The determinants of using cloud supply chain adoption. Issue 2 (11th March 2019)

• Record Type: Journal Article
• Authors: Lin, Chinho; Lin, Meichun
• Is Part Of: Industrial management & data systems. Volume 119:Issue 2(2019)
• Page Start: 351
• Page End: 366
• Publication Date: 2019-03-11
• Subjects: Elaboration likelihood model -- Supply chain management -- Commitment trust theory -- Cloud computing services; Industrial management -- Periodicals; Electronic data processing -- Periodicals; Business -- Periodicals; Industrial management -- Great Britain -- Periodicals; 658.05
• DOI: 10.1108/IMDS-12-2017-0589
• Languages: English
• ISSNs: 0263-5577

Abstract

Abstract : Purpose: It is necessary to determine the processes affecting cloud computing service applications in supply chain management (SCM) systems in order to facilitate cloud computing service exchanges and transmission of data among supply chain members. The paper aims to discuss these issues. Design/methodology/approach: Drawing on the elaboration likelihood model (ELM) and integrating the commitment trust theory, this paper develops a theoretical model using argument advantage and source credibility constructs to examine the relationships among perceived usefulness, attitude, trust and usage intention. Findings: The results indicate that both the central route and the peripheral route of the ELM have a positive influence on perceived usefulness. The argument advantage has a strong influence on perceived usefulness as compared to source credibility while source credibility has a strong impact on trust. Furthermore, the perceived usefulness of cloud computing services plays a pivotal role in attitude and intention, whereas trust has a weak effect on usage intention. Originality/value: The proposed model not only explores the argument that potential user evaluations of both the advantages of cloud computing services and source credibility influence their affective states, which in turn affect their usage intention, but it also examines the mediating factors that influence processes related to cloud SCM acceptance.