Filter Results:
(173)
Show Results For
- All HBS Web
(357)
- News (54)
- Research (173)
- Multimedia (7)
- Faculty Publications (110)
Show Results For
- All HBS Web
(357)
- News (54)
- Research (173)
- Multimedia (7)
- Faculty Publications (110)
Page 1 of 173
Results →
Sort by
- October 2015 (Revised January 2017)
- Exercise
Gender at Work
By: Boris Groysberg and Colleen Ammerman
Groysberg, Boris, and Colleen Ammerman. "Gender at Work." Harvard Business School Exercise 416-026, October 2015. (Revised January 2017.)
- 2024
- Working Paper
A Gender Backlash: Does Exposure to Female Labor Market Participation Fuel Gender Conservatism?
By: Paula Rettl, Diane Bolet, Catherine E. De Vries, Simone Cremaschi, Tarik Abou-Chadi and Sergi Pardos-Prado
The growing participation of women in the labor market has marked a significant societal transformation, coinciding with the rise of gender conservatism and far-right support. We study whether the economic consequences of labor market feminization and gender backlash... View Details
Keywords: Gender Bias; Gender Equality; Gender Inclusivity; Politics; Political Backlash; Political Culture; Conservatism; Gender; Government and Politics; Equality and Inequality; Prejudice and Bias; Labor
Rettl, Paula, Diane Bolet, Catherine E. De Vries, Simone Cremaschi, Tarik Abou-Chadi, and Sergi Pardos-Prado. "A Gender Backlash: Does Exposure to Female Labor Market Participation Fuel Gender Conservatism?" Harvard Business School Working Paper, No. 25-022, November 2024.
- 19 Nov 2019
- Op-Ed
Gender Bias Complaints against Apple Card Signal a Dark Side to Fintech
bias in Goldman Sachs’s underwriting model. (Goldman developed and issued the card.) Adding fuel to the fire, Apple co-founder Steve Wozniak shared that the same thing had happened to him and his wife. Officials from the New York... View Details
- May–June 2021
- Article
How to Close the Gender Gap
By: Colleen Ammerman and Boris Groysberg
Most companies say they’re committed to advancing women into leadership roles. What they may fail to recognize, though, is that systemic barriers are holding women back. As a result, women remain disadvantaged at every stage of their employment and underrepresented in... View Details
Keywords: Gender Discrimination; Employment; Gender; Prejudice and Bias; Talent and Talent Management; Organizational Change and Adaptation
Ammerman, Colleen, and Boris Groysberg. "How to Close the Gender Gap." Harvard Business Review 99, no. 3 (May–June 2021): 124–133.
- Forthcoming
- Article
Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure... View Details
Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Organization Science (forthcoming). (Pre-published online May 31, 2023.)
- 2023
- Working Paper
Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure... View Details
Keywords: STEM; Selection and Staffing; Gender; Prejudice and Bias; Training; Equality and Inequality; Competency and Skills
Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Harvard Business School Working Paper, No. 23-066, April 2023. (Accepted by Organization Science.)
- 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 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 2021
- Article
Gender Stereotypes in Deliberation and Team Decisions
By: Katherine B. Coffman, Clio Bryant Flikkema and Olga Shurchkov
We explore how groups deliberate and decide on ideas in an experiment with communication. We find that gender biases play a significant role in which group members are chosen to answer on behalf of the group. Conditional on the quality of their ideas, individuals are... View Details
Keywords: Gender Differences; Stereotypes; Teams; Economic Experiments; Gender; Prejudice and Bias; Groups and Teams; Perception
Coffman, Katherine B., Clio Bryant Flikkema, and Olga Shurchkov. "Gender Stereotypes in Deliberation and Team Decisions." Games and Economic Behavior 129 (September 2021): 329–349.
- 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
- Article
Men as Cultural Ideals: Cultural Values Moderate Gender Stereotype Content.
By: Amy Cuddy, Elizabeth Baily Wolf, Peter Glick, Susan Crotty, Jihye Chong and Michael I. Norton
Four studies tested whether cultural values moderate the content of gender stereotypes, such that male stereotypes more closely align with core cultural values (specifically, individualism vs. collectivism) than do female stereotypes. In Studies 1 and 2, using... View Details
Keywords: Gender Stereotypes; Stereotype Content; Individualism; Collectivism; Prejudice and Bias; Values and Beliefs; Culture; Gender
Cuddy, Amy, Elizabeth Baily Wolf, Peter Glick, Susan Crotty, Jihye Chong, and Michael I. Norton. "Men as Cultural Ideals: Cultural Values Moderate Gender Stereotype Content." Journal of Personality and Social Psychology 109, no. 4 (October 2015): 622–635.
- June 2021
- Article
The Role of Beliefs in Driving Gender Discrimination
By: Katherine B. Coffman, Christine L. Exley and Muriel Niederle
While there is ample evidence of discrimination against women in the workplace, it can be difficult to understand what factors contribute to discriminatory behavior. We use an experiment to both document discrimination and unpack its sources. First, we show that, on... View Details
Keywords: Gender Discrimination; Behavioral Decision Making; Gender; Attitudes; Prejudice and Bias; Economics; Behavior; Decision Making
Coffman, Katherine B., Christine L. Exley, and Muriel Niederle. "The Role of Beliefs in Driving Gender Discrimination." Management Science 67, no. 6 (June 2021).
- May 28, 2018
- Article
How Companies Can Identify Racial and Gender Bias in Their Customer Service
By: Alexandra C. Feldberg and Tami Kim
Research shows that minority customers — blacks and Asians — regularly receive worse customer service than whites in ways that are not immediately obvious to onlookers (or even managers). These results prompt a couple of questions for executives and managers. One, does... View Details
Keywords: Internal Audit; Customers; Service Delivery; Prejudice and Bias; Race; Gender; Organizational Change and Adaptation
Feldberg, Alexandra C., and Tami Kim. "How Companies Can Identify Racial and Gender Bias in Their Customer Service." Harvard Business Review (website) (May 28, 2018).
- 19 Mar 2009
- Working Paper Summaries
Beyond Gender and Negotiation to Gendered Negotiations
Keywords: by Deborah Kolb & Kathleen L. McGinn
- June 18, 2021
- Article
Who Do We Invent for? Patents by Women Focus More on Women's Health, but Few Women Get to Invent
By: Rembrand Koning, Sampsa Samila and John-Paul Ferguson
Women engage in less commercial patenting and invention than do men, which may affect what is invented. Using text analysis of all U.S. biomedical patents filed from 1976 through 2010, we found that patents with all-female inventor teams are 35% more likely than... View Details
Keywords: Innovation; Gender Bias; Health; Innovation and Invention; Research; Patents; Gender; Prejudice and Bias
Koning, Rembrand, Sampsa Samila, and John-Paul Ferguson. "Who Do We Invent for? Patents by Women Focus More on Women's Health, but Few Women Get to Invent." Science 372, no. 6548 (June 18, 2021): 1345–1348.
- 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
Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
- 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... View Details
Keywords: Executives; CEO; Promotion; Gender Bias; Personal Development and Career; Gender; Diversity; Power and Influence
Margolis, Joshua D., and Anne Donnellon. "Sonia Millar: Negotiating for the C-Suite." Harvard Business School Brief Case 920-555, September 2019.
- 22 Jan 2018
- Working Paper Summaries
When Gender Discrimination Is Not About Gender
- Forthcoming
- Article
Sampling Bias in Entrepreneurial Experiments
By: Ruiqing Cao, Rembrand Koning and Ramana Nanda
Using data from a prominent online platform for launching new digital products, we document that ‘sampling bias’—defined as the difference between a startup’s target customer base and the actual sample on which early ‘beta tests’ are conducted—has a systematic and... View Details
Cao, Ruiqing, Rembrand Koning, and Ramana Nanda. "Sampling Bias in Entrepreneurial Experiments." Management Science (forthcoming). (Pre-published online December 14, 2023.)