Relationships Among Dimensions of Information System Success and Benefits of Cloud

Despite the many benefits offered by cloud computing’s design architecture, there are many fundamental performance challenges for IT managers to manage cloud infrastructures to meet business expectations effectively. Grounded in the information systems success model, the purpose of this quantitative correlational study was to evaluate the relationships among the perception of information quality, perception of system quality, perception of service quality, perception of system use, perception of user satisfaction, and net benefits of cloud computing services. The participants (n = 137) were IT cloud services managers in the United States, who completed the DeLone and McLean ISS authors’ validated survey instrument. The multiple regression finding were signification, F(5, 131) = 85.16, p \u3c .001, R2 = 0.76. In the final model, perception of information quality (β = .188, t = 2.844, p \u3c .05), perception of service quality (β = .178, t = 2.102, p \u3c .05), and perception of user satisfaction (β = .379, t = 5.024, p \u3c .001) were statistically significant; perception of system quality and perception of system use were not statistically significant. A recommendation is for IT managers to implement comprehensive customer evaluation of the cloud service(s) to meet customer expectations and afford satisfaction. The implications for positive social change include decision-makers in healthcare, human services, social services, and other critical service organizations better understand the vital predictors of attitude toward system use and user satisfaction of customer-facing cloud-based applications

Experiential probabilistic assessment of cloud services

© 2019 Elsevier Inc. Substantial difficulties in adopting cloud services are often encountered during upgrades of existing software systems. A reliable early stage analysis can facilitate an informed decision process of moving systems to cloud platforms. It can also mitigate risks against system quality goals. Towards this, we propose an interactive goal reasoning approach which is supported by a probabilistic layer for the precise analysis of cloud migration risks to improve the reliability of risk control. The approach is illustrated using a commercial scenario of integrating a digital document processing system to Microsoft Azure cloud platform