvey, Henrik Bresman, Amy C. Edmondson and Gary P. Pisano
Research in strategic management and organizational behavior has increasingly focused on understanding how organizations achieve and sustain performance in fast-changing environments. Strategy research suggests that senior managers, through their decisions, influence... View Details
Keywords: Strategic Management; Organization Behavior; Teams; Organizational Capabilities; Groups and Teams; Learning; Management; Decision Making; Performance; Organizational Design
Harvey, Jean-François, Henrik Bresman, Amy C. Edmondson, and Gary P. Pisano. "A Strategic View of Team Learning in Organizations." Academy of Management Annals 16, no. 2 (July 2022): 476–507.
Learning by Supplying
Learning processes lie at the heart of our understanding of how firms build capabilities to generate and sustain competitive advantage: learning by doing, learning by exporting, learning from competitors, users, and alliance partners. In this paper we focus attention... 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
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.
- 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... View Details
- October 2004 (Revised March 2006)
- Background Note
Learning from Scandals: Responsibility of Professional Organizations
By: Ashish Nanda
This case comments on the responsibility of professional organizations to respond openly to public accusations of wrongdoing by its members. It briefly relates the circumstances of the sexual abuse scandal in the Boston archdiocese of the Roman Catholic Church and the... View Details
Nanda, Ashish. "Learning from Scandals: Responsibility of Professional Organizations." Harvard Business School Background Note 905-037, October 2004. (Revised March 2006.)
- February 1989
- Background Note
Learning with Cases
Gives some tips to maximize all learning; offers the pros and cons of experiential learning (cases) as a method; and gives some guidelines for effective case preparation, discussion, and learning. View Details
Bonoma, Thomas V. "Learning with Cases." Harvard Business School Background Note 589-080, February 1989.
- 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.)
- Article
On the Causality and Cause of Returns to Organizational Status: Evidence from the Grands Crus Classés of the Médoc
By: Daniel Malter
This paper identifies the causal symbolic effect of status on the prices organizations charge for their products. I exploit the classification of the châteaux of the Médoc, which sorted 61 wine producers into five growth classes in 1855, as a fixed hierarchical symbol... View Details
Keywords: Organizational Status; Quality Signals; Conspicuous Consumption; Wine Classification Of 1855; Grand Cru; Status and Position; Quality; Reputation; Price; France
Malter, Daniel. "On the Causality and Cause of Returns to Organizational Status: Evidence from the Grands Crus Classés of the Médoc." Administrative Science Quarterly 59, no. 2 (June 2014): 271–300.
- 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.)
- Article
Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles
By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
Keywords: CEOs; Communication Style; Machine Learning; Spoken Communication; Nonverbal Communication; Personal Characteristics; Analysis; Performance
Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Strategic Management Journal 40, no. 11 (November 2019): 1705–1732.
- 16 Mar 2011
- News
Learn From Failure
- Research Summary
Simultaneous Distinction, Democratization and Omnivorism Effects: A Longitudinal Analysis of Dynamic Symbolic Boundaries in Counterfeit Consumption Networks
Sociologists have long examined the interactive relationship between social structure, taste and power. This literature has overwhelmingly fallen into three, ostensibly competing, theoretical “camps”: Distinction, where high-status consumers use... View Details
- 10 Oct 2018
- Blog Post
6 Lessons Learned from a Summer of Entrepreneurship
employee benefit. We not only were challenged and learned a ton, but also had a lot of fun working on our venture in NYC. Here are the top 6 lessons we learned: 1. Identify your strengths early on. As the... View Details
Keywords: Entrepreneurship
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- 2003
- Chapter
Understanding Outcomes of Organizational Learning Interventions
By: Amy C. Edmondson and Anita Williams Woolley
Edmondson, Amy C., and Anita Williams Woolley. "Understanding Outcomes of Organizational Learning Interventions." Chap. 10 in Blackwell Handbook of Organizational Learning and Knowledge Management, edited by M. Easterby-Smith and M. Lyles, 185–211. Malden, MA: Blackwell Publishing, 2003.