Shin Oblander

Shin Oblander is an Assistant Professor at The University of British Columbia, Sauder School of Business, within the Marketing and Behavioural Science Division. His research interests include causal inference, representation learning, probabilistic machine learning, customer relationship management, bounded rationality, and e-commerce. Oblander has contributed to several forthcoming and published works in top-tier journals such as Marketing Science, International Journal of Research in Marketing, and Psychological Science. His work explores topics like the impact of promised delivery times on online purchasing, probabilistic modeling of consumer choices, and the long-term effects of major events on consumption patterns. He also teaches Marketing Analysis at the undergraduate level.

Shin Oblander is an Assistant Professor at the University of British Columbia, specializing in Marketing, econometrics, and statistics. Their research explores the intersection of these fields to understand consumer behavior, market dynamics, and the impact of major events on consumption patterns. Oblander's work includes analyzing the long-term effects of events like the COVID-19 pandemic, customer management strategies, and the application of machine learning for behavioral analysis. They also investigate causal inference methods and data fusion techniques to enhance consumer decision-making insights. Their research emphasizes scalable solutions for analyzing complex competitive decisions and the nonlinear effects of factors like delivery time on purchasing behavior.