Publications
Publications
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- All HBS Web
(11,330)
- Faculty Publications (3,194)
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... View Details
- 2025
- Working Paper
Turning Points in Inflation: A Structural Breaks Approach with Micro Data
By: Alberto Cavallo and Gastón García Zavaleta
We introduce a novel methodology for detecting inflation turning points that combines high-frequency, disaggregated price data with standard structural break techniques to provide policymakers with more precise and timely signals of inflation dynamics. The methodology... View Details
- 2023
- Working Paper
How Wicked Problems Drive Business Performance: A Review of the Academic Literature
By: Caroline Adelson, Charlotte Kuller, Cate Tompkins, Ellora Sarkar, Samantha Price and Marco Iansiti
Recent years have seen a rise in the number of businesses engaged in the pursuit of “purposeful” activities – that is, activities that engage with the broader community in ways that expand beyond the pursuit of shareholder value. Many of these activities involve... View Details
- April 12, 2023
- Article
Using AI to Adjust Your Marketing and Sales in a Volatile World
By: Das Narayandas and Arijit Sengupta
Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer... View Details
- 2024
- Working Paper
Using LLMs for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity as labor-augmenting
tools for programming, writing, and many other processes that benefit from quick text
generation. In this paper we explore the uses and benefits of LLMs for researchers and
practitioners... View Details
- April 5, 2023
- Article
We Need an Operation Warp Speed for Long COVID
By: Esther K. Choo and Scott Duke Kominers
With millions of people affected and at least $1 trillion of economic value at stake, long COVID is our next national health emergency. View Details
- April 2023 (Revised February 2024)
- Case
AI Wars
By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
In February 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI. Over a year ago, OpenAI released ChatGPT, a... View Details
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details
- March–April 2023
- Article
The New-Collar Workforce
By: Colleen Ammerman, Boris Groysberg and Ginni Rometty
Many workers today are stuck in low-paying jobs, unable to advance simply because they don’t have a bachelor’s degree. At the same time, many companies are desperate for workers and not meeting the diversity goals that could help them perform better while also reducing... View Details
- April 2023
- Article
The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences
By: Armin Falk, Anke Becker, Thomas Dohmen, David B. Huffman and Uwe Sunde
Incentivized choice experiments are a key approach to measuring preferences in economics but are also costly. Survey measures are a low-cost alternative but can suffer from additional forms of measurement error due to their hypothetical nature. This paper seeks to... View Details
- March 2023
- Teaching Note
VideaHealth: Building the AI Factory
By: Karim R. Lakhani
Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian... View Details
- March 2023 (Revised January 2024)
- Case
Nigeria: Africa's Giant
"Nigeria: Africa’s Giant" delves into the economic development and state building record of Africa’s most populous country. Despite being one of the continent’s largest oil-exporters, Nigeria’s economy has been struggling, and poverty is widespread. The country’s... View Details
- March 2023 (Revised May 2023)
- Case
Tribal Councils Investment Group of Manitoba Ltd.
By: David L. Ager
In the Fall of 2014, Heather Berthelette, the recently appointed COO of Tribal Councils Investment Group of Manitoba Ltd. (TCIG), was preparing a recommendation to the Board of Directors about whether to dissolve the company and return any remaining funds to the seven... View Details
- March 2023 (Revised December 2023)
- Background Note
Economic Analysis: The Hidden Costs of Layoffs and Managing Staff Reductions
By: Sandra J. Sucher, Marilyn Morgan Westner and Christopher Diak
Globally, over the past fifty years, more companies have used layoffs to cut costs during periods of decreased demand or economic downturns. But layoffs have far-reaching consequences, generate hidden costs, and harm the company in myriad ways. This note reviews ways... View Details
- March 2023 (Revised June 2023)
- Case
Layoffs in the Tech Industry: 2022–2023
By: Sandra J. Sucher and Marilyn Morgan Westner
This case examines the mass layoffs that swept through the tech industry (2022-2023) through the lens of four companies: Twitter, Stripe, Meta, and Google. How these companies implemented workforce change through mass layoffs raises critical questions applicable beyond... View Details
- March 2023 (Revised June 2023)
- Case
Doing Business in Kigali, Rwanda
By: Andy Zelleke, A. Zelleke, Leonard A. Schlesinger, Leonard A. Schlesinger, Pippa Tubman Armerding and Wale Lawal
This case examines the challenges and opportunities of doing business in Rwanda. It highlights Rwanda's economic transformation in the decades leading up to 2023 in the context of its history, culture, and politics. The case gives an overview of some of the main... View Details
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details