More recently, development of social computing tools (such as blogs and wikis) have allowed more unstructured, self-governing or ecosystem approaches to the transfer, capture and creation of knowledge, including the development of new forms of communities, networks, or matrixed organisations. However such tools for the most part are still based on text and code, and thus represent explicit knowledge transfer. These tools face challenges in distilling meaningful re-usable knowledge and ensuring that their content is transmissible through diverse channels (Andrus 2005).

Software tools in knowledge management are a collection of technologies and are not necessarily acquired as a single software solution. Furthermore, these knowledge management software tools have the advantage of using the organisation’s existing information technology infrastructure. Organisations and business decision makers spend a great deal of resources and make significant investments in the latest technology, systems and infrastructure to support knowledge management. It is imperative that these investments are validated properly, made wisely and that the most appropriate technologies and software tools are selected or combined to facilitate knowledge management. A set of characteristics that should support decision makers in the selection of software tools for knowledge management are available.

Knowledge management has also become a cornerstone in emerging business strategies such as Service Lifecycle Management (SLM) with companies increasingly turning to software vendors to enhance their efficiency in industries including, but not limited to, the aviation industry.

• Making available increased knowledge content in the development and provision of products and services
• Achieving shorter new product development cycles
• Facilitating and managing innovation and organizational learning
• Leveraging the expertise of people across the organization
• Increasing network connectivity between internal and external individuals
• Managing business environments and allowing employees to obtain relevant insights and ideas appropriate to their work
• Solving intractable or wicked problems
• Managing intellectual capital and intellectual assets in the workforce (such as the expertise and know-how possessed by key individuals)

Debate exists whether KM is more than a passing fad, though increasing amount of research in this field may hopefully help to answer this question, as well as create consensus on what elements of KM help determine the success or failure of such efforts (Wilson 2002)

One strategy to KM involves actively managing knowledge (push strategy). In such an instance, individuals strive to explicitly encode their knowledge into a shared knowledge repository, such as a database, as well as retrieving knowledge they need that other individuals have provided to the repository ^[11]. This is also commonly known as the Codification approach to KM.

Another strategy to KM involves individuals making knowledge requests of experts associated with a particular subject on an ad hoc basis (pull strategy). In such an instance, expert individual(s) can provide their insights to the particular person or people needing this (Snowden 2002). This is also commonly known as the Personalization approach to KM.

Other knowledge management strategies for companies include:

• rewards (as a means of motivating for knowledge sharing)
• storytelling (as a means of transferring tacit knowledge)
• cross-project learning
• after action reviews
• knowledge mapping (a map of knowledge repositories within a company accessible by all)
• communities of practice
• expert directories (to enable knowledge seeker to reach to the experts)
• best practice transfer
• competence management (systematic evaluation and planning of competences of individual organization members)
• proximity & architecture (the physical situation of employees can be either conducive or obstructive to knowledge sharing)
• master-apprentice relationship
• collaborative technologies (groupware, etc)
• knowledge repositories (databases, bookmarking engines, etc)
• measuring and reporting intellectual capital (a way of making explicit knowledge for companies)
• knowledge brokers (some organizational members take on responsibility for a specific “field” and act as first reference on whom to talk about a specific subject)
• social software (wikis, social bookmarking, blogs, etc)

Early research suggested that a successful KM effort needs to convert internalised tacit knowledge into explicit knowledge in order to share it, but the same effort must also permit individuals to internalise and make personally meaningful any codified knowledge retrieved from the KM effort. Subsequent research into KM suggested that a distinction between tacit knowledge and explicit knowledge represented an oversimplification and that the notion of explicit knowledge is self-contradictory. Specifically, for knowledge to be made explicit, it must be translated into information (i.e., symbols outside of our heads) (Serenko & Bontis 2004). Later on, Ikujiro Nonaka proposed a model (SECI for Socialization, Externalization, Combination, Internalization) which considers a spiraling knowledge process interaction between explicit knowledge and tacit knowledge (Nonaka & Takeuchi 1995). In this model, knowledge follows a cycle in which implicit knowledge is ‘extracted’ to become explicit knowledge, and explicit knowledge is ‘reinternalised’ into implicit knowledge.

A second proposed framework for categorising the dimensions of knowledge distinguishes between embedded knowledge of a system outside of a human individual (e.g., an information system may have knowledge embedded into its design) and embodied knowledge representing a learned capability of a human body’s nervous and endocrine systems (Sensky 2002).

A third proposed framework for categorising the dimensions of knowledge distinguishes between the exploratory creation of “new knowledge” (i.e., innovation) vs. the transfer or exploitation of “established knowledge” within a group, organisation, or community. Collaborative environments such as communities of practice or the use of social computing tools can be used for both knowledge creation and transfer

A broad range of thoughts on the KM discipline exists with no unanimous agreement; approaches vary by author and school. As the discipline matures, academic debates have increased regarding both the theory and practice of KM, to include the following perspectives:

• Techno-centric with a focus on technology, ideally those that enhance knowledge sharing and creation.
• Organisational with a focus on how an organisation can be designed to facilitate knowledge processes best.
• Ecological with a focus on the interaction of people, identity, knowledge, and environmental factors as a complex adaptive system akin to a natural ecosystem.

Regardless of the school of thought, core components of KM include People, Processes, Technology (or) Culture, Structure, Technology, depending on the specific perspective (Spender & Scherer 2007). Different KM schools of thought include various lenses through which KM can be viewed and explained, to include:

• community of practice (Wenger, McDermott & Synder 2001) ^[2]
• social network analysis ^[3]
• intellectual capital (Bontis & Choo 2002) ^[4]
• information theory ^[5] (McInerney 2002)
• complexity science ^[6][7]
• constructivism ^[8] (Nanjappa & Grant 2003)

In 1999, the term personal knowledge management was introduced which refers to the management of knowledge at the individual level (Wright 2005).

In terms of the enterprise, early collections of case studies recognized the importance of knowledge management dimensions of strategy, process, and measurement (Morey, Maybury & Thuraisingham 2002). Key lessons learned included: people, and the cultures that influence their behaviors, are the single most critical resource for successful knowledge creation, dissemination, and application; cognitive, social, and organizational learning processes are essential to the success of a knowledge management strategy; and measurement, benchmarking, and incentives are essential to accelerate the learning process and to drive cultural change. In short, knowledge management programs can yield impressive benefits to individuals and organizations if they are purposeful, concrete, and action-oriented.

More recently with the advent of the Web 2.0, the concept of knowledge management has evolved towards a vision more based on people participation and emergence. This line of evolution is termed Enterprise 2.0 (McAfee 2006). However, there is an ongoing debate and discussions (Lakhani & McAfee 2007) as to whether Enterprise 2.0 is just a fad that does not bring anything new or useful or whether it is, indeed, the future of knowledge management (Davenport 2008).

Transfer pengetahuan (salah satu aspek dari manajemen pengetahuan) dalam berbagai bentuk, telah sejak lama dilakukan. Contohnya adalah melalui diskusi sepadan dalam kerja, magang, perpustakaan perusahaan, pelatihan profesional, dan program mentoring. Walaupun demikian sejak akhir abad ke-20, teknologi tambahan telah diterapkan untuk melakukan tugas ini, seperti basis pengetahuan, sistem pakar, dan repositori pengetahuan.