Research & Publications

Sharmistha Sikdar’s research focuses on developing statistical and machine-learning methods to solve empirical problems in marketing. Some of the applications of her research methods include predicting customers' multichannel engagement and purchase behavior, and competitive price dynamics on e-commerce platforms.

Research Interests

Multivariate Modeling Problems, Ecommerce, Customer Relationship Management, Customer Analytics, Multichannel Marketing, Statistical Modeling, Machine Learning, Markov Models, Bayesian Methods

Manuscripts Under Review or Revision 

Sikdar Sharmistha, Vrinda Kadiyali and Giles Hooker, “Price Dynamics on Amazon Marketplace: A Machine Learning Approach”

Sikdar Sharmistha and Giles Hooker, “A Hidden Semi-Markov Model of Multi-channel Customer Engagement Dynamics”

Research in Progress 

Sikdar, Sharmistha, Giles Hooker and Vrinda Kadiyali, “Variable Importance Measures for Variable Selection and Statistical Inference in Multivariate Random Forests”