The Impact of Emerging Computing Models on Organizational Socio-technical System

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Abstract

Consolidated Enterprise IT solutions have proven to enhance business efficiency when significant fractions of local computing activities are migrating away from desktop PCs and departmental servers and are being integrated and packaged on the Web into "the computing cloud." Whether referred to Grid, Utility or Cloud Computing, the idea is basically the same: instead of investing in and maintaining expensive applications and systems, users access and utilize dynamic computing structures to meet their fluctuating demands on IT resources and pay a fixed subscription or an actual usage fee. The immense economic demands in the last several years, in conjunction with the immediate reduction of upfront capital and operational costs when cloud-based services are employed, increase the speed and the scale of cloud computing adoption both horizontally -across industries-, and vertically -in organizations' technology stacks. In actuality, the radical changes for organizations are in rethinking and reengineering their traditional IT resources, advancing them with cloud architectures and implementing services based on dynamic computing delivery models. The changes and business transformations are underway on a large scale, from providers and customers to vendors and developers. The key issues are not only in economics and management, but essentially how emerging IT models impact organizational structure, capabilities, business processes, and consequential opportunities. This paper explores the impact of the dynamic computing models on the organizational socio-technical system and provides the author's vision and experience in strategizing and utilizing emerging cloud-based applications and services. © Springer-Verlag Berlin Heidelberg 2013.

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APA

Ivanov, I. I. (2013). The Impact of Emerging Computing Models on Organizational Socio-technical System. In Communications in Computer and Information Science (Vol. 303, pp. 3–19). Springer Verlag. https://doi.org/10.1007/978-3-642-36177-7_1

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