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Perceived Usefulness, Perceived Security and Adoption of Mobile Government: An Empirical Research

Authors: Changlin Wang -; Runsheng Fang -; Kyungsoo Park -; Yuqiang Feng -; Zhenhua Lu -; Yonghao Cui -;

Perceived Usefulness, Perceived Security and Adoption of Mobile Government: An Empirical Research

Abstract

Despite m-government being in its infancy, it’s necessary to find what factors influence users to adopt it, as theoretical advances in this regard are still insufficient. Grounded in the Technology Acceptance Theory and the characteristics of m-government, we construct an m-government adoption model to analyze factors affecting users’ adoption. The theoretical model is tested by a PLS graph on a dataset of 117 samples .The results indicate that the key factors that influence m-government adoption are perceived usefulness and perceived value. Perceived security and perceived usefulness have a positive effect on perceived value while perceived value has a positive impact on intention to use and has been considered as a mediator between perceived security, perceived usefulness and the intention to use. Perceived security has a positive effect on perceived usefulness. This study is different from previous research because in our study perceived security does not significantly influence mgovernment adoption. These findings provide theoretical support and concrete means for building a service government. Implications for theory and practice as well as limitations and future directions are also discussed.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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