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Jesse Bockstedt

Goizueta Foundation Term Professor of Information Systems & Operations Management

Atlanta, GA, UNITED STATES

404-727-6628 bockstedt@emory.edu

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Biography

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

Behavioral EconomicsOnline Consumer BehaviorElectronic CommerceCrowdsourcingCybersecurityIT EvolutionMicroeconomicsOnline PrivacyPersonalization SystemsSocial Engineering

Education

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

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

CNN International  tv

2018-05-26

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

2015-06-30

"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

2015-11-12

"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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