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      • Faculty Publications  (37)

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      • March 2025
      • Article

      Optimal Illiquidity

      By: John Beshears, James J. Choi, Christopher Clayton, Christopher Harris, David Laibson and Brigitte C. Madrian
      We study the socially optimal level of illiquidity in an economy populated by households with taste shocks and present bias with naive beliefs. The government chooses mandatory contributions to accounts, each with a different pre-retirement withdrawal penalty.... View Details
      Keywords: Retirement; Financial Liquidity; Personal Finance; Saving
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      Beshears, John, James J. Choi, Christopher Clayton, Christopher Harris, David Laibson, and Brigitte C. Madrian. "Optimal Illiquidity." Art. 103996. Journal of Financial Economics 165 (March 2025).
      • January 2025
      • Article

      Everyone Steps Back?: The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High

      By: John (Jianqui) Bai, William R. Kerr, Chi Wan and Alptug Yorulmaz
      We study funding gaps on Kickstarter across multiple ethnic groups from 2009 to 2021. Scaling the concept of racially salient events, we quantify the close co-movement of minority funding gaps in crowd-funding to inflamed political rhetoric surrounding migration. The... View Details
      Keywords: Crowdfunding; Prejudice and Bias; Race; Immigration; Public Opinion
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      Bai, John (Jianqui), William R. Kerr, Chi Wan, and Alptug Yorulmaz. "Everyone Steps Back? The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High." Research Policy 54, no. 1 (January 2025).
      • January 2025
      • Article

      Reducing Prejudice with Counter-stereotypical AI

      By: Erik Hermann, Julian De Freitas and Stefano Puntoni
      Based on a review of relevant literature, we propose that the proliferation of AI with human-like and social features presents an unprecedented opportunity to address the underlying cognitive and affective drivers of prejudice. An approach informed by the psychology of... View Details
      Keywords: Prejudice and Bias; AI and Machine Learning; Interpersonal Communication; Social and Collaborative Networks
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      Hermann, Erik, Julian De Freitas, and Stefano Puntoni. "Reducing Prejudice with Counter-stereotypical AI." Consumer Psychology Review 8, no. 1 (January 2025): 75–86.
      • April 2024
      • Article

      Model-based Financial Regulations Impair the Transition to Net-zero Carbon Emissions

      By: Matteo Gasparini, Matthew C. Ives, Ben Carr, Sophie Fry and Eric Beinhocker
      Investments via the financial system are essential for fostering the green transition. However, the role of existing financial regulations in influencing investment decisions is understudied. Here we analyse data from the European Banking Authority to show that... View Details
      Keywords: Climate Change; Investment; Governing Rules, Regulations, and Reforms; Energy Sources
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      Gasparini, Matteo, Matthew C. Ives, Ben Carr, Sophie Fry, and Eric Beinhocker. "Model-based Financial Regulations Impair the Transition to Net-zero Carbon Emissions." Nature Climate Change 14, no. 5 (April 2024): 434–435.
      • March 2024
      • Case

      Unintended Consequences of Algorithmic Personalization

      By: Eva Ascarza and Ayelet Israeli
      “Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for... View Details
      Keywords: Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Customization and Personalization; Technology Industry; Retail Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Unintended Consequences of Algorithmic Personalization." Harvard Business School Case 524-052, March 2024.
      • December 4, 2023
      • Article

      Stop Assuming Introverts Aren't Passionate About Work

      By: Kai Krautter, Anabel Büchner and Jon M. Jachimowicz
      Society often assumes that the only way to be passionate is to act extroverted, but that is simply not true. In their new research, the authors found that regardless of their actual level of passion, extroverted employees are perceived as more passionate than... View Details
      Keywords: Passion; Personality; Extraversion; Scale Development; Personal Characteristics; Perception; Employees; Prejudice and Bias
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      Krautter, Kai, Anabel Büchner, and Jon M. Jachimowicz. "Stop Assuming Introverts Aren't Passionate About Work." Harvard Business Review Digital Articles (December 4, 2023).
      • 2023
      • Working Paper

      Complexity and Hyperbolic Discounting

      By: Benjamin Enke, Thomas Graeber and Ryan Oprea
      A large literature shows that people discount financial rewards hyperbolically instead of exponentially. While discounting of money has been questioned as a measure of time preferences, it continues to be highly relevant in empirical practice and predicts a wide range... View Details
      Keywords: Hyperbolic Discounting; Present Bias; Bounded Rationality; Cognitive Uncertainty; Behavioral Finance
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      Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Complexity and Hyperbolic Discounting." Harvard Business School Working Paper, No. 24-048, February 2024.
      • 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... View Details
      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
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      Israeli, Ayelet, and Eva Ascarza. "Artea Dashboard and Targeting Policy Evaluation." Harvard Business School Simulation 523-707, June 2023.
      • 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... View Details
      Keywords: AI and Machine Learning; Forecasting and Prediction; Prejudice and Bias
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      Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
      • 2023
      • Working Paper

      Feature Importance Disparities for Data Bias Investigations

      By: Peter W. Chang, Leor Fishman and Seth Neel
      It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
      Keywords: AI and Machine Learning; Analytics and Data Science; Prejudice and Bias
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      Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
      • 2024
      • Working Paper

      Everyone Steps Back?: The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High

      By: John (Jianqui) Bai, William R. Kerr, Chi Wan and Alptug Yorulmaz
      We study racial biases on Kickstarter across multiple ethnic groups from 2009-2021. Scaling the concept of racially salient events, we quantify the close co-movement of minority funding gaps to inflamed political rhetoric surrounding migration. The racial funding gap... View Details
      Keywords: Crowdfunding; Prejudice and Bias; Race; Immigration; Public Opinion
      Citation
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      Bai, John (Jianqui), William R. Kerr, Chi Wan, and Alptug Yorulmaz. "Everyone Steps Back? The Widespread Retraction of Crowd-Funding Support for Minority Creators When Migration Fear Is High." Harvard Business School Working Paper, No. 23-046, January 2023. (Revised February 2024.)
      • 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)... View Details
      Keywords: Present Bias; Procrastination; Personal Finance; Decision Making; Social Psychology; Retirement
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      Beshears, John, James J. Choi, David Laibson, and Peter Maxted. "Present Bias Causes and Then Dissipates Auto-enrollment Savings Effects." AEA Papers and Proceedings 112 (May 2022): 136–141.
      • 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... View Details
      Keywords: Diversity; Groups and Teams; Prejudice and Bias; Identity; Management Practices and Processes
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      Ely, Robin, and Colleen Ammerman. "Organizational Behavior Reading: Managing Differences." Core Curriculum Readings Series. Boston, MA: Harvard Business Publishing 8394, 2022.
      • 2023
      • Working Paper

      Fintech to the (Worker) Rescue: Access to Earned Wages, Financial Health and Employee Turnover

      By: Jose Murillo, Boris Vallée 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... View Details
      Keywords: Fintech; Present Bias; Earned Wage Access; Wages; Employees; Retention; Well-being; Mexico
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      Murillo, Jose, Boris Vallée, and Dolly Yu. "Fintech to the (Worker) Rescue: Access to Earned Wages, Financial Health and Employee Turnover." Working Paper, 2023.
      • 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
      Keywords: Customer Service; Customer Focus and Relationships; Service Delivery; Diversity; Prejudice and Bias; Organizational Change and Adaptation
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      Feldberg, Alexandra C., and Tami Kim. "Fighting Bias on the Front Lines." Harvard Business Review 99, no. 6 (November–December 2021): 90–98.
      • 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... View Details
      Keywords: Artificial Intelligence; Algorithmic Bias; Technological Innovation; Perception; Diversity; Equality and Inequality; Trust; AI and Machine Learning
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      Zhang, Shunyuan, Kannan Srinivasan, Param Singh, and Nitin Mehta. "AI Can Help Address Inequity—If Companies Earn Users' Trust." Harvard Business Review Digital Articles (September 17, 2021).
      • 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.... View Details
      Keywords: Women; Career; Gender Gap; Glass Ceiling; Gender; Employment; Personal Development and Career; Equality and Inequality; Organizational Culture; Diversity; Management; Strategy
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      Ammerman, Colleen, and Boris Groysberg. Glass Half-Broken: Shattering the Barriers That Still Hold Women Back at Work. Boston: Harvard Business Review Press, 2021.
      • 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... View Details
      Keywords: Film Industry; Bollywood; Tamil Cinema; Male Gaze; Social Impact; Stereotypes; Oral History; Film Entertainment; Gender; Race; Personal Characteristics; Prejudice and Bias; Business History; Motion Pictures and Video Industry; India
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      Sheth, Sudev, Geoffrey Jones, and Morgan Spencer. "Bollywood, Skin Color and Sexism: The Role of the Film Industry in Emboldening and Contesting Stereotypes in India after Independence." Harvard Business School Working Paper, No. 21-077, January 2021.
      • 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... View Details
      Keywords: Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Decision Making; Ethics; Customer Relationship Management; Retail Industry; Technology Industry; Apparel and Accessories Industry; United States
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      Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Teaching Note 521-035, September 2020. (Revised July 2022.)
      • 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... View Details
      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
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      Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Technical Note 521-020, September 2020. (Revised July 2022.)
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