The goal of cloud systems is to provide easy, scalable access to computing resources and IT services. However, the ability of the cloud system to transfer knowledge to assist the innovator should also be a key objective of cloud system deployment. This chapter presents an approach for assessment of cloud systems for innovation on the basis of the system’s abilities to differentiate between the various types of knowledge. In this regard, the chapter also proposes a number of success factors for deployment of cloud systems for innovation in a global setting.
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The intensity of growing competition fuelled by the strength of the rising globalization is presenting firms with further challenge and renewed pressure to innovate. Innovation could be pursued at one or all of the three innovation levels; namely: a) product innovation including creation of new products and/or modification to existing products; b) innovation in providing service to customers and c) innovation in the managerial aspects of the firm including changes of the firm’s structure, policies and or procedures (Soliman, 2012a).
Innovation is partly based on learning which in turn is dependent on knowledge and as such there are five stages of the innovation knowledge transfer process (Soliman, 2011b), these are:
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Knowledge Transfer: Identifying and transferring the necessary knowledge for the innovation (from external and internal sources of knowledge).
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Scanning: Scanning the transferred knowledge to exclude knowledge that is not directly relevant for the innovation.
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Decision: Regarding what to do with the scanned knowledge. That is to decide whether to adopt or reject the transferred knowledge with the view of weighing the advantages and the disadvantages of using that knowledge in its current form.
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Implementation: Employing the transferred knowledge depending on the situation and the usefulness of the knowledge for the innovation.
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Confirmation: Finalizing the decision to continue using the knowledge perhaps in its fullest potential. In this case, the knowledge may be referred to as innovation knowledge.
Knowledge may be defined as what makes personal, organizational, and societal intelligent behaviour possible (Spaeth, et al., 2010). Knowledge could be found in a number of different types and forms of artefacts that exist in the form of documents, files, papers, conversations, pictures, thoughts, software, databases, e-mail messages, and in any other form that are used to represent meaning and understanding of that knowledge (Haefliger, et al., 2008). In other words, knowledge artefacts flow throughout and between organisations and individuals in what is known as knowledge flows (Newman, 2004). Knowledge flows must be managed effectively to ensure that the basic objectives of organizations and individuals are attained to the greatest extent possible (Nonaka, et al., 2006). In this context, knowledge in modern organizations should be considered from the following five interrelated perspectives: