In the knowledge society (Lytras and Sicilia, 2005), enterprises are more and more
concerned with Knowledge Management (KM) as a key factor for improving their efficiency
and competitiveness, notably their innovative capabilities. However, very often,
KM is considered from a technological viewpoint that induces to consider knowledge
as an object independent of individuals. Thus, as observed by Kjaergaard et al.
(2008) “The practice of knowledge management is often reduced to the implementation
of new IT-based systems, procedures for documenting and sharing information, and
documents themselves though there are examples to the contrary. By focusing on externalization
and documentation of knowledge, important organizational aspects, in particular
human and social issues, can be overlooked (p. 71).” Those practices disregard
the innovative potentialities of KM. In our research group, supposing that knowledge
is not manageable as if it were a data or information, we postulate that KM must
address activities that utilize and create knowledge more than knowledge by itself.
With regard to this issue, we elaborated a sociotechnical approach of KM within
the enterprise, and we synthesized it into an empirical model called Model for General
Knowledge Management within the Enterprise (MGKME). Seven elements, classified into
two categories, characterize this model. In particular, two of these elements, the
‘ad hoc infrastructure’, and the ‘organizational learning processes’
are essential to ensure the learning process that leads people to use appropriate
concepts, methods and tools of KM considered as an innovative technology.
In this paper, after having put down background theory and assumptions, we present
MGKME, emphasizing on two of the operating elements suggested by this model: the
ad hoc infrastructures element, and the organizational learning processes element.
That leads to introduce the Nonaka’s Socialization, Externalization, Combination,
Internalization (SECI) model (Nonaka and Takeuchi, 1995), and the Japanese concept
of Ba (Nonaka and Konno, 1998). Then, considering the case of innovative technologies
deployment within a large industrial company, that are intelligence artificial and
Knowledge-Based Systems (KBS), we describe the ‘Semi-opened Infrastructure
Model’ (SopIM), which was implemented, highlighting the link with Nonaka’s
SECI model, and the Japanese concept of Ba. In that way, we make a transposition
that considers this model as an instance of the two MGKME’s element mentioned
above. Consequently, we partially validate MGKME. Furthermore, we consolidate SopIM
as a pattern of reference to deploy innovative technologies.
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