She is especially interested in questions related to market structure, firm strategies, and consumer behavior in digital markets. Her research combines economic modeling and data analytics to understand the online economy.
Sagit earned her PhD and MA in economics, and BSc in mathematics from Tel Aviv University. She joined the Coller School of Management in October 2017 as an assistant professor of Technology Management and Information Systems.
Sagit also conducts postdoctoral research at MIT’s Sloan School of Management and the MIT Initiative on the Digital Economy, where she remains a digital fellow.
Matt studies deviance in work involving machine intelligence, specifically robotics, and seeks answers to questions such as “How do workers, organizations, and AI engage in deviance, and what happens when they do?” He has also performed extensive field research on robotic surgery, robotic materials transport, and robotic telepresence in healthcare, elder care, and knowledge work.
Matt’s research on robotic surgery was published in 2018 at Administrative Science Quarterly and his work on robotic telepresence was published in 2014 in Organization Science. He was selected in 2012 as a Human Robot Interaction Pioneer, and is a regular contributor to popular outlets such as Wired, MIT’s Technology Review, TechCrunch, Forbes, and Robohub.
Matt received his Ph.D. from the Sloan School of Management at the Massachusetts Institute of Technology in the Information Technologies department. He also took a two-year hiatus from his doctoral studies to help found and fund Humatics, an MIT-connected, full-stack IoT startup.
Seth is an assistant professor of Management Science at the Argyros School of Business and Economics at Chapman University. He holds a Ph.D. in Economics. Before coming to Chapman University, Seth was a postdoctoral associate at the MIT Initiative on the Digital Economy. Seth received his Ph.D. in economics from Boston University in 2016. His dissertation advisor was Laurence Kotlikoff. He received a B.A. in economics and a B.S. in physics and mathematics from Tulane University in 2012.
Seth’s current projects with other Stanford Digital Economy Lab researchers focus on measuring skill biased technical change, taxation, and regulation of digital platforms, as well as the measurement of network effects and the macroeconomic implications of progress in artificial intelligence.
Seth has presented his research at the US Capitol and as an expert for a US international public diplomacy mission. His work has been published in AEJ: Applied Economics, PNAS, Sloan Management Review and other peer-reviewed and non-peer reviewed outlets.
He is an Assistant Professor in the Department of Information, Risk and Operations Management at the McCombs School of Business at The University of Texas at Austin. He is also a digital fellow at the MIT Initiative on the Digital Economy and the Stanford Digital Economy Lab.
Avinash holds a PhD in management science from the Sloan School of Management at Massachusetts Institute of Technology.
His research builds broadly on advances in the fields of labor economics, sociology, computational social science, network science, data science, political science, and complex systems.
Morgan is assistant professor in the Department of Informatics and Networked Systems and the Department of Information Culture and Data Stewardship in the School of Computing and Information at the University of Pittsburgh.
He is also an MIT Connection Science Fellow and digital fellow at the Stanford Institute for Human-Centered Artificial Intelligence. Morgan also serves as researcher at the Massachusetts General Hospital Center for Genomic Medicine and a research affiliate at the Institute for Cyber Law, Policy, and Security at the University of Pittsburgh.
Renée is an expert on the intersection between behavioral science and technology, and the implications for cognitive bias in human decision-making. She is a leading thinker on the science of digital brand strategy and her research and expertise have been published in various academic and trade publications.
Renée’s research examines how social structure and technology (e.g., Digital Customer Experience, Status, Social Media) affect performance and self-perception (as featured in her TEDx talk, “The Outsourced Mind”). Her projects have examined how cognitive style predicts preference for AI versus human input; the interaction of brand status and placebo effects in performance; how consumers determine real from fake products; the circumstances under which customers perceive value in platforms; and the effects of storytelling in social media on trust and persuasion.
Renée is a 2020 honoree on the Thinkers50 Radar List of thinkers who are “putting a dent in the universe,” and has been named one of the World’s Top 40 Professors under 40 by Poets and Quants.
Shan’s research focuses on the digital economy, social networks, and business analytics. Her current work investigates how new social media shapes the information environment and decision making that leads to non-negligible economic and social impacts. Specifically, her studies examine how social advertising and social referral affect product virality, how emotions shape online content diffusion, and how misinformation diffuses through weak ties in massive social networks.
Shan has a particular interest in understanding how certain phenomena vary across individuals, social ties, products, and markets, using population-scale datasets and large-scale field tests, and uses various research methodologies, including large-scale networked randomized field experiments, machine learning, and network analysis to pursue her research agenda.
Shan’s research has been published in prominent management journals, including Marketing Science and the Journal of Management Information Systems. She also collaborates with leading tech firms, such as Tencent, to understand cutting-edge digital phenomena and their implications for business and society.
She received a bachelor’s degree from Tsinghua University, a master’s degree from the University of British Columbia, and a Ph.D. from the MIT Sloan School of Management.
Xiang is deeply interested in understanding how efficiency and quality provision on such platforms could be enhanced through information design and platform strategies. He also examines the welfare impact of information technology and artificial intelligence in different fields.
Before joining WashU, Xiang was a postdoctoral associate at MIT Sloan Initiative on the Digital Economy. He received a Ph.D. in economics from Ohio State University.
Wang Jin is currently a research associate at the MIT Initiative on the Digital Economy and MIT Sloan School of Management. He was a former research fellow at IQSS Harvard University. Combining large-scale data from the Environmental Protection Agency and the Census,
Wang’s research concentrates on the impacts of information technology, structural management practices, and organizational structures on environmental performance and sustainability. He is also interested in identifying the effects of IT, management, and big data analytics on firms’ innovation capabilities.
Wang is currently involved in multiple Census projects, and has worked extensively within the U.S. Census Research Data Center, using business level confidential data protected under Title 13 and Title 26. He is also performing research on topics related to regulatory enforcement and firm compliance behavior.
Wang holds a Master’s degree in economics and recently received his PhD in economics from Clark University.
Her research is empirically oriented, covering topics in market designs, digital platforms, and economics of digitization.