Filter Results:
(92)
Show Results For
- All HBS Web
(350)
- Faculty Publications (92)
Show Results For
- All HBS Web
(350)
- Faculty Publications (92)
- 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
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.
- November–December 2020
- Article
Getting Serious About Diversity: Enough Already with the Business Case
By: Robin Ely and David A. Thomas
Leaders may mean well when they tout the economic payoffs of hiring more women and people of color, but there is no research support for the notion that diversifying the workforce automatically improves a company’s performance. This article critiques the popular... View Details
Ely, Robin, and David A. Thomas. "Getting Serious About Diversity: Enough Already with the Business Case." Harvard Business Review 98, no. 6 (November–December 2020): 114–122. (Winner, McKinsey Best Paper Award, 2021. Winner, Academy of Management, Organizational Behavior Division, Outstanding Practitioner-Orientated Publication in OB, 2021.)
- October 2020 (Revised April 2021)
- Case
Women Entrepreneurs and Tech Ecosystems: One City, Two Realities, and Four Diverse Women
By: Rosabeth Moss Kanter and Joyce J. Kim
Four diverse women entrepreneurs launched their ventures in a thriving entrepreneurial ecosystem that was part of a shift to a creative technology-driven economy for Miami. Although Miami was rated the #1 U.S. city for startups in 2017, the region contained structural... View Details
Keywords: Female Entrepreneur; Entrepreneurial Ecosystems; Inclusion; Innovation & Entrepreneurship; Racism; Sexism; Start-up; Entrepreneurship; Business Startups; Diversity; Gender; Race; Prejudice and Bias; Innovation and Invention; City; Culture; Miami
Kanter, Rosabeth Moss, and Joyce J. Kim. "Women Entrepreneurs and Tech Ecosystems: One City, Two Realities, and Four Diverse Women." Harvard Business School Case 321-083, October 2020. (Revised April 2021.)
- September 2020
- Case
The Black New Venture Competition
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
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)
- 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
- 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
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
- 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
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
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
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
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
- 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
- July 2020
- Teaching Plan
Girls Who Code
By: Brian Trelstad and Amy Klopfenstein
This teaching plan serves as a supplement to HBS Case No. 320-055, “Girls Who Code.” Founded 2012 by former lawyer Reshma Saujani, Girls Who Code (GWC) offered coding education programs to middle- and high school-aged girls. The organization also sought to alter... View Details
Keywords: Communication; Communication Strategy; Spoken Communication; Interpersonal Communication; Demographics; Age; Gender; Education; Curriculum and Courses; Learning; Middle School Education; Secondary Education; Leadership Style; Leadership; Social Enterprise; Nonprofit Organizations; Social Psychology; Attitudes; Behavior; Cognition and Thinking; Prejudice and Bias; Power and Influence; Identity; Social and Collaborative Networks; Motivation and Incentives; Society; Civil Society or Community; Culture; Public Opinion; Social Issues; Information Technology; Applications and Software; Education Industry; Technology Industry; North and Central America; United States
- July 2020 (Revised January 2021)
- Case
Rosalind Fox at John Deere
By: Anthony Mayo and Olivia Hull
Rosalind Fox, the factory manager at John Deere’s Des Moines, Iowa plant, has improved the financial standing of the factory in the three years she’s been at its helm. But employee engagement scores—which measured employees’ satisfaction with working conditions and... View Details
Keywords: Agribusiness; Change Management; Experience and Expertise; Talent and Talent Management; Diversity; Gender; Race; Engineering; Geographic Location; Globalized Markets and Industries; Leadership Development; Leadership Style; Leading Change; Management Style; Management Teams; Organizational Culture; Personal Development and Career; Prejudice and Bias; Power and Influence; Status and Position; Trust; Agriculture and Agribusiness Industry; United States
Mayo, Anthony, and Olivia Hull. "Rosalind Fox at John Deere." Harvard Business School Case 421-011, July 2020. (Revised January 2021.)
- June 2020 (Revised September 2020)
- Case
Shellye Archambeau: Becoming a CEO (A)
By: Tsedal Neeley and John Masko
With the economy in a freefall, MetricStream is losing customers, hemorrhaging cash and struggling to make payroll. Several board members are threatening to quit. Others are pressing to sell the company even at dismally low valuations. It’s 2008 and lightning has... View Details
Keywords: Leadership; Race; Gender; Leadership Style; Risk and Uncertainty; Change; Prejudice and Bias; Decision Making; Personal Development and Career; Technology Industry; California
Neeley, Tsedal, and John Masko. "Shellye Archambeau: Becoming a CEO (A)." Harvard Business School Case 420-071, June 2020. (Revised September 2020.)
- June 2020
- Supplement
Shellye Archambeau: Becoming a CEO (B)
By: Tsedal Neeley and Briana Richardson
With the economy in a freefall, MetricStream is losing customers, hemorrhaging cash and struggling to make payroll. Several board members are threatening to quit. Others are pressing to sell the company even at dismally low valuations. It’s 2008 and lightning has... View Details
Keywords: Race; Gender; Leadership Style; Risk and Uncertainty; Change; Prejudice and Bias; Decision Making; Personal Development and Career; Technology Industry; California
Neeley, Tsedal, and Briana Richardson. "Shellye Archambeau: Becoming a CEO (B)." Harvard Business School Supplement 420-073, June 2020.
- Article
The Impact of Penalties for Wrong Answers on the Gender Gap in Test Scores
By: Katherine B. Coffman and David Klinowski
Multiple-choice exams play a critical role in university admissions across the world. A key question is whether imposing penalties for wrong answers on these exams deters guessing from women more than men, disadvantaging female test-takers. We consider data from a... View Details
Coffman, Katherine B., and David Klinowski. "The Impact of Penalties for Wrong Answers on the Gender Gap in Test Scores." Proceedings of the National Academy of Sciences 117, no. 16 (April 21, 2020): 8794–8803.
- March 2020 (Revised August 2020)
- Case
Culture at Google
By: Nien-hê Hsieh, Amy Klopfenstein and Sarah Mehta
Beginning in 2017, technology (tech) company Google faced a series of employee-relations issues that threatened its unique culture of innovation and open communication. Issues included protests surrounding Google’s contracts with the U.S. government, restrictions of... View Details
Keywords: Human Resources; Employee Relationship Management; Recruitment; Retention; Resignation and Termination; Labor; Working Conditions; Employment; Labor Unions; Wages; Law; Lawsuits and Litigation; Rights; Ethics; Values and Beliefs; Fairness; Organizations; Organizational Culture; Mission and Purpose; Social Psychology; Attitudes; Behavior; Conflict Management; Trust; Motivation and Incentives; Prejudice and Bias; Power and Influence; Information Technology; Internet and the Web; Information Infrastructure; Society; Social Issues; Culture; Civil Society or Community; Demographics; Diversity; Ethnicity; Gender; Race; Technology Industry; North and Central America; United States; California
Hsieh, Nien-hê, Amy Klopfenstein, and Sarah Mehta. "Culture at Google." Harvard Business School Case 320-050, March 2020. (Revised August 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
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.)