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  • All HBS Web  (4,017)
    • People  (2)
    • News  (556)
    • Research  (2,848)
    • Events  (51)
    • Multimedia  (21)
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Show Results For

  • All HBS Web  (4,017)
    • People  (2)
    • News  (556)
    • Research  (2,848)
    • Events  (51)
    • Multimedia  (21)
  • Faculty Publications  (2,050)
← Page 61 of 4,017 Results →
  • 09 May 2014
  • Working Paper Summaries

‘My Bad!’ How Internal Attribution and Ambiguity of Responsibility Affect Learning from Failure

Keywords: by Christopher G. Myers, Bradley R. Staats & Francesca Gino
  • 14 May 2014
  • News

La révolution digitale à marche forcée

  • 2025
  • Book

The Experimentation Machine: Finding Product–Market Fit in the Age of AI

By: Jeffrey J. Bussgang
Leverage AI to be a 10x Founder

Today’s most successful founders know that the startups that learn the fastest will win. In The Experimentation Machine, I reveal how AI is transforming the way startups find product-market fit and scale.... View Details
Keywords: AI; Founder; Startup; AI and Machine Learning; Technology Adoption; Business Startups; Entrepreneurship; Market Entry and Exit
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Bussgang, Jeffrey J. The Experimentation Machine: Finding Product–Market Fit in the Age of AI. Damn Gravity Media, 2025.
  • Article

Third-Party Punishment as a Costly Signal of High Continuation Probabilities in Repeated Games

By: Jillian J. Jordan and David G. Rand
Why do individuals pay costs to punish selfish behavior, even as third-party observers? A large body of research suggests that reputation plays an important role in motivating such third-party punishment (TPP). Here we focus on a recently proposed reputation-based... View Details
Keywords: Direct Reciprocity; Evolution; Dispersal; Cooperation; Trust; Reputation; Game Theory
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Jordan, Jillian J., and David G. Rand. "Third-Party Punishment as a Costly Signal of High Continuation Probabilities in Repeated Games." Journal of Theoretical Biology 421 (May 21, 2017): 189–202.
  • March 1969 (Revised August 1997)
  • Case

Fabritek Corp.

Describes a large-volume automotive parts contract in a high-quality machine work company. Quality and delivery problems arise when one of the four men on the job is replaced with a high producer who cannot earn a substantial bonus because of machine interference. View Details
Keywords: Production; Performance Productivity; Auto Industry
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Holstein, William K., Linda Sprague, and Lawrence Bennigson. "Fabritek Corp." Harvard Business School Case 669-004, March 1969. (Revised August 1997.)

    Isamar Troncoso

    Isamar Troncoso is an Assistant Professor of Business Administration in the Marketing Unit at HBS. She teaches the Marketing course in the MBA required curriculum.

    Professor Troncoso studies problems related to digital marketplaces and new technologies. She... View Details

    Keywords: e-commerce industry; high technology; retailing
    • 24 Feb 2016
    • News

    Did William Alden Invent the Car of the Future in the 1960s?

    William Alden (MBA 1952) was sorting mail when he had the thought: The concept behind the automated conveyer system he was perfecting for routing letters could be used to move people. It was the 1950s, a time of great investment in... View Details
    • February 2021
    • Background Note

    Jobs to Be Done: A Toolbox

    By: Derek C. M. van Bever, Bob Moesta, Iuliana Mogosanu, Shaye Roseman and Katie Zandbergen
    The Jobs to Be Done methodology is both a theory and a practical approach for understanding customer behavior and why people make the choices they make. Many practitioners, whether they work for startups or incumbent businesses, find Jobs to Be Done useful because it... View Details
    Keywords: Customer Value and Value Chain; Decision Choices and Conditions; Knowledge Acquisition; Attitudes; Perception; Theory; Behavior; Customer Relationship Management
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    van Bever, Derek C. M., Bob Moesta, Iuliana Mogosanu, Shaye Roseman, and Katie Zandbergen. "Jobs to Be Done: A Toolbox." Harvard Business School Background Note 321-095, February 2021.
    • August 2017
    • Module Note

    Distinguishing Good Advice from Bad Advice: An Introduction to the HBS Course 'Building and Sustaining a Successful Enterprise' (BSSE)

    By: Clayton Christensen
    Overview of theoretical approach of HBS MBA Course "Building and Sustaining a Successful Enterprise"; distinguishing theory based on correlation from theory based on causal driver. View Details
    Keywords: Causation Vs. Correlation; BSSE; Theory; Business Ventures
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    Christensen, Clayton. "Distinguishing Good Advice from Bad Advice: An Introduction to the HBS Course 'Building and Sustaining a Successful Enterprise' (BSSE)." Harvard Business School Module Note 318-032, August 2017.
    • 8 Sep 2023
    • Conference Presentation

    Chatbots and Mental Health: Insights into the Safety of Generative AI

    By: Julian De Freitas, K. Uguralp, Z. Uguralp and Stefano Puntoni
    Keywords: AI and Machine Learning; Well-being
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    De Freitas, Julian, K. Uguralp, Z. Uguralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Paper presented at the Business & Generative AI Workshop, Wharton School, AI at Wharton, San Francisco, CA, United States, September 8, 2023.
    • 2022
    • Article

    Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods.

    By: Chirag Agarwal, Marinka Zitnik and Himabindu Lakkaraju
    As Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes critical to ensure that the stakeholders understand the rationale behind their predictions. While several GNN explanation methods have been proposed recently, there has... View Details
    Keywords: Graph Neural Networks; Explanation Methods; Mathematical Methods; Framework; Theory; Analysis
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    Agarwal, Chirag, Marinka Zitnik, and Himabindu Lakkaraju. "Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
    • autumn 1993
    • Article

    Motivational Synergy: Toward New Conceptualizations of Intrinsic and Extrinsic Motivation in the Workplace

    By: T. M. Amabile
    The foundation for a model of motivational synergy is presented. Building upon but going beyond previous conceptualizations, the model outlines the ways in which intrinsic motivation (which arises from the intrinsic value of the work for the individual) might interact... View Details
    Keywords: Motivation and Incentives; Theory; Creativity; Situation or Environment; Organizational Culture
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    Amabile, T. M. "Motivational Synergy: Toward New Conceptualizations of Intrinsic and Extrinsic Motivation in the Workplace." Human Resource Management Review 3, no. 3 (autumn 1993): 185–201.
    • November 2024 (Revised January 2025)
    • Case

    MiDAS: Automating Unemployment Benefits

    By: Shikhar Ghosh and Shweta Bagai
    In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details
    Keywords: Artificial Intelligence; AI; Machine Learning Models; Algorithmic Data; Automation; Benefits; Compensation; Cost Reduction; Government; Fraud; Government Technology; Public Sector; Systems; Systems Integration; Unemployment Insurance; Waste Heat Recovery; AI and Machine Learning; Government Administration; Insurance; Decision Making; Digital Transformation; Employment; Public Administration Industry; United States; Michigan
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    Ghosh, Shikhar, and Shweta Bagai. "MiDAS: Automating Unemployment Benefits." Harvard Business School Case 825-100, November 2024. (Revised January 2025.)
    • February 2024
    • Background Note

    Frederick Herzberg on Motivating Employees

    By: Willy C. Shih
    This background note summarizes Frederick Herzberg's development of his motivation-hygiene theory, his theory regarding job enrichment, and how the theory has evolved. This is at the core of extrinsic versus intrinsic motivation. View Details
    Keywords: Motivation and Incentives; Theory; Service Industry; Manufacturing Industry; United States
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    Shih, Willy C. "Frederick Herzberg on Motivating Employees." Harvard Business School Background Note 624-085, February 2024.
    • 1 Aug 1999
    • Conference Presentation

    Exploring New Models for Management Research: A Case of Academic Practioner Collaboration

    By: Teresa M. Amabile
    Keywords: Theory; Practice; Alliances
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    Amabile, Teresa M. "Exploring New Models for Management Research: A Case of Academic Practioner Collaboration." Paper presented at the Academy of Management Annual Meeting, Chicago, IL, August 01, 1999.
    • 27 Jan 2012
    • Working Paper Summaries

    Discretion Within the Constraints of Opportunity: Gender Homophily and Structure in a Formal Organization

    Keywords: by Adam M. Kleinbaum, Toby E. Stuart & Michael L. Tushman
    • Web

    The Intersection of Public Relations and Photography | Baker Library | Bloomberg Center | Harvard Business School

    giant factory spaces, colossal machinery, furious heat, rivers of molten iron, and white-hot steel. His photographic style, which he referred to as “camera-reporting,” revealed an arresting juxtaposition of... View Details
    • 11 Jun 2009
    • Working Paper Summaries

    Social Influence Given (Partially) Deliberate Matching: Career Imprints in the Creation of Academic Entrepreneurs

    Keywords: by Pierre Azoulay, Christopher C. Liu & Toby E. Stuart
    • 03 Sep 2024
    • Research & Ideas

    Is It Even Possible to Dam the Flow of Misleading Content Online?

    fundamental reason why we use theory here is that we’re trying to sort out all the possible rules you could ever try to use,” says Shapiro. “We’re reasoning about policies that have never been tested.” One View Details
    Keywords: by Jay Fitzgerald; Information Technology; Technology
    • 20 Mar 2017
    • Book

    Why Companies Are Placing Users at the Core of Their Innovation Strategies

    on what the company wants to achieve in their business model. Machine learning is one of the new core technologies that allow for data science. Many companies are relying on it for their advances. Google,... View Details
    Keywords: by Dina Gerdeman
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