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  • All HBS Web  (2,963)
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    • Research  (2,196)
    • Events  (43)
    • Multimedia  (14)
  • Faculty Publications  (1,424)

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  • All HBS Web  (2,963)
    • News  (476)
    • Research  (2,196)
    • Events  (43)
    • Multimedia  (14)
  • Faculty Publications  (1,424)
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  • December 2005
  • Article

Adjusting Choice Models to Better Predict Market Behavior

By: Greg Allenby, Geraldine Fennel, Joel Huber, Thomas Eagle, Tim Gilbride, Jaehwan Kim, Peter Lenk, Rich Johnson, Bryan Orme, Elie Ofek, Thomas Otter and Joan Walker
Keywords: Decision Choices and Conditions; Markets; Behavior
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Allenby, Greg, Geraldine Fennel, Joel Huber, Thomas Eagle, Tim Gilbride, Jaehwan Kim, Peter Lenk, Rich Johnson, Bryan Orme, Elie Ofek, Thomas Otter, and Joan Walker. "Adjusting Choice Models to Better Predict Market Behavior." Marketing Letters 16, nos. 3/4 (December 2005).
  • 30 May 2023
  • Research & Ideas

Can AI Predict Whether Shoppers Would Pick Crest or Colgate?

data.” The researchers also found that telling GPT that it had purchased a product before, such as yogurt, and how much of the product the “customer” already had at home, affected purchasing decisions in predictable ways: the more yogurt... View Details
Keywords: by Kristen Senz
  • Article

The Critical Role of Second-order Normative Beliefs in Predicting Energy Conservation

By: Jon M. Jachimowicz, Oliver P. Hauser, Julia D. O'Brien, Erin Sherman and Adam D. Galinsky
Sustaining large-scale public goods requires individuals to make environmentally friendly decisions today to benefit future generations. Recent research suggests that second-order normative beliefs are more powerful predictors of behaviour than first-order personal... View Details
Keywords: Climate Change; Energy; Environmental Sustainability; Household; Behavior; Values and Beliefs; Forecasting and Prediction
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Jachimowicz, Jon M., Oliver P. Hauser, Julia D. O'Brien, Erin Sherman, and Adam D. Galinsky. "The Critical Role of Second-order Normative Beliefs in Predicting Energy Conservation." Nature Human Behaviour 2, no. 10 (October 2018): 757–764.
  • May 2022
  • Article

Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks

By: Dan Amiram, Evgeny Lyandres and Daniel Rabetti
This study examines whether we can learn from the behavior of blockchain-based transfers to predict the financing of terrorist attacks. We exploit blockchain transaction transparency to map millions of transfers for hundreds of large on-chain service providers. The... View Details
Keywords: Blockchain; Bitcoin; Accounting; AI and Machine Learning; National Security; Governing Rules, Regulations, and Reforms
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Amiram, Dan, Evgeny Lyandres, and Daniel Rabetti. "Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks." Journal of Accounting Research 60, no. 2 (May 2022): 427–466.
  • February 2022
  • Teaching Note

Borusan CAT: Monetizing Prediction in the Age of AI

By: Navid Mojir
Teaching Note for HBS Case No. 521-053. View Details
Keywords: Monetization Strategy; Artificial Intelligence; Forecasting and Prediction; Applications and Software; Technological Innovation; Marketing; Segmentation; AI and Machine Learning; Construction Industry; Turkey
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Mojir, Navid. "Borusan CAT: Monetizing Prediction in the Age of AI." Harvard Business School Teaching Note 522-069, February 2022.
  • 2005
  • Article

Airline Security, the Failure of 9/11, and Predictable Surprises

By: M. Bazerman and M. Watkins
Keywords: National Security; Failure
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Bazerman, M., and M. Watkins. "Airline Security, the Failure of 9/11, and Predictable Surprises." International Public Management Journal 8, no. 3 (2005): 365–377.
  • fall 2004
  • Article

Predictable Negotiations: Should Have Seen This Coming (Book Excerpt)

By: M. Bazerman and Michael Watkins
Keywords: Negotiation; Books
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Bazerman, M., and Michael Watkins. "Predictable Negotiations: Should Have Seen This Coming (Book Excerpt)." Compass 2, no. 1 (fall 2004): 42–43.
  • Article

Mining Big Data to Extract Patterns and Predict Real-Life Outcomes

By: Michal Kosinki, Yilun Wang, Himabindu Lakkaraju and Jure Leskovec
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Kosinki, Michal, Yilun Wang, Himabindu Lakkaraju, and Jure Leskovec. "Mining Big Data to Extract Patterns and Predict Real-Life Outcomes." Psychological Methods 21, no. 4 (December 2016): 493–506.
  • 21 Jun 2013 - 22 Jun 2013
  • Conference Presentation

Stock Market Prediction via Social Media: The Importance of Competitors

By: Frank Nagle
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Nagle, Frank. "Stock Market Prediction via Social Media: The Importance of Competitors." Paper presented at the 11th ZEW Conference on the Economics of Information and Communication Technologies, Center for European Economic Research (ZEW), Mannheim, Germany, June 21–22, 2013.
  • 16 Mar 2018
  • Working Paper Summaries

Amount and Diversity of Digital Emotional Expression Predicts Happiness

Keywords: by Laura Vuillier, Alison Wood Brooks, June Gruber, Rui Sun, Michael I. Norton, Matthew James Samson, Emiliana Simon-Thomas, Paul Piff, Sarah Fan, Jordi Quoidbach, Charles Gorintin, Pete Fleming, Arturo Bejar, and Dacher Keltner
  • July– September 2002
  • Article

Predictive Value and the Usefulness of Game Theoretic Models

By: Ido Erev, Alvin E. Roth, Robert L. Slonim and Greg Barron
Keywords: Value; Games, Gaming, and Gambling; Theory
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Erev, Ido, Alvin E. Roth, Robert L. Slonim, and Greg Barron. "Predictive Value and the Usefulness of Game Theoretic Models." International Journal of Forecasting 18, no. 3 (July– September 2002): 359–368.
  • 21 Oct 2015
  • Research & Ideas

How to Predict if a New Business Idea is Any Good

other once unlikely, now successful startups (LinkedIn similarly got more than 20 rejections back in 2003) seem to beg: How do you tell a good idea from a bad one? “With startups, especially high-growth startups, it’s extremely hard to View Details
Keywords: by Michael Blanding; Accommodations; Financial Services
  • May 2018
  • Article

The Amount and Source of Millionaires' Wealth (Moderately) Predicts Their Happiness

By: Grant Edward Donnelly, Tianyi Zheng, Emily Haisley and Michael I. Norton
Two samples of more than 4,000 millionaires reveal two primary findings. First, only at high levels of wealth—in excess of $8 million (Study 1) and $10 million (Study 2)—are wealthier millionaires happier than millionaires with lower levels of wealth, though these... View Details
Keywords: Income; Well-being; Happiness; Wealth; Money; Attitudes; Situation or Environment
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Donnelly, Grant Edward, Tianyi Zheng, Emily Haisley, and Michael I. Norton. "The Amount and Source of Millionaires' Wealth (Moderately) Predicts Their Happiness." Personality and Social Psychology Bulletin 44, no. 5 (May 2018): 684–699.
  • Summer 2021
  • Article

Predictable Country-level Bias in the Reporting of COVID-19 Deaths

By: Botir Kobilov, Ethan Rouen and George Serafeim
We examine whether a country’s management of the COVID-19 pandemic relate to the downward biasing of the number of reported deaths from COVID-19. Using deviations from historical averages of the total number of monthly deaths within a country, we find that the... View Details
Keywords: COVID-19; Deaths; Reporting; Incentives; Government Policy; Health Pandemics; Health Care and Treatment; Country; Crisis Management; Outcome or Result; Reports; Policy
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Kobilov, Botir, Ethan Rouen, and George Serafeim. "Predictable Country-level Bias in the Reporting of COVID-19 Deaths." Journal of Government and Economics 2 (Summer 2021).
  • Article

Physical and Situational Inequality on Airplanes Predict Air Rage

By: K. A. DeCelles and Michael I. Norton
We posit that the modern airplane is a social microcosm of class-based society, and that the increasing incidence of “air rage” can be understood through the lens of inequality. Research on inequality typically examines the effects of relatively fixed, macrostructural... View Details
Keywords: Physical Inequality; Equality and Inequality; Behavior; Air Transportation; Situation or Environment
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DeCelles, K. A., and Michael I. Norton. "Physical and Situational Inequality on Airplanes Predict Air Rage." Proceedings of the National Academy of Sciences 113, no. 20 (May 17, 2016): 5588–5591.
  • March 2003
  • Article

Predictable Surprises: The Disasters You Should Have Seen Coming

By: Michael D. Watkins and Max H. Bazerman
Citation
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Watkins, Michael D., and Max H. Bazerman. "Predictable Surprises: The Disasters You Should Have Seen Coming." Harvard Business Review 81, no. 3 (March 2003). (Reprinted in H. Balanoff (Ed.), Public Administration, McGraw-Hill, 2004.)
  • March 2013
  • Article

Misvaluing Innovation

By: Lauren Cohen, Karl Diether and Christopher Malloy
We demonstrate that a firm's ability to innovate is predictable, persistent, and relatively simple to compute, and yet the stock market ignores the implications of past successes when valuing future innovation. We show that two firms that invest the exact same in... View Details
Keywords: Innovation; Return Predictability; R&D; Information; Forecasting and Prediction; Research and Development; Innovation and Invention
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Cohen, Lauren, Karl Diether, and Christopher Malloy. "Misvaluing Innovation." Review of Financial Studies 26, no. 3 (March 2013): 635–666.
  • 2023
  • Working Paper

Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial intelligence and machine learning business applications. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms)... View Details
Keywords: Analytics and Data Science
Citation
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Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
  • April 2024
  • Article

A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification

By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
Keywords: Health Disorders; Health Testing and Trials; AI and Machine Learning; Health Industry
Citation
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Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification." Journal of Pediatric Urology 20, no. 2 (April 2024): 271–278.
  • December 2023
  • Supplement

Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs

By: Jonas Heese and Jung Koo Kang
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Heese, Jonas, and Jung Koo Kang. "Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs." Harvard Business School Spreadsheet Supplement 124-708, December 2023.
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