Unraveling Multifaceted User Preferences on Digital Platforms: A Bayesian Deep-Learning Approach

Mingzhang Yin
Mingzhang Yin
[email protected]
https://orcid.org/0000-0002-5216-2437
Department of Marketing, University of Florida, Gainesville, Florida 32611
Search for more papers by this author
,
Ziwei Cong
Corresponding Author
Ziwei Cong
[email protected]
https://orcid.org/0000-0001-5196-7527
Department of Marketing, Georgetown University, Washington, District of Columbia 20057
Search for more papers by this author
,
Jia Liu
Jia Liu
[email protected]
https://orcid.org/0000-0002-0279-724X
Department of Marketing, IEDA, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
Search for more papers by this author

Mingzhang Yin

[email protected]

https://orcid.org/0000-0002-5216-2437

Department of Marketing, University of Florida, Gainesville, Florida 32611

Search for more papers by this author

,

Corresponding Author

Ziwei Cong

[email protected]

https://orcid.org/0000-0001-5196-7527

Department of Marketing, Georgetown University, Washington, District of Columbia 20057

Search for more papers by this author

,

Jia Liu

[email protected]

https://orcid.org/0000-0002-0279-724X

Department of Marketing, IEDA, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

Search for more papers by this author

Published Online:21 Apr 2026https://doi.org/10.1287/mksc.2024.1090

Supplemental Material

mksc.2024.1090.sm1.pdf

The replication files for this article are available HERE.

cover image Marketing Science

Articles In Advance

Article Information

Supplemental Material

Metrics

Information

Received:September 20, 2024
Accepted:February 01, 2026
Published Online:April 21, 2026

Copyright © 2026, INFORMS

Cite as

Mingzhang Yin, Ziwei Cong, Jia Liu (2026) Unraveling Multifaceted User Preferences on Digital Platforms: A Bayesian Deep-Learning Approach. Marketing Science 0(0).

https://doi.org/10.1287/mksc.2024.1090

Keywords

Acknowledgments

The authors thank Yixing Chen, John Lalor, Hui Li, and Khaled Boughanmi for thoughtful comments and the seminar participants at the 2024 China India Insights Program Conference and the ISMS Marketing Science conference for their feedback. The authors thank the senior editor, associate editor, and anonymous reviewers for constructive suggestions in the review process.