Advanced methods in personalization for marketing decisions

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Authors: Hong Deng
Cited by: 0

Abstract

Collectively, these three chapters provide marketers and researchers with powerful tools to address personalization challenges commonly encountered in real-time applications, especially when serving a continuous stream of customers on websites, platforms, or mobile devices. The research advances marketing methodology by integrating innovative approaches from machine learning and econometrics to tackle important and practical challenges in marketing. The proposed methods are interpretable, computationally efficient, and can be directly applied to realtime personalization applications. Overall, these contributions not only broaden methodological perspectives in personalization research but also offer actionable solutions for practitioners aiming to implement scalable and effective personalization strategies in today’s competitive and rapidly evolving digital marketplace.

Fields of Study & Subjects

Digital Marketing and Social Media Recommender Systems and Techniques Consumer Market Behavior and Pricing

Publication details

Journal / source
EUR Research Repository (Erasmus University Rotterdam)
Publication date
27 February 2026
Language
EN
Document type
Thesis