Should Innovation Knowledge be Assessed?

Should Innovation Knowledge be Assessed?

Fawzy Soliman (UTS Business School, University of Technology, Sydney, Australia)
Copyright: © 2015 |Pages: 10
DOI: 10.4018/978-1-4666-5888-2.ch461
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There is almost global perception that knowledge is a belief. This perception has led many scholars and management practitioners to evaluate knowledge on the basis of correctness of answers only. However, correctness of answers is not sufficient in determining the goodness or the appropriateness of knowledge for a given task. What is need is an evaluation method. However, available evaluation methods require measurements of knowledge characteristics. That is why Hunt (2003) proposed a method of knowledge measurement that has been criticised for leading to false results that in turn leads to unpredictable levels of uncertainty.

It has been shown that uncertainties could impact adversely on the qualities of the correctness answers or acceptable justifications (Hunt, 2003, p. 109). However, the research in uncertainties revealed that failure to formulate precise questions about acquiring, retaining and managing knowledge could adversely affect the ability to perform certain tasks safely and effectively within the desired levels of quality (Von Krogh and Von Hippel, 2006). The failure to identify mismatches between desired and actual quality levels has driven strong interest in researching uncertainties as a possible source of knowledge defects or knowledge gaps (Soliman, 2012).

Innovation knowledge that is usually created and transferred or disseminated within one single company or between a group of innovative companies (Nonaka & Von Krogh, 2009). Hull et al. (1999) suggests that the continuous and rapid evolution of information and communication technology has elevated knowledge to become an essential ingredient for the successful innovations. The paramount concern lies in the lack of identification of globally accepted set of knowledge characteristics that could be used to identify knowledge quality, fitness for the purpose and its usefulness for given tasks.

Soliman and Youssef (2003) points to the quality of information as a competitive advantage. Accordingly, to ensure better quality of information, knowledge should be assessed thought the organisational processes, in particular knowledge handling processes.

In recent times Soliman (2011) pointed out that the knowledge transfer processes must be carefully managed to support the strategic goals of innovation. This in turn means innovation knowledge must be managed effectively to ensure adherence to the basic objectives of innovation. In managing the innovation knowledge, Soliman (2011) proposed the following three interrelated domains of management of the innovation knowledge; namely The Knowledge Domain; The Learning Domain and The Innovation Domain. The common core activity flow between the three domains is the Innovation Knowledge (Soliman, 2011).



Managing business uncertainty is necessary but very difficult, especially in innovation projects. This is due to the fact that innovation projects are by definition full of risks. One of the significant risks that could lead to poor performance or failure of the innovation processes is the inappropriate managerial perceptions of uncertainties (Capon et al., 1992; Song & Montoya-Weiss, 1998). Soliman (2013a) has specified at least three main areas of uncertainties that could impact on the performance of business innovation; namely Economic Uncertainty, Market Uncertainty, Talent Uncertainty. However, uncertainties could be defined as “the inability of a manager to assess and predict any changes in regards to factors that are external to his/her organisations environment such as knowledge obtained from outside sources external to the organisation” (Soliman (2013a). Many scholars have associated uncertainties to complexity management. In turn complexity management is regarded by Hanseth (2007) as dependable on the level of complexity of technology used. In this regards Hanseth (2007) pointed out that “the use of more complex technologies are likely to increase the degree of uncertainty.” In innovation projects high degrees of uncertainties could be encountered thus leading to poor innovation outcomes (Rogers, 1995). Chun-Wang Tsou (2012) added that “the inherent difficulty of using a new technology is a major concern when deciding to adopt that technology.”

Key Terms in this Chapter

Internalisation: Internalisation is one of the four modes of knowledge creation as suggested by Nonaka et al (1996) .It involves conversion from explicit knowledge to tacit knowledge.

Externalisation: Externalisation is one of the four modes of knowledge creation as suggested by Nonaka et al (1996) . Involves conversion from tacit knowledge to explicit knowledge (doing it, then describing it).

Tacit Knowledge: Tacit knowledge refers to a knowledge which is only known by an individual and that is difficult to communicate to the rest of an organization. It has two dimensions where the first is the technical dimension, which encompasses the kind of informal personal skills or crafts often referred to as know-how.

Knowledge Management: Knowledge management is concerned the utilization of certain process in the creation, capturing and distribution of knowledge through different mechanisms to produce a blueprint that is essential in aiding organizations in achieving organizational excellence.

Management: Management entails all of those processes associated with the identification, sharing and creation of knowledge. This requires systems for the creation and maintenance of knowledge repositories and to cultivate and facilitate the sharing of knowledge and organizational learning.

Explicit Knowledge: Explicit knowledge refers to knowledge that is easy to communicate. It can be captured and expressed in words and numbers and shared in the form of data by courses or books for self-reading, scientific formulae, specifications, manuals and the like.

Socialisation: Socialisation is one of the four modes of knowledge creation as suggested by Nonaka et al (1996) . Involves conversion from individual tacit knowledge to group tacit knowledge.

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