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Skip to Main Content Contemporary Art Contemporary Art Schwartz Art Collection C. Ludens Ringnes Sculpture Collection Additional Outdoor Sculpture...
- 2021
- Article
Large-Scale Field Experiment Shows Null Effects of Team Demographic Diversity on Outsiders' Willingness to Support the Team
By: Edward H. Chang, Erika L. Kirgios and Rosanna K. Smith
Demographic diversity in the United States is rising, and increasingly, work is conducted in teams. These co-occurring phenomena suggest that it might be increasingly common for work to be conducted by demographically diverse teams. But to date, in spite of copious...
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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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- Article
Variety of Innovation in Global Value Chains
By: Giulio Buciuni and Gary P. Pisano
This article analyzes how the geography and organization of pre- and production stages in Global Value Chains (GVC) contribute to lead firms' innovation development. A novel approach in GVC studies is introduced based on transaction cost economics (TCE) and the...
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- February 2021
- Article
Platform Diffusion at Temporary Gatherings: Social Coordination and Ecosystem Emergence
By: Tommy Pan Fang, Andy Wu and David R. Clough
Software platforms create value by cultivating an ecosystem of complementary products and services. Existing explanations for how a prospective complementor chooses platforms to join assume the complementor has rich information about the range of available platforms....
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Keywords:
Innovation Ecosystems;
Technology Diffusion;
Hackathon;
Contagion;
Software Applications;
Software Development;
Software Engineering;
Technology Strategy;
Technology Adoption;
Technological Innovation;
Technology Platform;
Technology Networks;
Innovation Strategy;
Multi-Sided Platforms;
Network Effects;
Software;
Information Technology;
Technology Industry;
Computer Industry;
Information Technology Industry;
Video Game Industry
- January 2021
- Case
iOpenEye: Theater and #MeToo in Nigeria
By: Caroline M. Elkins, Tarun Khanna and Joyce J. Kim
In 2014, Ifeoma Fafunwa, an award-winning playwright and director, founded iOpenEye, a commercial production company dedicated to driving social change through performance art. iOpenEye’s flagship theatrical production was called “Hear Word! Naija Woman Talk True,”...
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- January 2021
- Supplement
Barbara Krakow Gallery (B): Art and the Pandemic
By: José B. Alvarez and David Lane
Updates (A) case by describing the early impact of the COVID-19 pandemic on the art market, the renaming of the gallery as the Krakow Witkin Gallery, and the response of its partners and staff to the pandemic.
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- January 2021 (Revised March 2021)
- Case
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...
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Keywords:
Data;
Data Analytics;
Artificial Intelligence;
Ai;
Ai Algorithms;
Ai Creativity;
Fashion;
Retail;
Retail Analytics;
Digital Marketing;
E-commerce;
E-commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Preference Prediction;
Predictive Analytics;
App Development;
＂marketing Analytics＂;
Advertising;
Mobile App;
Mobile Marketing;
Apparel;
Referral Rewards;
Referrals;
Female Ceo;
Female Entrepreneur;
Female Protagonist;
Data and Data Sets;
Analysis;
Creativity;
Marketing Strategy;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Forecasting and Prediction;
Marketing Channels;
Online Advertising;
Online Technology;
Mobile Technology;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- January 2021
- Technical Note
Tales of Life-changing Innovations: Early Detection, Precise Diagnoses | Note on the Development of Coronary Bypass Arterial Grafting (CABG) (through 2000)
By: Amar Bhidé, Srikant M. Datar and Fabio Villa
- January 2021
- Article
Commuting and Innovation: Are Closer Inventors More Productive?
By: Hongyu Xiao, Andy Wu and Jaeho Kim
We estimate the causal effect of workplace–home commuting distance on inventor productivity. We construct a novel panel of U.S. inventors with precisely measured workplace–home distances and inventor-level productivity. Our identification strategy exploits firm office...
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- Article
Incorporating the Arts to Create Technical Leaders of the Future
By: Linda A. Hill
Engineering education should be reimagined to create a new generation of technical leaders prepared to dream, invent, and steward the future. These leaders of tomorrow will need to bridge business, engineering, and the arts.
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- December 2020
- Supplement
Additional Supplement to Artea Teaching Note
By: Eva Ascarza and Ayelet Israeli
- Article
Corporate Headquarters in the Twenty-first Century: An Organization Design Perspective
By: Sven Kunisch, Markus Menz and David J. Collis
The corporate headquarters (CHQ) of the multi-business enterprise, which emerged as the dominant organizational form for the conduct of business in the twentieth century, has attracted considerable scholarly attention. As the business environment undergoes a...
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- Article
GitLab: Work Where You Want, When You Want
By: Prithwiraj Choudhury, Kevin Crowston, Linus Dahlander, Marco S. Minervini and Sumita Raghuram
GitLab is a software company that works “all remote” at the scale of more than 1,000 employees located in more than 60 countries. GitLab has no physical office and its employees can work from anywhere they choose. Any step of the organizational life of a GitLab...
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- Fall 2020
- Article
Christo and Jeanne‐Claude: The Negotiation of Art and Vice Versa
Over the past two decades the Program on Negotiation at Harvard Law School (PON) has named thirteen people as Great Negotiators. The project, directed by my colleague Jim Sebenius, has given us the opportunity to commend our honorees’ outstanding work and to learn from...
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- September 2020 (Revised March 2021)
- 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...
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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;
E-commerce Strategy;
Discrimination;
Targeted Advertising;
Targeted Policies;
Targeting;
Pricing Algorithms;
A/b Testing;
Ethical Decision Making;
Customer Base Analysis;
Customer Heterogeneity;
Coupons;
Marketing;
Race;
Gender;
Diversity;
Customer Relationship Management;
Marketing Communications;
Advertising;
Decision Making;
Ethics;
Retail Industry;
Apparel and Accessories Industry;
United States
- September 2020
- Supplement
Spreadsheet Supplement to "Artea: Designing Targeting Strategies"
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to "Artea: Designing Targeting Strategies" (521-021).
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- September 2020
- 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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- September 2020
- 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...
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- September 2020 (Revised March 2021)
- 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