A Mapping of Knowledge Management Techniques and Tools for Sustainable Growth in the Public Sector

A Mapping of Knowledge Management Techniques and Tools for Sustainable Growth in the Public Sector

Loukas K. Tsironis (Department of Business Administration, University of Macedonia, Greece) and Theodore Tarnanidis (University of Macedonia, Greece)
Copyright: © 2020 |Pages: 23
DOI: 10.4018/978-1-7998-1940-0.ch002

Abstract

This chapter seeks to determine the criteria that lead to the excellence of knowledge management in the public sector. The authors discuss issues of what exactly knowledge means and how knowledge management is defined, how an organization will capture, preserve, and diffuse knowledge, and why knowledge management is ultimately important for predictable future developments. Knowledge management is considered a prerequisite for achieving innovation and competitiveness both within and outside the organization as it promotes the consolidation of an organization in the long term with a clear focus on strategic importance. Likewise, knowledge management programs can be applied to different areas of an organization in the public sector. However, it should be mentioned that the difficulties that arise in their implementation are many, as various concerns arise, which are directly related to the equal mappings of knowledge and its measurement.
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Defining Knowledge Management In The Public Sector

According to Chourides et al. (2003) about knowledge is the understanding gained through experience, observation and daily operational tasks study. In a retrospective development of the rationale of knowledge, three different approaches or types of Knowledge are mentioned exist, (1) the positivistic approach, (2) the interpretative approach, and (3) the organic approach. Initially, there was a confusion in the definition of Data, Information, and Knowledge (Bhatt, 2001). More specifically and in accordance with the positivistic approach, Knowledge and Data have been used simultaneously. For this reason, particular emphasis was placed on data generation and measurement and storage for further use.

Later on, with the interpretive approach, it is perceived that there is a differentiation between data and information, and it is defined and knowledge management requires the conception and scheduling of information (Marr & Spender, 2002).With the organic approach, concepts are separated, defining Data as structured transaction records and Information as Data in a message format (Davenport & Prusak, 1998), in the sense of being a sender and a recipient. According to this definition, the Data inform and, by extension, influence or alter the perception of the recipient. The organic approach is supposed to reflect the current reality.

Key Terms in this Chapter

Knowledge Management: Knowledge management is a system that helps people in an organization share, access, and update business knowledge and information.

ICT: Refers to technologies that provide access to information through telecommunications. It is similar to information technology (IT), but focuses primarily on communication technologies.

Expert Tools: Designed to solve complex problems by reasoning through bodies of knowledge.

Data Mining: The actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records.

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