J
Jen-Her Wu
Researcher at National Sun Yat-sen University
Publications - 86
Citations - 7270
Jen-Her Wu is an academic researcher from National Sun Yat-sen University. The author has contributed to research in topics: Mobile commerce & Enterprise resource planning. The author has an hindex of 27, co-authored 83 publications receiving 6511 citations. Previous affiliations of Jen-Her Wu include Harvard University & Kaohsiung Medical University.
Papers
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Journal ArticleDOI
An empirical study on ERP-driven innovation in Taiwan
TL;DR: The results indicate that the ERP penetration rate for the ES industry is significantly higher than that for traditional industry and the degree of innovation success is low for all industry sectors and ERP packages.
Journal ArticleDOI
Improving physicians' performance with a stroke CDSS
TL;DR: The system usability test results showed that the developed stroke CDSS was acceptably accurate, able to lessen the cognitive effort as desired, and preferable for use due to the significant reduction in cognitive load.
Proceedings Article
Why Do Players Stick to a Specific Online Game? The Users and Gratifications Perspective
TL;DR: The important antecedents (i.e. gratifications, presence, service mechanisms, and continuance motivation) of stickiness intention on the online game are explored and the associated relationships among them are examined.
Proceedings ArticleDOI
Falling in love with online shopping carnival on singles' day in China: An uses and Gratifications perspective
TL;DR: A nomological model is developed to explain how incentivized gamification, hedonic presence, individual needs and platform synergy affect consumer active participation in the phenomena of online shopping carnival on singles' day in China.
Proceedings Article
An Empirical Study of Consumers Adopting Mobile Commerce in Taiwan: Analyzed by Structural Equation Modeling
Jen-Her Wu,Shu-Ching Wang +1 more
TL;DR: The extended technology acceptance model (TAM2) is adopted and integrated with the innovation diffusion theory and the perceived risk variable to model users’ acceptance of using MC.