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- All HBS Web (427)
- Faculty Publications (21)
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- 08 Oct 2013
- First Look
First Look: October 8
fundamental business model has not changed in more than 100 years: very smart outsiders go into organizations for a finite period of time and recommend solutions for the most difficult problems confronting their clients. But at...
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Sean Silverthorne
- 14 Jun 2022
- Cold Call Podcast
What Does It Take to Close the Opportunity Gap in America’s Labor Market?
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Re: V. Kasturi Rangan
- 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...
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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.)
- 28 Sep 2009
- Research & Ideas
Improving Accountability at the World Bank
accountability and effectiveness today? What should it do about them? With a detailed description of the Bank's challenges of democratic accountability, its constraints, and recommendations for the future, HBS professor Alnoor Ebrahim...
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by Alnoor Ebrahim
- 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 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...
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- 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...
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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 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...
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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...
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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;
Retail Industry;
Apparel and Accessories Industry;
Technology Industry;
United States
- 07 Nov 2023
- Research & Ideas
When Glasses Land the Gig: Employers Still Choose Workers Who 'Look the Part'
decisions. Troncoso adds that platforms must carefully design their recommendation systems, as practices like suggesting multiple freelancers for a particular job could further strengthen the use of pictures as tiebreakers. There are also...
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by Scott Van Voorhis
- 27 Feb 2024
- Research & Ideas
Why Companies Should Share Their DEI Data (Even When It’s Unflattering)
diversity data—even if it shows a disparity in the representation of employees of color—doesn’t hurt consumer attitudes toward a company. And, when the numbers show that a company’s workforce is relatively diverse, consumers feel even...
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by Shalene Gupta
- 30 Sep 2019
- Book
6 Steps to Building a Better Workplace for Black Employees
workers and offers advice to black employees who seek to advance in their careers. It also provides these recommendations for companies that are intent on building diverse workplaces: 1. Encourage employees...
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by Dina Gerdeman
- 11 Apr 2023
- Op-Ed
The First 90 Hours: What New CEOs Should—and Shouldn't—Do to Set the Right Tone
and the way unexpected crises can emerge rapidly, leaders must move faster and display more strategic agility than ever before. Much of Watkins’ advice about how company officials should assume a leadership post still holds true. It’s just that his View Details
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by John Quelch
- 13 Apr 2010
- First Look
First Look: April 13
by deviating frequently and in predictable ways from the recommendations offered by a centralized capacity planning model. Finally, we document that these discretionary capacity supply decisions exhibit a strong learning effect whereby...
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Martha Lagace
- 05 Jun 2007
- First Look
First Look: June 5, 2007
care. Challenges and hurdles to implementation are described for both the health plan and the IPU. Provides detailed data to allow students to evaluate success, identify current challenges, and recommend improvements to the integrated...
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Martha Lagace
- 04 Sep 2001
- Research & Ideas
Governing the Family-Run Business
communication and decision making within and across the family, the business, and the ownership groups. Figure 1: The "3-circle" model of family business Without belaboring an oft-made point about family business, reconciling these View Details
- 11 Apr 2022
- Research & Ideas
A World of Difference: What Keeps Companies from Becoming More Inclusive
to be more inclusive. "Inclusion always begets difference, but diversity may or may not beget inclusion." One of the reasons there hasn’t been as much progress on DEI as you would expect is that the sequencing of the words—diversity,...
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by Jen McFarland Flint
- 25 Jun 2012
- Research & Ideas
Collaborating Across Cultures
metacognition," Chua says. "The fact they have to deal with people from different cultures more causes them to question their own assumptions more." For those who don't have a culturally diverse network already, he View Details
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by Michael Blanding
- 09 Apr 2019
- First Look
New Research and Ideas, April 9, 2019
increasing inclusion in the workplace and gender diversity and reducing environmental damage and progress towards tackling climate change. The early results from his efforts were promising, but was there more he could do? Purchase this...
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Dina Gerdeman
- 07 Feb 2022
- Research & Ideas
Digital Transformation: A New Roadmap for Success
participants say that employees will likely reject data instead of incorporating it into the daily practices in their organizations. It’s also imperative to have team members represent diversity of thought, and some participants argued...
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