Types of Knowledge

The identification of the types of knowledge used in organizational activities is important for the achievement and sustainment of advantage (Silvi & Cuganesan, 2006). All knowledge is not the same; Nonaka places knowledge on spectrum between explicit and tacit (Ikujiro Nonaka & Takeuchi, 1995). These classifications of knowledge are widely used within KM literature, albeit they are sometimes referred to as objective or subjective (respectively). The categories of the explicit and tacit knowledge have been constructed as a conceptual convenience, and in reality knowledge will have varying elements of both types (Leonard & Sensiper, 1998). Some even argue that the division between explicit and tacit knowledge is no longer necessary.

That the distinction between tacit and explicit knowledge, while it provided utility as a means of making knowledge a less problematic word, is no longer useful, since the concept of tacit knowledge has become problematic in turn. We now need to recognize the importance of both narrative and concrete knowledge: we always know more than what we can say and we will always say more than we can write down. (Snowden, 2005, p. 3)

Despite some conflicting claims regarding the utility of the distinction between explicit and tacit knowledge, it remains useful for this study. It is particularly useful because the majority of KM programs within the USMC have been focused on explicit knowledge (Johnson, 2010). Table 1 summarizes the contrast of characteristics, from KM literature, between tacit and explicit knowledge (Panahi, Watson, & Partridge, 2012). The following section will describe the characteristics of both explicit and tacit knowledge.

Table 1. Properties of Tacit and Explicit Knowledge (From Panahi et al., 2012)

Explicit knowledge is easily managed, distributed and consumed; it is objective and easily transferred. Explicit knowledge can exist in the form of recipes, books, documents, procedures, and other mediums of information exchange (Nissen, 2006; Ikujiro Nonaka & Takeuchi, 1995). According to Nonaka, Von Krogh, and Voelpel, “Knowledge that can be uttered, formulated in sentences, captured in drawings and writing, is explicit” (2006, p. 1182). These pieces of explicit knowledge enable action through description, instruction or example (Nissen, 2006). Many modern IT and KM systems perform the function of storing, cataloging, and distributing large chunks of explicit knowledge, with ever-increasing success as technology advances. Consider books, Microsoft’s SharePoint, enterprise network storage (e.g., shared drives), digital storage or even the World Wide Web as examples of these tools, applications, or platforms that perform this function. Technology has increased our access to information, and many believe we now exist in an era of information overload (Cotton, 2005). The mountains of data and information now available are useful only if one has the requisite knowledge to act upon such information, or if it has been constructed in such a way that enables action. Some explicit knowledge can be used to teach a person how to interpret

student can use any school textbook or manual (explicit knowledge) to learn about an idea, process, or task. Nissen presents the example of learning to fly an aircraft: a student pilot can easily read instructions for how to properly fly an airplane, but this student cannot safely fly the plane without generating the requisite tacit knowledge (e.g., direct instructor mentoring, hands-on supervised instruction). These basic forms of learning, made possible by explicit knowledge, can enable action, but it is difficult to replicate the valuable personal experience (tacit knowledge) associated with doing or performing the task at hand over time.

Polanyi established the concept of tacit knowledge and emphasized the social interaction necessary for its transfer (1966). The basic premise behind tacit knowledge is that people tend to know much more than they can actually explain or communicate (Nissen, 2006; Polanyi, 1966; Sveiby, 1997). The experience gained or learned over a career or lifetime is contained within an individual as tacit knowledge. Obviously, tacit knowledge is valuable. Tacit knowledge is highly subjective because it is both personal and experience-based. Why else would experience remain one of the significant contributors to credibility in the modern world? Tacit knowledge becomes even more critical as the complexity of an organization’s operating environment increases (Polanyi, 1966). The difficulty in transferring tacit knowledge is one large reason people remain so critical to the operation of any organization, despite significant advances in automation, technology, and computing. If rich tacit knowledge were easily transferred or stored in an IT system, organizations would have no need to invest so much in human resources.

The literature regarding tacit knowledge generally falls into one of two camps: those who believe knowledge is binary (either tacit or explicit) and those who believe there are degrees of tacitness or explicitness (Panahi, Watson, & Partridge, 2013). Ambrosini and Bowman’s description of the degrees of tacitness is useful for the operationalization of tacit knowledge in the context of this study (Ambrosini & Bowman, 2001). Lower degrees of tacitness can be more easily converted into explicit form or transferred to others via knowledge sharing. Higher degrees of tacitness are more difficult or impossible to transfer due to the strong (sometimes unconscious) contextual existence within a person’s mind. Figure 4 illustrates Ambrosini and Bowman’s degrees of

tacitness. It is important to note that despite an abundance of theoretical research, there seems to be a lack of empirical evidence operationalizing the concept of tacit knowledge (Panahi et al., 2013). Despite this observation, the theoretical construct of tacit knowledge is adequate for this study.

Figure 4. Degree of Tacitness (From Ambrosini & Bowman, 2001)

For obvious reasons, both explicit and tacit knowledge are valuable resources for individuals and organizations alike. The relationship and interplay between these two types of knowledge is useful for understanding how the transfer of knowledge happens and learning occurs (Leonard & Sensiper, 1998). Nonaka and Takeuchi’s seminal 1995 study establishes a learning model consisting of four stages: socialization, externalization, combination, and internalization (SECI). This theoretical collection of processes is frequently referenced as the SECI model in the both organizational learning and KM literature. Socialization is the mechanism by which tacit knowledge is shared between individuals. Typically this is achieved through face-to-face interaction and rich interpersonal dialogue. Socialization is a tacit to tacit transfer. Externalization is the process that attempts to convert or articulate tacit knowledge into explicit form; this translation is subject to high attenuation because “we can know more than we can tell” (Polanyi, 1966) and tacit knowledge loses some of its value or usefulness during the conversion process (Nissen, 2006). Externalization is a tacit-to-explicit transfer. Combination is the process of combining pieces of explicit knowledge in useful or novel ways (e.g., knowing what and how to apply existing explicit knowledge). Combination is

personal tacit knowledge and experience. Internalization is explicit-to-tacit. This SECI learning process, also considered a knowledge conversion process, explains the value- adding knowledge-creating interaction between personal knowledge and group knowledge (Nonaka et al., 2006). It is important to note that social interaction is a requirement emphasized by three of the four processes—socialization, externalization, and combination (Chua, 2002).

Figure 5. SECI Model of Organizational Learning (From Ikujiro Nonaka & Takeuchi, 1995)

Modern KM programs and KMS, discussed in more detail later, seek to facilitate and improve the SECI processes within organizations (Gordeyeva, 2010). Traditionally, these systems have been highly successful in the management of explicit knowledge (Alavi & Leidner, 2001; Hislop, 2002; Nissen, 2006). Now that the types of knowledge have been discussed, the following section will explore current theory on the dynamics of knowledge.