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      • Faculty Publications  (106)

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      • March 2021
      • Article

      Deliberately Prejudiced Self-driving Vehicles Elicit the Most Outrage

      By: Julian De Freitas and Mina Cikara
      Should self-driving vehicles be prejudiced, e.g., deliberately harm the elderly over young children? When people make such forced-choices on the vehicle’s behalf, they exhibit systematic preferences (e.g., favor young children), yet when their options are unconstrained... View Details
      Keywords: Moral Judgment; Autonomous Vehicles; Driverless Policy; Moral Outrage; Moral Sensibility; Judgments; Transportation; Policy
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      De Freitas, Julian, and Mina Cikara. "Deliberately Prejudiced Self-driving Vehicles Elicit the Most Outrage." Cognition 208 (March 2021).
      • November–December 2021
      • Article

      Does Gender Matter? The Effect of Management Responses on Reviewing Behavior

      By: Davide Proserpio, Isamar Troncoso and Francesca Valsesia
      We study the effect of management responses on the reviewing behavior of self-identified female and male reviewers. Using data from Tripadvisor, we show that after hotels begin to respond to reviews, the probability that a negative review comes from a self-identified... View Details
      Keywords: Word Of Mouth; Online Reviews; Management Responses; E-commerce; Gender; Prejudice and Bias; Digital Platforms; Customers
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      Proserpio, Davide, Isamar Troncoso, and Francesca Valsesia. "Does Gender Matter? The Effect of Management Responses on Reviewing Behavior." Marketing Science 40, no. 6 (November–December 2021): 1199–1213.
      • September 2020
      • Case

      The Black New Venture Competition

      By: Karen Mills, Jeffrey J. Bussgang, Martin Sinozich and Gabriella Elanbeck
      Black entrepreneurs encounter many unique obstacles when raising capital to start and grow a business. During their second year at Harvard Business School (HBS), MBA students Kimberly Foster and Tyler Simpson decided to do something to make a difference for... View Details
      Keywords: Startup; Start-up; Startup Financing; Startups; Start-ups; African-American Protagonist; African-american Entrepreneurs; African-american Investors; African-Americans; African-American Women; Black Leadership; Black Inventors; Black Entrepreneurs; Harvard Business School; Harvard; Business And Society; Early Stage Funding; Early Stage Finance; Technology Entrepreneurship; Discrimination; Technology Ventures; Entrepreneurial Finance; Entrepreneurial Financing; Business Plan; Business Startups; Business Ventures; Financing and Loans; Business Growth and Maturation; Diversity; Gender; Race; Entrepreneurship; Venture Capital; Small Business; Leadership; Information Technology; Competition; Technology Industry
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      Mills, Karen, Jeffrey J. Bussgang, Martin Sinozich, and Gabriella Elanbeck. "The Black New Venture Competition." Harvard Business School Case 821-029, September 2020.
      • 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.)
      • September 2020 (Revised February 2024)
      • Teaching Note

      Artea (A), (B), (C), and (D): Designing Targeting Strategies

      By: Eva Ascarza and Ayelet Israeli
      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 A/B testing analysis and... View Details
      Keywords: Targeted Advertising; Targeting; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School Teaching Note 521-041, September 2020. (Revised February 2024.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (B): Including Customer-Level Demographic Data

      By: Eva Ascarza and Ayelet Israeli
      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 A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
      Keywords: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-Level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (C): Potential Discrimination through Algorithmic Targeting

      By: Eva Ascarza and Ayelet Israeli
      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 A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
      Keywords: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (C): Potential Discrimination through Algorithmic Targeting." Harvard Business School Exercise 521-037, September 2020. (Revised July 2022.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (D): Discrimination through Algorithmic Bias in Targeting

      By: Eva Ascarza and Ayelet Israeli
      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 A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
      Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
      • September 2020 (Revised June 2023)
      • Exercise

      Artea: Designing Targeting Strategies

      By: Eva Ascarza and Ayelet Israeli
      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 A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
      Keywords: Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; "Marketing Analytics"; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analytics; Data Analysis; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Targeting; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Algorithmic Bias; 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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      Ascarza, Eva, and Ayelet Israeli. "Artea: Designing Targeting Strategies." Harvard Business School Exercise 521-021, September 2020. (Revised June 2023.)
      • September 2020 (Revised July 2022)
      • Supplement

      Spreadsheet Supplement to Artea (B) and (C)

      By: Eva Ascarza and Ayelet Israeli
      Spreadsheet Supplement to "Artea (B): Including Customer-level Demographic Data" and "Artea (C): Potential Discrimination through Algorithmic Targeting" View Details
      Keywords: Gender; Race; Diversity; Marketing; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Spreadsheet Supplement to Artea (B) and (C)." Harvard Business School Spreadsheet Supplement 521-704, September 2020. (Revised July 2022.)
      • September 2020 (Revised June 2023)
      • Supplement

      Spreadsheet Supplement to Artea Teaching Note

      By: Eva Ascarza and Ayelet Israeli
      Spreadsheet Supplement to Artea Teaching Note 521-041. 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 A/B testing analysis and... View Details
      Keywords: Targeted Advertising; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Spreadsheet Supplement to Artea Teaching Note." Harvard Business School Spreadsheet Supplement 521-705, September 2020. (Revised June 2023.)
      • 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... View Details
      Keywords: Behavioral Economics; Coronavirus; Discrimination; Homophily; Labor Market Mobility; Limited Attention; Resumes; Personal Characteristics; Prejudice and Bias
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      Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Subhradip Sarker. "(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial." Harvard Business School Working Paper, No. 21-038, September 2020.
      • 2020
      • Book

      The Power of Experiments: Decision-Making in a Data-Driven World

      By: Michael Luca and Max H. Bazerman
      Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of changes to an... View Details
      Keywords: Experiments; Randomized Controlled Trials; Organizations; Decision Making; Analytics and Data Science; Management Analysis, Tools, and Techniques
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      Luca, Michael, and Max H. Bazerman. The Power of Experiments: Decision-Making in a Data-Driven World. Cambridge, MA: MIT Press, 2020.
      • December 2019 (Revised December 2021)
      • Case

      Negotiating for Equal Pay: The U.S. Women's National Soccer Team (A)

      By: Christine Exley, John Beshears, Manuela Collis and Davis Heniford
      In 2019, members of the U.S. Women's National Soccer Team (WNT) filed a gender discrimination lawsuit against the U.S. Soccer Federation. The case describes the history of the WNT's quest for equal pay leading up to this event. View Details
      Keywords: Equal Pay; Negotiation; Compensation and Benefits; Equality and Inequality; Gender; Prejudice and Bias; Negotiation Tactics; Corporate Governance; Lawsuits and Litigation; Sports; Sports Industry; United States
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      Exley, Christine, John Beshears, Manuela Collis, and Davis Heniford. "Negotiating for Equal Pay: The U.S. Women's National Soccer Team (A)." Harvard Business School Case 920-029, December 2019. (Revised December 2021.)
      • December 2019
      • Article

      The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment

      By: Donald Ngwe, Kris J. Ferreira and Thales Teixeira
      Many online stores are designed such that shoppers can easily access any available discounted products. We propose that deliberately increasing search frictions by placing small obstacles to locating discounted items can improve online retailers’ margins and even... View Details
      Keywords: Online Retailing; Friction; Effor; Search Costs; Price Discrimination; Marketing; Consumer Behavior; Strategy; Price; E-commerce; Retail Industry; Fashion Industry
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      Ngwe, Donald, Kris J. Ferreira, and Thales Teixeira. "The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment." Journal of Marketing Research (JMR) 56, no. 6 (December 2019): 944–959.
      • November 2019 (Revised February 2020)
      • Case

      Starbucks: Reaffirming Commitment to the Third Place Ideal

      By: Francesca Gino, Katherine B. Coffman and Jeff Huizinga
      On April 12, 2018, two African American entrepreneurs had scheduled a business meeting at a Starbucks in Philadelphia’s Rittenhouse Square neighborhood. They sat without ordering, waiting for a local businessman to show up for the meeting. The store manager called 911... View Details
      Keywords: Mission and Purpose; Values and Beliefs; Prejudice and Bias; Crisis Management; Employees; Training
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      Gino, Francesca, Katherine B. Coffman, and Jeff Huizinga. "Starbucks: Reaffirming Commitment to the Third Place Ideal." Harvard Business School Case 920-016, November 2019. (Revised February 2020.)
      • September 2019 (Revised December 2022)
      • Background Note

      African American Inequality in the United States

      By: Janice H. Hammond, A. Kamau Massey and Mayra G. Garza
      This note describes how historical and on-going policies and practices that discriminate against African Americans led to present-day inequality. Topics include slavery, segregation, Jim Crow laws, “black codes,” and policies and practices relating to criminal justice,... View Details
      Keywords: African Americans; Justice; Slavery; Discrimination; Race; Equality and Inequality; Prejudice and Bias; Policy; History; United States
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      Hammond, Janice H., A. Kamau Massey, and Mayra G. Garza. "African American Inequality in the United States." Harvard Business School Background Note 620-046, September 2019. (Revised December 2022.)
      • September 2019
      • Article

      Contingent Capital Trigger Effects: Evidence from Liability Management Exercises

      By: Boris Vallée
      This paper investigates the so called liability management exercises by European banks, which bear comparable effects to triggering contingent capital. I first explore the determinants of these exercises. I then study market reactions to these operations as well as... View Details
      Keywords: Contingent Capital; Financial Distress; Regulatory Capital; Financial Institutions; Legal Liability; Management; Banking Industry; Europe
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      Vallée, Boris. "Contingent Capital Trigger Effects: Evidence from Liability Management Exercises." Review of Corporate Finance Studies 8, no. 2 (September 2019): 235–259.
      • June 2019
      • Article

      Brokers vs. Retail Investors: Conflicting Interests and Dominated Products

      By: Mark Egan
      I study how brokers distort household investment decisions. Using a novel convertible bond dataset, I find that consumers often purchase dominated bonds—cheap and expensive versions of otherwise identical bonds coexist in the market. The empirical evidence suggests... View Details
      Keywords: Brokers; Fiduciary Standard; Consumer Finance; Structured Products; Household; Investment; Decisions; Motivation and Incentives; Conflict of Interests
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      Egan, Mark. "Brokers vs. Retail Investors: Conflicting Interests and Dominated Products." Journal of Finance 74, no. 3 (June 2019): 1217–1260.
      • 2019
      • Working Paper

      The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment

      By: Donald Ngwe, Kris J. Ferreira and Thales Teixeira
      Many online stores are designed such that shoppers can easily access any available discounted products. We propose that deliberately increasing search frictions by placing small obstacles to locating discounted items can improve online retailers’ margins and even... View Details
      Keywords: E-commerce; Online Retailing; Friction; Effor; Search Costs; Price Discrimination; Consumer Behavior; Price; Search Technology
      Citation
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      Ngwe, Donald, Kris J. Ferreira, and Thales Teixeira. "The Impact of Increasing Search Frictions on Online Shopping Behavior: Evidence from a Field Experiment." Harvard Business School Working Paper, No. 19-080, January 2019.
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