You can contact Zhen Tang at email@example.com.
Zhen Tang, who also goes by Richard, is from Huaiyuan, a beautiful one-million-population small town in eastern China. Though Richard wanted to be a software engineer when he was in high school, he graduated from East China University of Science and Technology with B.A. and M.S. in Business Administration. He then earned his Ph.D. in Marketing from the University of Arizona. He is interested in two research topics: one is about how to design an organization’s structure to make the employees be both productive and happy; the other one is about how to adapt an organization’s structure to realize the full potential of technological innovations like business analytics. Richard’s teaching interests include business analytics, marketing strategy, and introduction to marketing. In his life, Richard enjoys many sports, talking with people, and cooking.
University of Arizona: Ph.D., Marketing 2019
East China University of Science and Technology: M.S., Marketing 2013
East China University of Science and Technology: B.A., Marketing 2010
Areas of Expertise (6)
Vincent Chen, MSBA ’20 and Kayla Tanli, MSBA ’20, advised by Richard Tang, conducted a training workshop at the IM Data Annual Conference about building a SEIR model for predicting COVID-19 for the Computational Challenge launched by the City of Los Angeles and RMDS and they illustrated the model’s impressive predictive power.
Event Appearances (2)
"How Data Analytics Can Be Misleading: Context, Method, and Validity"
IM Data Annual Conference Virtual Workshop
Application of Natural Language Processing (NLP) in business analytics
Commentary—Lessons from Nature: Enhancing the Adaptable Potential of Service EcosystemsService Science
Organisms and species have evolved through adaptation and extinction for over a billion years. Service science can learn from this large library of success and failure because species interact and struggle for survival in biological ecosystems in many of the same way as organizations and other actors behaves in service ecosystems. The authors draw upon their collective knowledge of biological ecosystems, biological evolution, business, and service science to develop an integrated framework, including rules of adaptability, adaptability practices, and guidelines for creating adaptable systems. Collectively, these key lessons from the biological world can be used to help organizations be a vital part of service ecosystems adaptability and can be the catalyst for the emergence of innovation.