Liangbin is a doctoral candidate in marketing at the Wharton School of the University of Pennsylvania.
Liangbin’ research interests fall in two domains: 1) group decisions and social influence, and 2) online and digital marketing. In the area of group decisions and social influence, she is interested in understanding how individuals form or join groups, how group members interact with and influence each other, and how group members make both individual and joint decisions, aiming to improve marketers’ ability to infer individuals’ preferences and customize their marketing strategies accordingly (e.g., targeted advertising). Her dissertation focuses on inferring heterogeneous individual preferences and examining various types of intergroup and intragroup dynamics when consumption information is partially observed. She develops novel joint consumption models which capture the effects of intergroup and intragroup interaction in a theoretically meaningful way, designs innovative computation algorithms which overcome estimation challenges, and incorporates several behavioral factors into the models. In the area of online and digital marketing, she focuses on theories and explanations for variation in the performance of online/digital marketing campaigns, aiming to help marketers allocate resources more efficiently within and across channels/platforms and design optimal targeted advertising and promotion strategies, in which she explicitly takes behavioral factors (e.g., social influence, reference dependence, loss aversion, variety-seeking, inertial etc.) into account. Her preferred methodologies include Bayesian methods, applied econometrics, behavioral and experimental economics, and machine learning.
