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- 2023
- Working Paper
Using GPT for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have quickly become popular 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 who...
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Keywords:
Large Language Model;
Research;
AI and Machine Learning;
Analysis;
Customers;
Consumer Behavior;
Technology Industry;
Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using GPT for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023.
- December 2022
- Article
The Task Bind: Explaining Gender Differences in Managerial Tasks and Performance
This multi-method study of managers in a grocery chain identifies a novel mechanism by which threats of gender stereotypes undermine women’s ability to be effective managers. I find that women managers face a task bind, a dilemma that managers experience as they try to...
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Feldberg, Alexandra C. "The Task Bind: Explaining Gender Differences in Managerial Tasks and Performance." Administrative Science Quarterly 67, no. 4 (December 2022): 1049–1092.
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed...
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Keywords:
Machine Learning;
Econometric Analysis;
Instrumental Variable;
Random Forest;
Causal Inference;
AI and Machine Learning;
Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- 2022
- White Paper
The American Opportunity Index: A Corporate Scorecard of Worker Advancement
By: Matt Sigelman, Joseph Fuller, Nik Dawson and Gad Levanon
The American Opportunity Index: A Corporate Scorecard of Worker Advancement is a new effort to give companies and other stakeholders a set of robust tools that measure how well major employers are doing in fostering economic mobility for workers and how they could do...
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Keywords:
Upward Mobility;
Career Advancement;
Personal Development and Career;
Compensation and Benefits;
Employees;
Wages;
Human Capital;
Recruitment
Sigelman, Matt, Joseph Fuller, Nik Dawson, and Gad Levanon. "The American Opportunity Index: A Corporate Scorecard of Worker Advancement." White Paper, Burning Glass Institute, October 2022 (A joint project with Harvard Business School Project on Managing the Future of Work and Schultz Family Foundation.)
- August, 2022
- Article
Billing and Insurance-Related Administrative Costs: A Cross-National Analysis
By: Barak D. Richman, Robert S. Kaplan, Japees Kohli, Dennis Purcell, Mahek Shah, Igna Bonfrer, Brian Golden, Rosemary Hannam, Will Mitchell, Daniel Cehic, Garry Crispin and Kevin A. Schulman
Billing and insurance-related costs are a significant source of wasteful health care spending in Organization for Economic Cooperation and Development nations, but these administrative burdens vary across national systems. We executed a microlevel accounting of these...
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Richman, Barak D., Robert S. Kaplan, Japees Kohli, Dennis Purcell, Mahek Shah, Igna Bonfrer, Brian Golden, Rosemary Hannam, Will Mitchell, Daniel Cehic, Garry Crispin, and Kevin A. Schulman. "Billing and Insurance-Related Administrative Costs: A Cross-National Analysis." Health Affairs 41, no. 8 (August, 2022): 1098–1106.
- June 2022
- Case
Business Implications from Regulating Carbon Emissions in the EU
By: George Serafeim and Benjamin Maletta
In the beginning of the 21st century, the European Union (the EU) had led the global fight against climate change with a wide array of policy measures. The EU’s primary approach to climate policy had been taxation via the European Union Emissions Trading System (EU...
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Keywords:
Regulation;
Carbon Emissions;
Trade;
Sustainability;
Decarbonization;
Performance;
Climate Change;
Analysis;
Strategy;
Taxation;
Policy;
Environmental Regulation;
Industry Structures;
European Union
Serafeim, George, and Benjamin Maletta. "Business Implications from Regulating Carbon Emissions in the EU." Harvard Business School Case 122-106, June 2022.
- 2022
- Working Paper
Measuring the Tolerance of the State: Theory and Application to Protest
By: Veli Andirin, Yusuf Neggers, Mehdi Shadmehr and Jesse M. Shapiro
We develop a measure of a regime's tolerance for an action by its citizens. We ground our measure in an economic model and apply it to the setting of political protest. In the model, a regime anticipating a protest can take a costly action to repress it. We define the...
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Keywords:
Political Protests;
Modeling And Analysis;
Government and Politics;
Conflict and Resolution
Andirin, Veli, Yusuf Neggers, Mehdi Shadmehr, and Jesse M. Shapiro. "Measuring the Tolerance of the State: Theory and Application to Protest." NBER Working Paper Series, No. 30167, June 2022.
- 2022
- Working Paper
Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers
By: Magie Cheng and Shunyuan Zhang
The growth of the influencer marketing industry warrants an empirical examination of the effect of posting sponsored videos on an influencer’s reputation. We collect a novel dataset of user-generated YouTube videos created by prominent English-speaking influencers in...
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Keywords:
Influencer Marketing;
Social Influencers;
Brand;
Sponsorship;
Video Analytics;
Marketing;
Brands and Branding;
Media;
Reputation
Cheng, Magie, and Shunyuan Zhang. "Reputation Burning: Analyzing the Impact of Brand Sponsorship on Social Influencers." Harvard Business School Working Paper, No. 22-067, April 2022.
- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public...
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Keywords:
Prescriptive Analytics;
Heterogeneous Treatment Effects;
Optimization;
Observed Rank Utility Condition (OUR);
Between-treatment Heterogeneity;
Machine Learning;
Decision Making;
Analysis;
Mathematical Methods
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
- December 2021
- Article
Employee Responses to Compensation Changes: Evidence from a Sales Firm
By: Jason Sandvik, Richard Saouma, Nathan Seegert and Christopher Stanton
What are the long-term consequences of compensation changes? Using data from an inbound sales call center, we study employee responses to a compensation change that ultimately reduced take-home pay by 7% for the average affected worker. The change caused a significant...
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Keywords:
Employees;
Wages;
Compensation and Benefits;
Change;
Performance;
Resignation and Termination;
Retention;
Analysis
Sandvik, Jason, Richard Saouma, Nathan Seegert, and Christopher Stanton. "Employee Responses to Compensation Changes: Evidence from a Sales Firm." Management Science 67, no. 12 (December 2021): 7687–7707.
- Article
Behavioral and Neural Representations en route to Intuitive Action Understanding
By: Leyla Tarhan, Julian De Freitas and Talia Konkle
When we observe another person’s actions, we process many kinds of information—from how their body moves to the intention behind their movements. What kinds of information underlie our intuitive understanding about how similar actions are to each other? To address this...
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Keywords:
Action Perception;
Intuitive Similarity;
Multi-arrangement;
fMRI;
Representational Similarity Analysis;
Behavior;
Perception
Tarhan, Leyla, Julian De Freitas, and Talia Konkle. "Behavioral and Neural Representations en route to Intuitive Action Understanding." Neuropsychologia 163 (December 2021).
- May 2021
- Simulation
Customer Compatibility Exercise Application
By: Ryan W. Buell
Customers impose considerable variability on the operating systems of service organizations. They show up when they wish (arrival variability), they ask for different things (request variability), they vary in their willingness and ability to help themselves (effort...
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- May 2021
- Article
Risk-Mitigating Technologies: The Case of Radiation Diagnostic Devices
By: Alberto Galasso and Hong Luo
We study the impact of consumers’ risk perception on firm innovation. Our analysis exploits a major surge in the perceived risk of radiation diagnostic devices following extensive media coverage of a set of over-radiation accidents involving CT scanners in late 2009....
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Keywords:
Risk Perception;
Innovation;
Medical Devices;
Liability Risk;
Risk and Uncertainty;
Perception;
Technological Innovation
Galasso, Alberto, and Hong Luo. "Risk-Mitigating Technologies: The Case of Radiation Diagnostic Devices." Management Science 67, no. 5 (May 2021): 3022–3040.
- 2021
- Working Paper
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the...
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Keywords:
Difference In Differences;
Staggered Difference-in-differences Designs;
Generalized Difference-in-differences;
Dynamic Treatment Effects;
Mathematical Methods
Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" European Corporate Governance Institute Finance Working Paper, No. 736/2021, February 2021. (Harvard Business School Working Paper, No. 21-112, April 2021.)
- March 2021
- Article
The Customer May Not Always Be Right: Customer Compatibility and Service Performance
This paper investigates the impact of customer compatibility – the degree of fit between the needs of customers and the capabilities of the operations serving them – on customer experiences and firm performance. We use a variance decomposition analysis to quantify the...
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Keywords:
Customer Compatibility;
Satisfaction;
Profitability;
Service Operations;
Customer Relationship Management;
Customer Satisfaction;
Performance
Buell, Ryan W., Dennis Campbell, and Frances X. Frei. "The Customer May Not Always Be Right: Customer Compatibility and Service Performance." Management Science 67, no. 3 (March 2021): 1468–1488.
- February 2021 (Revised May 2021)
- Case
SafeGraph: Selling Data as a Service
By: Ramana Nanda, Abhishek Nagaraj and Allison Ciechanover
Set in January 2021, the CEO of SafeGraph, a four-year-old startup that sold Data as a Service, looked to the future. His aim was to become the most trusted source for data about a physical place. The company provided points of interest (POI) and foot traffic data on...
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Keywords:
Data As A Service;
Monetization;
Pricing;
Business Startups;
Analytics and Data Science;
Consumer Behavior;
Analysis;
Business Model;
Health Pandemics;
Information Industry;
United States
Nanda, Ramana, Abhishek Nagaraj, and Allison Ciechanover. "SafeGraph: Selling Data as a Service." Harvard Business School Case 821-082, February 2021. (Revised May 2021.)
- February 2021
- Tutorial
Getting Started in RStudio Cloud
By: Chiara Farronato and Caleb Kwon
This video provides an introduction to the free programming language R using an online cloud version of RStudio, which is the most popular editor and interface for writing and executing R code. The video begins by providing a brief background of R and RStudio and...
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- 2021
- Article
Fair Algorithms for Infinite and Contextual Bandits
By: Matthew Joseph, Michael J Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
We study fairness in linear bandit problems. Starting from the notion of meritocratic fairness introduced in Joseph et al. [2016], we carry out a more refined analysis of a more general problem, achieving better performance guarantees with fewer modelling assumptions...
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Joseph, Matthew, Michael J Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Fair Algorithms for Infinite and Contextual Bandits." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 4th (2021).
- Winter 2021
- Editorial
Introduction
This issue of Negotiation Journal is dedicated to the theme of artificial intelligence, technology, and negotiation. It arose from a Program on Negotiation (PON) working conference on that important topic held virtually on May 17–18. The conference was not the...
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Wheeler, Michael A. "Introduction." Special Issue on Artificial Intelligence, Technology, and Negotiation. Negotiation Journal 37, no. 1 (Winter 2021): 5–12.
- 2022
- Working Paper
Where the Cloud Rests: The Location Strategies of Data Centers
By: Shane Greenstein and Tommy Pan Fang
This study provides an analysis of the entry strategies of third-party data centers in the United States. We examine the market before the pandemic in 2018 and 2019, when supply and demand for data services were geographically stable. We compare with the entry...
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Greenstein, Shane, and Tommy Pan Fang. "Where the Cloud Rests: The Location Strategies of Data Centers." Harvard Business School Working Paper, No. 21-042, September 2020. (Revised June 2022.)