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  • All HBS Web  (13,144)
    • People  (70)
    • News  (4,039)
    • Research  (5,711)
    • Events  (60)
    • Multimedia  (96)
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← Page 2 of 13,144 Results →
  • 11 Dec 2023
  • Research & Ideas

Doing Well by Doing Good? One Industry’s Struggle to Balance Values and Profits

Is it still possible to build a career that is both morally satisfying and materially rewarding? To do well by doing good? Professionals and executives in a range of fields... View Details
Keywords: by Scott Van Voorhis
  • 08 Sep 2015
  • News

Knowledge Transfer: You Can't Learn Surgery By Watching

  • 19 Jun 2012
  • News

A Brief History of Doing Well by Doing Good

  • May 2011
  • Teaching Note

China Environment Fund: Doing Well by Doing Good (TN)

By: Christopher Marquis and Alison Comings
Teaching Note for 410142. View Details
Keywords: Financial Services Industry; China
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Marquis, Christopher, and Alison Comings. "China Environment Fund: Doing Well by Doing Good (TN)." Harvard Business School Teaching Note 411-098, May 2011.
  • 18 Nov 2016
  • Conference Presentation

Rawlsian Fairness for Machine Learning

By: Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
Motivated by concerns that automated decision-making procedures can unintentionally lead to discriminatory behavior, we study a technical definition of fairness modeled after John Rawls' notion of "fair equality of opportunity". In the context of a simple model of... View Details
Keywords: Machine Learning; Algorithms; Fairness; Decision Making; Mathematical Methods
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Joseph, Matthew, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Rawlsian Fairness for Machine Learning." Paper presented at the 3rd Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), November 18, 2016.
  • 2007
  • Chapter

Learning by Experimentation: Prototyping and Testing

By: Stefan Thomke
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Thomke, Stefan. "Learning by Experimentation: Prototyping and Testing." In Handbook of New Product Development Management, edited by Christoph Loch and Stylianos Kavadias. Oxford: Butterworth-Heinemann, 2007.
  • 2023
  • Working Paper

Learning by Investing: Entrepreneurial Spillovers from Venture Capital

By: Josh Lerner, Jinlin Li and Tong Liu
This paper studies how investing in venture capital (VC) affects the entrepreneurial outcomes of individual limited partners (LPs). Using comprehensive administrative data on entrepreneurial activities and VC fundraising and investments in China, we first document that... View Details
Keywords: Partners and Partnerships; Entrepreneurship; Venture Capital; Investment; China
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Lerner, Josh, Jinlin Li, and Tong Liu. "Learning by Investing: Entrepreneurial Spillovers from Venture Capital." Harvard Business School Working Paper, No. 24-029, November 2023. (Revise and resubmit, Review of Financial Studies.)
  • Fall 2015
  • Article

Doing Well by Doing Good? Community Development Venture Capital

By: Josh Lerner and Anna Kovner
This paper examines the investments and performance of community development venture capital (CDVC). We find substantial differences between CDVC and traditional venture capital (VC) investments: CDVC investments are far more likely to be in nonmetropolitan regions and... View Details
Keywords: Social Enterprise; Venture Capital
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Lerner, Josh, and Anna Kovner. "Doing Well by Doing Good? Community Development Venture Capital." Journal of Economics & Management Strategy 24, no. 3 (Fall 2015): 643–663.
  • Article

Learning Models for Actionable Recourse

By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely... View Details
Keywords: Machine Learning Models; Recourse; Algorithm; Mathematical Methods
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Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
  • Working Paper

Doing Bad by Doing Good? Theft and Abuse by Lenders in Inadequately Regulated Microfinance Markets

By: Catherine S. M. Duggan
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Duggan, Catherine S. M. "Doing Bad by Doing Good? Theft and Abuse by Lenders in Inadequately Regulated Microfinance Markets." Working Paper.
  • Article

Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
Keywords: Machine Learning; Algorithms; Fairness; Mathematical Methods
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Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
  • September 2012
  • Article

Learning Agility: In Search of Conceptual Clarity and Theoretical Grounding

By: D. Scott DeRue, Susan J. Ashford and Christopher G. Myers
As organizations become more complex and dynamic, individuals' ability to learn from experience becomes more important. Recently, the concept of learning agility has attracted considerable attention from human resource professionals and consultants interested in... View Details
Keywords: Learning And Development; Learning
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DeRue, D. Scott, Susan J. Ashford, and Christopher G. Myers. "Learning Agility: In Search of Conceptual Clarity and Theoretical Grounding." Industrial and Organizational Psychology: Perspectives on Science and Practice 5, no. 3 (September 2012): 258–279.
  • March 2022
  • Article

Learning to Rank an Assortment of Products

By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue... View Details
Keywords: Online Learning; Product Ranking; Assortment Optimization; Learning; Internet and the Web; Product Marketing; Consumer Behavior; E-commerce
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Ferreira, Kris, Sunanda Parthasarathy, and Shreyas Sekar. "Learning to Rank an Assortment of Products." Management Science 68, no. 3 (March 2022): 1828–1848.
  • January 2022 (Revised November 2023)
  • Case

Expanding the Culture of Learning at Kraft Heinz

By: Ashley V. Whillans and Carolyn Watson
The Kraft Heinz Company (KHC) was an American food company formed in 2015 by the merger of Kraft Foods Group, Inc and the H.J. Heinz Company. The company sold food products like Heinz Ketchup, Kraft Mac & Cheese, Kool-Aid, and Philadelphia cream cheese to supermarkets,... View Details
Keywords: Learning; Culture; Work Culture; Workplace Practices; Mergers; Mergers and Acquisitions; Competitive Advantage; Human Capital; Training; Performance Evaluation; Growth and Development; Personal Development and Career; Employee Relationship Management; Organizational Change and Adaptation; Organizational Culture; Food and Beverage Industry
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Whillans, Ashley V., and Carolyn Watson. "Expanding the Culture of Learning at Kraft Heinz." Harvard Business School Case 922-036, January 2022. (Revised November 2023.)
  • 2019
  • Article

An Empirical Study of Rich Subgroup Fairness for Machine Learning

By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details
Keywords: Machine Learning; Fairness; AI and Machine Learning
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Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "An Empirical Study of Rich Subgroup Fairness for Machine Learning." Proceedings of the Conference on Fairness, Accountability, and Transparency (2019): 100–109.
  • 14 Mar 2021
  • News

Podcast: What do we really learn from failure?

  • 30 Nov 2015
  • Research & Ideas

Donors Are Turned Off by Overhead Costs. Here’s What Charities Can Do

showed that participants were turned off by overhead. The higher the level of overhead associated with a donation to charity: water, the lower the percentage of participants who chose to donate to it. When they View Details
Keywords: by Carmen Nobel
  • Article

From Orientation to Behavior: The Interplay Between Learning Orientation, Open-mindedness, and Psychological Safety in Team Learning

By: Jean-François Harvey, Kevin J. Johnson, Kathryn S. Roloff and Amy C. Edmondson
Do teams with motivation to learn actually engage in the behaviors that produce learning? Though team learning orientation has been found to be positively related to team learning, we know little about how and when it actually fosters team learning. It is obviously not... View Details
Keywords: Emergent States; Goal Orientation; Open-mindedness; Psychological Safety; Team Learning; Teams; Groups and Teams; Learning; Goals and Objectives
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Harvey, Jean-François, Kevin J. Johnson, Kathryn S. Roloff, and Amy C. Edmondson. "From Orientation to Behavior: The Interplay Between Learning Orientation, Open-mindedness, and Psychological Safety in Team Learning." Human Relations 72, no. 11 (November 2019): 1726–1751.
  • September 2017
  • Article

The Advocacy Trap: When Legitimacy Building Inhibits Organizational Learning

By: Tiona Zuzul and Amy C. Edmondson
This paper describes a relationship between legitimacy building and learning for a new firm in a nascent industry. Through a longitudinal study of a new firm in the nascent smart city industry, we found that the firm failed to make progress on important internal... View Details
Keywords: Organizational Learning; Advocacy; Organizations; Learning; Organizational Culture; Entrepreneurship
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Zuzul, Tiona, and Amy C. Edmondson. "The Advocacy Trap: When Legitimacy Building Inhibits Organizational Learning." Academy of Management Discoveries 3, no. 3 (September 2017): 302–321.
  • 20 Jun 2016
  • Working Paper Summaries

What Else Do Shareholders Want? Shareholder Proposals Contested by Firm Management

Keywords: by Eugene F. Soltes, Suraj Srinivasan, and Rajesh Vijayaraghavan
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