Cross-channel Recommendation
Cross-Channel Recommendation is a recommendation framework that integrates user behavior and contextual data across multiple interactive platforms or touchpoints to generate personalized suggestions, distinguished by its capacity to unify disparate channel-specific signals into coherent, cross-environment recommendation strategies.
6
Publications
246
Citations
21
Authors
9
Institutions
Publications per year
2017–2026
4
Parents
6
How Recommendation Affects Customer Search: A Field Experiment
Zhe Yuan, AJ Yuan Chen, Yitong Wang et al. · Information Systems Research · 2024 · 19 citations
1–5 of 6
21
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1
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1
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1–5 of 21
9
Tsinghua University
Beijing, China
1 h-index
5 publications
170 citations
Wuhan University
Wuhan, China
1 h-index
2 publications
114 citations
University of Bayreuth
Bayreuth, Germany
1 h-index
3 publications
267 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
1 h-index
2 publications
68 citations
Hubei University Of Economics
Wuhan, China
1 h-index
2 publications
114 citations

DePaul University
Chicago, United States
1 h-index
5 publications
70 citations
Ministry of Education of the People's Republic of China
Beijing, China
1 h-index
1 publications
18 citations

Lehigh University
Bethlehem, United States
1 h-index
1 publications
57 citations
1–8 of 9
2 publications · 107 citations
2
h-index
JM · 1 publications · 57 citations
1
h-index
1 publications · 34 citations
1
h-index
TKDE · 1 publications · 34 citations
1
h-index
ISR · 1 publications · 19 citations
1–5