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Show Results For
- All HBS Web
(1,131)
- News (183)
- Research (755)
- Events (8)
- Multimedia (14)
- Faculty Publications (497)
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- March 2021
- Supplement
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Power Point Supplement to 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... View Details
Keywords: Targeted Advertising; Targeting; Algorithmic Data; Bias; A/B Testing; Experiment; Advertising; Gender; Race; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
- October 2017
- Article
The Size of the LGBT Population and the Magnitude of Anti-Gay Sentiment Are Substantially Underestimated
By: Katherine Baldiga Coffman, Lucas C. Coffman and Keith M. Marzilli Ericson
We demonstrate that widely used measures of anti-gay sentiment and the size of the LGBT population are misestimated, likely substantially. In a series of online experiments using a large and diverse but non-representative sample, we compare estimates from the standard... View Details
Keywords: LGBTQ; Social Trends ＆ Culture; Economic Theory; Prejudice; Prejudice and Bias; Diversity; Economics; Demographics
Coffman, Katherine Baldiga, Lucas C. Coffman, and Keith M. Marzilli Ericson. "The Size of the LGBT Population and the Magnitude of Anti-Gay Sentiment Are Substantially Underestimated." Management Science 63, no. 10 (October 2017): 3168–3186.
- May–June 2024
- 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 35, no. 3 (May–June 2024): 911–927.
- 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 2018
- Article
Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia
By: Shane Greenstein and Feng Zhu
Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective,... View Details
Keywords: Online Community; Collective Intelligence; Wisdom Of Crowds; Bias; Wikipedia; Britannica; Knowledge Production; Knowledge Sharing; Knowledge Dissemination; Prejudice and Bias
Greenstein, Shane, and Feng Zhu. "Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia." MIS Quarterly 42, no. 3 (September 2018): 945–959.
- 2023
- Working Paper
Auditing Predictive Models for Intersectional Biases
By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details
Boxer, Kate S., Edward McFowland III, and Daniel B. Neill. "Auditing Predictive Models for Intersectional Biases." Working Paper, June 2023.
- November 30, 2020
- Editorial
Don't Focus on the Most Expressive Face in the Audience
By: Amit Goldenberg and Erika Weisz
Research has shown that when speaking in front of a group, people’s attention tends to gets stuck on the most emotional faces, causing them to overestimate the group’s average emotional state. In this piece, the authors share two additional findings: First, the larger... View Details
Goldenberg, Amit, and Erika Weisz. "Don't Focus on the Most Expressive Face in the Audience." Harvard Business Review (website) (November 30, 2020).
- Article
Price and Quality Decisions by Self-Serving Managers
By: Marco Bertini, Daniel Halbheer and Oded Koenigsberg
We present a theory of price and quality decisions by managers who are self-serving. In the theory, firms stress the price or quality of their products, but not both. Accounting for this, managers exploit any uncertainty about the cause of market outcomes to credit... View Details
Keywords: Causal Reasoning; Self-serving Bias; Strategic Orientation; Managerial Decision-making; Price; Quality; Decision Making; Theory
Bertini, Marco, Daniel Halbheer, and Oded Koenigsberg. "Price and Quality Decisions by Self-Serving Managers." International Journal of Research in Marketing 37, no. 2 (June 2020): 236–257.
- 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; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories 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.)
- Article
Whites See Racism as a Zero-Sum Game That They Are Now Losing
By: Michael I. Norton and Samuel R. Sommers
Although some have heralded recent political and cultural developments as signaling the arrival of a post-racial era in America, several legal and social controversies regarding "reverse racism" highlight Whites' increasing concern about anti-White bias. We show that... View Details
Keywords: Racism; Zero-sum Game; Bias; Affirmative Action; Prejudice and Bias; Race; Social Issues; United States
Norton, Michael I., and Samuel R. Sommers. "Whites See Racism as a Zero-Sum Game That They Are Now Losing." Perspectives on Psychological Science 6, no. 3 (May 2011): 215–218.
- 10 Jan 2013
- Working Paper Summaries
The Novelty Paradox & Bias for Normal Science: Evidence from Randomized Medical Grant Proposal Evaluations
- 2016
- Working Paper
PathBreakers? Women's Electoral Success and Future Political Participation
By: Sonia Bhalotra, Irma Clots-Figueras and Lakshmi Iyer
We investigate whether the event of a woman being competitively elected as a state legislator encourages the subsequent political participation of women, using a regression discontinuity design on constituency level data from India. We find that female incumbents are... View Details
Keywords: Political Participation; Women; Candidates; Gender Bias; Backlash; Minority Representation; Regression Discontinuity; India; Prejudice and Bias; Political Elections; Gender; Public Administration Industry; India
Bhalotra, Sonia, Irma Clots-Figueras, and Lakshmi Iyer. "PathBreakers? Women's Electoral Success and Future Political Participation." Harvard Business School Working Paper, No. 14-035, November 2013. (Revised January 2016.)
- Article
Physician–patient Racial Concordance and Disparities in Birthing Mortality for Newborns
By: Brad N. Greenwood, Rachel R. Hardeman, Laura Huang and Aaron Sojourner
Recent work has emphasized the benefits of patient–physician concordance on clinical care outcomes for underrepresented minorities, arguing it can ameliorate outgroup biases, boost communication, and increase trust. We explore concordance in a setting where racial... View Details
Greenwood, Brad N., Rachel R. Hardeman, Laura Huang, and Aaron Sojourner. "Physician–patient Racial Concordance and Disparities in Birthing Mortality for Newborns." Proceedings of the National Academy of Sciences 117, no. 35 (September 1, 2020): 21194–21200.
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
- May 18, 2020
- Other Article
Media Bias? But Not What You Think It Is
The media are often accused of political bias. But news outlets reflect many political beliefs in a fragmented media environment. However, an almost across-the-board bias is how news media talk about digital business, and the pandemic has exacerbated that bias, which... View Details
Cespedes, Frank V. "Media Bias? But Not What You Think It Is." Medium (May 18, 2020).
- 2022
- Working Paper
Hate Crime Increases with Minoritized Group Rank
People are on the move in unprecedented numbers within and between countries. How does demographic change affect local intergroup dynamics? In complement to accounts that emphasize stereotypical features of groups as determinants of their treatment, we propose the... View Details
- 2024
- Working Paper
Should I Stay or Should I Disclose? How Omission Bias Guides Our Disclosure Decisions
By: Elinora Pentcheva and Leslie John
- Article
Temporal View of the Costs and Benefits of Self-Deception
By: Zoe Chance, Michael I. Norton, Francesca Gino and Dan Ariely
Researchers have documented many cases in which individuals rationalize their regrettable actions. Four experiments examine situations in which people go beyond merely explaining away their misconduct to actively deceiving themselves. We find that those who exploit... View Details
Keywords: Hindsight Bias; Lying; Motivated Reasoning; Self-enhancement; Social Psychology; Perception; Performance Expectations
Chance, Zoe, Michael I. Norton, Francesca Gino, and Dan Ariely. "Temporal View of the Costs and Benefits of Self-Deception." Proceedings of the National Academy of Sciences 108, no. S3 (September 13, 2011): 15655–15659.
- 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; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
- December 2023
- Article
Brokerage Relationships and Analyst Forecasts: Evidence from the Protocol for Broker Recruiting
By: Braiden Coleman, Michael Drake, Joseph Pacelli and Brady Twedt
In this study, we offer novel evidence on how the nature of brokerage-client relationships can influence the quality of equity research. We exploit a unique setting provided by the Protocol for Broker Recruiting to examine whether relaxed broker non-compete agreement... View Details
Keywords: Brokers; Analysts; Forecasts; Bias; Protocol; Investment; Research; Forecasting and Prediction
Coleman, Braiden, Michael Drake, Joseph Pacelli, and Brady Twedt. "Brokerage Relationships and Analyst Forecasts: Evidence from the Protocol for Broker Recruiting." Review of Accounting Studies 28, no. 4 (December 2023): 2075–2103.