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- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea...
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Keywords:
Algorithm Bias;
Algorithmic Data;
Race And Ethnicity;
Experimentation;
Promotion;
Marketing And Society;
Big Data;
Privacy;
Data-driven Management;
Data Analysis;
Data Analytics;
E-Commerce Strategy;
Discrimination;
Targeted Advertising;
Targeted Policies;
Pricing Algorithms;
A/B Testing;
Ethical Decision Making;
Customer Base Analysis;
Customer Heterogeneity;
Coupons;
Marketing;
Race;
Gender;
Diversity;
Customer Relationship Management;
Marketing Communications;
Advertising;
Decision Making;
Ethics;
E-commerce;
Analytics and Data Science;
Retail Industry;
Apparel and Accessories Industry;
United States
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false...
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- 2022
- Working Paper
Politics at Work
By: Emanuele Colonnelli, Valdemar Pinho Neto and Edoardo Teso
We study how individual political views shape firm behavior and labor market outcomes. Using new micro-data on the political affiliation of business owners and private-sector workers in Brazil over the 2002–2019 period, we first document the presence of political...
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- 2023
- Working Paper
Scapegoating and Discrimination in Times of Crisis: Evidence from Airbnb
By: Michael Luca, Elizaveta Pronkina and Michelangelo Rossi
We present evidence that discrimination against Asian-American Airbnb users sharply increased at the
start of the COVID-19 pandemic. Using a DiD approach, we find that hosts with distinctively Asian
names experienced a 20 percent decline in guests relative to hosts...
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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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- 2022
- Other Teaching and Training Material
Organizational Behavior Reading: Managing Differences
By: Robin Ely and Colleen Ammerman
This reading provides principles and practices managers can draw upon to leverage differences in social identities - such as gender and race - to create more effective work relationships, teams, and organizations. The Essential Reading's first section draws upon...
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- 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
- 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
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 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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- 2021
- Book
Glass Half-Broken: Shattering the Barriers That Still Hold Women Back at Work
By: Colleen Ammerman and Boris Groysberg
Why does the gender gap persist and how can we close it? For years women have made up the majority of college-educated workers in the United States. In 2019, the gap between the percentage of women and the percentage of men in the workforce was the smallest on record....
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- 2021
- Working Paper
Bollywood, Skin Color and Sexism: The Role of the Film Industry in Emboldening and Contesting Stereotypes in India after Independence
By: Sudev Sheth, Geoffrey Jones and Morgan Spencer
This working paper examines the social impact of the film industry in India during the first four decades after Indian Independence in 1947. It shows that Bollywood, the mainstream cinema in India and the counterpart in scale to Hollywood in the United States, shared...
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- September 2020 (Revised July 2022)
- Teaching Note
Algorithmic Bias in Marketing
By: Ayelet Israeli and Eva Ascarza
Teaching Note for HBS No. 521-020. This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and...
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- September 2020 (Revised July 2022)
- Technical Note
Algorithmic Bias in Marketing
By: Ayelet Israeli and Eva Ascarza
This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing...
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Keywords:
Algorithmic Data;
Race And Ethnicity;
Promotion;
＂Marketing Analytics＂;
Marketing And Society;
Big Data;
Privacy;
Data-driven Management;
Data Analysis;
Data Analytics;
E-Commerce Strategy;
Discrimination;
Targeting;
Targeted Advertising;
Pricing Algorithms;
Ethical Decision Making;
Customer Heterogeneity;
Marketing;
Race;
Ethnicity;
Gender;
Diversity;
Prejudice and Bias;
Marketing Communications;
Analytics and Data Science;
Analysis;
Decision Making;
Ethics;
Customer Relationship Management;
E-commerce;
Retail Industry;
Apparel and Accessories Industry;
United States
- 2020
- Working Paper
(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial
By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker
While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between...
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- 2022
- Working Paper
Optimal Illiquidity
By: John Beshears, James J. Choi, Christopher Clayton, Christopher Harris, David Laibson and Brigitte C. Madrian
We calculate the socially optimal level of illiquidity in an economy populated by households with taste shocks and naive present bias. The government chooses mandatory contributions to accounts, each witha different pre-retirement withdrawal penalty. Collected...
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Keywords:
Illiquidity;
Commitment;
Flexibility;
Savings;
Social Security;
Retirement;
Government Legislation;
Taxation;
Saving
- March 2020
- Article
Which Early Withdrawal Penalty Attracts the Most Deposits to a Commitment Savings Account?
By: John Beshears, James J. Choi, Christopher Harris, David Laibson, Brigitte C. Madrian and Jung Sakong
Previous research has shown that some people voluntarily use commitment contracts that restrict their own choice sets. We study how people divide money between two accounts: a liquid account that permits unrestricted withdrawals and a commitment account that is...
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- September 2019
- Case
Sonia Millar: Negotiating for the C-Suite
By: Joshua D. Margolis and Anne Donnellon
This case addresses the nuances of gender dynamics and career progression at the top of the organization, where even women who have strong leadership expertise, experience, and alliances with powerful male colleagues still get stuck. Told from the point of view of...
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- Article
The Mixed Effects of Online Diversity Training
By: Edward H. Chang, Katherine L. Milkman, Dena M. Gromet, Robert W. Rebele, Cade Massey, Angela L. Duckworth and Adam M. Grant
We present results from a large (n = 3,016) field experiment at a global organization testing whether a brief science-based online diversity training can change attitudes and behaviors toward
women in the workplace. Our preregistered field experiment included an...
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- Article
Choice Architects Reveal a Bias Toward Positivity and Certainty
By: David P. Daniels and Julian Zlatev
Biases influence important decisions, but little is known about whether and how individuals try to exploit others’ biases in strategic interactions. Choice architects—that is, people who present choices to others—must often decide between presenting choice sets with...
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