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Publications

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  • All HBS Web  (4,046)
    • People  (2)
    • News  (559)
    • Research  (2,867)
    • Events  (51)
    • Multimedia  (21)
  • Faculty Publications  (2,071)

Show Results For

  • All HBS Web  (4,046)
    • People  (2)
    • News  (559)
    • Research  (2,867)
    • Events  (51)
    • Multimedia  (21)
  • Faculty Publications  (2,071)
← Page 2 of 4,046 Results →
  • August 2020
  • Article

Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation

By: Prithwiraj Choudhury, Evan Starr and Rajshree Agarwal
The use of machine learning (ML) for productivity in the knowledge economy requires considerations of important biases that may arise from ML predictions. We define a new source of bias related to incompleteness in real time inputs, which may result from strategic... View Details
Keywords: Machine Learning; Bias; Human Capital; Management; Strategy
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Choudhury, Prithwiraj, Evan Starr, and Rajshree Agarwal. "Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation." Strategic Management Journal 41, no. 8 (August 2020): 1381–1411.
  • April 2020
  • Article

Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning

By: Ariel Dora Stern and W. Nicholson Price, II
In recent years, the applications of Machine Learning (ML) in the health care delivery setting have grown to become both abundant and compelling. Regulators have taken notice of these developments and the U.S. Food and Drug Administration (FDA) has been engaging... View Details
Keywords: Machine Learning; Causal Inference; Health Care and Treatment; Safety; Governing Rules, Regulations, and Reforms
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Stern, Ariel Dora, and W. Nicholson Price, II. "Regulatory Oversight, Causal Inference, and Safe and Effective Health Care Machine Learning." Biostatistics 21, no. 2 (April 2020): 363–367.
  • October 2017 (Revised April 2018)
  • Case

Improving Worker Safety in the Era of Machine Learning (A)

By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson
Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details
Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States
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Toffel, Michael W., Dan Levy, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (A)." Harvard Business School Case 618-019, October 2017. (Revised April 2018.)
  • July 1989 (Revised August 1990)
  • Background Note

New Theories of International Trade

By: David B. Yoffie and Heather A. Hazard
Explores the "new" theories of international trade--also called strategic trade policy--which were developed in the 1980s. Examines why economists and policy makers thought new approaches were necessary to explain international trade, the contributions of industrial... View Details
Keywords: Corporate Strategy; Theory; Policy; Trade
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Yoffie, David B., and Heather A. Hazard. "New Theories of International Trade." Harvard Business School Background Note 390-001, July 1989. (Revised August 1990.)
  • March 2015
  • Article

Institutional Theory and the Natural Environment: Research in (and on) the Anthropocene

By: Andrew J. Hoffman and P. Devereaux Jennings
This review article summarizes the main tenets of institutional theory as they apply to the topic of the Anthropocene in the domain of organization and the natural environment. But our review is distinctive for two reasons: First, it is focused on providing avenues... View Details
Keywords: Institutional Theory; Natural Environment; Society
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Hoffman, Andrew J., and P. Devereaux Jennings. "Institutional Theory and the Natural Environment: Research in (and on) the Anthropocene." Special Issue on Review of the Literature on Organizations and Natural Environment: From the Past to the Future edited by Stephanie Bertels and Frances Bowen. Organization & Environment 28, no. 1 (March 2015): 8–31.
  • January 2021
  • Article

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details
Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning
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Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
  • July 2012
  • Case

Owen's Precision Machining

By: Ramana Nanda and James McQuade
For the second time in fourteen months, Christopher Owen, the second-generation owner of Owen's Precision Machining (OPM), found himself running out of cash. Owen wondered what he was doing wrong. How much additional money would he need to raise to get OPM through the... View Details
Keywords: Family Business; Cash Flow; Mergers and Acquisitions; Decision Making; Problems and Challenges; Business Strategy; Corporate Finance; Manufacturing Industry; Massachusetts
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Nanda, Ramana, and James McQuade. "Owen's Precision Machining." Harvard Business School Case 813-036, July 2012.
  • February 2021
  • Tutorial

Assessing Prediction Accuracy of Machine Learning Models

By: Michael Toffel and Natalie Epstein
This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and... View Details
Keywords: Statistics; Experiments; Forecasting and Prediction; Performance Evaluation; AI and Machine Learning
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Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021. (Click here to access this tutorial.)
  • June 2004
  • Article

A Catering Theory of Dividends

By: Malcolm Baker and Jeffrey Wurgler
We propose that the decision to pay dividends is driven by prevailing investor demand for dividend payers. Managers cater to investors by paying dividends when investors put a stock price premium on payers, and by not paying when investors prefer nonpayers. To test... View Details
Keywords: Dividends; Catering; Financial Instruments; Investment Return; Business and Shareholder Relations
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Baker, Malcolm, and Jeffrey Wurgler. "A Catering Theory of Dividends." Journal of Finance 59, no. 3 (June 2004): 1125–1165.
  • 2010
  • Chapter

A Contingency Theory of Leadership

By: Jay W. Lorsch
The idea of a contingency theory of leadership is not novel. In the 1960s several scholars conducted research and proposed such an approach arguing that the style of leadership that would be most effective depended upon the situation (Fiedler, Tannenbaum and Schmidt,... View Details
Keywords: Leadership Style; Situation or Environment; Behavior; Theory
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Lorsch, Jay W. "A Contingency Theory of Leadership." Chap. 15 in Handbook of Leadership Theory and Practice, edited by Nitin Nohria and Rakesh Khurana. Harvard Business Press, 2010.
  • 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
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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.
  • 2020
  • Working Paper

A General Theory of Identification

By: Iavor Bojinov and Guillaume Basse
What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree on a definition in the context of parametric statistical models — roughly, a parameter θ in a model P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective.... View Details
Keywords: Identification; Econometric Models; Analytics and Data Science; Theory
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Bojinov, Iavor, and Guillaume Basse. "A General Theory of Identification." Harvard Business School Working Paper, No. 20-086, February 2020.
  • 06 Apr 2020
  • Working Paper Summaries

A General Theory of Identification

Keywords: by Iavor Bojinov and Guillaume Basse
  • February 2013
  • Article

An Activity-Generating Theory of Regulation

By: Joshua Schwartzstein and Andrei Shleifer
We propose an activity-generating theory of regulation. When courts make errors, tort litigation becomes unpredictable and as such imposes risk on firms, thereby discouraging entry, innovation, and other socially desirable activity. When social returns to activity are... View Details
Keywords: Courts and Trials; Lawsuits and Litigation; Governing Rules, Regulations, and Reforms; Theory
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Schwartzstein, Joshua, and Andrei Shleifer. "An Activity-Generating Theory of Regulation." Journal of Law & Economics 56, no. 1 (February 2013): 1–38. (Lead Article.)
  • 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
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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.)
  • 31 Dec 2012
  • News

Big Data: Rise of the Machines

    Handbook of Leadership Theory and Practice

    The Handbook of Leadership Theory and Practice seeks to bridge this disconnect. Based on the Harvard Business School Centennial Colloquium "Leadership: Advancing an Intellectual Discipline" and edited by HBS professors Nitin Nohria and Rakesh Khurana, this volume... View Details
    • April 1980 (Revised December 1991)
    • Case

    Hampton Machine Tool Co.

    A bank lending officer must decide whether to extend and increase a loan to a small machine tool company. Case provides sufficient data for preparation of cash budgets and pro forma financial statements in order to analyze the lending officer's problem. Other issues... View Details
    Keywords: Machinery and Machining; Financing and Loans; Financial Statements; Manufacturing Industry
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    Mullins, David W., Jr. "Hampton Machine Tool Co." Harvard Business School Case 280-103, April 1980. (Revised December 1991.)
    • 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
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    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.
    • Research Summary

    Making Machine Learning Models Fair

    By: Himabindu Lakkaraju
    The goal of this research direction is to ensure that the machine learning models we build and deploy do not discriminate against individuals from minority groups. View Details
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