Cloud enterprise resource planning (C‐ERP) represents an evolution of traditional ERP, which also offers the advantages of cloud computing (CC) such as ease of use and resource elastic-ity. This article presents the opportunities and challenges of the C‐ERP adoption for industry 4.0 in the United States as well as the factors that boost or hinder such a decision. The quantitative research method is used to gather the predictor factors and correlation amongst them. An online survey questionnaire received 109 responses, mainly decision‐makers and professionals from the US consumer goods industry. Statistical analysis has been carried out to rank the different levels of influence in the C‐ERP adoption decision. The predictor’s complexity and regulatory compliance positively influence C‐ERP private service deployment, whereas technology readiness is a good predictor of community service deployment. This paper also proposes a decision support system (DSS), tailored to industry 4.0, and aimed at assisting decision‐makers in adopting C‐ERP as an effective resource for decision‐making. The DSS is built upon the predictors using the analytic hierarchy process (AHP) and it supports decision‐makers in the selection of services and deployment models for C‐ERP as a resource.

Effective cloud resource utilisation in cloud erp decision‐making process for industry 4.0 in the united states

Savaglio C.
;
2021-01-01

Abstract

Cloud enterprise resource planning (C‐ERP) represents an evolution of traditional ERP, which also offers the advantages of cloud computing (CC) such as ease of use and resource elastic-ity. This article presents the opportunities and challenges of the C‐ERP adoption for industry 4.0 in the United States as well as the factors that boost or hinder such a decision. The quantitative research method is used to gather the predictor factors and correlation amongst them. An online survey questionnaire received 109 responses, mainly decision‐makers and professionals from the US consumer goods industry. Statistical analysis has been carried out to rank the different levels of influence in the C‐ERP adoption decision. The predictor’s complexity and regulatory compliance positively influence C‐ERP private service deployment, whereas technology readiness is a good predictor of community service deployment. This paper also proposes a decision support system (DSS), tailored to industry 4.0, and aimed at assisting decision‐makers in adopting C‐ERP as an effective resource for decision‐making. The DSS is built upon the predictors using the analytic hierarchy process (AHP) and it supports decision‐makers in the selection of services and deployment models for C‐ERP as a resource.
2021
Cloud ERP
Cloud models
Cloud services
Consumer goods industry
Decision making process
Decision support tool
Industry 4.0
Resource utilisation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/360685
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