A CLOUD UPDATE OF THE DELONE AND MCLEAN MODEL OF INFORMATION SYSTEMS SUCCESS

As cloud computing became on one of the top technology investments in public and private organizations and represents expenses of billions yearly, little research was conducted about the factors that affect the success of cloud systems. This research study investigates the impact of free flow of information, flexibility of IT infrastructure, cloud system quality, IT security, and cloud privacy concerns on the increased net benefits of cloud computing use. The intent is to extend DeLone and McLean’s Information Systems Success Theory for today’s cloud-centric information technology world and add to the body of knowledge of cloud computing adoption. The results from surveying 117 IT professionals working in the United States with a minimum of three 3 years of experience were obtained and analyzed using Structural Equation Modelling (SEM) show that free flow of information and overall cloud system quality can lead to overall information systems success.

[1]  K. Atuahene–Gima,et al.  The Effects of Centrifugal and Centripetal Forces on Product Development Speed and Quality: How Does Problem Solving Matter? , 2003 .

[2]  D. Karras.  Statistical methodology: II. Reliability and validity assessment in study design, Part B. , 1997, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[3]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[4]  Sucheta Nadkarni,et al.  A Task-Based Model of Perceived Website Complexity , 2007, MIS Q..

[5]  Wynne W. Chin,et al.  A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic - Mail Emotion/Adoption Study , 2003, Inf. Syst. Res..

[6]  John P. Meyer,et al.  A three-component conceptualization of organizational commitment , 1991 .

[7]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[8]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[9]  Arun Rai,et al.  Interfirm Strategic Information Flows in Logistics Supply Chain Relationships , 2009, MIS Q..

[10]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[11]  Barbara H Wixom,et al.  A Theoretical Integration of User Satisfaction and Technology Acceptance , 2005, Inf. Syst. Res..

[12]  Gautam Ray,et al.  Information Technology and the Performance of the Customer Service Process: A Resource-Based Analysis , 2005, MIS Q..

[13]  Sung S. Kim,et al.  Internet Users' Information Privacy-Protective Responses: A Taxonomy and a Nomological Model , 2008, MIS Q..

[14]  H. Jeff Smith,et al.  Information Privacy: Measuring Individuals' Concerns About Organizational Practices , 1996, MIS Q..

[15]  Eduardo B. Fernández,et al.  An analysis of security issues for cloud computing , 2013, Journal of Internet Services and Applications.

[16]  Ken Kwong-Kay Wong,et al.  Partial Least Squares Structural Equation Modeling (PLS-SEM) Techniques Using SmartPLS , 2013 .

[17]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[18]  Willow A. Sheremata.  Centrifugal and Centripetal Forces in Radical New Product Development Under Time Pressure , 2000 .

[19]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[20]  Per E. Pedersen,et al.  Influences of co-creation on brand experience The role of brand engagement , 2017 .