Yanni Ping

Assistant Professor
PhD, Decision Sciences, Lebow College of Business, Drexel UniversityMS, Industrial Engineering, Georgia Institute of TechnologyBS, Material Science and Engineering, Shanghai Jiao Tong University
Yanni Ping is an Assistant Professor in the Business Analytics and Information System Department at St. Johns's University. She holds a Ph.D. in Decision Sciences from Lebow College of Business at Drexel University and has a M.S. in Industrial Engineering from Georgia Institute of Technology. Her main area of research is predictive analytics for E-commerce marketing. Her recent research explores the economic and social impact of consumer reviews. She also investigates the application of novel marketing strategies on eCommerce platforms both empirically and theoretically. Dr. Ping teaches Business Statistics, prescriptive analytics to both undergraduate and MBA students at Tobin College of Business.

Teaching Interests

Business Statistics, Prescriptive Analytics, Data Science and Machine Learning

Research Interests

Predictive Analytics, Machine Learning, Social Media Marketing, Operations Management with Marketing Interface

Courses Taught

BUA
631
PRESCP ANALYTC & SPRDSHT MODEL
BUA
2333
MODERN STATISTICS I
BUA
2334
MODERN STATISTICS II
BUA
3346
OPTIMIZTN FOR BUS DECISION MKG

Select Publications

Journal Articles

Ping, Y., and Kim, S. In-House vs Outsourcing: the Effect of Volume-Based Learning on Quality Competition (forthcoming). International Journal of Operational Research.

Ping, Y., Shen, W., and Lev, B. (2019). Using Buyback Contract to Coordinate the Supply Chain with Group Buying. International Journal of Operations and Quantitative Management. vol. 25, pp. 135-151.

Chao, C., Ping, Y., and Wang, Y. (2019). The Advertising Effectiveness: Fighting Between ECommence and Traditional Retailers--An Empirical Study. Journal of Marketing Management, aripd.org. vol. 7, pp. 76-82.

Chao, C., Ping, Y., and Wang, Y. (2019). The Advertising Spending Trends: Mobile VS Traditional Media-- An Empirical Study. Management and Organizational Studies. vol. 6, pp. 1-8.

Ping, Y., Kim, S., and Wang, M. (2018). A Supplier Selection Model with Quality-Driven Demand and Capacitated Suppliers. International Journal of Operations and Quantitative Management. vol. 24, pp. 1-22.

Keywords:
  • Business/Predictive Analytics
  • Machine Learning
  • Operations and Supply Chain