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  • 23 Oct 2018
  • First Look

New Research and Ideas, October 23, 2018

forecast less extreme)? To answer these questions, we introduce a class of optimal aggregators. These aggregators are Bayesian ensembles because they follow from a Bayesian model of the underlying information experts have. Each ensemble... View Details
Keywords: Dina Gerdeman
  • January 2011
  • Article

Good Intentions, Optimistic Self-Predictions, and Missed Opportunities

By: Derek Koehler, Rebecca White and Leslie K. John
Self-predictions are highly sensitive to current intentions but often largely insensitive to factors influencing the readiness with which those intentions are translated into future behavior. When such factors are under a person's control, they could be used to... View Details
Keywords: Planning; Saving; Behavior; Forecasting and Prediction
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  • February 2025
  • Tutorial

Preparing Business Leaders for an Era of Climate Instability: Understanding and Managing Physical Climate Risk

By: Michael W. Toffel and Spencer Glendon
In this compelling video, Spencer Glendon, founder of Probable Futures and Executive Fellow at Harvard Business School, describes the profound implications of climate change for businesses, the economy, and societies around the world. Drawing from his background in... View Details
Keywords: Modeling; Climate Change; Adaptation; Risk and Uncertainty; Risk Management; Forecasting and Prediction
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  • October 2024
  • Article

Canary Categories

By: Eric Anderson, Chaoqun Chen, Ayelet Israeli and Duncan Simester
Past customer spending in a category is generally a positive signal of future customer spending. We show that there exist “canary categories” for which the reverse is true. Purchases in these categories are a signal that customers are less likely to return to that... View Details
Keywords: Churn; Churn Management; Churn/retention; Assortment Planning; Retail; Retailing; Retailing Industry; Preference Heterogeneity; Assortment Optimization; Customers; Retention; Consumer Behavior; Forecasting and Prediction; Retail Industry
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  • 2011
  • Chapter

Prospective Codes Fufilled: A Potential Neural Mechanism of Will

By: Thalia Wheatley and Christine E. Looser
One of my few shortcomings is that I can’t predict the future.
Lars Ulrich, Metallica.

Lars Ulrich was right and wrong. He was right in the way we most often think about the future—as a long stretch of time during which multiply... View Details
Keywords: Free Will; Neuroscience; Responsibility; Prospection; Forecasting and Prediction; Science; Cognition and Thinking
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  • TeachingInterests

Decision Making Under Uncertainty

By: David E. Bell

Many of the decisions we face are made complicated by having uncertain consequences: how should I set my inventory when I don’t know what demand will be, should I refinance my mortgage when rates might go lower, how big a bet shall I make in a new business, and so... View Details

  • Article

Towards Robust and Reliable Algorithmic Recourse

By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan approvals), there has been growing interest in post-hoc techniques which provide recourse to affected individuals. These techniques generate recourses under the assumption... View Details
Keywords: Machine Learning Models; Algorithmic Recourse; Decision Making; Forecasting and Prediction
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  • Forthcoming
  • Article

An AI Method to Score Celebrity Visual Potential from Human Faces

By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton
It has long been a mantra of marketing practice that, particularly in low-involvement situations, spokespeople should be physically attractive. This paper suggests there is a higher probability of gaining fame and influence (i.e., celebrity potential) than is captured... View Details
Keywords: Personal Characteristics; AI and Machine Learning; Forecasting and Prediction; Marketing
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  • 12 Aug 2014
  • First Look

First Look: August 12

arises from behavioral biases and misperceptions of probability distributions. Finally, nonpecuniary taste-based factors may be important in motivating both the decisions to enter into and to persist in entrepreneurship. Publisher's link:... View Details
Keywords: Sean Silverthorne
  • June 2009
  • Article

Highbrow Films Gather Dust: Time-inconsistent Preferences and Online DVD Rentals

By: Katherine L. Milkman, Todd Rogers and Max H. Bazerman
We report on a field study demonstrating systematic differences between the preferences people anticipate they will have over a series of options in the future and their subsequent revealed preferences over those options. Using a novel panel data set, we analyze the... View Details
Keywords: Decision Choices and Conditions; Forecasting and Prediction; Film Entertainment; Demand and Consumers; Renting or Rental; Power and Influence; Prejudice and Bias; Online Technology; Motion Pictures and Video Industry
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  • 2011
  • Article

A Choice Prediction Competition for Social Preferences in Simple Extensive Form Games: An Introduction

By: Eyal Ert, Ido Erev and Alvin E. Roth
Two independent, but related, choice prediction competitions are organized that focus on behavior in simple two-person extensive form games: one focuses on predicting the choices of the first mover and the other on predicting the choices of the second mover. The... View Details
Keywords: Forecasting and Prediction; Behavior; Decision Choices and Conditions; Competition; Motivation and Incentives; Game Theory; Fairness
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  • Web

Behavioral Finance & Financial Stability

price increases do not predict lower returns going forward, these increases do predict substantial heightened probability of a crash. Simple attributes related to the price run up can help predict both the crash View Details
  • 26 Apr 2016
  • First Look

April 26

intermediaries—called outsourcing agencies—have emerged in these markets. This paper shows that agencies signal to employers that inexperienced workers are high quality. Workers affiliated with an agency have substantially higher job-finding View Details
Keywords: Sean Silverthorne
  • 05 Feb 2013
  • First Look

First Look: Feb. 5

earns an average risk-adjusted return of 4.68% per year. Firms with central boards also experience higher future growth in return-on-assets (ROA) with analysts failing to fully reflect this information in their earnings forecasts. Return prediction, growth in ROA, and... View Details
Keywords: Sean Silverthorne
  • 01 Dec 2023
  • News

Thinking Ahead

20-person team when your venture is pre-revenue is not impressive; it could be worrisome.” While the forecast is far from sunny, entrepreneurs are still raising funds, Austin notes—and plenty is still possible with little to no financial... View Details
Keywords: Julia Hanna; Illustrations by Chris Gash; News, Library, Internet, and Other Services; Information
  • 25 Jan 2010
  • Research & Ideas

A Macroeconomic View of the Current Economy

going to depreciate tomorrow or next week or even next month. But over time, you expect it to depreciate. So if you're a business manager, you probably want to be fairly well hedged against this possibility, either by making use of... View Details
Keywords: by Sean Silverthorne
  • 21 Oct 2015
  • Research & Ideas

How to Predict if a New Business Idea is Any Good

Operations Management unit at Harvard Business School. “They didn’t know it would turn out to be a multibillion dollar industry.” “By definition, when an investor makes an investment, it changes the probability of success” In a new... View Details
Keywords: by Michael Blanding; Accommodations; Financial Services
  • 04 May 2015
  • Research & Ideas

Need to Solve a Problem? Take a Break From Collaborating

Chatter, Microsoft's Yammer, and Jive Software's suite of namesake products. The global enterprise social software market is forecast to grow to $8.14 billion in 2019, according to MarketWatch, from $4.77 billion in 2014. “When it comes... View Details
Keywords: by Carmen Nobel; Video Game; Web Services
  • Web

Research - Behavioral Finance & Financial Stability

fintech platform, the authors find that, compared to actual outcomes of the fintech platform’s model, the counterfactual outcomes based on a “traditional model” used for regulatory reporting purposes would result in a 60% higher View Details
  • 07 Jun 2004
  • Research & Ideas

What Drives Supply Chain Behavior?

forecasts as well as decisions about inventory. In this interview with HBS Working Knowledge, Oliva and Watson say a key to understanding and avoiding supply chain inefficiency may be a better understanding of the behavioral side of the... View Details
Keywords: by Sarah Jane Johnston