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  • All HBS Web  (2,939)
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  • May 2021 (Revised February 2024)
  • Teaching Note

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Ayelet Israeli and Jill Avery
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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Israeli, Ayelet, and Jill Avery. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Teaching Note 521-097, May 2021. (Revised February 2024.)
  • April 12, 2022
  • Article

Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States

By: Estee Y. Cramer, Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li and et al.
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models... View Details
Keywords: COVID-19; Forecasting and Prediction; Health Pandemics; Mathematical Methods; Partners and Partnerships
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Cramer, Estee Y., Evan L. Ray, Velma K. Lopez, Johannes Bracher, Andrea Brennen, Alvaro J. Castro Rivadeneira, Michael Lingzhi Li, and et al. "Evaluation of Individual and Ensemble Probabilistic Forecasts of COVID-19 Mortality in the United States." e2113561119. Proceedings of the National Academy of Sciences 119, no. 15 (April 12, 2022). (See full author list here.)
  • Research Summary

Entrepreneurial Management

By: Howard H. Stevenson
Howard H. Stevenson is researching and writing on the need for and consequences of predictability. In work designed for a managerial audience, he is examining the roles played by organizations, cultures, and ethical systems in enabling individuals to predict the... View Details
  • 20 Oct 2011
  • Research & Ideas

Getting the Marketing Mix Right

their FSL model, however, the results provided much greater detail about the potential effects of different marketing investments. For example, the model predicted that sales gains from DTCA and M&E would come primarily through... View Details
Keywords: by Dina Gerdeman
  • 14 Mar 2023
  • Cold Call Podcast

Can AI and Machine Learning Help Park Rangers Prevent Poaching?

Keywords: Re: Brian L. Trelstad; Computer; Information Technology; Technology
  • 17 Dec 2020
  • Research & Ideas

The 10 Most Popular Stories of 2020

about the most interesting business trends of the year, and your predictions for 2021. Top 10 most popular stories Merck CEO Ken Frazier Discusses a COVID Cure, Racism, and Why Leaders Need to Walk the Talk Ken Frazier, one of only four... View Details
Keywords: by Dina Gerdeman
  • 07 Apr 2003
  • Research & Ideas

Three Steps for Crisis Prevention

to actually mobilizing the resources required to stop it. We term this the "RPM process": recognition, prioritization, mobilization. Failure at any of these three stages will leave a company vulnerable to potentially devastating View Details
Keywords: by Michael D. Watkins & Max H. Bazerman
  • January 1995
  • Background Note

A Note on Distribution of Venture Investments

By: Josh Lerner
Venture capitalists typically exit investments by distributing shares to investors. These transfers pose challenges for these investors. Predictions and evidence about the behavior of stock prices of firms around the time of these distributions are presented. View Details
Keywords: Forecasting and Prediction; Venture Capital; Stocks; Investment; Price
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Lerner, Josh. "A Note on Distribution of Venture Investments." Harvard Business School Background Note 295-095, January 1995.
  • 2023
  • Working Paper

New Facts and Data about Professors and Their Research

By: Kyle Myers, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural and Yilun Xu
We introduce a new survey of professors at roughly 150 of the most research-intensive institutions of higher education in the US. We document seven new features of how research-active professors are compensated, how they spend their time, and how they perceive their... View Details
Keywords: Research; Higher Education; Compensation and Benefits; Measurement and Metrics; Equality and Inequality; Performance Productivity
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Myers, Kyle, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural, and Yilun Xu. "New Facts and Data about Professors and Their Research." Harvard Business School Working Paper, No. 24-036, December 2023.
  • March 2005
  • Article

Short- and Long-term Demand Curves for Stocks: Theory and Evidence on the Dynamics of Arbitrage

By: Robin Greenwood
I develop a framework to analyze demand curves for multiple risky securities at extended horizons in a setting with limits-to-arbitrage. Following an unexpected change in uninformed investor demand for several assets, I predict returns of each security to be... View Details
Keywords: Limits To Arbitrage; Event Studies; Demand Curves; Portfolio Choice; Framework; Demand and Consumers; Change; Risk and Uncertainty; Debt Securities; Forecasting and Prediction; Stocks; Assets; Investment Portfolio; System Shocks; Price; Japan
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Greenwood, Robin. "Short- and Long-term Demand Curves for Stocks: Theory and Evidence on the Dynamics of Arbitrage." Journal of Financial Economics 75, no. 3 (March 2005): 607–649.
  • 05 Aug 2024
  • Research & Ideas

Watching for the Next Economic Downturn? Follow Corporate Debt

What really fuels a boom-and-bust cycle in the modern global economy? It’s not always household debt, says a new paper that parses in-depth data across 115 countries. Instead, rising corporate debt may flash the clearest warning that a fiscal crisis is on the horizon.... View Details
Keywords: by Rachel Layne
  • December 2019
  • Case

Forecasting ClimaCell

By: Joshua Lev Krieger, Christopher Stanton and James Barnett
A weather technology startup, ClimaCell considers the R&D trade-offs and financing implications of pursuing a proposed contract with a major automobile maker, rather than continuing its focus on building a scalable, all-purpose weather prediction engine. View Details
Keywords: Weather; Forecasting and Prediction; Technological Innovation; Research and Development; Finance; Cost vs Benefits; Decision Making; Strategy
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Krieger, Joshua Lev, Christopher Stanton, and James Barnett. "Forecasting ClimaCell." Harvard Business School Case 820-044, December 2019.
  • 2019
  • Working Paper

Soul and Machine (Learning)

By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, improved medical diagnostics, and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to rich media... View Details
Keywords: Machine Learning; Technological Innovation; Marketing; AI and Machine Learning
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Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Harvard Business School Working Paper, No. 20-036, September 2019.
  • December 2015
  • Article

What Is Disruptive Innovation?

By: Clayton M. Christensen, Michael Raynor and Rory McDonald
For the past 20 years, the theory of disruptive innovation has been enormously influential in business circles and a powerful tool for predicting which industry entrants will succeed. Unfortunately, the theory has also been widely misunderstood, and the "disruptive"... View Details
Keywords: Disruptive Innovation; Theory
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Christensen, Clayton M., Michael Raynor, and Rory McDonald. "What Is Disruptive Innovation?" Harvard Business Review 93, no. 12 (December 2015): 44–53.
  • 2017
  • Working Paper

Investment Timing with Costly Search for Financing

By: Samuel Antill
I develop a dynamic model of investment timing in which firms must first choose when to search for external financing. Search is costly and the arrival of investors is uncertain, leading to delay in financing and investment. Depending on parameters, my model can... View Details
Keywords: Real Options; Search And Bargaining; Time-varying Financial Conditions; Investment; Venture Capital; Mathematical Methods
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Antill, Samuel. "Investment Timing with Costly Search for Financing." Working Paper, December 2017.
  • August 2018 (Revised April 2019)
  • Supplement

Chateau Winery (B): Supervised Learning

By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
Keywords: Data Science; Clustering; Analytics and Data Science; Customers; Marketing; Analysis
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Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
  • Research Summary

Making Machine Learning Models Interpretable

By: Himabindu Lakkaraju
I work on developing various tools and methodologies which can help decision makers (e.g., doctors, managers) to better understand the predictions of machine learning models. View Details
  • December 2020 (Revised March 2022)
  • Teaching Note

Forecasting ClimaCell

By: Joshua Lev Krieger, Christopher Stanton and James Barnett
A weather technology startup, ClimaCell considers the R&D trade-offs and financing implications of pursuing a proposed contract with a major automobile maker, rather than continuing its focus on building a scalable, all-purpose weather prediction engine. View Details
Keywords: Weather; Forecasting and Prediction; Business Startups; Research and Development; Finance; Cost vs Benefits; Decision Making; Strategy; United States; Israel; Massachusetts; Colorado
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Krieger, Joshua Lev, Christopher Stanton, and James Barnett. "Forecasting ClimaCell." Harvard Business School Teaching Note 821-008, December 2020. (Revised March 2022.)
  • Article

Measuring Audit Quality

By: Shivaram Rajgopal, Suraj Srinivasan and Xin Zheng
In this paper, we document 45 specific allegations related to audit deficiencies based on GAAS, as detailed in 141 AAERs and 153 securities class action lawsuits over the violation years 1978–2016. Next, we use these allegations to validate existing popular proxies of... View Details
Keywords: Audit Quality; Audit Deficiency; AAER; Securities Class Action Lawsuits; Enforcement; Accounting Audits; Quality; Measurement and Metrics
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Rajgopal, Shivaram, Suraj Srinivasan, and Xin Zheng. "Measuring Audit Quality." Review of Accounting Studies 26, no. 2 (June 2021): 559–619.
  • March 2024
  • Article

The Asymmetric Mispricing Information in Analysts’ Target Prices

By: Jeremiah Green, John R. M. Hand and Anywhere Sikochi
We study the mispricing information present in the target prices of U.S. and international analysts. We hypothesize that asymmetry in the value-relevance of the information that managers supply to analysts, combined with asymmetry in the incentives facing analysts to... View Details
Keywords: Analysts; Target Prices; Mispricing; Cost Of Equity; Valuation; Price; Cost; Analysis; Theory
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Green, Jeremiah, John R. M. Hand, and Anywhere Sikochi. "The Asymmetric Mispricing Information in Analysts’ Target Prices." Review of Accounting Studies 29, no. 1 (March 2024): 889–915.
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