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  • All HBS Web  (1,917)
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    • News  (215)
    • Research  (1,370)
    • Events  (15)
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  • All HBS Web  (1,917)
    • People  (2)
    • News  (215)
    • Research  (1,370)
    • Events  (15)
    • Multimedia  (13)
  • Faculty Publications  (907)
← Page 25 of 1,917 Results →
  • 2020
  • Working Paper

When Do Experts Listen to Other Experts? The Role of Negative Information in Expert Evaluations for Novel Projects

By: Jacqueline N. Lane, Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan and Karim R. Lakhani
The evaluation of novel projects lies at the heart of scientific and technological innovation, and yet literature suggests that this process is subject to inconsistency and potential biases. This paper investigates the role of information sharing among experts as the... View Details
Keywords: Project Evaluation; Innovation; Knowledge Frontier; Negativity Bias; Projects; Innovation and Invention; Information; Diversity; Judgments
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Lane, Jacqueline N., Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan, and Karim R. Lakhani. "When Do Experts Listen to Other Experts? The Role of Negative Information in Expert Evaluations for Novel Projects." Harvard Business School Working Paper, No. 21-007, July 2020. (Revised November 2020.)
  • 10 Jan 2017
  • First Look

First Look at New Research: January 10, 2017

How did he do these deals? What strategies and tactics worked and what failed? Why and under what conditions? What ethical challenges does this approach present? Is there an underlying logic and method to his approach that, well beyond... View Details
Keywords: Sean Silverthorne
  • 21 Feb 2005
  • Op-Ed

Is Business Management a Profession?

reason that the issue of trust arises is that these individuals are expected to exercise judgment—based on specialized knowledge and methods of analysis that they alone are thought to possess—in areas in which their decisions affect the... View Details
Keywords: by Rakesh Khurana, Nitin Nohria & Daniel Penrice
  • November 2022
  • Article

Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings

By: Kristin Blesch, Oliver P. Hauser and Jon M. Jachimowicz
Prior research has found mixed results on how economic inequality is related to various outcomes. These contradicting findings may in part stem from a predominant focus on the Gini coefficient, which only narrowly captures inequality. Here, we conceptualize the... View Details
Keywords: Economic Inequalty; Gini Coefficient; Income Inequality; Equality and Inequality; Social Issues; Health; Status and Position
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Blesch, Kristin, Oliver P. Hauser, and Jon M. Jachimowicz. "Measuring Inequality beyond the Gini Coefficient May Clarify Conflicting Findings." Nature Human Behaviour 6, no. 11 (November 2022): 1525–1536.
  • 09 Jan 2024
  • Blog Post

Insights From Harvard Business School’s Peek Program

Peek is an annual online program for current undergraduate students that provides an opportunity to try out the HBS case method of study, join a leadership development discussion, gain an understanding of the career flexibility and... View Details

    Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

    Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data,... View Details
    • 23 Apr 2018
    • Research & Ideas

    Sponsorship Programs Could Actually Widen the Gender Gap

    well, too. Sponsorship is a pretty new concept, but it’s becoming more popular, especially in professional service firms.” Sponsorship programs are meant to boost confidence among protégés, increasing the likelihood that they will compete more effectively against their... View Details
    Keywords: by Carmen Nobel
    • March 2022 (Revised January 2025)
    • Technical Note

    Linear Regression

    By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
    This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to... View Details
    Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
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    Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Technical Note 622-100, March 2022. (Revised January 2025.)
    • 2015
    • Working Paper

    Financial Patent Quality: Finance Patents After State Street

    By: Josh Lerner, Andrew Speen, Mark Baker and Ann Leamon
    In the past two decades, patents of inventions related to financial services ("finance patents"), as well as litigation around these patents, have surged. One of the repeated concerns voiced by academics and practitioners alike has been about the quality of these... View Details
    Keywords: Patents; Lawsuits and Litigation; Finance
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    Lerner, Josh, Andrew Speen, Mark Baker, and Ann Leamon. "Financial Patent Quality: Finance Patents After State Street." Harvard Business School Working Paper, No. 16-068, December 2015.
    • 2020
    • Article

    Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion

    By: Dimitris Bertsimas and Michael Lingzhi Li
    We formulate the problem of matrix completion with and without side information as a non-convex optimization problem. We design fastImpute based on non-convex gradient descent and show it converges to a global minimum that is guaranteed to recover closely the... View Details
    Keywords: Mathematical Methods
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    Bertsimas, Dimitris, and Michael Lingzhi Li. "Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion." Journal of Machine Learning Research 21, no. 1 (2020).
    • October–December 2022
    • Article

    Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

    By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
    Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
    Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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    Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
    • 16 Sep 2019
    • Research & Ideas

    Crowdsourcing Is Helping Hollywood Reduce the Risk of Movie-Making

    anything as monumental as a multimillion-dollar feature film." The answer resonates beyond Hollywood, carrying implications for any industry in which the stakes are high, uncertainty looms large, and alternative methods to de-risk ideas... View Details
    Keywords: by Michael Blanding; Motion Pictures & Video
    • June 2010
    • Article

    Are You a High Potential?

    By: Douglas A. Ready, Jay A. Conger and Linda A. Hill
    Some employees are more talented than others, and nearly every company has its method for identifying their high-potential managers. So how can you get on your company's high-potential list? Douglas A. Ready, of the talent-management research center ICEDR; Jay A.... View Details
    Keywords: Talent and Talent Management; Employees; Leadership Development; Personal Development and Career; Personal Characteristics
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    Ready, Douglas A., Jay A. Conger, and Linda A. Hill. "Are You a High Potential?" Harvard Business Review 88, no. 6 (June 2010).
    • Research Summary

    Overview

    Social psychologist Amy Cuddy, an associate professor at Harvard Business School, uses experimental methods to investigate how people judge each other and themselves. Her research suggests that judgments along two critical trait dimensions – warmth/trustworthiness and... View Details

      The Impact of Artificial Intelligence on Innovation

      Artificial intelligence promises to greatly increase the efficiency of the economy. But it may have an even larger impact on the economy by serving as a new general-purpose “method of invention” that can reshape the nature of the... View Details

      • 2019
      • Article

      Overcoming Cultural Resistance to Open Source Innovation

      By: John Winsor, Jin Hyun Paik, Michael Tushman and Karim R. Lakhani
      Purpose: This article offers insight on how to effectively help incumbent organizations prepare for global business shifts to open source and digital business models.
      Design/methodology/approach: Discussion related to observation, experience and case studies... View Details
      Keywords: Open Source Innovation; Organizational Culture; Organizational Change and Adaptation; Business Model; Technological Innovation; Collaborative Innovation and Invention
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      Winsor, John, Jin Hyun Paik, Michael Tushman, and Karim R. Lakhani. "Overcoming Cultural Resistance to Open Source Innovation." Strategy & Leadership 47, no. 6 (2019): 28–33.
      • Research Summary

      Overview

      By: Alison Wood Brooks
      Professor Brooks studies the psychology of conversation and emotion—topics at the intersection of how people think, feel, and interact. From pitching ideas to seeking advice, from asking questions to giving compliments, from talking about (or hiding) our feelings and... View Details
      Keywords: Anxiety; Emotion; Emotion Regulation; Reappraisal; Negotiation; Trust; Performance
      • 2021
      • Working Paper

      Technology Differentiation and Firm Performance

      By: Sam Arts, Bruno Cassiman and Jianan Hou
      Prior work has extensively studied how investing in R&D and building a technology portfolio relate to superior firm performance. However, the value of a firm’s technology portfolio should also be driven by the degree to which it is more unique and technologically... View Details
      Keywords: Technology Portfolio; Differentiation; Competitiveness; Organizations; Technology; Performance; United States
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      Arts, Sam, Bruno Cassiman, and Jianan Hou. "Technology Differentiation and Firm Performance." Harvard Business School Working Paper, No. 22-040, December 2021.
      • August 2021
      • Article

      Multiple Imputation Using Gaussian Copulas

      By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky
      Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use... View Details
      Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation
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      Hollenbach, F.M., I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward, and A. Volfovsky. "Multiple Imputation Using Gaussian Copulas." Special Issue on New Quantitative Approaches to Studying Social Inequality. Sociological Methods & Research 50, no. 3 (August 2021): 1259–1283. (0049124118799381.)
      • Research Summary

      Executive Compensation

      By: Tatiana Sandino

      Professor Sandino’s other stream of research examines players that influence the design of an executive’s compensation. She has examined the role shareholder activists can play in influencing CEO pay and found that a compensation-related shareholder proposal could... View Details

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