Unraveling Multifaceted User Preferences on Digital Platforms: A Bayesian Deep-Learning Approach
This paper proposes a Bayesian deep-learning model that captures multifaceted, time-varying user activities on digital platforms, yielding interpretable and dynamic preference estimations at the platform and individual levels.
Authors
- Ziwei Cong (ORCID: https://orcid.org/0000-0001-5196-7527)
- Mingzhang Yin (ORCID: https://orcid.org/0000-0002-5216-2437)
- Jia Liu (ORCID: https://orcid.org/0000-0001-7895-4339)
Institutions
- Georgetown University (US)
- Hong Kong University of Science and Technology (HK)
- University of Florida (US)
- University of Hong Kong (HK)
Publication Details
- Journal
- Marketing Science
- Published
- 2026-04-21
- DOI
- https://doi.org/10.1287/mksc.2024.1090
- Primary Topic
- Persona Design and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00