Publications
Publications
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- Faculty Publications (9)
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- August 28, 2018
- Article
How Intermittent Breaks in Interaction Improve Collective Intelligence
By: Ethan Bernstein, Jesse Shore and David Lazer
People influence each other when they interact to solve problems. Such social influence introduces both benefits (higher average solution quality due to exploitation of existing answers through social learning) and costs (lower maximum solution quality due to a...
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Keywords:
Transparency;
Social Influence;
Collective Intelligence;
Interaction;
Problem Solving;
Collaboration;
Intermittant;
Breaks;
Always On;
Communication Technologies;
Communication;
Design;
Information;
Management;
Leadership;
Organizational Design;
Organizational Structure;
Performance;
Social and Collaborative Networks;
Information Technology
- November 2017
- Teaching Note
Predicting Consumer Tastes with Big Data at Gap
By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big...
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Keywords:
Brands;
Brand ＆ Product Management;
Big Data;
＂marketing Analytics＂;
Consumer Behavior;
Predictive Analytics;
Forecasting;
Preferences;
Operation Management;
Distribution Channels;
Marketing;
Marketing Channels;
Marketing Strategy;
Brands and Branding;
Forecasting and Prediction;
Data and Data Sets;
Retail Industry;
Fashion Industry;
Apparel and Accessories Industry;
United States;
North America
- August 2017 (Revised July 2019)
- Case
GROW: Using Artificial Intelligence to Screen Human Intelligence
By: Ethan Bernstein, Paul McKinnon and Paul Yarabe
Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro...
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- May 2017 (Revised March 2018)
- Case
Predicting Consumer Tastes with Big Data at Gap
By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big...
View Details
Keywords:
Retailing;
Preference Elicitation;
Big Data;
Predictive Analytics;
Artificial Intelligence;
E-commerce;
Fashion;
Marketing;
Marketing Strategy;
Marketing Channels;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Data and Data Sets;
Forecasting and Prediction;
Apparel and Accessories Industry;
Consumer Products Industry;
Fashion Industry;
Retail Industry;
United States;
Canada;
North America
- 2015
- Working Paper
Crowdsourced Digital Goods and Firm Productivity: Evidence from Open Source Software
By: Frank Nagle
As firms increasingly rely on crowdsourced digital goods, understanding their impact on productivity becomes critical. This study measures the firm-level productivity impact of one such good, non-pecuniary (free) open source software (OSS). The results show a...
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- 2014
- Other Unpublished Work
Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia
By: Shane Greenstein
- October 14, 2013
- Article
Intelligent Redesign of Health Care
By: Robert S. Kaplan, Thomas W. Feeley, Mary L. Witkowski and Heidi Albright
- Forthcoming
- Article
Ideological Segregation Among Online Collaborators: Evidence from Wikipedians
By: Shane Greenstein, Grace Gu and Feng Zhu
Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that...
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- Forthcoming
- Article
Ideological Segregation Among Online Collaborators: Evidence From Wikipedians
By: Shane Greenstein, Grace Gu and Feng Zhu
Online communities bring together participants from diverse backgrounds and often face challenges in aggregating their opinions. We infer lessons from the experience of individual contributors to Wikipedia articles about U.S. politics. We identify two factors that...
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