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Publications

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  • All HBS Web  (2,884)
    • News  (476)
    • Research  (2,210)
    • Events  (43)
    • Multimedia  (14)
  • Faculty Publications  (1,424)

Show Results For

  • All HBS Web  (2,884)
    • News  (476)
    • Research  (2,210)
    • Events  (43)
    • Multimedia  (14)
  • Faculty Publications  (1,424)
← Page 10 of 2,884 Results →
  • 2018
  • Working Paper

Moral Prospection: Cognitive Bias and the Failure to Predict Moral Backlash Toward an Organization

By: J. Lees
Citation
Related
Lees, J. "Moral Prospection: Cognitive Bias and the Failure to Predict Moral Backlash Toward an Organization." Working Paper, November 2018.
  • 2014
  • Working Paper

Amount and Diversity of Emotional Expression on Facebook Predicts Life Satisfaction around the World

By: A. Kogan, F. Zhang, R. Sun, E. Simon-Thomas, P. Piff, S. Fan, J. Gruber, J. Quoidbach, M. I. Norton, C. Gronin, P. Fleming, D. Keltner and A.W. Brooks
Citation
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Kogan, A., F. Zhang, R. Sun, E. Simon-Thomas, P. Piff, S. Fan, J. Gruber, J. Quoidbach, M. I. Norton, C. Gronin, P. Fleming, D. Keltner, and A.W. Brooks. "Amount and Diversity of Emotional Expression on Facebook Predicts Life Satisfaction around the World." Working Paper, 2014.
  • 2022
  • Working Paper

TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations

By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet they have become more complex and harder to understand. To address this issue, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use explainability... View Details
Keywords: Natural Language Conversations; Predictive Models; AI and Machine Learning
Citation
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Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations." Working Paper, 2022.
  • June 2019
  • Supplement

Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics

By: Michael W. Toffel and Dan Levy
Citation
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Toffel, Michael W., and Dan Levy. "Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics." Harvard Business School Spreadsheet Supplement 619-719, June 2019.
  • 2013
  • Working Paper

Appendix to 'Return Predictability in the Treasury Market: Real Rates, Inflation, and Liquidity'

By: Carolin E. Pflueger and Luis M. Viceira
Citation
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Pflueger, Carolin E., and Luis M. Viceira. "Appendix to 'Return Predictability in the Treasury Market: Real Rates, Inflation, and Liquidity'." Working Paper, September 2013.
  • fall 1999
  • Article

(Dis)Respecting versus (Dis)liking: Status and Interdepenences Predict Ambivalent Stereotypes of Competence and Warmth

By: S.T. Fiske, J. Xu, A.J.C. Cuddy and P. Glick
Keywords: Status and Position; Attitudes; Competency and Skills
Citation
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Fiske, S.T., J. Xu, A.J.C. Cuddy, and P. Glick. "(Dis)Respecting versus (Dis)liking: Status and Interdepenences Predict Ambivalent Stereotypes of Competence and Warmth." Journal of Social Issues 55, no. 3 (fall 1999): 473–490.
  • 1998
  • Book

Do Lunch or Be Lunch: The Power of Predictability in Creating Your Future

By: H. H. Stevenson and Jeffrey L. Cruikshank
Keywords: Personal Development and Career
Citation
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Stevenson, H. H., and Jeffrey L. Cruikshank. Do Lunch or Be Lunch: The Power of Predictability in Creating Your Future. Boston: Harvard Business School Press, 1998.
  • Article

Learning and Equilibrium as Useful Approximations: Accuracy of Prediction on Randomly Selected Constant Sum Games

By: Ido Erev, Alvin E. Roth, R. Slonim and Greg Barron
Keywords: Learning; Forecasting and Prediction; Outcome or Result
Citation
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Erev, Ido, Alvin E. Roth, R. Slonim, and Greg Barron. "Learning and Equilibrium as Useful Approximations: Accuracy of Prediction on Randomly Selected Constant Sum Games." Special Issue on Behavioral Game Theory. Economic Theory 33, no. 1 (October 2007): 29–51.
  • September 1998
  • Article

Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria

By: Ido Erev and A. E. Roth
Keywords: Games, Gaming, and Gambling; Forecasting and Prediction; Learning; Strategy
Citation
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Erev, Ido, and A. E. Roth. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria." American Economic Review 88, no. 4 (September 1998): 848–881.
  • 01 Jun 2023
  • News

3-Minute Briefing: Jeremy Grantham (MBA 1966)

change, geopolitics, declining fertility rates, bad agricultural practices, high levels of debt, shortages of labor and raw materials, and more. You can’t predict the stress point, but the fact that something will crack is not... View Details
Keywords: climate change; finance; sustainability; prediction; Finance
  • 2006
  • Working Paper

Learning and Equilibrium As Useful Approximations: Accuracy of Prediction on Randomly Selected Constant Sum Games

By: Ido Erev, Alvin E. Roth, Robert L. Slonim and Greg Barron
Citation
Related
Erev, Ido, Alvin E. Roth, Robert L. Slonim, and Greg Barron. "Learning and Equilibrium As Useful Approximations: Accuracy of Prediction on Randomly Selected Constant Sum Games." Harvard Business School Working Paper, No. 07-004, July 2006.
  • 2021
  • Working Paper

When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making

By: Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage and Himabindu Lakkaraju
Citation
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McGrath, Sean, Parth Mehta, Alexandra Zytek, Isaac Lage, and Himabindu Lakkaraju. "When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making." Working Paper, January 2021.
  • Article

Modeling dependencies between rating categories and their effects on prediction in a credit risk portfolio

Citation
Related
Czado, Claudia, and Carolin Elisabeth Pflueger. "Modeling dependencies between rating categories and their effects on prediction in a credit risk portfolio." Applied Stochastic Models in Business and Industry 24, no. 3 (May–June 2008).
  • 02 Feb 2025
  • News

Why the 2024 US Election, and So Many Others, Were So Hard to Predict

  • 20 Feb 2023
  • News

Some Predicted an Imminent Death for Twitter. It’s Still Here. Can Elon Musk Keep It Alive?

  • 15 Jun 2004
  • Conference Presentation

What is the Best Measure of Adiposity for Predicting Testosterone? Results from the Massachusetts Male Aging Study

By: William B. Simpson, Frances J. Hayes, Andre B. Araujo and John B. McKinlay
Keywords: Measurement and Metrics; Health Testing and Trials; Age Characteristics; Gender Characteristics; Massachusetts
Citation
Related
Simpson, William B., Frances J. Hayes, Andre B. Araujo, and John B. McKinlay. "What is the Best Measure of Adiposity for Predicting Testosterone? Results from the Massachusetts Male Aging Study." Paper presented at the Enocrine Society Annual Meeting, New Orleans, LA, June 15, 2004.
  • 2019
  • Working Paper

Managing Churn to Maximize Profits

By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability, or their responsiveness to a... View Details
Keywords: Churn Management; Defection Prediction; Loss Function; Stochastic Gradient Boosting; Customer Relationship Management; Consumer Behavior; Profit
Citation
SSRN
Read Now
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Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Harvard Business School Working Paper, No. 14-020, September 2013. (Revised December 2019. Forthcoming at Marketing Science.)
  • July 2019
  • Article

I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice

By: Kate Barasz, Tami Kim and Ioannis Evangelidis
People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen... View Details
Keywords: Self-other Difference; Social Perception; Inference-making; Preferences; Consumer Behavior; Prediction; Prediction Error; Decision Choices and Conditions; Perception; Behavior; Forecasting and Prediction
Citation
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Barasz, Kate, Tami Kim, and Ioannis Evangelidis. "I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice." Special Issue on The Cognitive Science of Political Thought. Cognition 188 (July 2019): 85–97.
  • September–October 2020
  • Article

Managing Churn to Maximize Profits

By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability or their responsiveness to a... View Details
Keywords: Churn Management; Defection Prediction; Loss Function; Stochastic Gradient Boosting; Customer Relationship Management; Consumer Behavior; Profit
Citation
SSRN
Find at Harvard
Related
Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Marketing Science 39, no. 5 (September–October 2020): 956–973.
  • August 2021
  • Case

Precision Paint Co.

By: Iavor I. Bojinov, Chiara Farronato, Janice H. Hammond, Michael Parzen and Paul Hamilton
Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case. View Details
Keywords: Regression; Prediction; Forecasting; Data Science; Analysis; Forecasting and Prediction
Citation
Educators
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Related
Bojinov, Iavor I., Chiara Farronato, Janice H. Hammond, Michael Parzen, and Paul Hamilton. "Precision Paint Co." Harvard Business School Case 622-055, August 2021.
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