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Jesse Bockstedt - Emory University, Goizueta Business School. Atlanta, GA, US

Jesse Bockstedt Jesse Bockstedt

Goizueta Foundation Term Associate Professor of Information Systems & Operations Management | Emory University, Goizueta Business School





Jesse Bockstedt completed his Ph.D. in Information Systems at the University of Minnesota's Carlson School of Management in 2008. Prior to joining the faculty at Emory in 2016, Bockstedt held positions at George Mason University and the University of Arizona. Bockstedt's primary research focus is behavioral economic issues in technology-mediated environments. His articles have been published in a number of leading journals including Production and Operations Management, MIS Quarterly, Information Systems Research, and Journal of MIS.

Areas of Expertise (10)

Behavioral Economics

Online Consumer Behavior

Electronic Commerce



IT Evolution


Online Privacy

Personalization Systems

Social Engineering

Education (3)

Carlson School of Management, University of Minnesota – Twin Cities: Ph.D., Information Systems 2008

University of Minnesota – Twin Cities: M.S., Mechanical Engineering 2004

University of Wisconsin - Madison: B.S., Mechanical Engineering 1999

Media Appearances (3)

CNN Newsroom | What to know re: New E.U. Privacy Law (GDPR)

CNN International  tv


Associate Professor, Information Systems Jesse Bockstedt explains New Internet Privacy Rules (GDPR).

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Apple Music Launch: Too Bad Steve Jobs Is Not Around

Forbes  online


"Does Apple Music’s song recommendations live up to this potential? The simple answer is no. I tested Apples Music’s recommendation engines with Jesse Bockstedt, a faculty member at University of Arizona who is a music aficionado and has done some very interesting research on recommendation engines. We both downloaded Apple Music and formed a preliminary impression on the quality of its recommendations..."

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How Virtual Recommendations Shape Your Music Preferences

Carlson School of Management  online


"Thanks to a growing number of streaming services like Apple Music, it’s now easier than ever for listeners to discover their new favorite song or artist among millions of choices.

Online platforms that suggest new music, movies, and products based on consumers’ established preferences are powered by recommender systems—dynamic algorithms that leverage users’ virtual behavior to suggest products or content that they have not yet purchased, experienced, or considered..."

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