Y
Young Eun Lee
Researcher at Fordham University
Publications - 10
Citations - 997
Young Eun Lee is an academic researcher from Fordham University. The author has contributed to research in topics: Context (language use) & Web 2.0. The author has an hindex of 8, co-authored 10 publications receiving 921 citations. Previous affiliations of Young Eun Lee include University of British Columbia.
Papers
More filters
Journal ArticleDOI
The effects of virtual reality on consumer learning: an empirical investigation
Kil-Soo Suh,Young Eun Lee +1 more
TL;DR: The results support the predictions that VR interfaces increase overall consumer learning about products and that these effects extend to VHE products more significantly than to VLE products.
Journal ArticleDOI
Interface design for mobile commerce
Young Eun Lee,Izak Benbasat +1 more
TL;DR: Understanding the unique characteristics of m-commerce to enhance and improve the user interface and how these characteristics can be leveraged for improved user interface quality and efficiency is key.
Journal ArticleDOI
A Framework for the Study of Customer Interface Design for Mobile Commerce
Young Eun Lee,Izak Benbasat +1 more
TL;DR: The 2M's and 7C's are proposed as a new framework for mobile commerce interfaces, and two new elements (2M's) are identified: mobile setting and mobile device constraints.
Journal ArticleDOI
Research Note---The Influence of Trade-off Difficulty Caused by Preference Elicitation Methods on User Acceptance of Recommendation Agents Across Loss and Gain Conditions
Young Eun Lee,Izak Benbasat +1 more
TL;DR: This study examines whether an RA's PEM generates trade-off difficulty, which, in turn, affects users' evaluations of an RA and the resultant acceptance of the RA, and whether the decision context in which users employ a PEM moderates the degree to which that PEM generated trade-offs.
Journal ArticleDOI
Interaction design for mobile product recommendation agents: Supporting users' decisions in retail stores
Young Eun Lee,Izak Benbasat +1 more
TL;DR: Empirical results support the notion that mobile RAs should be designed to fit the user's task undertaken in the particular context, as RA-AL users made more accurate decisions than RA-AT users due to theRA-AL's interaction style, which was compatible with the way in which users processed information and made decisions in the store.