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Publications

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  • All HBS Web  (1,257)
    • Faculty Publications  (9)

    Show Results For

    • All HBS Web  (1,257)
      • Faculty Publications  (9)

      Collective Intelligence Remove Collective Intelligence →

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      Do Experts or Collective Intelligence Write with More Bias?
      Do Experts or Collective Intelligence Write with More Bias? Evidence from Encyclopædia Britannica and Wikipedia
      → Search All HBS Web
      • 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...  View Details
      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
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      Bernstein, Ethan, Jesse Shore, and David Lazer. "How Intermittent Breaks in Interaction Improve Collective Intelligence." Proceedings of the National Academy of Sciences 115, no. 35 (August 28, 2018).
      • 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...  View Details
      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
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      Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Teaching Note 518-053, November 2017.
      • 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...  View Details
      Keywords: Big Data; Artificial Intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan
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      Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017. (Revised July 2019.)
      • 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
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      Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
      • 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...  View Details
      Keywords: Open Source Distribution; Performance Productivity; Software
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      Nagle, Frank. "Crowdsourced Digital Goods and Firm Productivity: Evidence from Open Source Software." Harvard Business School Working Paper, No. 15-062, January 2015. (Revised June 2015.)
      • 2014
      • Other Unpublished Work

      Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia

      By: Shane Greenstein
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      Greenstein, Shane. "Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia." 2014.
      • October 14, 2013
      • Article

      Intelligent Redesign of Health Care

      By: Robert S. Kaplan, Thomas W. Feeley, Mary L. Witkowski and Heidi Albright
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      Kaplan, Robert S., Thomas W. Feeley, Mary L. Witkowski, and Heidi Albright. "Intelligent Redesign of Health Care." Leading Health Care Innovation (blog) (October 14, 2013). (New England Journal of Medicine & Harvard Business Review Online Forum.)
      • 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...  View Details
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      Greenstein, Shane, Grace Gu, and Feng Zhu. "Ideological Segregation Among Online Collaborators: Evidence from Wikipedians." Management Science (forthcoming).
      • 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...  View Details
      Keywords: Online Community; Collective Intelligence; Ideology; Bias; Wikipedia; Knowledge Sharing; Perspective; Government and Politics
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      Greenstein, Shane, Grace Gu, and Feng Zhu. "Ideological Segregation Among Online Collaborators: Evidence From Wikipedians." Management Science (forthcoming).
      • 1

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      Do Experts or Collective Intelligence Write with More Bias?
      Do Experts or Collective Intelligence Write with More Bias? Evidence from Encyclopædia Britannica and Wikipedia
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