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- 2023
- Working Paper
Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure...
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- 2023
- Working Paper
Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program?
By: Sergey Chernenko, Nathan Kaplan, Asani Sarkar and David S. Scharfstein
We use the 2020 Small Business Credit Survey to study the sources of racial disparities in use of the Paycheck Protection Program (PPP). Black-owned firms are 8.9 percentage points less likely than observably similar white-owned firms to receive PPP loans. About 55% of...
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- 2022
- Working Paper
Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have “private” information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by...
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- 2022
- Working Paper
Confidence, Self-Selection and Bias in the Aggregate
By: Benjamin Enke, Thomas Graeber and Ryan Oprea
The influence of behavioral biases on aggregate outcomes like prices and allocations depends in part on self-selection: whether rational people opt more strongly into aggregate interactions than biased individuals. We conduct a series of betting market, auction and...
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- 2022
- Chapter
Redirecting Rawlsian Reasoning Toward the Greater Good
By: Joshua D. Greene, Karen Huang and Max Bazerman
In A Theory of Justice, John Rawls employed the ‘veil of Ignorance’ as a moral reasoning device designed to promote impartial thinking. By imagining the choices of decision-makers who are blind to biasing information, one might see more clearly the organizing...
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- June 2022
- Article
The Use and Misuse of Patent Data: Issues for Finance and Beyond
By: Josh Lerner and Amit Seru
Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing...
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- May 2022 (Revised April 2023)
- Case
LOOP: Driving Change in Auto Insurance Pricing
By: Elie Ofek and Alicia Dadlani
John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing...
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- Article
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that...
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- Article
Fighting Bias on the Front Lines
By: Alexandra C. Feldberg and Tami Kim
Most companies aim for exceptional customer service, but too few are attentive to the subtle discrimination by frontline employees that can alienate customers, lead to lawsuits, or even cause lasting brand damage by going viral.
This article presents research... View Details
This article presents research... View Details
- October 2021
- Article
Changing Gambling Behavior through Experiential Learning
By: Shawn A. Cole, Martin Abel and Bilal Zia
This paper tests experiential learning as a debiasing tool to reduce gambling in South Africa, through a randomized field experiment. The study implements a simple, interactive game that simulates the odds of winning the national lottery through dice rolling....
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- September 2021
- Article
Gender Stereotypes in Deliberation and Team Decisions
By: Katherine B. Coffman, Clio Bryant Flikkema and Olga Shurchkov
We explore how groups deliberate and decide on ideas in an experiment with communication. We find that gender biases play a significant role in which group members are chosen to answer on behalf of the group. Conditional on the quality of their ideas, individuals are...
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- Summer 2021
- Article
Predictable Country-level Bias in the Reporting of COVID-19 Deaths
We examine whether a country’s management of the COVID-19 pandemic relate to the downward biasing of the number of reported deaths from COVID-19. Using deviations from historical averages of the total number of monthly deaths within a country, we find that the...
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- June 2021
- Case
Bozoma Saint John: Leading with Authenticity and Urgency
By: Francesca Gino and Frances X. Frei
In this multimedia case, Bozoma Saint John recounts numerous defining moments from her childhood and work experiences. We learn what empowered and inspired her to be her authentic self, to be vulnerable and open to new experiences, to find commonality with others, to...
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- May 2021
- Article
Ideology and Composition Among an Online Crowd: Evidence From Wikipedians
By: Shane Greenstein, Grace Gu and Feng Zhu
Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that...
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- Article
Missing the Near Miss: Recognizing Valuable Learning Opportunities in Radiation Oncology
By: Palak Kundu, Olivia Jung, Luca F. Valle, Amy C. Edmondson, Nzhde Agazaryan, John Hegde, Michael Steinberg and Ann Raldow
“Near miss” events are valuable low-cost learning opportunities in radiation oncology as they do not result in patient harm and are more pervasive than adverse events that do. Near misses vary depending on the presence of a latent error of behavior or process, and the...
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- 2021
- Article
Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring
By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju
Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the...
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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
- Teaching Plan
The Black New Venture Competition
Black entrepreneurs encounter many unique obstacles when raising capital to start and grow a business, some stemming from deep systemic discrimination. During their second year at Harvard Business School (HBS), MBA students Kimberly Foster and Tyler Simpson decided to...
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Keywords:
Analytics;
Startup;
Start-up;
Startup Financing;
Financing;
Startups;
Start-ups;
Business And Community;
Business And Society;
Business Growth;
Discrimination;
Women;
Women-owned Businesses;
African Americans;
African-american Entrepreneurs;
African-american Investors;
African-American Protagonist;
African-American Women;
Early Stage Funding;
Early Stage;
Innovation ＆ Entrepreneurship;
Innovation Competitions;
Entrepreneurial Financing;
Business Plan;
Business Startups;
Diversity;
Gender;
Race;
Entrepreneurship;
Venture Capital;
Small Business;
Leadership;
Information Technology;
Competition
- March 2021 (Revised September 2021)
- Case
Applied: Using Behavioral Science to Debias Hiring
By: Ashley Whillans and Jeff Polzer
The UK government’s Behavioural Insights Team (BIT) needed to hire a new associate and were trying to increase the diversity of their job candidates. This decision was based on academic research showing that recruiters and managers often fell into common traps like...
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- March 2021
- Article
Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment
By: Yang Xiang, Thomas Graeber, Benjamin Enke and Samuel Gershman
This paper theoretically and empirically investigates the role of Bayesian noisy cognition in perceptual judgment, focusing on the central tendency effect: the well-known empirical regularity that perceptual judgments are biased towards the center of the...
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