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Maria Binz Scharf

Maria Binz Scharf

Maria Christina (MC) Binz-Scharf is associate professor of management in the Colin Powell School for Civic and Global Leadership at City College of the City University of New York (CUNY), where she teaches undergraduate and graduate courses in organizational behavior, social entrepreneurship, and information and technology management. Her research examines how individuals search for and share knowledge through networks in order to accomplish work. Funded by the National Science Foundation, the National Institutes of Health, and the US Department of Education, among others, her studies have been published in a wide variety of journals, including American Review of Public Administration, Cancer, and American Behavioral Scientist. Her research has also been featured in national and international press outlets such as The Wall Street Journal, Inc., Hispanic Outlook, Wiener Zeitung, and Tribun Jogja (Indonesia). Currently, she is writing a book on the future of work in the networked economy. Beyond her scholarly pursuits, MC is active as a social justice advocate for gender equality and the advancement of underserved populations in the workplace. Before joining the faculty at City College in 2004, MC was a postdoctoral fellow at the Harvard Kennedy School. Prior to her postdoc at Harvard, she cofounded and managed the Center of Excellence for Electronic Government at the University of St. Gallen, Switzerland, and worked at the European Commission in Brussels, Belgium. MC holds a Ph.D. in business economics from the University of St. Gallen and a B.A. from Bocconi University in Milan, Italy. When she’s not observing people at work or advocating for the underserved, MC enjoys skiing, yoga, spending time with her husband and kids, learning about art, and exploring the world.


As an organization scientist, I am interested in how knowledge workers create, use, and maintain their social networks to get their jobs done. I was trained as an ethnographer, and I observe people at work for a living. What, one might ask, does this small-data girl have to say about Big Data?

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