Davenport and Prusak (1998: 1) indicate that
Knowledge is neither information nor data, though it is related to both, and the differences between these terms are often a matter of degree.According to Melkas and Harmaakorpi (2008), data is unprocessed elements of information, which are based on fact whereas Lillrank (1997, 2003 cited in Melkas and Harmaakorpi, 2008) states that data becomes information as soon as it is processed and deliver meaningfully. Nonaka et al. (2000) mention that when well structured and placed in a meaningful context, information transforms into knowledge. According to Krogh et al. (2000), Knowledge is defined as a representation of reality whereas Miller et al. (2001: 365) define knowledge as
“… That which is derived and inferred from assimilating information against perceived context, experience or business rules”
Davenport and Prusak (1998) point out that for information to be knowledge, it should be in a state, which can be communicated, connected, compared, carried out by human to bring results knowledge is a flow of information, which is formally structures. Newell et al. (2002) provide a comparison between structural and processual perspective on knowledge where the former illustrates knowledge as a distinct entity generated through a particular social process and acquired by individual and organizations whereas the later states the dynamism of knowledge, which is generated amid individuals and organizations via application, actions and social interactions.
Nonaka et al. (2000) mention that knowledge can be either tacit or explicit According to them, explicit knowledge is codified or expressed in written or published form or the like through which it is communicated and exchanged to others whereas implicit or tacit knowledge cannot be codified and communicated as this is what people have inside them – their personal knowledge, insights, perception and the like and embedded in the execution of their actions. Alavi and Leidner (1999) point out that when codified, expressed and communicated, knowledge becomes information.
However, Sanchez (2003) points out that effective management such knowledge is very crucial for the efficacy of the organizations. DeJarnett (1996: 3) defines Knowledge Management as
“…knowledge creation, which is followed by knowledge interpretation, knowledge dissemination and use, and knowledge retention and refinement”
Alavi and Leidner (1999) provide three different viewpoints of Knowledge Management:
Information based viewpoint states that knowledge management is organization’s information store that provides information to employees who contains the knowledge and where, how to find and use them. The viewpoint also tells about information features and their effective and efficient use. Technology based perspective shows an association between knowledge management and information technology where organizational size and existing information system determine the efficacy of knowledge management system whereas the culture based perspective indicates that knowledge management is a function of continuous learning, communication and dissemination. Quintas et al. (1997: 387) view knowledge management as
“Knowledge management is the process of continually managing knowledge of all kinds to meet existing and emerging needs, to identify and exploit acquired knowledge assets and to develop new opportunities”
Laudon and Laudon (2000) imply that organizational efficacy lies on the capability of how effectively the organizations learn, exert, and manage knowledge in different states in an organizational setting.
• Alavi, M. and Leidner, D. E. (1999), “Knowledge Management Systems: Issues, Challenges, and Benefits”, Communication of AIS, Vol. 1, No. 7, pp. 2-37.
• Davenport, T. H. and Prusak, L. (1998), Working Knowledge: How Organizations Manage what They Know, Harvard University Press, Boston, Mass.
• DeJarnett, L.R. (1996), “Knowledge–The Latest Thing”, Information Strategy: The Executive’s Journal, Vol. 12, No. 2, pp. 3-5.
• Krogh, G. V., Ichijo, K. and Nonaka, I. (2000), Enabling Knowledge Creation: How to Unlock the Mystery of Tacit Knowledge and Release the Power of Innovation, Oxford University Press, US.
• Laudon, K. C. and Laudon, J. P. (2000), Management information systems: organization and technology in the networked enterprise, Prentice Hall, Upper Saddle River: NJ.
• Melkas, H. and Harmaakorpi, V. (2008), “Data, Information and Knowledge in Regional Innovation Networks: Quality considerations and brokerage functions”, European Journal of Innovation Management, Vol. 11, No. 1, pp. 103-124.
• Miller, B., Malloy, M. A., Masek, E. and Wild, C. (2001), “Towards a Framework for Managing the Information Environment”, Information and Knowledge Systems Management, Vol. 2, No. 4, pp. 359-384.
• Newell, S., Robertson, M., Scarbrough, and Swan, J. (2002), Managing Knowledge Work, Palgrave, Basingstoke, Hampshire, NY.
• Nonaka, I., Toyama, R. and Konno, N. (2000), “SECI, Ba, and Leadership: A Unified Model of Dynamic Knowledge Creation”, Long Range Planning, Vol. 33, No. 1, pp. 5-34.
• Quintas, P., Lefrere, P. and Jones, G. (1997), “Knowledge Management: A Strategic Agenda”, Journal of Long Range Planning, Vol. 30 No. 3, pp. 385-391.
• Sanchez, R. (2003), Knowledge and Organizational Competence, Oxford University Press, US.