淡江大學機構典藏:Item 987654321/113075
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/113075


    Title: A Comparison of Competing Models for Understanding Industrial Organization’s Acceptance of Cloud Services
    Authors: Shui-Lien Chen;June-Hong Chen;Yung-Hsin Lee
    Keywords: cloud services;technology acceptance theory;competing model;model development strategy;structural equation modeling
    Date: 2018-03
    Issue Date: 2018-04-12 12:10:45 (UTC+8)
    Abstract: Cloud computing is the next generation in computing, and the next natural step in the
    evolution of on-demand information technology services and products. However, only a few studies
    have addressed the adoption of cloud computing from an organizational perspective, which have not
    proven whether the research model is the best-fitting model. The purpose of this paper is to construct
    research competing models (RCMs) and determine the best-fitting model for understanding industrial
    organization’s acceptance of cloud services. This research integrated the technology acceptance model
    and the principle of model parsimony to develop four cloud service adoption RCMs with enterprise
    usage intention being used as a proxy for actual behavior, and then compared the RCMs using
    structural equation modeling (SEM). Data derived from a questionnaire-based survey of 227 firms in
    Taiwan were tested against the relationships through SEM. Based on the empirical study, the results
    indicated that, although all four RCMs had a high goodness of fit, in both nested and non-nested
    structure comparisons, research competing model A (Model A) demonstrated superior performance
    and was the best-fitting model. This study introduced a model development strategy that can most
    accurately explain and predict the behavioral intention of organizations to adopt cloud services.
    Relation: Sustainability 10(3), 673
    DOI: 10.3390/su10030673
    Appears in Collections:[Department of Management Sciences] Journal Article

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