EDBT 2026 Demo / reviewers in the wild / expert
Aihui Chen
dblp:151/8424
· DBLP profile ↗
4ranked-venue papers in the field
4as first author
3since 2021 · last 2025
0000-0002-8357-3503ORCID · verified
Domains — venue-derived; a paper can count in several
Knowledge Engineering, Semantic Web & Information Systems · 4 (4 first)
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Cracking the AI recruitment code: Striving for transparency in finding the right person-job fit
Aihui Chen, Feifei Han, Yaobin Lu |
Inf. Manag. | 1 |
| 2025 | Speciesism toward AI: The mechanism of AI affection expression on user satisfaction
Aihui Chen, Yunshuang Yu, Yaobin Lu |
Inf. Manag. | 1 |
| 2022 | Higher Price: A Benefit of Online Value Co-Creation Activities in Sponsored Communities
Aihui Chen, Yaobin Lu, Yeming (Yale) Gong |
Inf. Manag. | 1 |
| 2017 | Enhancing the Decision Quality through Learning from the Social Commerce ComponentsabstractThe adoption of social networks introduced a new set of components to the e-commerce environment, which are called social commerce components (SCCs) (e.g., forums and communities, rating and reviews and social recommendations). Although various SCCs have transformed customer behaviors and decision patterns, few studies have investigated their roles together in enhancing customers' decision quality. In this study, based on the social learning theory, the authors develop a research model to explore how customers learn from the SCCs to influence their uncertainty in shopping experience, and thus improve their decision quality. The results from 243 actual customers of social commerce site in China suggest that demand uncertainty is one of the most important factors that reduces decision quality, whereas product quality uncertainty has a significant positive influence on decision quality, and seller quality uncertainty has no influence on decision quality. Also, learning from forums and communities, learning from rating and reviews and learning from social recommendations play different roles on forming customers' uncertainty. In addition, product type can moderate most of the above associations. In summary, these findings increase one's understanding of the customers' decision pattern in social commerce context and extend the scope of social learning theory and uncertainty theory. The findings also provide insights for social commerce practitioners in developing strategies for improved implementation of social commerce as well as the design of social commerce sites. Aihui Chen, Yaobin Lu, Sumeet Gupta 0002 |
J. Glob. Inf. Manag. | 1 |