Publications

Publications

Filter Results: (3,381) Arrow Down
Filter Results: (3,381) Arrow Down Arrow Up

Show Results For

Show Results For

← Page 37 of 3,381 Results →
  • 05 Dec 2024
  • HBS Seminar

Amanda Sharkey, Mendoza College of Business

  • Web

Summer Venture in Management

tech, sectors in which attending business school was not as common or encouraged. SVMP showed me the value of an MBA, and the unique power of the case method teaching style. I saw firsthand how learning business skills through discussion... View Details
  • 05 Jul 2006
  • Working Paper Summaries

Measuring Consumer and Competitive Impact with Elasticity Decompositions

Keywords: by Thomas J. Steenburgh; Advertising
  • 01 May 2020
  • News

Use Tested Techniques To Help Optimize Your Performance

    Jenny Wang

    Jenny Shan Wang is a doctoral student in the Technology and Operations Management program at Harvard Business School (HBS). She is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods... View Details
    • 03 Sep 2024
    • News

    Welcoming the MBA Class of 2026 to Harvard Business School

    • 06 Dec 2021
    • News

    The Popular Stock Metric That Can Lead Investors Astray

    • 2025
    • Working Paper

    Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning

    By: Liangzong Ma, Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
    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
    Related
    • 2023
    • Article

    MoPe: Model Perturbation-based Privacy Attacks on Language Models

    By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
    Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
    Keywords: Large Language Model; AI and Machine Learning; Cybersecurity
    Related
    • 13 Apr 2012
    • HBS Seminar

    Drazen Prelec, Professor of Management Science and Economics at MIT Sloan School of Management

    • 17 May 2022
    • News

    Delivering a Personalized Shopping Experience with AI

    • 2023
    • Working Paper

    In-Context Unlearning: Language Models as Few Shot Unlearners

    By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju
    Machine unlearning, the study of efficiently removing the impact of specific training points on the trained model, has garnered increased attention of late, driven by the need to comply with privacy regulations like the Right to be Forgotten. Although unlearning is... View Details
    Keywords: AI and Machine Learning; Copyright; Information
    Related
    • June 2024
    • Article

    Economics of Enhanced Methane Oxidation Relative to Carbon Dioxide Removal

    By: Conor Hickey and Myles Allen
    Mitigating short-term global warming is imperative, and a key strategy involves reducing atmospheric methane (CH4) due to its high radiative forcing and short lifespan. This objective can be achieved through methods such as oxidising methane at its source or... View Details
    Keywords: Greenhouse Gas Mitigation; Climate Change; Environmental Regulation; Pollutants; Research; Measurement and Metrics
    Related
    • January 22, 2020
    • Article

    Making Honest Conversations the Norm

    By: Michael Beer
    Much admired companies like Boeing and Wells Fargo sacrifice their competitive advantage. Some make huge ethical blunders. As a result, shareholders suffer huge losses in value while employees, customers, and society lose trust and confidence in the institution. Based... View Details
    Keywords: Honesty; Interpersonal Communication; Framework; Organizational Culture; Trust; Performance Effectiveness
    Related
    • November 2016 (Revised October 2018)
    • Case

    IguanaFix

    By: Frank V. Cespedes, Thomas R. Eisenmann, Maria Fernanda Miguel and Laura Urdapilleta
    IguanaFix is a rapidly scaling Latin American startup that provides an online platform connecting consumers with home improvement contractors. The founders have acquired customers through both B2C and B2B methods. But in seeking to grow and scale the business, they now... View Details
    Keywords: Entrepreneurial Marketing; Home Improvement Services; Marketing Management; Scaling; Entrepreneurship; Marketing; Sales; Online Advertising; Latin America
    Related
    • 21 Jan 2009
    • News

    Harvard Business School Students Immersed in Experiential Learning

    • 11 May 2018
    • News

    Online Ad Targeting Does Work—As Long As It's Not Creepy

    • 09 Nov 2021
    • HBS Seminar

    Susan Murphy, Harvard-SEAS

    • 2020
    • Working Paper

    Strategic Foresight as Dynamic Capability: A New Lens on Knightian Uncertainty

    By: J. Peter Scoblic
    This paper proposes to treat strategic foresight as a dynamic capability, providing a new theoretical lens on managerial judgment. Formulating strategy under uncertainty is a central challenge facing the modern firm. Analogy is thought to help managers make sense of... View Details
    Keywords: Foresight; Dynamic Capabilities; Managerial Judgment; Risk and Uncertainty; Management; Strategy
    Related
    • 2023
    • Working Paper

    PRIMO: Private Regression in Multiple Outcomes

    By: Seth Neel
    We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
    Keywords: Analytics and Data Science; Mathematical Methods
    Related