In order to develop a theoretical framework that provides insights into the impact of cultural factors on sharing knowledge in organisational context, an understanding is required about what knowledge sharing actually is, or at least, how it is conceptualised in this research. In this chapter, we examine current theories and concepts that contribute to this understanding, resulting in a working definition for this research.
Conceptualising knowledge sharing is a challenging endeavour for two reasons. First, the relevant theories and concepts are not to be found within one single research discipline, but can be distributed over several social science disciplines and sub-disciplines. Second, it is noticed that a substantial part of the literature is engaged in an epistemological discourse about knowledge, without emerging in a clear consensus. Despite the importance of classifications, taxonomies and other conceptualisations of knowledge, this research does not intend to contribute to this ongoing and probably never-ending debate about the nature of knowledge.
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First, different perspectives on knowledge sharing are described within the social sciences in general, and within management theory in particular. Then, the notion of knowledge is conceptualised, by addressing the distinction between knowledge, information and data, by explaining the difference between explicit and tacit knowing and by describing the distinction between individual and organisational knowledge. Also different perspectives on and taxonomies of knowledge are presented.
After conceptualising knowledge, the knowledge sharing process is addressed, by determining the scope of knowledge sharing processes taken into account in this research. The sharing process itself is described, by explaining the concept of communication genre as institutionalised ways of communicating. Then, the conditions that enable or inhibit knowledge sharing within organisations are described. The importance of the cultural dimension of knowledge sharing, being the focus in this research, is described. The chapter ends with concluding remarks with respect to the situated nature of knowledge sharing.
2.2 Knowledge sharing: A variety of perspectives
Researchers within different social science disciplines have addressed the topic of knowledge sharing. Between, and even within, these disciplines the level of sophistication of their developed knowledge-related theories differ and the assumptions about and perspectives on knowledge sharing can differ (Schulze & Leidner, 2002). Since the adopted assumptions and perspectives in a research largely determine its outcome, it is important to explicate and justify them. In this section a broad overview of the diversity of research areas dealing with knowledge sharing is provided.
2.2.1 Within Social science
Knowledge sharing is a social phenomenon, thus this research can be classified as social science research. However, this does not mean that the natural sciences do not provide interesting insights about knowledge sharing. For example, a neurobiology discipline can provide important insights in the functioning of the human brain, which can be connected to knowledge sharing process, and mathematicians develop algorithms and build simulations, which are related to knowledge sharing networks. Industrial and software engineers (localise between the social and natural sciences) also analyse knowledge sharing processes, while designing user-interfaces, developing groupware tools or virtual reality applications and improving programming languages. Nevertheless, limited by the personal interests and background of the researcher, his focus, and his capabilities, these natural scientific disciplines are not part of the scope of this research.
Nevertheless, even within the social sciences many different approaches to knowledge sharing exist. Within economics, for example, knowledge sharing is primarily considered at a macro level as something that occurs between universities, business and different countries, whereas, psychology takes a more micro perspective focusing on individual cognitive learning processes. In this research, a management orientation is adopted, focusing on people sharing knowledge in an organisational context. Eventually, this research wants to contribute to improve the efficacy and efficiency of organisations.
Whereas, the notion of 'knowledge' has been topic of research in several social disciplines, it came particularly into the picture within the business community around the 1980's. (This not to mean that before the 1980's, organisations were not dealing with knowledge-related issues, since they always have dealt with them, however, these issues and their purposes were not recognized or expressed explicitly)
Especially at the end of the last century, articles about knowledge (processes) were published and consultants carried out a number of knowledge management projects for organisations (Scarbrough and Swan, 2001). Many companies characterised themselves as 'knowledge intensive organisations' operating in a 'knowledge economy' employing 'knowledge officers' implementing 'knowledge management'.
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Several interrelated reasons and motives can be identified why knowledge became a fashionable issue within the business practice for example due to increasing competition and incited by consultants, managers are very willing to try new concepts in order not to loose its competitive advantage. However, management concepts become outdated increasingly fast (Karsten &Veen, 1998). For example, in the 1950s and 1960s the focus was on efficiency, from 1971 until 1982, the focus shifted towards quality; from 1983 until 1992, the emphasis was on flexibility and from 1993 onwards, the focus is on innovation. Often organisations adopt a fashionable idea without adequate analysis because rest of the industry is doing so. In times of great prosperity, organisations will take the chance with the idea: 'it can't do any harm and it may do some good'. This is why people have labelled knowledge management as 'hype'. Reframing former initiatives as knowledge management initiatives ('Learning Organisation', 'Total Quality Management', 'Business Process Redesign' and 'Core Competencies') intensifies this impression.
Another motive for adopting knowledge management is to keep control over people's knowledge. Organisations have to face trends like globalisation, flexibilisation and mobilisation of knowledge workers. Managing the employees becomes more difficult, and many organisations were looking for a way to get some level of control. In this respect, one can make the analogy with Taylorism, which became popular in a period where employees became more emancipated and management as well as the employees were looking for more structure. In line with information management, managers believe that the use of information and communication technologies could provide them with control by building knowledge bases and implementing other technologies.
Consequently, knowledge-related issues became a domain of research within the academic world. Products became more knowledge intensive, knowledge became outdated increasingly fast, and this knowledge became increasingly specialised and spatially distributed (Drucker, 1993). Many organisations began to recognise knowledge as a fourth production factor, in addition to labour, land and capital. The argument was that since knowledge constituted a crucial way of differentiating oneself from its competitors, it should also be managed.
Since knowledge has been studied within an organisational context as a scientific discipline only for a short while, it is useful to consult disciplines like philosophy and psychology, which do have a longer record of accomplishment in thinking about knowledge and knowledge sharing, although not necessarily within an organisational context. Therefore, this research will build upon the insights of other disciplines as well, to better understand how culture affects sharing knowledge within organisational context.
2.2.2 within management theory
Management theory is not a homogeneous discipline but comprises several different sub disciplines, like strategic management, marketing, information management and financial management. Among the variety of sub disciplines, one discipline focuses specifically on knowledge (processes), i.e. knowledge management. Within this area, there are many of academic units such as strategic management, information systems, and innovation management. The ambiguity of knowledge management makes it amenable to multiple interpretations and remoulding, which potentially extend its relevance across different research communities (Scarbrough & Swan, 2001). Based on an extensive review of literature, Boersma (2002) has identified different knowledge management approaches: a strategic approach, a human resource management approach, a learning organisation approach, an intellectual capital approach, a knowledge technology approach, an ICT approach, an organisational approach, an innovation approach, a network approach and a quality control approach. Wiig (1993, pp. 432-443) has proposed another classification addressing comparable approaches, based on scope (narrow, broad) and focus (technical, nontechnical).
Underlying these approaches four recurring and interrelated components in knowledge management can be identified: people, technology, the organisation of both, and strategy. Although all four components are involved in knowledge-related management research, the attention given to each of these components tends to vary. Some research is technology-based, heavily cantering on technical solutions. Other research is not technically orientated and primarily focuses at people, strategy or the organisation. The background of the researcher can heavily influence the adopted research focus. Rather than limiting this research to any of these single sub disciplines, this research preserves and builds upon what is existed in the fields which is considered related. For each of the sub disciplines their main contributions to the understanding of knowledge sharing are outlined. In subsequent sections, a more detailed review of particular parts of the relevant literature is provided.
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Within strategic management, one deals with choices with respect to strategy "In what direction should a firm channel its activities?" (Tsoukas, 2004, P. 94) Traditional concerns in strategic management include issues of strategic choice and competitive advantage. With respect to knowledge, strategic management argues that organisations have to deal with two questions: How can the crucial knowledge are improved to perform better? In addition, how can this crucial knowledge be applied differently into new products to increase the value and demand of these products? (Alavi & Leidner, 2001) pointed that, "A knowledge-based perspective of the firm has emerged in the strategic management literature (Cole 1998; Spender 1996a, 1996b; Nonaka & Takeuchi 1995). This perspective builds upon and extends the resource-based theory of the firm initially promoted by Penrose (1959) and expanded by others (Barney 1991; Conner 1991; Wernerfelt1984)" (P. 108). Grant (1996) says that, "The resource-based view perceives the firm as a unique bundle of idiosyncratic resources and capabilities where the primary task of management is to maximise value through the optimal deployment of existing resources and capabilities, while developing the firm's resource base for the future"(p.110). The resource-based theory of the firm has also developed in the core competencies approach. This approach argues that organisations have to focus at the things that they are really good at. (Stalk, et al., 1992) asserts that, "The goal is to identify and develop the hard-to-imitate organisational capabilities that distinguish a company from its competitors in the eyes of customers" (p.62).
The strengths of the strategic management literature with respect to knowledge sharing is that it emphasises the value of knowledge for the organisation and makes a link between knowledge processes and the organisational objectives explicitly. On the other side, the process of knowledge sharing itself is only discussed at an abstract conceptual level without further operationalising what it is; Knowledge sharing is considered as a black box.
Within the field of information management, one primarily focuses on technology as a tool for coordinating, communicating, storing and sharing knowledge. This approach assumes that when knowledge elicitation and modelling is performed with sufficient expertise and the affected work is redesigned, the knowledge systems will be very useful. An important aim is to develop standardised technology that captures and deploys knowledge across the organisation. In addition, artificial intelligence can be used to automate human reasoning in an expert system. These applications continue to increase in sophistication from rule-based expert systems to systems that include neural networks, case-based reasoning, and fuzzy or qualitative reasoning.
Human resource management
The central idea within this sub discipline is that working relations must organise to be beneficial for both the employer and the employees. Human resource management deals with issues like knowledge profiling (systems that contain extensive information about areas of expertise of employees, levels of proficiency), personnel evaluation (identify personnel growth paths and determine educational needs), and introduction of performance-enhancing work aids.
Within the human resource management discipline, theories dealing with organisational learning have contributed to the understanding about knowledge sharing (Argyris and Schön, 1978; Huber, 1991; Kim, 1993; Levitt and March, 1988). The rationale behind organisational learning is that an organisation must build explicit practices to learn quickly and thoroughly and implement what is learned faster. This research elaborates on how organisational learning relates to knowledge sharing later in this chapter.
Within innovation management, one deals with product development processes, product and process innovation trajectories. With respect to knowledge, this approach emphasises knowledge acquisitions for new products. Furthermore, much research has been conducted that deals with the R&D - Marketing interface. Knowledge sharing plays a crucial role here.
Whereas, organisational learning emphasises the acquisition of existing knowledge, innovation management stresses the development of new knowledge. Nonaka (1994) has tried to connect the organisational learning with the innovation perspective by not only focusing on socialising, internalising and combining processes, but especially on externalising.
In the light of this various approaches, knowledge management is not easy to define. Many definitions available in the literature are highly abstract. Some examplesof such definitions are: "the field of deliberately and systematically analysing, synthesising, assessing, and implementing knowledge-related changes to attain a set of objectives" (Wiig, 1993, p. 458). "initiating and maintaining flows of knowledge within an organization resulting in improvement of the learning capacity" (Berenschot 1995) or "a loosely connected set of ideas, tools and practices centering on the communication and exploitation of knowledge in organizations" (Scarbrough & Swan, 2001, P. 3).
Essers and Schreinemakers (1996) argue that the difference between managing knowledge and managing information does not so much lie in their respective objects (since they believe that these cannot be fundamentally distinct), but in their fundamental objectives or guiding principles. Historically, information management has been primarily guided by the objective of reducing uncertainty and freedom of choice for the members of the organisation. On the other hand, knowledge management recognises that managing (instead of dismissing) the incommensurability and difference between rivalling mental models that are operative within and between organisations is of paramount importance to their creativity and ability to learn. Thus, instead of reducing uncertainty and constraining choice, knowledge may deliberately broaden the scope of the decision.
Several authors provide an overview of knowledge management literature (Alavi & Leidner, 2001; Wiig, 1997). Scarbrough and Swan (2001) provide an account of the emergence and diffusion of knowledge management. According to them, knowledge management was rather technology oriented initially, pushed by the new opportunities of information and communication technologies. When one realised that just implementing fancy tools was not very successful, the human aspects, driven by a customer pull were identified. The challenge has become to include the push and pull, the technical and the human. In either case, one needs to understand why knowledge is being shared and how it relates to the strategy of an organisation.
Many scholars argue that knowledge management deals with managing different knowledge processes. Wiig (1993) distinguishes four of knowledge processes: "1) Building knowledge 2) Holding knowledge 3) Pooling knowledge and 4) Applying knowledge." (PP. 55-63) The functions of building knowledge consist of obtaining, analysing, reconstructing, codifying and organising knowledge. The functions of holding knowledge comprise remembering, cumulating, embedding and archiving of knowledge. The functions of pooling knowledge comprise coordinating, assembling and retrieving knowledge. The functions of applying knowledge are for example: using established knowledge to perform, to survey, to describe and analyse a situation, select relevant knowledge, synthesise alternative solutions, evaluate potential alternatives, to make decisions, to implement the selected alternative.
Van der Spek and Spijkervet (1997, pp. 18-20) distinguish four similar processes in which the basic operations required for knowledge management have been implemented: 1) Developing new knowledge 2) Combining available knowledge 3) Distributing knowledge and 4) Securing new and existing knowledge. Tsoukas (1996) refers to how knowledge is produced, used and transformed and Davenport and Prusak (1998) talk about the following knowledge processes: 1) Generating knowledge 2) Codifying knowledge 3) Transferring knowledge and 4) Storing knowledge.
Despite the small differences in labelling the knowledge processes, most scholars identify the same processes. The knowledge processes are considered to be chains in some kind of knowledge value chain, which is followed iteratively and repetitively. Knowledge being created becomes increasingly valuable for an organisation when it is combined with other knowledge, when it is shared among its members, when it is also used by these organisation members and finally when it is maintained and stored for future use.
Many scholars perceive the importance of each of the knowledge processes differently. For example, whereas, Nonaka (1991) primarily focus on knowledge creation, Grant (1996) asserts that the primary role of organisations is to integrate knowledge, referring to a coordinated application of knowledge. Although, it is believed that the distinguishing between the knowledge processes is not absolute and that they are interrelated, this research focuses on knowledge sharing since it is interested in the cultural motivation to do so. The notion of 'sharing' is chosen, rather than distributing, transferring or transmitting, in order to stress the social, interactive and situated nature of the process. In this context, knowledge sharing is just one, yet very important, of the knowledge processes that is addressed within knowledge management.
Each discipline has its own assumptions and has a different level of sophistication. Their points of view are based on some, often unstated, assumptions with respect to their epistemology, ontology, perspective, and axiology. These in turn influence how knowledge sharing processes, human beings and organisations are conceptualised. Therefore, the underlying basis of the relevant concepts and ideas has to be examined. The following two sections elaborate on how epistemology and ontology affect the way in which academics and businessmen conduct inquiry and construct theories about knowledge sharing.
2.3 Conceptualisation of knowledge
Before being able to understand and analyse knowledge sharing, one has to understand the way knowledge is perceived. "Knowledge is a broad and abstract notion that has defined epistemological debate in western philosophy since the classical Greek era" (Alavi & Leidner, 2001, P.107). Although the question of what is knowledge? It was the quaintest question for the greatest thinkers in the world (e.g. Descartes, Foucault, Kant, Kuhn, Popper), no clear consensus has emerged. Therefore, the objective of this research is not to join this never-ending discourse. Only those characteristics of knowledge are addressed that have related to this research.
First, knowledge is distinguished from data and information and it is concluded that knowledge only resides in the mind of intelligent operating agents. Second, different perspectives on knowledge are described. Third, the important distinction between explicit and tacit knowing is addressed. Finally, it is discussed whether something like organisational knowledge actually exists and can be identified in practice.
2.3.1 Data, information and knowledge
One way to define knowledge is by distinguishing it from concepts; information and data. After all, "if knowledge is not something that is different from data or information, then there is nothing new or interesting in knowledge management" (Fahey and Prusak, 1998, P. 265)
Dretske (1981) describes information as "that commodity capable of yielding knowledge, and what information a signal carries is what we can learn from it. (â€¦) Knowledge is identified with information-produced (or sustained) belief, but the information a person receives is relative to what he or she already knows about the possibilities at the source" (PP. 44, 86). Davenport and Prusak (1998) give the following description: "Knowledge is a fluid mix of framed experience, values, contextual information, and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices, and norms (â€¦) Knowledge derives from information as information derives from data. If information is to become knowledge, humans must do virtually all the work." (PP. 3, 4)
Boissot (1998) gives a quite similar description: "Knowledge builds on information that is extracted from data. (â€¦) Data (â€¦) may or may not convey information to an agent. Whether it does so or not depends on an agent's prior stock of knowledge. (â€¦) Thus whereas, data can be characterized as a property of things, knowledge is a property of agents predisposing them to act in a particular circumstances. Information is that subset of the data residing in things that activates an agent - it is filtered from the data by the agent's perceptual or conceptual apparatus. Information, in effect, establishes a relationship between things and agents. (â€¦) (Knowledge) either consolidates or undergoes modifications with the arrival of new information. In contrast to information, knowledge cannot be directly observed. Its existence can only be inferred from the action of agents." (P. 12)
Not all authors regard knowledge as something "higher" than information - Tuomi (1999) proposes a reversed hierarchy where data comes last - knowledge is regarded as a prerequisite and used to create information and data: "There are no isolated pieces of simple facts unless someone has created them using his or her knowledge. Data can emerge only if a meaning structure, or semantics, is first fixed and then used to represent information". (P. 107)
"A commonly held view (...) is that data is raw numbers and facts, information is processed data, and knowledge is authenticated information. (...) Yet, the presumption of a hierarchy from data to information to knowledge, with each varying along some dimension such as context, usefulness or interpretability, rarely survives scrupulous evaluation. 'The' key (...) 'distinction' between information and knowledge is not found in their content, structure, accuracy or utility, 'but in the fact that' knowledge is information possessed in the mind of individuals."( Alavi & Leidner (2001, P. 109) And they "posit that information is converted to knowledge once it is processed in the mind of individuals and knowledge becomes information once it is articulated and presented in the form of text, graphics, words, or other symbolic forms." (P. 109)
Some authors (Boersma and Stegwee, 1996; Spek and Spijkervet, 1997) argue that knowledge can also be embedded in entities other than human beings. Besides human knowledge (knowledge in the heads of the people of an organisation), Boersma and Stegwee (1996) also identifies "Mechanized knowledge is usually aimed at the accomplishment of a specific task. As the knowledge is embedded within a machine, it is almost impossible to access, transfer, or alter mechanized knowledge. It basically is just there and performs its function in the daily operations of the organization.", "Documented knowledge is usually not necessary for the day-to-day operations of an organization. It should, however, be available and easily accessible, because the organization has to be able to probe it's 'memory'. Audits and lawsuits are bound to rely upon documented knowledge, but also may research and development initiatives. The need to access documented knowledge is often hard to anticipate, but documented knowledge should always be available for offhand retrieval." and "Automated knowledge is found in information, expert, or knowledge-based systems. These systems contain information and sometimes knowledge necessary to carry out tasks like diagnosis, design, therapy, and planning. Often they are designed as decision support systems, assisting the human operator of the system in taking the appropriate decision within a specified domain." (PP. 6, 7)
This classification resembles Laseur's (1991) distinction between 'humanware', 'hardware' and 'paperware'. In addition, Van Der Spek and Spijkervet (1997) argue that knowledge can be 'carried' by people, documentation (including automated documentation) and technology.
The importance of information embedded in documented routines and technologies is acknowledged important in the process of knowing and doing (for example, technologies might yield knowledge with reverse engineering). However, documented, mechanised and automated knowledge are considered as information in this research, rather than knowledge, following the definition of Alavi and Leidner (2001)
2.3.2 Perspectives on knowledge
More than one perspective on knowledge has existed among scholars and practitioners (Wasko and Faraj, 2000). Knowledge may be viewed as an object, and it is defined as "justified true belief". This perspective considers knowledge to be "an integral, self-sufficient substance, theoretically independent of the situations in which it is learned and used" (Brown, et al., 1989, P. 32), and assumes "that 'knowledge' can be codified and separated from the minds of people." (Wasko and Faraj, 2000, P. 157) Following the description of Alavi and Leidner, this perspective on knowledge actually refers to information.
Whereas, the second perspective "defines knowledge as "that which is known", and it suggests that, "knowledge resides only in the mind of individuals. Only people can 'know' and convert 'knowing' into action, and it is the act of thinking that can transform information into knowledge and create new knowledge" (Wasko & Faraj, 2000, P. 159), This in line with Polanyi (1998) who considers knowledge to be embedded in individuals.
While these two perspectives on knowledge still considers as a starting point for many of studies, another perspective has been received the attention, which defines knowledge as "the social practice of knowing", addressing the social character of knowledge (Blackler, 1995). This perspective considers Knowledge to be "embedded in community perspective suggests that knowledge supercedes any one individual, is highly context dependent and is embedded within a community." (Wasko & Faraj, 2000, P. 160) "Rather than talking of knowledge, with its connotations of abstraction, progress, permanency and mentalism, it is more helpful to talk about the process of knowing" (Blackler, 1995, 1035), consequently, the three perspectives of Wasko and Faraj (2000) can be relabelled as 'potential knowing', 'personal knowing' and 'social knowing'. Other authors have come up with other types of perspectives on knowledge, addressing different epistemological and ontological characteristics of knowledge. For example, Hedlund and Nonaka (1993) propose three perspectives to view knowledge: 1) knowledge as a stock (focus on storing), 2) knowledge as a flow (focus on transferring), and 3) knowledge as interactions (focus on transformation). Alavi and Leidner (2001) distinguish five other perspectives on knowledge: "1) a state of mind (the state of knowing and understanding), 2) an object (knowledge to be stored and manipulated), 3) a process (applying expertise), 4) knowledge as a condition of access to information, or 5) a capability (knowledge as the potential to influence action)." (P. 109) Grant (1996) addresses the following characteristics "as pertinent to the utilisation of knowledge within the firm to create value, transferability, capacity for aggregation, appropriability" (PP. 110-120).
In line with defining knowledge as "justified belief that increases an entity's capacity for effective action" (Huber, 1991; Nonaka, 1994), in this research knowledge is defined as: "collective understanding plus the ability to transform this understanding into actions (skills), which yields performance being dependent of the situation in which it is learned and used"
Knowledge being shared in the case studies may not always meet the requirements of this definition. This definition of knowledge, it is chosen in order to stress its situated nature and its action orientation. The definition is meant to indicate how knowledge is perceived in this research, rather than strictly limiting the scope of this research.
2.3.3 Knowledge taxonomies
Besides different perspectives on knowledge, many other classifications and taxonomies of knowledge have been developed. In this section, examples are briefly addressed with respect to different types, classes, domains, cruciality, level of detail and images of knowledge.
Types: Anderson (1983) distinguishes between 'declarative' and 'procedural' knowledge to capture the difference between knowing facts and having the skills to do something. Paris, Lipson and Wixson (1983, P. 303) add a third type, which they label 'conditional knowledge' in order to characterise the knowledge that signals when and how to apply declarative and procedural knowledge. Also, Sackmann (1992) uses the heading 'cultural knowledge' to refer to commonly held types of knowledge. She identifies four types of cultural knowledge: dictionary knowledge (commonly held descriptions, words, definitions), directory knowledge (commonly held practices), recipe knowledge (commonly held ideas about how things should be, norms), and axiomatic knowledge (commonly held assumptions about why things happen).
Classes: Machlup (1980) classifies knowledge into five classes: (1) practical e.g., professional or political; (2) intellectual, satisfying cultural curiosity; (3) pastime, recreational knowledge; (4) spiritual, religious knowledge; and (5) unwanted knowledge, accidentally acquired and of no immediate interest." (P. 108)
Domain: Knowledge is frequently classified based on domains that are useful to organisations. Bertrams (2003) distinguishes between specialised knowledge (knowledge which is required in order to produce products or services), market knowledge (knowledge about current and potential markets, like competitors, suppliers, consumers), client knowledge (knowledge about the needs and characteristics of the consumers) and organisation knowledge (knowledge about the mission, objectives, strategy, division of employees over different departments etcetera).
Cruciality: Boersma (2002) addresses the cruciality of knowledge and distinguishes three kinds of knowledge: basic, specific and crucial knowledge. Basic knowledge is inherent to running a company and is available in each organisation. This knowledge is independent from the organisation type and is mostly not part of the core competence of an organisation. Specific knowledge is related to a particular industry in which an organisation is operating. The knowledge is needed to analyse and solve specific problems. Crucial knowledge comprises the knowledge that provides an organisation with its competitive advantage, narrowly related to the core competence of the organisation. The more crucial particular knowledge is for the organisation, the better managers have to monitor it. Developments in the market can lead to the necessity to construct new crucial knowledge or to dispose of obsolete knowledge, which makes the typology relative in nature.
Level of detail: Wigg (1993) distinguishes between eight knowledge detail dimensions: Knowledge domain, knowledge region, knowledge section, knowledge segment, knowledge element, knowledge fragment and knowledge atom. Also, Boisot (1995; 1998) distinguishes between abstract and concrete knowledge.
Images: Blacker (1995), based on the work of Collins (1993), presents a classification of knowledge images as embodied, embrained, embedded, encoded and encultured. Embodied knowledge is action orientated and only partly explicit. This type of knowledge is "individual- tacit" (Lam, 1998, P. 9). It represents the "know-how" of the individual. Embedded is knowledge that resides in systemic routines. "Embedded knowledge is analysable in system terms, the relationship between, for example, technologies, roles, formal procedures and emergent routines" (Blacker, 1995, P. 1024). Lam states: "Embedded knowledge is organic and dynamic; it is an emergent form of knowledge capable of supporting complex patterns of interaction in the absence of written rules. It is, however, also 'sticky' and 'path dependent': its generation and application can be constrained by the established organising principles and patterns of social relations" (Lam, 1998, P. 11). Embedded knowledge can be linked, according to Lam to communities of practice and can thus relate to "know-who".
Embrained is knowledge that is dependent on conceptual skill and cognitive abilities. According to Lam, embrained knowledge is individually explicit, this type of knowledge can be "acquired primarily through formal education and training, in other words 'learning-by-studying'" (Lam, 1998, P. 10), this type of knowledge can relate to the "know what" of individuals.
Encultured refers to the process of achieving shared understandings. Here we are dealing with cultural meaning systems that are constructed within the organisation. This knowledge is linked to socialisation as well as language (Collins, 1993).
Encoded knowledge is information conveyed by signs and symbols. This type of knowledge is collective explicit accessible to the wider organisation. (Lam, 1998).
2.3.4 Explicit and tacit knowing
A classification that can be seen as one of the most influential in the knowledge management literature is the distinction between explicit and tacit knowledge. A large number of authors refer to this typology and use it extensively when approaching knowledge or defining knowledge management. Stewart (2003); Tsoukas (2005); Tsoukas (2001); Castells (2000); Snowden (2002); Snowden (2000); Seely Brown & Duguid (1998); Fowler (2000); Firestone & McElroy (2003); Stacey (2001); Stacey (2000); Allee (1997a); Wigg (1997a); Popadiuk & Choo (2006); Tuomi (2002); Bhardwaj & Monin (2006); Mooradian (2005); Alavi & Leidner (2001).
Michael Polanyi (1983; 1998) who developed this distinction originally and it was Nonaka (1991; 1994; 1995) who popularised the concepts of explicit and tacit knowledge with his own interpretation of Polanyi's work. In this section, Nonaka's interpretation of organisational knowledge is described in order to clarify how has identified between tacit and explicit knowledge. Following Brohm (2005), it is believed that Polanyi's original distinction is more valuable than that of Nonaka, and this is based on the argument, which says that Nonaka mixes up explicit knowledge with codified knowledge, as is described next.
Spiral of organisational knowledge creation
Nonaka (1994) introduced his model of organisational knowledge creation, which demonstrates the relation between the epistemological dimension and ontological dimension of knowledge creation (see Figure 3). The epistemological dimension focuses on a distinction between 'tacit' and 'explicit' knowledge. According to Nonaka and Takeuchi, the main classification is as follows: "we classify human knowledge into two kinds. One is explicit knowledge, which can be articulated in formal language including grammatical statements, mathematical expressions, specifications, manuals, and so forth. This kind of knowledge thus can be transmitted across individuals formally and easily. (...)A more important kind of knowledge is tacit knowledge, which is hard to articulate with formal language. It is personal knowledge embedded in individual experience and involves intangible factors such as personal belief, perspective, and the value system" (Nonaka &Takeuchi, 1995, p. viii). In this definition, explicit knowledge is regarded as an item that can more easily be managed and shared. In this definition, explicit knowledge is "formal and systematic" (Nonaka, 1999)
Figure 5. spiral of organizational knowledge creation
Source: (Nonaka, 1994 p.20)
The ontological dimension of the model of knowledge creation deals with the level of social interaction. Nonaka argues that knowledge may be held on an individual, a group, an organisation and even by several organisations level. The emphasis is on individual knowledge becoming shared knowledge through interaction, the context and the content of knowledge. The explicit / tacit dimension can also be linked to the conversion of knowledge, transforming existing knowledge into new knowledge bringing about innovation within the organisation.
Although knowledge starts with an individual, "a process 'organizationally' amplifies the knowledge created by individuals and crystallizes it as a part of the knowledge network of the organization." (Nonaka & Takeuchi, 1995, P. 59)
The assumption of Nonaka's model is that organisational knowledge is created through conversion between tacit and explicit knowledge through of four modes of conversion. These four phases of knowledge conversion are:
In this mode, an individual can acquire tacit knowledge through interaction and sharing. The individual can learn through seeing and doing, a type of "on the job" knowledge acquisition. Externalization
This is the process where tacit knowledge is converted to explicit concepts. What is learnt through socialisation can now be utilised in explicit form.
Combination occurs when individuals bring together various elements of explicit knowledge from various sources to produce new explicit knowledge
With internalisation, explicit knowledge is converted into tacit knowledge and the cycle can start again to share this tacit knowledge via socialisation.
Whereas, 'socialisation' is related to organisational culture, 'combination' to information processing and 'internalisation' to organisational learning, Nonaka argues that 'externalisation' is not well developed. Based on several success stories, he describes how tacit knowledge can be converted into explicit knowledge within organisations by connecting contrdictive ideas through metaphors; these contradictions are resolving through analogies; and the new created concepts are crystallising and embodying in models.
Following Nonaka, Spender (1996b) argues that an individual can hold knowledge or a collectively and that knowledge can be tacit and explicit. Spender distinguishes "four types of organisational knowledge: conscious knowledge (explicit knowledge held by individual), objectified knowledge (explicit knowledge held by the organization), automatic knowledge (preconscious knowledge held by individual) and collective knowledge (highly context-dependent knowledge which is manifested in the practice of an organization)." (P. 52)
Cook and Brown (1999) come up with a similar typology but do not believe in Nonaka's knowledge conversion and try to connect the knowledge perspective with the knowing perspective. Cook and Brown make three contentions:
"First, each of the four categories of knowledge inherent in the explicit-tacit and individual-group distinctions is a distinct form of knowledge on equal standing with the other three, non is subordinate to or made up out of any other. Also, this distinct character is reflected in the fact that each form of knowledge does work that the others cannot." (P. 52). This means that no one of forms of knowledge (explicit or tacit) can be converted into the other one. Nevertheless, "each form of knowledge can often be used as an aid in acquiring the other." (P. 56)
Second, "in addition to talking about the four distinct forms of knowledge we also want to be able to speak about the epistemic work done by human action itself - that is, about what is part of practice as well as what is possessed in the head. (...) Therefore, in addition to the traditional epistemology of possession, there needs to be, in our view, a parallel epistemology of practice, which takes ways of knowing as its focus.", "what is possessed 'knowledge' and what is part of action 'knowing'." (P. 53)
Third, knowledge and knowing are not "competing, but complementary and mutually enabling." (p.53), although the suggested epistemology of practice is preferred, this research dissociates itself from the classification as such, as is described later, because both dichotomies: tacit / explicit or individual / group they are not considered distinct types of knowledge.