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As Francis Bacon said, Knowledge is power (Liao, 2003). Knowledge has been a subject of philosophy for centuries. It is challenging to develop accurate definitions for knowledge and debate on its anatomy. Generally, knowledge is made up of both data and information.
Data is usually raw symbols, alphabets and numbers that merely exist and have no significance beyond its existence. Data represent objects, events and/or their properties (Nunamaker, Romano and Briggs, 2001). Raw data are lacks of context and does not have meaning in and of it, nor does it have any meaningful relations to anything. However, data are carriers of information where information can be stored or transferred (Kock, McQueen and Corner, 1997). Hence, this make data indispensable as it is the basic structural and functional unit of all information.
On the contrary, information consists of organised data and presented in a significance manner, in the form of relationships, chronologies or structures. Information is a representation, an outline, sketch, or giving form. It is a set of data that has been given meaning, to the recipient, through relational associations (Nunamaker et al., 2001). Therefore, we regard information as meaningful, useful data, and learning about information as the process of giving form to data (Bierly, Kessler and Christensen, 2000).
Knowledge is information organised into meaningful patterns where these patterns are more than mere relations as they demonstrate a completeness and consistency of relations and to create their own context (Nunamaker et al., 2001). Knowledge is contextual information, values, framed experience and expert insights that provides a framework for evaluating and incorporating new experience and information (Yahya and Goh, 2002). While information is being descriptive, where it refers to the past and present, knowledge is saliently predictive, where it provides the basis for the prediction of the future with a degree of certainty, based on information about the past and present (Kock et al., 1997). In a nutshell, data are organised sequence of items or events, information is a context-based arrangement of items by relations between these data, and knowledge is the judgement of the significance of events and items, which comes form a particular context and/or theory (Koh, Gunasekaran, Thomas and Arunachalam, 2005).
Differences of data, information and knowledge can only be discovered through external means or from user s point of perception. Table 2 1 briefly outlines the distinctions of the three concepts. Data and information are often distinguished based on their presentation whereas information and knowledge are distinguished based on interpretation of recipient (Bhatt, 2001). Although the concepts of data, information and knowledge are three distinct and abstract entities, they are seamlessly integrated. They can be seen as existing on a single continuum (Koh et al., 2005). Figure 2 1shows the data-knowledge continuum.
Table 2 1: Distinctions of the three entities
Data Raw facts
Information Meaningful, useful data
Knowledge Clear understanding of information
SOURCE: Bierly et al. (2000). Organisational learning, knowledge and wisdom. Journal of Organisational Change Management, 13(6), 595-618.
Figure 2 1: Data and Knowledge Continuum
SOURCE: Probst, Raub and Romhardt s (2000) study as cited in Koh et al. (2005) The application of knowledge management in call centres, Journal of Knowledge Management, Vol. 9, No. 4, pp. 56-59.
In many literature, researchers divide knowledge into two main areas; tacit and explicit knowledge. Polanyi proposed the knowledge dichotomy of explicit and tacit dimension back in 1950s (Li and Gao, 2003). Tacit knowledge is defined as non-verbalised, intuitive and unarticulated, action-based and unformulated, highly personal and hard to transfer. It is the personal knowledge used by individuals to perform their work and achievable through personal experience but cannot, or difficult, to be articulated (Mohamed, Stankosky and Murray, 2006). Another form of tacit knowledge, implicit knowledge, is the kind of knowledge that is shared and comprehend by people or community who are either unwilling, or unable to express it explicitly (for instance, due to cultural factors) without a proper space (Li and Gao, 2003). There are two dimension of tacit knowledge; i.e. technical dimension, which comprises of informal personal skill sets or crafts (often referred to know-how ) and cognitive dimension, that encompassed belief, values, models and schema (Civi, 2000).
On the other hand, explicit knowledge is tangible, clearly stated and consisting of details, which can be recorded and stored. Explicit knowledge is formalised and written, expressed in the form of data, verbal, diagrams, scientific formulae, specifications, manual, or textbooks. Knowledge of such category is transferred easily in community and accessible by others as it is codified and stored in different repositories. Differences in both school of knowledge can be best described in an example of architecting a sculpture. Explicit knowledge for design covers templates and practical geometric notion that masons and artisans would use to explain, plan and execute the task whereas tacit knowledge in this activity would include craftsmanship such as the artisan s knowledge of how hard to hit a stone without cracking it. While objectivity is the hallmark of explicit knowledge, tacit knowledge is characterised by subjectivity (Sivakumar and Roy, 2004). Table 2 2 depicts the differences between the two types of knowledge.
Table 2 2: Differences between the two types of knowledge
Tacit Knowledge (Subjective) Explicit Knowledge (Objective)
Knowledge of experience (body) Knowledge or rationality (mind)
Simultaneous knowledge (here and now) Sequential knowledge (there and then)
Analogue knowledge (practice) Digital Knowledge (theory)
SOURCE: Nonaka and Takeuchi s (1995) study as cited in Perez and Pablos (2003). Knowledge Management and Organisational Competitiveness: A framework for human capital analysis. Journal of Knowledge Management, 7(3), 82-91.
Although there is a distinction between tacit and explicit knowledge, they are not mutually exclusive to each other (Gao, Li and Clarke, 2008). Knowledge moves from tacit to explicit, vice-versa, and any other combinations. In 1994, Nonaka established a model of knowledge creation where knowledge are interacted and interchanged among mankind in their creative activities. Generally, the model discussed four different modes of knowledge conversion models as illustrated in Figure 2 2.
Nonaka (1994) postulated that knowledge is created through diffusion between tacit and explicit knowledge in four different dimension of knowledge conversion: (1) from tacit knowledge to tacit knowledge, (2) from explicit to explicit knowledge, (3) from tacit to explicit knowledge, and (4) from explicit to tacit knowledge.
Figure 2 2: Four modes of knowledge conversion
SOURCE: Nonaka, I. (1994). A Dynamic Theory of Organisational Knowledge Creation. Organisation Science, 5(1), 14-37.
Tacit knowledge to tacit knowledge, is also called socialisation, is a process of sharing experiences which creates tacit knowledge, such as shared mental models and technical skills. The significant note here is that a learner can acquire tacit knowledge without spoken speech. Apprentices work with their mentors and discover craftsmanship through observation, imitation, and practice, in addition to verbal instructions.
Tacit to explicit knowledge, or externalisation, is a knowledge creation process where tacit knowledge becomes explicit, taking the shapes of metaphors, analogies, concepts, formulae, specifications, hypotheses or models.
Explicit knowledge to explicit knowledge, combination, involves combining different bodies of explicit knowledge. Individuals exchange and combine knowledge through exchange mechanisms, such as meetings and telephone conversations. The reconfiguring of existing information through arranging, adding, regrouping, and reapplying of explicit knowledge can lead to new knowledge.
Explicit knowledge to tacit knowledge, also referred as internalisation, is a process of incarnating explicit knowledge to tacit knowledge. This flux is similar to on-the-job (OJT) training in commercial setting. Explicit knowledge created is shared throughout an organisation and converted into tacit knowledge by individuals through internalisation (Nonaka, Toyama and Konno, 2000).
In the knowledge-creating organisation, these four conventions exist in dynamic interaction and form a spiral of knowledge (Nonaka, 1991). Knowledge created through each of the four styles of knowledge conversion interacts in the spiral of knowledge creation (Nonaka et al, 2000). Figure 2 3 shows the four styles of knowledge conversion and the evolving spiral movement of knowledge through the SECI (Socialisation, Externalisation, Combination, and Internalisation) process.
In the spiral of knowledge creation, the interaction between tacit and explicit knowledge is amplified through the four styles of knowledge conversion. This spiral grows as it hikes through the ontological levels. Discovery of knowledge through the SECI process can trigger a new spiral of knowledge creation, expanding horizontally and vertically across organisation.
Figure 2 3: SECI Process
SOURCE: Nonaka et al. (2000). SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation. Long Range Planning, 33(1) 5-34.
Nonaka (1991) exemplify the flow by citing Ikuko Tanaka s case in Matsushita. First, she learns the secrets of the Osaka International Hotel baker, through socialisation. Then, she transforms them into explicit knowledge where she can articulate to her team members at Matsushita. Subsequently, her team standardises this information, translate it into workbook and combine it in a product. Finally, they successfully internalise their own tacit knowledge repository through the experience of creating a new product. In this context, they understand in an intuitive way that products like the home bread-making machine, can provide professional quality bread.
Then, the spiral of knowledge kicks off all over again to a higher level. The new tacit insight about genuine and superior quality, developed in designing the home bread-making machine, is informally disseminated to other Matsushita employees. They adopted it to formulate equivalent quality standards for other new Matsushita products, whether household appliances or audiovisual equipments. In this way, the organisation s knowledge base grows broader in a long run.
The power of knowledge is a very important resource for upholding valuable heritage, discovering new subjects, resolving problems, creating core competencies, and initiating new situations for both individual and organisations now and in the future (Liao, 2003). In the age of rapid knowledge expansion, external and internal knowledge sources are available in abundance (Tsai and Lee, 2006). In business lexicon, questions of how knowledge is being assimilated to a competitive advantage are often asked. To benefit from knowledge, it, first, have to be managed. This is where knowledge management comes into mankind s history. So, where did knowledge manage come from?
2.2 Evolution of Knowledge Management
History of managing knowledge goes back to the earliest civilisations (Wiig, 1997a) as rational observation indicates that knowledge has been pursued as long as records of human activities are available. In the forth century BC, Aristotle noted All men by nature desire knowledge (Bogdanowicz and Bailey, 2002).
In the oral tradition, pre-writing era, knowledge are transferred by mouth to ear. Although there was no structured and proper method of managing, storing and sharing knowledge at that time, relevant knowledge was passed on from generation to generation (Cheng, 2002). For hundreds of years, owners of family businesses have passed off their commercial wisdom to their children, master craftsmen have painstakingly taught their trades to apprentices, and workers have exchanged ideas as well as know-how on the job (Hansen, Nohria and Tierney, 1999). The earliest surviving example of action to record and disseminate knowledge was first demonstrated in China, before AD 220, using woodblock printing technique for printing text, images or patterns on cloth. There is also the cuneiform of Sumer and Akkad that used a wooden stylus on baked wet clay (Ives, Torry and Gordon, 1998). Then, invention of alphabetic writing came parallel with developments in the technologies of recording media and devices. Hence, sheer quantity of knowledge, such as literary and academic works, steadily increased with the development of papyrus where they are easily recorded and transported.
Knowledge management has been studied and practiced by philosophers for centuries though the terminology was not widely used until end of 20th century. Wiig (1997b) highlights that historic developments may be portrayed by the following descriptive stages of dominant economic activities and foci:
(1) Agrarian Economies: activities revolved around accumulation and dissemination knowledge regarding hunting and gathering activities. Through their experiences, hunter-gatherers managed to develop a high level of comprehension in their territory, such as the sources of food, the dangers, and the opportunities (Cheng, 2002). Knowledge was not explicitly recognised then.
(2) Natural Resource Economies: People facilitate conversion of natural resources to commodity and sell them to markets. Knowledge started to be recognised, within the guilds and its masters.
(3) Industrial Revolution: During the 19th centuries, conversion of natural resources and manufacturing of products were increasingly better organised and mechanised to improve the efficiency of the processes adopting Frederick W. Taylor s scientific management (Bohn, 2005). Individual workers produce as much goods as possible using formalised knowledge and standardised procedures.
(4) Product Revolution: During the first half of the 20th century, notion of product sophistication started to paint the history of business. Exchange of expertise knowledge between professionals and craftsmen, particularly in the form of skills, increase tremendously.
(5) Information Revolution: During the second half of 20th century, information technology (IT) became available and resulted closer control of manufacturing, logistics, and marketing. An overwhelming of information flows between enterprises and their suppliers as well as customers.
(6) Knowledge Revolution. In the 1990s, real basis for competition has shifted towards how well knowledge and other intellectual assets are brought to make the organisations customers successful. This realisation has led to emergence of new critical success factor, how best to serve individual customers. The versatility and intelligent behaviour of knowledgeable employees in an organisation become the power and drivers that make it possible, to meet a wide range of individual customers sophisticated requirements and modem market demands.
2.3 Review of Knowledge Management
2.3.1 Definition of Knowledge Management
Although there is a strong and undoubted interest from the commercial world, the term knowledge management has no universally accepted definition (Earl and Scott, 1999) and no consensus about what the term really means (Shin, Holden and Schmidt, 2001; Salisbury, 2003). As the academic development of knowledge management has not stabilised and filtered into the industry (Choy, Yew and Lin, 2006), researchers are constantly attempting to forge their own definitions (Salisbury, 2003). Hence, different definitions of knowledge management in literatures, from the various contexts and perspectives, are specific to the researcher and their fields (Choy et al., 2006).
Bhatt (2001) posits knowledge management as a process of knowledge creation, validation, presentation, distribution, and application. Salisbury (2003) further accentuates that ongoing knowledge management cycle as deployment of comprehensive system that enhances the growth of an organisation s knowledge by creating, preserving and disseminating knowledge. As this cycle continues to build upon itself, it becomes a knowledge spiral as in the SECI process (Nonaka, et. al, 2000).
Knowledge management is a process that helps organisations find, select, organise, disseminate, and transfer important information and necessary expertise for activities, such as problem solving, dynamic learning, strategic planning and decision making (Gupta, Iyer and Aronson, 2000; Beveren, 2002). Similarly, Horwitch and Armacost (2002) defines knowledge management as the practice of creating, capturing, transferring and accessing the right knowledge information in order to design better policy, modify action and deliver results.
O Dell and Grayson (1998) believe knowledge management is a process of identifying, capturing and leveraging knowledge to help the company compete. In the same way, Singh (2008) asserts that management of knowledge is budgeting learning at an organisational level, which can be assimilated by an organisation and its members for self-renewal.
Knowledge management is the process of continually managing knowledge of all kinds to meet existing and emerging needs, to identify, exploit and develop new opportunities (Quintas, Lefrere and Jones, 1997). Knowledge management is to understand, and manage systematic knowledge, and deliberate knowledge building renewal, and application to maximise the enterprise's knowledge-related effectiveness (Wiig, 1997b).
To summarise, knowledge management are efforts designed to (1) capture knowledge; (2) store knowledge (Martensson, 2000); (3) convert personal knowledge to group-available knowledge; (4) connect people to people, people to knowledge, knowledge to people, and knowledge to knowledge; and (5) measure that knowledge to facilitate management of resources and help understand its evolution (O Leary, 1998). Knowledge management can be viewed as the management of knowledge-related activities in order to create value for an organisation (Wong and Aspinwall, 2004).
In a nutshell, knowledge management will lead an organisation to perform better and be more competitive. The purpose of managing and leveraging a company s knowledge is to maximise the returns to the organisation (Bose, 2004) and sustain its competitiveness in the global oriented market of today (Ergazakis, Karnezis, Metaxiotis, and Psarras, 2005).
2.3.2 Knowledge Management Framework
How to manage knowledge has emerged into an important issue in the past few decades, and knowledge management community has developed a wide range of technologies and applications for both academic research and practical applications (Liao, 2003). In this study, there have been several efforts in developing frameworks of knowledge management.
Wiig propose knowledge management framework of three pillars, as in Figure 2 4, which represents the major functions needed to manage knowledge. The pillars are based on a broad understanding of knowledge creation, manifestation, use, and transfer.
Figure 2 4: Pillars of Knowledge management
SOURCE: Wiig s study as cited in Holsapple, C. W., and Joshi, K. D. (1999). Description and Analysis of Existing Knowledge Management Frameworks. Proceedings of the 32nd Hawaii International Conference on System Sciences, Maui, USA.
Choo advance a knowing organisation framework (as illustrated in Figure 2 5), where an organisation uses information strategically for sense-making, knowledge creation, and decision making. These three processes are linked as a continuum of nested information activities that define an organisation which possesses the information and knowledge to act intelligently .
Figure 2 5: Model of knowing organisation
SOURCE: Choo s study as cited in Holsapple, C. W., and Joshi, K. D. (1999). Description and Analysis of Existing Knowledge Management Frameworks. Proceedings of the 32nd Hawaii International Conference on System Sciences, Maui, USA.
Van der Spek and Spijkervet identify a cycle of four knowledge management stages; i.e. conceptualise, reflect, act, and retrospect. Conceptualising phase revolves around collecting insights into knowledge resources. Subsequently, in the reflection stage, the conceptualised knowledge is evaluated using a variety of criteria, required improvements are established, and an improvement process is planned. During the act stage, new knowledge is developed, distributed, combined, and upheld. Final stage; retrospect, recognises the effects of the act stage, evaluates the results achieved in that stage, and compares old and new situations. Figure 2 6 denotes that these stages in the cycle are impacted by internal and external developments.
Figure 2 6: Framework of knowledge management
SOURCE: Van der Spek and Spijkervet study as cited in Holsapple, C. W., and Joshi, K. D. (1999). Description and Analysis of Existing Knowledge Management Frameworks. Proceedings of the 32nd Hawaii International Conference on System Sciences, Maui, USA.
Leonard advocates four knowledge-building activities that surround the core capabilities; (1) shared and creative problem solving (to produce current products), (2) implementing and integrating new methodologies and tools (to enhance internal operations), (3) experimenting and prototyping (to develop capabilities for future usage), and (4) importing and assimilating external technologies. These are knowledge creating and diffusing activities as schematise in Figure 2 7.
Figure 2 7: Core Capabilities and Knowledge Building Activities
SOURCE: Leonard s study as cited in Holsapple, C. W., and Joshi, K. D. (1999). Description and Analysis of Existing Knowledge Management Frameworks. Proceedings of the 32nd Hawaii International Conference on System Sciences, Maui, USA.
Petrash (1996) engenders a knowledge management model involves three types of organisational resources that are referred as intellectual capital: human capital, organisational capital, and customer capital as shown in Figure 2 8. Human capital is the knowledge that each individual possesses and develops. Organisational capital is the knowledge that has been recognised as the norms, processes and culture of an organisation. Then, customer capital is the perceived value determined by a customer from doing business with a supplier of goods and/or services. (Holsapple and Joshi, 1999). Flux of these capitals would lead to value creation to the organisation.
Figure 2 8: Intellectual capital model
SOURCE: Petrash, G. (1996). Dow's Journey to a Knowledge Value Management Culture. European Management Journal, 14(4), 365-373.
Nonaka (1994) posits that organisational knowledge creation, as distinct from individual knowledge creation, takes place when all four modes of knowledge creation; socialisation, combination, externalisation and internalisation, are organisationally managed to form a continual cycle. This cycle is shaped by a series of shifts between different modes of knowledge conversion. The interactions between tacit knowledge and explicit knowledge will tend to improve and grow as more participants the organisation become involved. Thus, organisational knowledge creation can be viewed as an upward spiral march, commencing at the individual level moving up to the collective level, and then to the organisational level, sometimes reaching out to the inter-organisational level. Figure 2 9 portrays the transfusion of knowledge.
Figure 2 9: Spiral of organisation knowledge creation
SOURCE: Nonaka et al. (2000). SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation. Long Range Planning, 33(1), 5-34.
Stankosky and Baldanza developed a conceptual knowledge management framework comprises of four pillars as foundation of any knowledge management system (Mohamed, Stankosky and Murray, 2006). This is portrayed in Figure 2 10. The four pillars personify:
(1) leadership that, develops a business strategy to survive, vision itself to succeed, establishes and implements the strategy, and nourishes the culture and climate, as well as interacts with the environment.
(2) organisation, a structure which supports strategy. The right business processes and performance management system must be strong enough to deal with turbulence yet flexible enough to adapt to change.
(3) technology is an enabler, essential asset for decision support, data warehousing, process modelling, management tools, and overall communications. Technology must support the business strategy, add value, and be measured.
(4) learning, lessons learned are actualised to improve effectiveness and efficiency. It must build from managing information, to building enterprise-wide knowledge, to managing that knowledge, to organisational learning and change.
Figure 2 10: Knowledge management four pillars
SOURCE: Stankosky and Baldanza s (2000) study as cited in Mohamed, M., Stankosky, M. and Murray, A. (2006). Knowledge management and information technology: Can they work in perfect harmony? Journal of Knowledge Management, 10(3), 103-116.
Firestone and McElroy (2005) presented a three-tier framework (as in Figure 2 11) of business processes and outcomes differentiating operational business processes, knowledge processes, and procedures for managing knowledge processes. Knowledge management is the set of process that seeks to change the organisation s existing pattern of knowledge processing to enhance its outcomes. There are two knowledge processes and knowledge integration. Knowledge production is the process where an organisation executes as well as produces new general knowledge; and other knowledge, where creation is non-routine. On the other hand, knowledge integration is the process to convey this new knowledge to individuals and groups in the organisation Operational processes are merely using use knowledge but, apart from routinely cultivating knowledge about specific situations and conditions, do not produce or integrate it.
Figure 2 11: Three-tier framework
SOURCE: Firestone, and McElroy. (2005). Doing knowledge management. The Learning Organisation, 12(2), 189-212.
Each of the framework or models addresses certain knowledge management elements; however, none of them appears to subsume all of the others. However, these frameworks represent a congruence of many bodies of literature including management, organisational behaviour and information systems. Thus, successful knowledge management initiatives require a tripartite view; namely the incorporation of people, process and technology (Bhatt, 2001; Massey, Montoya-Weiss, and O Driscoll, 2002; Gorelick and Tantawy-Bonsou, 2003; Cong and Pandya, 2003; Yang, Chen, and Shao, 2004; Ergazakis et al., 2005; Wickramasinghe, 2006; Dyer, 2007; and Deng, 2008). Generally, knowledge management involves four key steps of creating knowledge, storing knowledge, transferring knowledge and reusing knowledge. Hence, the synergy of three knowledge management essences; people, process and technology, on the four steps of knowledge management forms knowledge management diamond as shown in Figure 2 12.
Figure 2 12: Knowledge management diamond
SOURCE: Wickramasinghe, N. (2006). Knowledge creation: a meta-framework. International Journal of Innovation and Learning, 3(5), 558-573.
The premise for knowledge management is based on a paradigm shift in the business environment, where knowledge is central to organisational performance (Wickramasinghe, 2006). Organisational knowledge is form through unique patterns of interactions between people, process and technology, which other organisation cannot imitate easily, because these interactions are form by the organisation s unique history and culture (Bhatt, 2001). The interactions between people, process and technology has critical significance on knowledge management because hallmark of interaction between technologies, techniques, and people is unique to an organisation, and it cannot be traded easily in the marketplace. Thus, people, processes, and technology are the three key elements of the environment. As the business environment becomes more turbulent and time dependent, organisational productivity often depends on an in-depth knowledge of people, processes, and technology (Nelson and Cooprider, 1996).