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Beibei Li, Ph.D.

Affiliations: 
2012 Information, Operations, and Management Sciences New York University, Graduate School of Business Administration 
Area:
Marketing Business Administration, Commerce-Business Economics, Computer Science, Multimedia Communications
Google:
"Beibei Li"
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Parents

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Anindya Ghose grad student 2012 New York University, Graduate School of Business Administration
 (Analyzing Consumer Behavior on Product Search Engines: Interplay between Search and Social Media.)

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Publications

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Ghose A, Li B, Liu S. (2019) Mobile Targeting Using Customer Trajectory Patterns Management Science. 65: 5027-5049
Ghose A, Ipeirotis PG, Li B. (2019) Modeling Consumer Footprints on Search Engines: An Interplay with Social Media Management Science. 65: 1363-1385
Zhang Y, Li B, Luo X, et al. (2019) Personalized Mobile Targeting with User Engagement Stages: Combining a Structural Hidden Markov Model and Field Experiment Information Systems Research. 30: 787-804
Gong J, Abhishek V, Li B. (2018) Examining The Impact Of Keyword Ambiguity On Search Advertising Performance: A Topic Model Approach Management Information Systems Quarterly. 42: 805-829
Wang Q, Li B, Singh PV. (2018) Copycats vs. Original Mobile Apps: A Machine Learning Copycat-Detection Method and Empirical Analysis Information Systems Research. 29: 273-291
Zhang Y, Li B, Hong J. (2017) Using Online Geotagged and Crowdsourced Data to Understand Human Offline Behavior in the City: An Economic Perspective Acm Transactions On Intelligent Systems and Technology. 9: 32
Zhang Y, Qian Z(, Sprei F, et al. (2016) The impact of car specifications, prices and incentives for battery electric vehicles in Norway: Choices of heterogeneous consumers Transportation Research Part C: Emerging Technologies. 69: 386-401
Ghose A, Ipeirotis PG, Li B. (2014) Examining the impact of ranking on consumer behavior and search engine revenue Management Science. 60: 1632-1654
Ghose A, Ipeirotis PG, Li B. (2012) Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content Marketing Science. 31: 493-520
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