Publications
Publications
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- Faculty Publications (19)
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- 2024
- Chapter
Regulating Collective Emotions
By: Amit Goldenberg
When we think of emotion and emotion regulation, we typically think of them as processes occurring at the individual level. Even when emotions are experienced by multiple people who interact with each other, analysis is typically centered around individual-level... View Details
- December 2023 (Revised August 2024)
- Supplement
Microsoft Azure and the Cloud Wars (B)
By: Andy Wu and Matt Higgins
By 2023, the global market for cloud infrastructure had consolidated into a three-horse race. As of Q4 2022, Amazon, Microsoft, and Google collectively accounted for 66% of the global market. AWS had a market share of 33%, Microsoft Azure had 23%, and Google Cloud had... View Details
- November–December 2023
- Article
Network Centralization and Collective Adaptability to a Shifting Environment
By: Ethan S. Bernstein, Jesse C. Shore and Alice J. Jang
We study the connection between communication network structure and an organization’s collective adaptability to a shifting environment. Research has shown that network centralization—the degree to which communication flows disproportionately through one or more... View Details
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
- 2022
- Working Paper
Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15... View Details
- May 2021 (Revised February 2024)
- Teaching Note
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Ayelet Israeli and Jill Avery
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... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
- May 2021
- Article
Ideology and Composition Among an Online Crowd: 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
- 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... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
- October 2019
- Case
Feeling Machines: Emotion AI at Affectiva
By: Shane Greenstein and John Masko
In 2016, Affectiva—a Boston-based emotion AI software company with a long track record of building emotion-sensing software for market research—had attempted to expand into new verticals by releasing a mobile software development kit (SDK) that downloaders could adapt... View Details
- 2019
- Working Paper
Intelligent Design of Inclusive Growth Strategies
By: Robert S. Kaplan, George Serafeim and Eduardo Tugendhat
Improving corporate engagement with society, as advocated in the Business Roundtable’s 2019 statement, should not be viewed as a zero-sum proposition where attention to new stakeholders detracts from delivering shareholder value. Corporate programs for sustainable and... View Details
- 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
- 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
- Article
The Impact of the 'Open' Workspace on Human Collaboration
By: Ethan Bernstein and Stephen Turban
Organizations’ pursuit of increased workplace collaboration has led managers to transform traditional office spaces into “open,” transparency-enhancing architectures with fewer walls, doors, and other spatial boundaries, yet there is scant direct empirical research on... View Details
Keywords: Open Office; Transparency; Collaboration; Collective Intelligence; Workspace; Workspace Design; Architecture; Cubicles; Boundaries; Spatial Boundaries; Human Behavior; Propinquity; Co-location; Interaction; Sociometers; People Analytics; Buildings and Facilities; Communication; Design; Human Resources; Leadership; Management; Organizational Design; Organizational Structure; Networks; Social and Collaborative Networks; Information Technology; United States
- 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
- 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; AI and Machine Learning; Analytics and Data Science; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan
- 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; Fashion; Marketing; Marketing Strategy; Marketing Channels; Brands and Branding; Consumer Behavior; Demand and Consumers; Analytics and Data Science; Forecasting and Prediction; E-commerce; 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... View Details
- 2014
- Other Unpublished Work
Neutral Point of View and Collective Intelligence Bias: The Case of Wikipedia
By: Shane Greenstein
- September 2013 (Revised August 2015)
- Background Note
Leadership and Teaming
By: Ethan Bernstein
Small differences in the leadership of teams can have large consequences for the success of their efforts. Many initiatives fail not because of a fatal error in judgment or insufficient ideas, knowledge, motivation, or capabilities to deliver a solution. They fail... View Details
Keywords: Teams; Teaming; Leadership And Managing People; Leadership; Team Effectiveness; Team Performance; Team Design; Team Leadership; Teamwork; Team Process; Team Function; Team Launch; 60/30/10 Rule; Team Boundary; Distribution Of Leadership Authority; Self-Managed Teams; Virtual Teams; Unbounded Teams; Acts Of Leadership; Execution Teams; Decision Making Teams; Creativity Teams; Team Size; Task Design; Team Timeline; Team Roles; Team Representation; Diversity; Team Familiarity; Collective Intelligence; Team Stages Of Development; Team Coaching; Performance Pressure; X-Teams; Team Focus; Interaction; Management Teams; Managerial Roles; Management Systems; Management Style; Management Skills; Management Practices and Processes; Organizational Design; Organizational Structure; Performance Effectiveness; Performance Efficiency; Performance Productivity; Groups and Teams; Networks; Social Psychology; Behavior; Conflict and Resolution; Creativity; Social and Collaborative Networks; Satisfaction; Prejudice and Bias; Power and Influence; Personal Characteristics; Familiarity; Cognition and Thinking; Attitudes; Projects; Organizational Culture; Organizational Change and Adaptation; Leadership Development; Leadership Style; Leading Change; Knowledge Use and Leverage; Knowledge Sharing; Collaborative Innovation and Invention; Innovation and Management; Innovation Leadership; Design; Interpersonal Communication; Accommodations Industry; Accounting Industry; Advertising Industry; Aerospace Industry; Agriculture and Agribusiness Industry; Air Transportation Industry; Apparel and Accessories Industry; Auto Industry; Banking Industry; Battery Industry; Beauty and Cosmetics Industry; Bicycle Industry; Biotechnology Industry; Chemical Industry; Communications Industry; Computer Industry; Construction Industry; Consulting Industry; Consumer Products Industry; Distribution Industry; Education Industry; Electronics Industry; Employment Industry; Energy Industry; Entertainment and Recreation Industry; Fashion Industry; Financial Services Industry; Fine Arts Industry; Food and Beverage Industry; Forest Products Industry; Forestry Industry; Green Technology Industry; Health Industry; Industrial Products Industry; Information Industry; Information Technology Industry; Insurance Industry; Journalism and News Industry; Legal Services Industry; Manufacturing Industry; Media and Broadcasting Industry; Medical Devices and Supplies Industry; Mining Industry; Motion Pictures and Video Industry; Motorcycle Industry; Music Industry; Pharmaceutical Industry; Public Administration Industry; Public Relations Industry; Publishing Industry; Pulp and Paper Industry; Rail Industry; Real Estate Industry; Retail Industry; Rubber Industry; Semiconductor Industry; Service Industry; Shipping Industry; Sports Industry; Steel Industry; Technology Industry; Telecommunications Industry; Tourism Industry; Transportation Industry; Travel Industry; Utilities Industry; Video Game Industry; Web Services Industry; Asia; North and Central America; South America; Atlantic Ocean; Central Asia; Europe; Latin America; Middle East; Oceania; West Indies