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Antecedents and optimal industrial customers on cloud services adoption

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  • Lily Shui-Lien Chen
  • June-Hong Chen

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.

Suggested Citation

  • Lily Shui-Lien Chen & June-Hong Chen, 2021. "Antecedents and optimal industrial customers on cloud services adoption," The Service Industries Journal, Taylor & Francis Journals, vol. 41(9-10), pages 606-632, July.
    • Handle: RePEc:taf:servic:v:41:y:2021:i:9-10:p:606-632
    DOI: 10.1080/02642069.2018.1437907
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    Cited by:

    1. Vatankhah, Sanaz & Bamshad, Vahideh & Altinay, Levent & De Vita, Glauco, 2023. "Understanding business model development through the lens of complexity theory: Enablers and barriers," Journal of Business Research, Elsevier, vol. 155(PA).

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