Two Awarded for Statistics in Marketing
by Charles Hofacker
Min Kim and Omid Rafieian have won research awards from the Statistics in Marketing Section of the American Statistical Association
Author: Kinshuk Jerath
The Statistics in Marketing Section of the American Statistical Association is pleased to announce the winners of the 2020 Annual Doctoral Research Award. The winners are:
- Min Kim from The University of Maryland, College Park for his research titled “Discovering Online Shopping Preference Structures in Large and Frequently Changing Assortments.” This work develops a scalable stock-keeping-unit-level modeling framework of discovering consumers’ preference structures in large and frequently-changing assortments at the store/marketplace level. The model identifies the underlying “topics of interest” that drive online browsing/purchase activities concerning the entire store assortment. Based on the inferred individuals’ preference structures, the paper proposes a personalized product recommendation system.
- Omid Rafieian from the University of Washington, Seattle, for his research on the topic of “Adaptive Ad Sequencing.” This work focuses on the sequential adaptive delivery of advertisements in a digital environment. The proposed framework determines how a publisher can personalize a sequence of ads for a user to maximize engagement, as well as how it can monetize these sequences through auctions to optimize revenues.
The award recognizes and supports outstanding statistics-based research applied to marketing problems. It includes a grant of USD 1,000. The proposals were reviewed by academic and industry experts at ASA.
The candidates considered for the award were those who submitted entries for the 2019 Marketing Science Institute Alden G. Clayton Dissertation Proposal Competition. ASA thanks MSI for the partnership and assistance.
On behalf of the Statistics in Marketing Section of the American Statistical Association,
Kinshuk Jerath (Award Committee Chair) and Lan Luo (Section Chair).