Publications

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

Keywords: Large Language Model; Research; AI and Machine Learning; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry

SSRN

04 Apr 2011
Research & Ideas

Attention Medical Shoppers: What Health Care Can Learn from Walmart and Amazon

In order to get its financial and management woes under control, the health care industry might want to peek at the playbooks of retail giants like Walmart, Google, and Amazon.com. This was a key conversation point at "Perspectives on Health Care as a Management... View Details

Keywords: by Carmen Nobel; Health

January–February 2022
Article

Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

By: Ryan Allen and Prithwiraj Choudhury

How does a knowledge worker’s level of domain experience affect their algorithm-augmented work performance? We propose and test theoretical predictions that domain experience has countervailing effects on algorithm-augmented performance: on one hand, domain experience... View Details

Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance

2021
Chapter

Towards a Unified Framework for Fair and Stable Graph Representation Learning

By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik

As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details

Keywords: Graph Neural Networks; AI and Machine Learning; Prejudice and Bias

2023
Working Paper

Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality

By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani

The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine... View Details

Keywords: Large Language Model; AI and Machine Learning; Performance Efficiency; Performance Improvement

SSRN

November 2024 (Revised January 2025)
Case

MiDAS: Automating Unemployment Benefits

By: Shikhar Ghosh and Shweta Bagai

In 2015, the state of Michigan considered whether to nominate its Michigan Integrated Data Automated System (MiDAS) for a prestigious state technology award. Launched in 2013 amid severe budget pressures, the $47 million automated fraud detection system was designed to... View Details

Educators

Web

Preview the Harvard Business School Online Learning Experience

real-world learning model . Or, download an e-book to dive deeper into a vital business topic and develop insights you can apply to your company or career. Explore Sample Lessons Free Business E-Books and... View Details

2024
Working Paper

Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python

By: Melissa Ouellet and Michael W. Toffel

This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details

Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods

SSRN

2020
Working Paper

Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

By: Ryan Allen and Prithwiraj Choudhury

Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing... View Details

Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Decision-making; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance

June, 2021
Article

Learning from Deregulation: The Asymmetric Impact of Lockdown and Reopening on Risky Behavior During COVID-19

By: Edward L. Glaeser, Ginger Zhe Jin, Benjamin T. Leyden and Michael Luca

During the COVID-19 pandemic, states issued and then rescinded stay-at-home orders that restricted mobility. We develop a model of learning by deregulation, which predicts that lifting stay-at-home orders can signal that going out has become safer. Using restaurant... View Details

Keywords: COVID-19; Lockdown; Reopening; Impact; Coronavirus; Public Health Measures; Mobility; Health Pandemics; Governing Rules, Regulations, and Reforms; Consumer Behavior

June 2020 (Revised May 2022)
Case

Vanguard Retail Operations (A)

By: Willy C. Shih and Antonio Moreno

The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or... View Details

Keywords: Pooling; Generalist Model; Specialist Model; Operations; Service Operations; Management; Job Design and Levels; Financial Services Industry; United States

Educators

26 May 2015
Blog Post

5 Ways the Case Method Changes How You Learn

it. Here’s what Ashley Daniels (MBA’16), Jeremy Watson (MBA ‘16), and Ezra Okon (MBA ‘15) had to say about the case method and how it’s changed how they learn. The case method disrupts the traditional lecture-based classroom model Jeremy:... View Details

October 2023
Case

Fixie and Conversational AI Sidekicks

By: Jeffrey J. Bussgang and Carin-Isabel Knoop

In March 2023, Fixie Co-Founder and Chief Architect Matt Welsh and co-founders had the kind of meeting no founders want to have. The president of leading artificial intelligence (AI) research and deployment firm OpenAI, which had catapulted into fame with its ChatGPT... View Details

Keywords: Large Language Model; Entrepreneurship; Decision Choices and Conditions; AI and Machine Learning; Technological Innovation; Competitive Strategy; Technology Industry; United States

Educators

March 2019
Article

A Structural Analysis of the Role of Superstars in Crowdsourcing Contests

By: Shunyuan Zhang, Param Singh and Anindya Ghose

We investigate the long-term impact of competing against superstars in crowdsourcing contests. Using a unique 50-month longitudinal panel data set on 1677 software design crowdsourcing contests, we illustrate a learning effect where participants are able to improve... View Details

Keywords: Crowdsourcing Contests; Superstar Effect; Bayesian Learning; Utility; Economics Of Information System; Dynamic Structural Model; Dynamic Programming; Markov Chain; Monte Carlo; Learning; Competition; Performance Improvement

June 2020 (Revised August 2020)
Supplement

Vanguard Retail Operations (B)

By: Willy C. Shih and Antonio Moreno

The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or... View Details

Keywords: Pooling; Generalist Model; Specialist Model; Service Operations; Management; Financial Services Industry; United States

24 Apr 2018
Op-Ed

Op-Ed: What Mark Zuckerberg Can Learn About Crisis Leadership from Starbucks

Facebook’s current data privacy crisis, could learn a lot from Johnson. Let’s examine how Johnson and Zuckerberg measured up against what I have identified as 7 Lessons for Leading in Crisis. #1: Face reality, starting with yourself.... View Details

Keywords: by Bill George; Technology; Food & Beverage

February 2012
Article

CEO Relational Leadership and Strategic Decision Quality in Top Management Teams: The Role of Team Trust and Learning from Failure

By: Abraham Carmeli, Asher Tishler and Amy C. Edmondson

In this study, we examine a complex pathway through which CEOs, who exhibit relational leadership, may improve the quality of strategic decisions of their top management teams (TMTs) by creating psychological conditions of trust and facilitating learning from failures... View Details

Keywords: Leadership Development; Decisions; Management Teams; Trust; Learning; Management Analysis, Tools, and Techniques; Managerial Roles; Failure

June 30, 2020
Article

Scaling Up Behavioral Science Interventions in Online Education

By: Rene F. Kizilcec, Justin Reich, Michael Yeomans, Christoph Dann, Emma Brunskill, Glenn Lopez, Selen Turkay, Joseph J. Williams and Dustin Tingley

Online education is rapidly expanding in response to rising demand for higher and continuing education, but many online students struggle to achieve their educational goals. Several behavioral science interventions have shown promise in raising student persistence and... View Details

Keywords: Online Learning; Behavioral Interventions; Scale; Education; Online Technology; Performance Improvement