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- June 2022
- Article
Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation
By: Jacqueline N. Lane, Misha Teplitskiy, Gary Gray, Hardeep Ranu, Michael Menietti, Eva C. Guinan and Karim R. Lakhani
The evaluation and selection of novel projects lies at the heart of scientific and technological innovation, and yet there are persistent concerns about bias, such as conservatism. This paper investigates the role that the format of evaluation, specifically information...
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- 2022
- Working Paper
Are Experts Blinded by Feasibility?: Experimental Evidence from a NASA Robotics Challenge
By: Jacqueline N. Lane, Zoe Szajnfarber, Jason Crusan, Michael Menietti and Karim R. Lakhani
Resource allocation decisions play a dominant role in shaping a firm’s technological trajectory and competitive advantage. Recent work indicates that innovative firms and scientific institutions tend to exhibit an anti-novelty bias when evaluating new projects and...
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- May 2022
- 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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- May 2022
- Case
Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models
By: Tsedal Neeley and Stefani Ruper
Dr. Timnit Gebru—a leading artificial intelligence (AI) computer scientist and co-lead of Google’s Ethical AI team—was messaging with one of her colleagues when she saw the words: “Did you resign?? Megan sent an email saying that she accepted your resignation.” Heart...
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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
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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- Article
Present Bias Causes and Then Dissipates Auto-enrollment Savings Effects
By: John Beshears, James J. Choi, David Laibson and Peter Maxted
Present bias causes procrastination, which leads households to stick with auto-enrollment defaults. However, present bias also engenders overconsumption. Separation from each employer generates a rollover of 401(k) balances to an individual retirement account (IRA)...
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- May 2022
- Article
When Harry Fired Sally: The Double Standard in Punishing Misconduct
By: Mark Egan, Gregor Matvos and Amit Seru
We examine gender differences in misconduct punishment in the financial advisory industry. We find evidence of a “gender punishment gap”: following an incident of misconduct, female advisers are 20% more likely to lose their jobs and 30% less likely to find new jobs...
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- April 2022
- Teaching Note
Gender Equality in Business: 100 Years of Progress?
By: Boris Groysberg and Colleen Ammerman
Teaching Note for HBS Case No. 422-066, "Gender Equality in Business: 100 Years of Progress?" The case traces the history of women in management from the early 20th to early 21st century through analysis of Harvard Business Review's coverage of women and gender. The...
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- April 2022
- Case
Gender Equality in Business: 100 Years of Progress?
By: Boris Groysberg and Colleen Ammerman
"Gender Equality in Business: 100 Years of Progress?" traces the history of women in management from the early 20th to early 21st century through analysis of Harvard Business Review's coverage of women and gender. The case identifies six distinct phases in the...
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- Other Article
Sustainable Strategies and Net-Zero Goals
By: Mark L. Frigo, Robert S. Kaplan and Karthik Ramanna
In a recent Harvard Business Review article, Kaplan and Ramanna describe a rigorous approach, the E-liability method, for companies’ ESG reporting, especially as it pertains to GHG emissions measurements. They argue that the current standards for measuring...
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- Article
Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)
By: Eva Ascarza and Ayelet Israeli
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details
- 2022
- Working Paper
Fintech to the (Worker) Rescue: Earned Wage Access and Employee Retention
By: Jose Murillo, Boris Vallee and Dolly Yu
Using novel data from a Mexican FinTech firm, we study the usage by workers of earned wages access, an innovative financial service offered by firms to their employees as a benefit. We find usage to be significant and concentrated towards the end of the pay cycle. We...
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Keywords:
Fintech;
Present Bias;
Earned Wage Access;
Wages;
Employees;
Retention;
Well-being;
Mexico
- 2022
- 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 within and between countries. How does demographic change affect local intergroup dynamics? In complement to accounts that emphasize stereotypical features of groups as determinants of their treatment, we propose the...
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- 2022
- Chapter
Fiscal Development under Colonial and Sovereign Rule
By: Ewout Frankema and Marlous van Waijenburg
This chapter explores differences in the making of a ‘modern’ fiscal state under colonial and sovereign rule. Focusing on African and Asian colonies (1820–1970) and their respective European metropoles, it argues that while the introduction of ‘modern’...
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Keywords:
Fiscal Modernization;
Colonial Rule;
Economic History;
Sovereign Finance;
History;
Taxation;
Africa;
Asia
- 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
Can Self-Regulation Save Digital Platforms?
By: Michael A. Cusumano, Annabelle Gawer and David B. Yoffie
This article explores some of the critical challenges facing self-regulation and the regulatory environment for digital platforms. We examine several historical examples of firms and industries that attempted self-regulation before the Internet. All dealt with similar...
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- October 2021
- Article
Fintech Borrowers: Lax Screening or Cream-Skimming?
By: Marco Di Maggio and Vincent Yao
Personal credit is the fastest-growing segment of the consumer credit market, mainly driven by fintech lenders' staggering expansion. We study this market using a unique individual-level data, which covers most of the top fintech and traditional lenders, and provides...
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- September–October 2021
- Article
Frontiers: Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb
By: Shunyuan Zhang, Nitin Mehta, Param Singh and Kannan Srinivasan
We study the effect of Airbnb’s smart-pricing algorithm on the racial disparity in the daily revenue earned by Airbnb hosts. Our empirical strategy exploits Airbnb’s introduction of the algorithm and its voluntary adoption by hosts as a quasi-natural experiment. Among...
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- 2021
- Working Paper
Invisible Primes: Fintech Lending with Alternative Data
By: Marco Di Maggio, Dimuthu Ratnadiwakara and Don Carmichael
We exploit anonymized administrative data provided by a major fintech platform to investigate whether using alternative data to assess borrowers’ creditworthiness results in broader credit access. Comparing actual outcomes of the fintech platform’s model to...
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- September 17, 2021
- Article
AI Can Help Address Inequity—If Companies Earn Users' Trust
By: Shunyuan Zhang, Kannan Srinivasan, Param Singh and Nitin Mehta
While companies may spend a lot of time testing models before launch, many spend too little time considering how they will work in the wild. In particular, they fail to fully consider how rates of adoption can warp developers’ intent. For instance, Airbnb launched a...
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