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    • COVID-19 Business Impact Center
      COVID-19 Business Impact Center
      Cold Call
      A podcast featuring faculty discussing cases they've written and the lessons they impart.
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      • 06 Apr 2021
      • Cold Call Podcast

      Disrupting the Waste Industry with Technology

      Rubicon began with a bold idea: create a cloud-based, full-service waste management platform, providing efficient service anywhere in the US. Their mobile app did for waste management what Uber had done for taxi service. Five years after the case’s publication, Harvard Business School Associate Professor Shai Bernstein and Rubicon founder and CEO Nate Morris discuss how the software startup leveraged technology to disrupt the waste industry and other enduring lessons of professor Bill Sahlman’s case about Rubicon.  Open for comment; 0 Comment(s) posted.

      Read the Transcript

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      Forecasting and PredictionRemove Forecasting and Prediction →

      New research on forecasting and predication from Harvard Business School faculty on issues including forecasting success or failure of new ventures, why countries have difficulty controlling budget deficits, and new models for predicting the success of marketing investments.
      Page 1 of 23 Results →
      • 24 Sep 2020
      • Research & Ideas

      Financial Meltdowns Are More Predictable Than We Thought

      by Danielle Kost

      Robin Greenwood and Samuel G. Hanson discuss new research that shows economic crises follow predictable patterns. Open for comment; Comment(s) posted.

      • 02 Aug 2020
      • What Do You Think?

      Is the 'Experimentation Organization' Becoming the Competitive Gold Standard?

      by James Heskett

      SUMMING UP: Digital experimentation is gaining momentum as an everyday habit in many organizations, especially those in high tech, say James Heskett's readers. Open for comment; Comment(s) posted.

      • 21 Jul 2020
      • Working Paper Summaries

      Business Reopening Decisions and Demand Forecasts During the COVID-19 Pandemic

      by Dylan Balla-Elliott, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, and Christopher Stanton

      Findings from a nationwide survey underscore the importance of demand projections and interdependencies among businesses for owners’ reopening decisions. Businesses expect the demand for their services will be greatly depressed for many months to come.

      • 04 May 2020
      • Research & Ideas

      Predictions, Prophets, and Restarting Your Business

      by Frank V. Cespedes

      Businesses are starting to plan their re-entry into the market, but how do they know what that market will look like? Frank V. Cespedes warns against putting too much trust in forecasters. Open for comment; Comment(s) posted.

      • 04 Dec 2019
      • Book

      Creating the Experimentation Organization

      by Michael Blanding

      New tools allow companies to innovate on an unprecedented scale, in every aspect of business. But the organization must also change. Stefan Thomke previews his forthcoming book, Experimentation Works. Open for comment; Comment(s) posted.

      • 13 Nov 2019
      • Research & Ideas

      Don't Turn Your Marketing Function Over to AI Just Yet

      by Kristen Senz

      Lacking human insight, artificial intelligence will be limited when it comes to helping marketers open the black box of market prediction, says Tomomichi Amano. Open for comment; Comment(s) posted.

      • 22 Oct 2019
      • Research & Ideas

      Use Artificial Intelligence to Set Sales Targets That Motivate

      by Michael Blanding

      Setting sales targets has always been an inexact science, with serious consequences if done poorly. Using AI-based advanced analytics might be the answer, argues Doug Chung. Open for comment; Comment(s) posted.

      • 18 Sep 2019
      • Working Paper Summaries

      Using Models to Persuade

      by Joshua Schwartzstein and Adi Sunderam

      “Model persuasion” happens when would-be persuaders offer receivers a streamlined way of understanding data they already know, especially when the data is open to interpretation. Using examples from finance, politics, and law, the authors find that truthtellers do not eliminate the impact of misleading persuasion because wrong models may better fit the past than correct models.

      • 07 Jun 2019
      • Working Paper Summaries

      Reflexivity in Credit Markets

      by Robin Greenwood, Samuel G. Hanson, and Lawrence J. Jin

      Investors’ biases and market outcomes affect each other in a two-way feedback loop. This study develops a model of a credit market feedback loop, finding that when investors become more bullish this can predict positive returns in the short run, even if expected returns become more negative at longer horizons.

      • 10 May 2019
      • Working Paper Summaries

      Consumer Inertia and Market Power

      by Alexander MacKay and Marc Remer

      Consumers are often more likely to buy a product if they have purchased it previously. This paper provides a means to estimate the magnitude of this phenomenon (i.e., consumer inertia) and shows how it affects the prices of firms in competitive settings. Perhaps surprisingly, greater consumer inertia can result in smaller price increases after a merger.

      • 27 Feb 2019
      • Working Paper Summaries

      Judgment Aggregation in Creative Production: Evidence from the Movie Industry

      by Hong Luo, Jeffrey T. Macher, and Michael Wahlen

      Selecting early-stage ideas in creative industries is challenging because consumer taste is hard to predict and the quantity to sift through is large. Using The Black List that ranks scripts annually based on nominations from film executives, this study shows that aggregating expert opinions helps reduce quality uncertainty and can influence high-budget production.

      • 07 Jan 2019
      • Research & Ideas

      The Better Way to Forecast the Future

      by Roberta Holland

      We can forecast hurricane paths with great certainty, yet many businesses can't predict a supply chain snafu just around the corner. Yael Grushka-Cockayne says crowdsourcing can help. Open for comment; Comment(s) posted.

      • 26 Nov 2018
      • Working Paper Summaries

      Demand Estimation in Models of Imperfect Competition

      by Alexander MacKay and Nathan H. Miller

      The study shows how knowledge about firm behavior can be modeled to better predict demand. Firms tend to raise prices in response to higher demand, so observed relationships between price and quantity can be quite misleading. The authors provide an adjustment that can be used when price experiments or instrumental variables are not available.

      • 01 Nov 2018
      • Working Paper Summaries

      Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

      by Xiaojia Guo, Yael Grushka-Cockayne, and Bert De Reyck

      Passengers arriving at international hubs often endure delays, especially at immigration and security. This study of London’s Heathrow Airport develops a system to provide real-time information about transfer passengers’ journeys through the airport to better serve passengers, airlines, and their employees. It shows how advanced machine learning could be accessible to managers.

      • 17 Oct 2018
      • Working Paper Summaries

      Quantile Forecasts of Product Life Cycles Using Exponential Smoothing

      by Xiaojia Guo, Kenneth C. Lichtendahl Jr., and Yael Grushka-Cockayne

      Many important business decisions rely on a manager’s forecast of a product or service’s life cycle. One of the most widely used forecasting techniques is exponential smoothing models. This paper introduces a model suitable for large-scale forecasting environments where key operational decisions depend on quantile forecasts.

      • 05 Mar 2018
      • Working Paper Summaries

      Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change

      by Edward L. Glaeser, Hyunjin Kim, and Michael Luca

      This study finds that data from digital platforms (in this case, Yelp) can help forecast which neighborhoods are gentrifying and provide new ways to measure business landscape changes that accompany demographic changes.

      • 23 Sep 2017
      • Working Paper Summaries

      Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale

      by Edward L. Glaeser, Hyunjin Kim, and Michael Luca

      Data from online platforms ranging from Yelp to Zillow offer the potential for improved measurement of the local economy. This paper finds that Yelp data can predict business growth, as measured by the Census Bureau, before official statistics are released. Predictive power increases with population density, income, and education level.

      • 20 Mar 2017
      • Working Paper Summaries

      Bubbles for Fama

      by Robin Greenwood, Andrei Shleifer, and Yang You

      Nobel laureate Eugene F. Fama has famously claimed that there is no such thing as a bubble, which he defines as a large price run-up that predictably crashes. Analyzing industry data for the US and internationally, the authors find that Fama is mostly right that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward. Yet the authors show that there is much more to a bubble than merely increases in prices; they show a number of characteristics that predict an end to the bubble.

      • 25 Jul 2016
      • Working Paper Summaries

      Bias in Official Fiscal Forecasts: Can Private Forecasts Help?

      by Jeffrey A. Frankel and Jesse Schreger

      Why do countries find it so hard to get their deficits under control? The authors bring together data on private sector forecasts with official government forecasts of 26 countries, and identify systematic patterns in errors that official budget agencies make in their forecasts—particularly over-optimistic forecasts of GDP growth and budget balances. Incorporating private sector forecasts into the budget process could reduce violations of limits set by fiscal rules by identifying errors ahead of time rather than just afterwards.

      • 21 Oct 2015
      • Research & Ideas

      How to Predict if a New Business Idea is Any Good

      by Michael Blanding

      Professor Pian Shu tackles one of the most difficult questions in the startup world: How can you tell if a new business will succeed? Open for comment; Comment(s) posted.

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