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Skip to Main Content Health & Safety Health & Safety How We Are Keeping You Safe Quarantine Policies for Students Arriving or Returning On- or...
- 2021
- Article
Large-Scale Field Experiment Shows Null Effects of Team Demographic Diversity on Outsiders' Willingness to Support the Team
By: Edward H. Chang, Erika L. Kirgios and Rosanna K. Smith
Demographic diversity in the United States is rising, and increasingly, work is conducted in teams. These co-occurring phenomena suggest that it might be increasingly common for work to be conducted by demographically diverse teams. But to date, in spite of copious...
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- April 2021
- Article
Homing and Platform Responses to Entry: Historical Evidence from the U.S. Newspaper Industry
By: K. Francis Park, Robert Seamans and Feng Zhu
We examine how heterogeneity in customers’ tendencies to single-home or multi-home affects a platform’s competitive responses to new entrants in the market. We first develop a formal model to generate predictions about how a platform will respond. We then empirically...
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- 2021
- Working Paper
Cognitive Biases: Mistakes or Missing Stakes?
By: Benjamin Enke, Uri Gneezy, Brian Hall, David Martin, Vadim Nelidov, Theo Offerman and Jeroen van de Ven
Despite decades of research on heuristics and biases, empirical evidence on the effect of large incentives—as present in relevant economic decisions—on cognitive biases is scant. This paper tests the effect of incentives on four widely documented biases: base rate...
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- March 2021
- Supplement
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Power Point Supplement to Teaching Note for HBS No. 521-021,521-022,521-037,521-043. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on...
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- March 18, 2021
- Article
A Feasibility Study Using Time-driven Activity-based Costing as a Management Tool for Provider Cost Estimation: Lessons from the National TB Control Program in Zimbabwe in 2018
By: J. Chirenda, B. Nhlema Simwaka, C. Sandy, K. Bodnar, S. Corbin, P. Desai, T. Mapako, S. Shamu, C. Timire, E. Antonio, A. Makone, A. Birikorang, T. Mapuranga, M. Ngwenya, T. Masunda, M. Dube, E. Wandwalo, L. Morrison and R. S. Kaplan
Background: This study used process maps and time-driven activity-based costing to document TB service delivery processes. The analysis identified the resources required to sustain TB services in Zimbabwe, as well as several opportunities for more effective and...
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- March 2021
- Case
VideaHealth: Building the AI Factory
By: Karim R. Lakhani and Amy Klopfenstein
Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new...
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- 2021
- Chapter
Dis-Atlanticism: The West in an Era of Global Fragmentation
By: Rawi Abdelal and Ulrich Krotz
BOOK ABSTRACT: Is the EU a Success or a Failure? Should It Stay or Should It Go? Britain and the EU. The Big Waste or Essential to Feed Europe? The Common Agricultural Policy. Observers of the European Union could be forgiven in thinking that since its inception the EU...
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- March 2021
- Article
Opting-in to Prosocial Incentives
By: Daniel Schwartz, Elizabeth A. Keenan, Alex Imas and Ayelet Gneezy
The design of effective incentive schemes that are both successful in motivating employees and keeping down costs is of critical importance. Research has demonstrated that prosocial incentives, where individuals’ effort benefits a charitable organization, can sometimes...
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- February 2021
- Tutorial
Assessing Prediction Accuracy of Machine Learning Models
By: Michael Toffel and Natalie Epstein
This video describes how to assess the accuracy of machine learning prediction models, primarily in the context of machine learning models that predict binary outcomes, such as logistic regression, random forest, or nearest neighbor models. After introducing and...
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- February 2021
- Tutorial
Getting Started in R Cloud Studio
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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- February 2021
- Tutorial
T-tests: Theory and Practice
This video provide an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with...
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- February 2021
- Case
Bairong and the Promise of Big Data
By: Lauren Cohen, Xiaoyan Zhang and Spencer C.N. Hagist
Bairong CEO Felix Zhang, in launching his credit scoring start-up that incorporates 74,000 variables per individual, found strong initial success. However, the shifting regulatory environment, growing breadth of competitors, difficulties in retaining top talent, and...
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Keywords:
Fintech;
Big Data;
Artificial Intelligence;
Credit Scoring;
Finance;
Credit;
Business Startups;
China
- 2021
- Book
Sales Management That Works: How to Sell in a World That Never Stops Changing
Selling is changing, but the impact on sales of megatrends like ecommerce, big data, and AI is often misunderstood and not supported by empirical data. Managers who fail to separate fact from hype will make decisions based on bad assumptions and, in a competitive...
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- January–February 2021
- Article
Cross‐firm Return Predictability and Accounting Quality
By: Wen Chen, Mozaffar Khan, Leonid Kogan and George Serafeim
We test the hypothesis that if poor accounting quality (AQ) is associated with poor investor understanding of firms’ revenue and cost structures, then poor AQ stocks likely respond more slowly than good AQ stocks to new non‐idiosyncratic information that affects both...
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- Winter 2021
- Article
Making Economics More Useful: How Technological Eclecticism Could Help
By: Amar Bhide
Keynes thought it would be ‘splendid’ if economists became more like dentists. Disciplinary economics
has instead become more like physics in focusing on concise, universal propositions verified
through decisive tests. This focus, I argue, limits the practical utility...
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- 2021
- Working Paper
Information Avoidance and Image Concerns
By: Christine L. Exley and Judd B. Kessler
A rich literature finds that individuals avoid information, even information that is instrumental to their choices. A common hypothesis posits that individuals strategically avoid information to hold particular beliefs or to take certain actions--such as behaving...
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- 2020
- Working Paper
Don't Get It or Don't Spread It? Comparing Self-interested versus Prosocial Motivations for COVID-19 Prevention Behaviors
By: Jillian J. Jordan, Erez Yoeli and David Rand
Efforts to avoid COVID-19 infection may be seen as self-interested or prosocial. Using American samples from Amazon Turk and Prolific (total n = 6,850), we investigated which framing is more effective—and motivation is stronger—for fostering intentions to engage in...
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- 2020
- Working Paper
Hate Crime Increases with Minoritized Group Rank
By: Mina Cikara, Vasiliki Fouka and Marco Tabellini
People are on the move in unprecedented numbers across the globe. How does migration affect local intergroup dynamics? In contrast to accounts that emphasize stereotypical features of groups as determinants of their treatment, we propose the social group reference...
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- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect...
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- 2020
- Working Paper
Algorithm-Augmented Work Performance 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...
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