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Conference Paper: To use a tree or a forest in behavioral intention
Title | To use a tree or a forest in behavioral intention |
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Authors | |
Issue Date | 2014 |
Publisher | Association for Information Systems (AIS). |
Citation | The 18th Pacific Asia Conference on Information Systems (PACIS 2014), Chengdu, China, 24-28 June 2014. In the Proceedings of the 18th Pacific Asia Conference on Information Systems (PACIS), 2014, p. abstract no. 215 How to Cite? |
Abstract | Cloud computing is a new technology that has been applied to education and has e nabled the
development of cloud computing classrooms; however, student behavioral intentions toward cloud
computing remain unclear. Most researchers have evaluated, integrated, or compared few (1 to 3)
theories to examine user behavioral intentions and few have addressed additional theories or models.
In this study, we test, compare, and unify six well -known theories, namely, service quality (SQ), self -
efficacy (SE), the motivational model (MM), technology acceptance model (TAM), theory of reason
action (TRA)/theory of planned behavior (TPB), and innovation diffusion theory (IDT) in the context
of cloud computing classrooms. This empirical study was conducted using an online survey. The data
collected from the samples (n=478) were analyzed using structural equation modeling. We
independently analyzed each of the six theories, formulating a united model. The analysis yielded
three valuable findings. First, comparing the explained variance and degree of freedom (df) difference,
yielded the following ranking in explained variance: MM=TAM>IDT>TPB>SE=SQ (equal =;
superior to>). Second, comparing the explained variance yielded the following ranking in explained
variance: MM>TAM>IDT>TPB>SE=SQ. Third, based on the united model of six theories, some
factors significantly affect behavioral intention and others do not. The implications of this study are
critical for both researchers and practitioners. |
Description | Conference Theme: IT ubiquity and innovation Session 9-7: IS Innovation, Adoption, and Diffusion |
Persistent Identifier | http://hdl.handle.net/10722/201497 |
DC Field | Value | Language |
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dc.contributor.author | Shiau, WL | en_US |
dc.contributor.author | Chau, PYK | en_US |
dc.date.accessioned | 2014-08-21T07:28:47Z | - |
dc.date.available | 2014-08-21T07:28:47Z | - |
dc.date.issued | 2014 | en_US |
dc.identifier.citation | The 18th Pacific Asia Conference on Information Systems (PACIS 2014), Chengdu, China, 24-28 June 2014. In the Proceedings of the 18th Pacific Asia Conference on Information Systems (PACIS), 2014, p. abstract no. 215 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/201497 | - |
dc.description | Conference Theme: IT ubiquity and innovation | - |
dc.description | Session 9-7: IS Innovation, Adoption, and Diffusion | - |
dc.description.abstract | Cloud computing is a new technology that has been applied to education and has e nabled the development of cloud computing classrooms; however, student behavioral intentions toward cloud computing remain unclear. Most researchers have evaluated, integrated, or compared few (1 to 3) theories to examine user behavioral intentions and few have addressed additional theories or models. In this study, we test, compare, and unify six well -known theories, namely, service quality (SQ), self - efficacy (SE), the motivational model (MM), technology acceptance model (TAM), theory of reason action (TRA)/theory of planned behavior (TPB), and innovation diffusion theory (IDT) in the context of cloud computing classrooms. This empirical study was conducted using an online survey. The data collected from the samples (n=478) were analyzed using structural equation modeling. We independently analyzed each of the six theories, formulating a united model. The analysis yielded three valuable findings. First, comparing the explained variance and degree of freedom (df) difference, yielded the following ranking in explained variance: MM=TAM>IDT>TPB>SE=SQ (equal =; superior to>). Second, comparing the explained variance yielded the following ranking in explained variance: MM>TAM>IDT>TPB>SE=SQ. Third, based on the united model of six theories, some factors significantly affect behavioral intention and others do not. The implications of this study are critical for both researchers and practitioners. | - |
dc.language | eng | en_US |
dc.publisher | Association for Information Systems (AIS). | - |
dc.relation.ispartof | Proceedings of the 18th Pacific Asia Conference on Information Systems (PACIS 2014) | en_US |
dc.title | To use a tree or a forest in behavioral intention | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Chau, PYK: pchau@business.hku.hk | en_US |
dc.identifier.authority | Chau, PYK=rp01052 | en_US |
dc.description.nature | published_or_final_version | - |
dc.identifier.hkuros | 233809 | en_US |
dc.identifier.spage | abstract no. 215 | - |
dc.identifier.epage | abstract no. 215 | - |
dc.publisher.place | United States | - |