Generative Models - Publications - Faculty & Research - Harvard Business School

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20 Aug 2024
Interview

Angel City Football Club: A New Business Model for Women’s Sports

By: Jeffrey F. Rayport, Brian Kenny and Nicole Tempest Keller

Angel City Football Club (ACFC) was founded in 2020 by venture capitalist Kara Nortman, entrepreneur Julie Uhrman, and actor and activist Natalie Portman. As outsiders to professional sports, the all-female founding team had rewritten the playbook for how to build a... View Details

Keywords: Brands and Branding; Gender; Franchise Ownership; Business Model; Sports Industry

Article

Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses

By: Kaivalya Rawal and Himabindu Lakkaraju

As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to... View Details

Keywords: Predictive Models; Decision Making; Framework; Mathematical Methods

September 2018
Article

Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia

By: Shane Greenstein and Feng Zhu

Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective,... View Details

Keywords: Online Community; Collective Intelligence; Wisdom Of Crowds; Bias; Wikipedia; Britannica; Knowledge Production; Knowledge Sharing; Knowledge Dissemination; Prejudice and Bias

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20 Aug 2024
Cold Call Podcast

Angel City Football Club: A New Business Model for Women’s Sports

Keywords: Re: Jeffrey F. Rayport; Sports; Entertainment & Recreation

23 Sep 2013
Working Paper Summaries

Applying Random Coefficient Models to Strategy Research: Testing for Firm Heterogeneity, Predicting Firm-Specific Coefficients, and Estimating Strategy Trade-Offs

Keywords: by Juan Alcácer, Wilbur Chung, Ashton Hawk & Gonçalo Pacheco-de-Almeida

January 2022 (Revised August 2022)
Case

Hello Heart: The Next Generation of Chronic Disease Management Apps

By: Ariel D. Stern and Danielle Golan

Hello Heart, a hypertension management app debated whether to go deep and cover other heart conditions, or to expand its solution to other chronic conditions. View Details

July–August 2016
Article

Beyond the Holacracy Hype: The Overwrought Claims—and Actual Promise—of the Next Generation of Self-Managed Teams

By: Ethan Bernstein, John Bunch, Niko Canner and Michael Lee

Holacracy and other forms of self-organization have been getting a lot of press. Proponents hail them as "flat" environments that foster flexibility, engagement, productivity, and efficiency. Critics say they're naive, unrealistic experiments. We argue, using evidence... View Details

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Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation.

Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers' decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to... View Details

2023
Working Paper

Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation

By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov

Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to... View Details

Keywords: Performance Evaluation; Research and Development; Analytics and Data Science; Consumer Behavior

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

March 2022
Article

Estimating the Effectiveness of Permanent Price Reductions for Competing Products Using Multivariate Bayesian Structural Time Series Models

By: Fiammetta Menchetti and Iavor Bojinov

Researchers regularly use synthetic control methods for estimating causal effects when a sub-set of units receive a single persistent treatment, and the rest are unaffected by the change. In many applications, however, units not assigned to treatment are nevertheless... View Details

Keywords: Causal Inference; Partial Interference; Synthetic Controls; Bayesian Structural Time Series; Mathematical Methods

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October 2022
Article

How Leaders with Divergent Visions Generate Novel Strategy: Navigating the Paradox of Preservation and Modernization in Swiss Watchmaking

By: Ryan Raffaelli, Rich DeJordy and Rory M. McDonald

How do leaders with divergent visions for their organization come together to create a novel strategy? This paper employs paradox as a lens to investigate how leader-dyads can integrate opposing strategies to produce a new, generative approach. Drawing on a qualitative... View Details

Keywords: Strategic Paradoxes; Senior Leaders; Organizational Reinvention; Leadership; Technological Innovation; Innovation and Management; Innovation Strategy; Change; Manufacturing Industry; Consumer Products Industry; Switzerland

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Article

Robust and Stable Black Box Explanations

By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani

As machine learning black boxes are increasingly being deployed in real-world applications, there has been a growing interest in developing post hoc explanations that summarize the behaviors of these black boxes. However, existing algorithms for generating such... View Details

Keywords: Machine Learning; Black Box Models; Framework

October 2024
Technical Note

Prompt Engineering

By: Michael Parzen and Jo Ellery

This note covers the basics of prompt engineering, a key tool for making use of modern generative AI. We discuss the principles of prompt engineering and illustrate these principles with techniques for asking questions. We further list the types of prompts that can be... View Details

Keywords: Large Language Model; AI and Machine Learning

2005
Working Paper

Additive Rules for the Quasi-linear Bargaining Problem

By: Christopher P. Chambers and Jerry R. Green

We study the class of additive rules for the quasi-linear bargaining problem introduced by Green. We provide a characterization of the class of all rules that are e¢ cient, translation invariant, additive, and continuous. We present several subfamilies of rules: the... View Details

Keywords: Econometric Models

Article

Counterfactual Explanations Can Be Manipulated

By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh

Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details

Keywords: Machine Learning Models; Counterfactual Explanations

October 2012
Case

Riding the Wave of Technological Change at RE/MAX, LLC.

By: Lynda M. Applegate, Ramiro Montealegre and Jeffrey Sweeney

David Liniger, cofounder of RE/MAX, LLC., wondered if his business was prepared to exploit the next wave of business opportunities in the real estate market. This industry had moved from one in which broker/owners controlled all of the consumers' access to information,... View Details

Keywords: General Management; Business Strategy; Entrepreneurship; Business Model; Information Technology; Transformation; Organizational Change and Adaptation

1977
Working Paper

Mitigating Demographic Risk Through Social Insurance

By: Jerry R. Green

A two-period lifetime overlapping generations growth model is used to evaluate the possibility that social insurance can effectively offset economic risks associated with uncertainty about the rate of population growth. Crude measures of the seriousness of this type of... View Details

Keywords: Social Insurance; Econometric Models; Public Sector; Government Administration; Policy; Human Needs; Social Issues; Risk and Uncertainty

May 2012 (Revised November 2015)
Case

The National Geographic Society (A) (Abridged)

By: David A. Garvin and Annelena Lobb

In January 2010, John Fahey, president, CEO, and chairman of the board of trustees' executive committee of the Washington, D.C.–based National Geographic Society (NGS), must decide how best to organize the 121-year old mission-driven organization for a world of... View Details

Keywords: General Management; Change Management; Media And Publishing; Digital Convergence; Strategy Development; Business Models; Information Publishing; Online Technology; Business Model; Organizational Structure; Business Strategy; Publishing Industry

April 2025
Article

Crisis Interventions in Corporate Insolvency

By: Samuel Antill and Christopher Clayton

We model the optimal resolution of insolvent firms in general equilibrium. Collateral-constrained banks lend to (i) solvent firms to finance investments and (ii) distressed firms to avoid liquidation. Liquidations create negative fire-sale externalities. Liquidations... View Details

Keywords: Insolvent Firms; Government Intervention; Liquidation; Econometric Models; Insolvency and Bankruptcy; Policy

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