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International Journal of Innovation and Applied Studies
ISSN: 2028-9324     CODEN: IJIABO     OCLC Number: 828807274     ZDB-ID: 2703985-7
 
 
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Determinants of Software-as-a-Service Adoption and Intention to Use for Enterprise Applications


Volume 10, Issue 1, January 2015, Pages 138–148

 Determinants of Software-as-a-Service Adoption and Intention to Use for Enterprise Applications

Lisa Y. Chen1

1 Associate Professor, Dept. of Information Management, I-Shou University, Kaoshiung, Taiwan

Original language: English

Copyright © 2015 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


With the increasing popularity of cloud computing, many vendors have entered the software as a service (SaaS) market to provide new services and applications. Although cloud computing services make new demands and seek added value through the Internet, SaaS is still in the early stages of development, and is subject to build a cloud environment so the development is limited. However, the adoption of cloud computing services still remains very low in Taiwan. Research has been carried out to explore issues related to the cloud computing services, but there is still a lack of research in this field and research of cloud computing services remains extremely limited, thus offering insufficient evidence as to how effective adoption and successful diffusion of advanced information systems is explicitly excluded in the context of cloud computing services. Therefore, this study intends to explore the identified factors affecting the adoption of cloud computing SaaS in Taiwan by developing a comprehensive research framework. This study adopted technology acceptance model (TAM) to explore the relationships between constructs and their effect on users' intention to use SaaS. Data was collected using a self-administered survey to test the hypotheses. This study used SPSS to compute descriptive statistics. The proposed model was then estimated using the partial least squares (PLS) regression technique and SmartPLS 3.0 to analyze the measurement and structural models. The results of the analysis supported all hypotheses. Some recommendations and identify limitations of this study were provided for future research.

Author Keywords: Software-as-a-Service, SaaS, Enterprise Applications, cloud computing, Internet.


How to Cite this Article


Lisa Y. Chen, “Determinants of Software-as-a-Service Adoption and Intention to Use for Enterprise Applications,” International Journal of Innovation and Applied Studies, vol. 10, no. 1, pp. 138–148, January 2015.