淡江大學機構典藏:Item 987654321/113074
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/113074


    Title: Antecedents and Optimal Industrial Customers on Cloud Services Adoption
    Authors: Shui-Lien Chen;June-Hong Chen
    Keywords: Cloud services;technology acceptance theory;optimal industrial customer;structural equation modeling;technique for order performance by similarity to ideal solution
    Date: 2018-02-16
    Issue Date: 2018-04-12 12:10:43 (UTC+8)
    Publisher: Taylor & Francis
    Abstract: The rapid flourishing of the cloud service market necessitates investigating the underlying determinants of cloud services adoption and identifying optimal industrial customers for business-to-business (B2B) service encounters. Many studies have addressed technical and operational concerns related to cloud services. However, only a few studies have addressed the adoption of cloud computing from an organizational perspective, and none of them have considered the practical application of cloud computing in society. Therefore, in this paper, a research model is constructed to understand an industrial organization’s acceptance of cloud services and apply the results in order to explore optimal industrial customers. A questionnaire-based survey was used to collect data from the population, 227 firms in the manufacturing and services industries in Taiwan. Causal relationships were tested through structural equation modeling and the ordering of optimal industrial customers was evaluated by using the Technique for Order of Preference by Similarity to Ideal Solution method.
    Relation: The Service Industries Journal 41(9-10)
    DOI: 10.1080/02642069.2018.1437907
    Appears in Collections:[Department of Management Sciences] Journal Article

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