The Knowledge-stream Model
A Comprehensive Model for Knowledge Circulation in
Communities of Knowledgeable Practitioners
Federico Cabitza, Andrea Cerroni, Angela Locoro
and Carla Simone
Università degli Studi di Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy
Keywords: Knowing Community, Knowledge-Stream Model, Knowledge Artifact.
Abstract: In this paper we present an original position on how knowledge is created and shared in organizational
domains. We propose a metaphor of diffusion, borrowed from genetics, and a four phase model, which aims
to be as simple as the SECI model proposed within the OKCT, but also more comprehensive and
sociologically-informed. Our model takes into account the individual, social and cultural dimensions of
knowledge (what we denote as co-knowledge) to account for the various ways knowledge is “circulated”
among people (i.e., members of any social structure); we also propose ancillary concepts like that of
“Knowing Community” and “Knowledge Artifact”, as analytical constructs to represent, respectively, the
environment hosting such a circulation and the technological driver that either enables or supports it.
1 INTRODUCTION
In this paper we propose a novel model, the
Knowledge-Stream Model, to account for the main
phenomena that are related to knowledge creation,
acquisition, sharing and circulation within social
settings, like communities, organizations and even
bigger social structures, up to the level of an entire
society. To this aim, we will first put our proposal in
the light of a knowledge conceptualization that
extends the previous ones in the organizational
studies and the Knowledge Management scholarly
field (KM). We will then present the sensitizing
concepts that would help understand our model. And
finally, we will outline the model, and challenge its
descriptive power against one of the most well
known theory and model adopted in KM, the
Organizational Knowledge Creation (OKC) Theory
of Nonaka and colleagues (Nonaka and Takeuchi,
1995; Nonaka and Von Krogh, 2009; Nonaka, 1994)
by a series of small and illustrative examples.
Our proposal has been developed within the
research strand that is usually denoted as the “social
practice perspective” (Brown and Duguid, 2001;
Wenger, 1998), which is grounded on what Schatzki
et al. called the “practice turn” in the social sciences
(Schatzki et al., 2001). Differently from other
viewpoints, among which the cognitive one is
probably the most widespread and common in the
KM literature (Moradi et al., 2012), the social
practice perspective assumes neither that knowledge
resides in the minds of individual members of a
collective ensemble (like an organization), nor that
these members can transform what they know into
communicable forms and exchange it in terms of
“explicit knowledge”. Rather, the social practice
viewpoint conceives knowledge as a social practice,
i.e., “any coherent, complex, coordinated form of
human activity” (Tsoukas, 2003) that is aimed at
some purpose, communicative in nature, and
“socially built”, i.e., agreed upon, representative of a
social group, and local to a particular cultural
context and milieu.
Since the cognitive perspective puts a strong
emphasis on the ways in which “tacit knowledge” is
converted into “explicit knowledge” and vice versa,
we will argue in opposition to how the OKC theory
mentioned above looks at that conversion, that is as
an alternation of four processes that is often referred
to as SECI model as it includes “socialization”,
“externalization”, “combination”, and
“internalization”. Our model addresses knowledge
circulation by considering any idea of “conversion”
inapplicable, as (tacit) knowledge resides in social
practices, and these are but socially meaningful
behaviors and relational interactions. In so doing, we
maintain many of the objections raised in regard to
367
Cabitza F., Cerroni A., Locoro A. and Simone C..
The Knowledge-stream Model - A Comprehensive Model for Knowledge Circulation in Communities of Knowledgeable Practitioners.
DOI: 10.5220/0005154803670374
In Proceedings of the International Conference on Knowledge Management and Information Sharing (KMIS-2014), pages 367-374
ISBN: 978-989-758-050-5
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
the OKC Theory and the SECI model by a number
of scholars (Bereiter, 2002; D’eredita and Barreto,
2006; Essers and Schreinemakers, 1997; Gourlay,
2006; Ribeiro and Collins, 2007; Schmidt, 2012;
Tsoukas, 2003), but also contribute in a positive
manner as we provide an alternative framework that
is more comprehensive, precise and sociologically
informed than the SECI model within the research
strand mentioned above.
2 AN OUT-OF-THE-(BLACK)BOX
VIEW OF KNOWLEDGE
First of all, we need to provide the reader with an
operational definition of knowledge that is
compatible with our idea of “circulation”. To this
aim, we rely on our comprehension of the main
tenets of the “social practice” view mentioned above
(Brown and Duguid, 2001); of the behavioral
framework within which “any knowing is a doing”
(Maturana and Varela, 1992) and “knowings are
behaviors” (cf. Dewey and Bentley, cited in
(Gourlay, 2004)); of the “epistemology of practice”
held in (Cook and Brown, 1999); and of the Schön’s
idea of knowledge as “knowing-in-action” (Schön,
1983), which in its turn draws on Polanyi's notion of
“tacit” knowing (Polanyi, 1983). That said, the main
idea is that no-thing is really circulated (or moved)
among the individuals, but that these latter are
informed (influenced) by the others in social
interactions where knowledge is afforded (Cook and
Brown, 1999).
Thus, we clearly depart from the idea of
knowledge as of “justified true belief”, which is a
common conceptualization dating back to Plato
(Fine, 2003). We rather advocate a different stance,
where knowledge is a knowledgeable behavior
(where the quality of being “knowledgeable” refers
to the social element and in some way subsumes the
quality of being appropriate and effective).
Contrasting the idea of knowledge as “belief” entails
to consider that, even when knowledge regards
ideas, notions and models of the world (that are
explicitly expressed in some way), it is but a
“convincingly plausible claiming” (that is,
trustworthy claims, even self-directed). The content
of the claim is “information”, which is representable
linguistically and has a potential to affect the
behaviors of others, also (but not necessarily) for
their higher knowledgeability.
Some simple examples will show what we mean
with this position: one knows how to drive a car
only when she actually drives a car. Obviously, she
can also remember to have proficiently driven a car
some day in the past, and likewise be quite sure and
confident to be able to drive a car some other day in
the future. These two cases should not be mistaken
for “knowledge” stricto sensu, but rather by
metonymy (e.g., intellectual knowledge, declarative
knowledge). Moreover, knowing how to drive is
social in that this has to be performed compliantly
with the “rules of the road” and, therefore (although
the two things do not always coincide), the
expectations of the other drivers (and car drivers in
Rome could have different expectations than drivers
in Teheran or Stockholm, as well).
Likewise, one does not really know that America
was discovered in 1492: rather she remembers to
have heard or read this “fact” somewhere and she
trusts that source (or her memory) as reliable (a
“source of knowledge”); moreover she can be
sufficiently convincing in repeating this notion to
someone else, who will possibly trust her. Of course,
I can know something (i.e., I believe something as
true, I hold an idea), but this is knowledge only if I
can express it (e.g., by performing a speech act) so
that someone else can understand my belief and
believe it in her turn (in other words,
knowledgeability is in the “eye of the beholder”). As
recently accepted, this mechanism can regard
personal opinions as well as scientific “facts”
(Latour, 1987).
That said, we have to address two matters of
concern. First, how we reconcile the idea that
knowledge is a perceivable behavior with the idea
that it can circulate within communities, and that this
circulation follows main general patterns (which can
be easily modelled). Second, how to avoid the
pitfalls of purely behaviorist approaches that neglect
the inner, mental part of knowledge, i.e., what is
totally hidden to the “others” but yet quite
indubitable for any knower (cf. Descartes).
To address these both concerns we turn to the
varied body of work on cultural transmission that is
often put under the rubric of memetics (Heylighen,
1998; Moritz, 1990; Speel, 1996). Being aware of
the changing fortunes of this field (Burman, 2012),
we rely just on the main concepts that were proposed
originally in this research strand, without borrowing
any of the most recent and complex models of
knowledge transmission within and across
communities of people, if not the simple idea that
knowledge can spread over even without making
anything “explicit” about it.
Indeed, in memetics the main mechanism is
imitation and memes were first and originally
KMIS2014-InternationalConferenceonKnowledgeManagementandInformationSharing
368
defined as “units of imitation” (Dawkins, 2006) and
as any “idea or behavior that spreads from person to
person within a culture” (cf. the Merriam Webster
Dictionary) like, e.g., “ways of making pots or of
building arches” (Dennett, 1990). On the other hand,
imitation is also how “tacit knowledge” is said to be
shared among human beings, since when Polanyi
has assimilated imitation to learning by doing and
learning by example (Polanyi, 1983).
More precisely, we propose to adopt a conceptual
analogy with what in the life sciences has been
discussed in terms of genotype-phenotype, and
assimilate knowledge to a memotype – phenotype
indissoluble dyad. To clarify this point it is
necessary to provide some short definitions. In
genetics, a genome is considered the entire genetic
code characterizing a whole species or individual. A
genotype is a collection of genes that underlie the
expression of a phenotype. A phenotype is any
actually observed trait or property of an organism, as
well as its development or behavior, or related
effects on the environment. The extended phenotype
includes all the effects that a genotype has on its
environment, inside or outside of the body of the
individual organism (Dawkins, 1999).
Thus, consistently with the use of this term both in
genetics and memetics, a specific trait of a human
being that others would recognize as a
knowledgeable behavior is but a phenotype. On the
other hand, we define a “memotype” as “the
capacity of expressing that phenotype in a given
environment”. Thus, neither could exist without the
other.
Why do we propose this sensitizing analogy as
first step towards the proposal of new model for
knowledge circulation in human communities
(including organizations and the broader society)?
The memotype-phenotype dyad allows us to go
beyond the typical distinction by which knowledge
is both “the actuality of skillful action” and its
“potentiality” (Stehr and others, 1992). The dyad
subsumes both these aspects. Moreover, we go
beyond the idea of single memes as “units” that
could be transferred (which we would consider a
reductionist and simplistic view at best): we do not
mean memotypes in the literal meaning of ‘complex
ensemble of memes that interact with each other and
the environment to produce articulated phenotypes’
but more simply as “what allows for a specific
knowledgeable trait to be expressed by someone and
recognized by someone else”.
In this view, knowledge circulation is framed as
the mutual influence among phenotypes, including
the exchange of language utterances, the sharing or
common use of material resources, like written
inscriptions (i.e., a surrogate of spoken language)
and objects. However, to say that someone would
share the memotype with another one, or even that a
memotype has been transferred, would probably
miss the point: the memotype-phenotype is given as
indissoluble and therefore to speak of “transmission”
(as often done in memetics) would hide the simple
(and more important to our aims) fact that one
person has influenced the latter, with her behaviors,
including communication and her products, broadly
speaking. Traditional views of (tacit) knowledge,
which do not consider its outer effects, miss the
point of what happens in imitation and physical
association, and thus they need to theorize an
explicit counterpart of knowledge to give account
for knowledge diffusion. On the contrary, the
memotype-genotype viewpoint focuses on influence:
thus in the very same way a genotype responsible for
blue eyes would not produce any perceivable
phenotype for potential mates that cannot detect
colors, and hence would not directly spread through
sexual selection in a blue-blind community of
partners, so knowledge circulation is more a matter
of mutual alignment (within a stream, so to say),
than of “transfer” of knowledge units.
An example will help clarify this point: for
instance, if I want to share a way of, say, hunting
with a bow and arrows, I can say “Watch me and do
as I do. Watch closely!” (Judges 7:17); I can
describe the whole procedure in words like in a
manual (how to draw the arc, aim at the prey, to
shoot the arrow, etc.). Or I can hand the person an
arc and arrow directly: as these latter are built so that
usage is somehow afforded, and the shape of the
arrow has been progressively tweaked and refined
for more and precise aiming (and so forth) I could be
confident that trials and errors could lead to some
clear results in a matter of time, irrespective of my
constant intervention as an expert, as long as I stand
for the pupil as a master or influential teacher (this
approach is also magnificently described in
(Herrigel, 1999)).
In short, framing knowledge as a memotype-
phenotype dyad allows to see knowledge both i) at
the granularity level (i.e., single ideas, more
articulated arguments, whole theories: all
encompassed in the idea of memotype); and ii) at the
conceptual level (i.e., mind, behaviors, objects: all
encompassed in the concept of phenotype) that one
feels more comfortable with.
The inscribed and material resources that we trace
back to the concept of extended phenotype are often
denoted, respectively, as “explicit or symbolic
TheKnowledge-streamModel-AComprehensiveModelforKnowledgeCirculationinCommunitiesofKnowledgeable
Practitioners
369
knowledge” and “embodied or objectified
knowledge” (cf. Marx). Our point is that this is
useful and effective only in a metaphorical way, and
in virtue of the non-totally unproblematic
metonymies that are applied every time knowledge
is said to be embedded in a technology (e.g., (Argote
and Darr, 2000), in documents, organizational
routines, practices and norms (Davenport and
Prusak, 1998), social structures (Stehr, 2005), and in
the “physical structure of the workplace” (Argote
and Ingram, 2000). Here we rather claim that neither
language nor material objects do carry or, notably,
represent “memotypes”. However, these are all
resources that, even if not necessarily produced to
this aim, can facilitate the influence of individuals
on other individuals, so that these latter can develop
“something” that would eventually allow them to
express the same skills, competencies and behaviors:
a related knowledge along the continuous
development of human capabilities in a cross-
human, overindividual, cultural dimension (the
genus). To this respect, landscapes produced by
societies over the centuries, sometimes for artistic
reasons and more often for practical needs, ranging
from low-tech agricultural countrysides to ambitious
urban skylines integrating computational services
and hyperconnected “Webs of Things” can be seen
as the stratified product of Co-knowledge over time,
which both inspire and affect knowing, innovation
and learning much alike texts and common objects
are said to do (Cerroni, 2006).
3 CONCEPTS IN THE STREAM
The Knowledge-Stream model moves on three
analytical levels (Cerroni, 2006,Cerroni, 2007): the
(socialized) individual; the social structure (both at
micro scale, i.e., any community, and at the macro
scale, i.e., the whole society itself); and the human
genus (Gattung in Marx). Processes belonging to
these three dimensions show a different essential
nature, but all of them partake in the circulation “in
the sea” of the (Co)Knowledge (see next), of which
any single expression of knowledge, as we know it,
can be seen as a sort of “local hardening” or
“ripple”. In the words of Stehr: “knowing is, then,
grosso modo participation in the cultural resources
of society.” (Stehr, 2005)
At the individual level we typically find daily life
processes with a biographical time-scale dynamics
(roughly speaking, socially relevant cognitions and
actions and what else is supposed to have, after
Aristotle, both an ontological and methodological
primacy in a scientific inquiry). At the (strictly
speaking) social level, we find roles configurations
within the reference community, what we call the
“knowing community” (Cabitza et al., 2014), and
interactions among communities (i.e. negotiations
and both symbolical and economical exchanges). At
the genus level, we place what we call Co-
Knowledge. This is the knowledge-related part of
the “complex whole” of known techniques,
practices, implicatures, beliefs, “arts, customs [...]
and any other capabilities and habits acquired by
man as a member of [a] society” that is usually
denoted as “Culture” since Tylor (Tylor, 1871),
comprising (indeed, resulting from) multiple
“epistemic cultures” (Knorr-Cetina, 1999); this can
also be seen as a sort of “memoma” in accordance
with the memetics perspective outlined above.
Obviously the “Co” prefix is proposed to stress the
fact that knowledge is intrinsically social, co-
produced in and constituted of relational and
meaningful interactions among individuals in a
given social and cultural context, so as to retake the
“*ko” root (“together”) that characterizes the Latin
term “cognoscentia” and all its derivates.
The overall phenotype of this social and
overindividual “memome” encompasses all possible
knowledge productions: that is, both symbolic
representations related to (i.e., both triggering and
resulting from) the processes of knowing, what we
refer to as “knowledge artifact” (Cabitza and
Locoro, 2014); and these latter processes too, like
idea expression and exchange, content and structure
negotiation, meaning reconciliation, collective
deliberation, new product and process co-design,
knowledge representation at various degrees of
(under)specification, problem framing and solving,
mutual learning, novice training and any possible
interpretation of the representations mentioned
above (cf. semeiosis) (Gourlay, 2004).
4 THE PHASES OF THE
KNOWLEDGE STREAM
We can model knowledge circulation as four logical
phases between close levels (see Figure 1).
In this metaphorical flow, Production regards the
creation of a knowledge-claim (e.g., any assertion,
discourse, content intentionally produced to
contribute to a knowledge body, as well as any
expression of practical knowledge) in some
representation language by individuals and its
proposal to the reference-community; within the
KMIS2014-InternationalConferenceonKnowledgeManagementandInformationSharing
370
global society we speak of production because this
phase regards the expression or “bringing forth” (cf.
pro-ducere) of some knowledgeable behavior by
some individual agency, that is a single person, or a
tight team of people acting in close accord: in other
terms it is both creating and making this creation
publicly visible within a social ensemble. How
“creation” actually occurs is beyond the model’s
scope, as it probably pertains more to cognitive and
group psychology, and to how ingenuity and
intuition work in creative settings. In the case of
product design, for instance, the new knowledge
should not be reduced to the technical sketches that
represent the “new” thing (the product of
knowledge). Rather, it is the process of creating such
a new thing, which encompasses procuring the
materials, shaping them into single components, and
assembling these components together, and even
testing the final outcome for overall quality (that is
performance expectations are embedded in the
process also in terms of what should certify its
quality, as well of the output of the process).
According to the innovations that are implemented,
new knowledge can also encompass the procurement
of the needed pieces, the packaging (and to some
extent also marketing the product effectively, and
delivering it efficiently).
Thus, with reference to the widely discussed case
study presented in (Nonaka and Takeuchi, 1995)
new knowledge regards “how” to “build” a “better”
bread machine, not “how” to knead bread so to make
it “good”. The product designer Tanaka could have
found inspiration in spending time with some master
baker, and found a way to emulate the right
kneading with “special mechanic ribs”, and maybe
have even become a good baker himself in the
process but one kind of tacit know-how (i.e., making
the bread) has not been converted into design
sketches and hardware. Rather, one “knowledge”
has influenced another “knowledge” (e.g., designing
machines), in that a product innovation always
entails a process innovation, that is the very process
of building the product. This process then is enabled
and supported by colocated associations, lots of
conversations (Ljungberg, 1997; Suchman, 2011), as
well as documents and material resources, like
sketches, 3D models, material scale models,
resource management plans (even workforce
schedules), to which this new knowledge can never
be totally reduced.
Institutionalization regards the identification,
selection, validation, structuring organization and
“design for diffusion” of the knowledge produced
and shared in that community, and that this latter
one, often represented by the seniors, the gurus, the
recognized experts (Wenger, 1998a), the managers
somehow acknowledges and announces, by ratifying
and making it further public, making it the potential
Co-Knowledge mentioned above (a sort of
Capitalized Knowledge that is collectively available
in some form). From the memetic viewpoint,
institutionalization refers to the phase of a meme
circulation where this process gains an inflation of
reproduction power, like a top-down or peer-driven
legitimation in “fertilizing” the other members of the
community, and a call to these latter to make
themselves more sensitive and receptive, if possible,
to the related phenotype (including the symbolic and
material representations mobilized). Moreover, as it
also regards the appropriation of knowledge by
someone else than the original contributor(s), this
phase has also a transformative power, as it can
entail a reconciliation of meanings, a
systematization, and an integration into existing
nomenclatures, habits, procedures and “standards”.
This phase makes our proposal deeply different from
the SECI model: while in the OKTC communities
are seen as mere places where multiple individuals
meet and interact, our model, conversely,
acknowledges the transforming role of the
overarching social structure(s) in which the new
contributions are proposed (and new phenotypes
emerge).
Diffusion refers to the “rippling percolation” of the
Co-Knowledge by multiple and heterogeneous
means like textual accounts, knowledge-affording
objects, symbolic signs, and through essentially
communicative processes, which also cross to the
boundaries between other communities than the
original one, up to – at least in principle – the whole
(knowledge) society (Stehr, 1994)(Burke, 2012).
Accordingly, diffusion regards the process in which
people become more and more sensitive to
innovation and pay some effort in actively
perceiving or relaxing barriers to be influenced by
the related extended phenotype, which, it is
important to emphasize it, encompasses both
behaviors, actions and their direct outputs. Then,
diffusion is never a “top-down” or “transmission” or
“dissemination” process, but a still cooperative –
although not intended to be so –, properly
communicative and creative process of co-
production of a shared knowledge, not necessarily
an “expert” one, ideally entailing the whole social
environment.
Finally, Socialization deals with what the SECI
model denotes as internalization and introjection
(Nonaka and van Krogh, 2009), as well as with
TheKnowledge-streamModel-AComprehensiveModelforKnowledgeCirculationinCommunitiesofKnowledgeable
Practitioners
371
Figure 1: The knowledge stream model.
education and regulation (i.e., sociologically
normative) processes, through which knowledge
productions acquire a reference value, which is both
publicly sanctioned (by, e.g., rule of law, technical
regulation, accountable behavior), privately
interiorized (the Self, professional ethos, her/his own
responsibility) and transformed in that kind of
"structured and structuring disposition" that
individuals can learn only through their participation
in social practices (Bourdieu and Wacquant, 1992).
This is the process in which the phenotype can be
replicated (adopted) by someone other than whom
generated the original dyad memotype-phenotype:
the behavior or the skill is said to have been
internalized in that another member is recognized by
the community as able to produce the intended (and
institutionalized) behavior. Notably, where Nonaka
speaks of internalization, we prefer speaking of
socialization: in fact, Nonaka pointed out that
internalization is “closely related [to] the traditional
notion of learning”. In doing so, however, he seems
to neglect that education is a "bringing up out" (e-
ducare) the “raw” individual into the overarching
patterns of behaviors and beliefs that are deemed
appropriate for a specific social group (and society
in the large): so what it is "closely related to
learning" is not pouring into someone’s mind some
knowledge, but rather to acculturate her (i.e.,
assimilate her into a culture) and socialize her, i.e.,
to make her social, or “fit for life in companionship
with others” (cf. the Random House Dictionary,
2014
)
. In other words, for the individuals,
socialization regards being “socialized to” some
knowledge and to be educated to use it creatively so
as (also) to move forward; while for the society in
the large, socialization regards the incorporation of
knowledge into its culture.
Thus, in regard to the bread machine case study,
we can reinterpret it in the following terms:
Institutionalization regards the “bringing the new
bread machine into production", with the
commitment of the management, including the
mobilization of the needed resources, the creation of
commitment in several organizational roles, and
their alignment towards the objective to deploy the
new (innovated) bread machine. Diffusion regards
how the changes in the production process are
disseminated to the roles involved, including the
marketing force and salespeople, and how it changes
in value through this active “dissemination”: the
complex memotype herein involved encompasses
also a new confidence (no matter whether ill-
grounded or not) that the bread made with the new
machine is better and similar to the “good real bread
of the baker”. Socialization is the process in which
the people involved get proficient in the new
production&marketing line and come to trust it is an
actual and valuable innovation.
The same phases can be recognized also outside
the company that produces the new bread machine.
In this case the “new thing” is not the bread
machine, which is said to be “materializing the skill
of kneading [of the master baker] into specific
mechanics” (Nonaka and Takeuchi, 1995, p. 101);
but rather it is the related process of “making the
bread at home”, that includes a bread-making
machine, of course. To this respect, we then see a
company bringing forth a new method (and related
practice) that obviously employs a new product of
theirs (what they want to sell to increase their market
share and revenues). This method must be
“institutionalized” within the community of potential
consumers (e.g., by a customer association, or some
guru, like a famous chef with some visibility on TV,
or knowledgeable representatives, like a journalist of
some cuisine magazine, and the like) that is,
KMIS2014-InternationalConferenceonKnowledgeManagementandInformationSharing
372
accepted as a legitimate and adoptable behavior (to
this aim, advertisement and social semiotic
techniques are also to be factored in). Diffusion
refers to the process in which people come to buy
the new machine and kitchen books with recipes on
how to make the homemade bread with the new
machine (cf. the case of the Vorwerk Bimby-
Thermomix), start to use it with daily creativity, and
spread the word about its quality. Socialization is the
process in which “making the bread at home with,
say, the Thermomix” is considered mainstream and
socially desirable, changing community habits and
(to some extent) values.
This example allowed us to show that the overall
circulation process described by the model is scale
invariant. In particular the last three phases of the
“stream” can occur at various scales: i.e., within
single communities of peers, experts or practitioners;
between different communities (cf. cross-
fertilization); and in progressively vaster
communities, up to the level of the Global
Knowledge Society (see Figure 1).
5 CONCLUSIONS
In this position paper we have presented a novel
model of knowledge circulation in social settings,
including organizations. Our model extends but also
opposes the SECI model by Nonaka and colleagues
(Nonaka and van Krogh, 2009) in a number of
points: most notably that there is no continuum
between tacit and explicit knowledge, no need to
theorize the existence of a “cognitive tacit
knowledge” (i.e., mental models of the world), of
“explicit” knowledge, and indeed the idea itself of
conversion at all. Accordingly, we maintain that
“explicit knowledge” is not really “knowledge” (i.e.,
an object autonomous in its own), but rather a sort of
scaffolding for its expression (Orlikowski, 2006),
within a social process in fieri that must be
maintained alive to keep it valuable; we have also
proposed the metaphorical dyad “memotype –
phenotype” to account for the “what” that could be
exhibited and learnt within a social arrangement by
people through observation, imitation and
communication.
That said, new lines of investigation could regard
to get a better understanding of how local
knowledge (i.e., dyads memotype – phenotype) is
appropriated at collective level and continually
transformed in the process of circulating it, that is of
letting it flow into what we called Co-Knowledge. In
so doing, we intend to go beyond the OKC theory in
that our model acknowledges that knowledge can be
created ex novo (differently from the OKTC where
emphasis is either on externalization or
internalization), it accounts for the ways in which
“concepts are systematized into a knowledge
system” without the need to theorize any
combination of explicit knowledge (Nonaka and
Takeuchi, 1995) [p. 67] and, most notably, it takes
the social dimension of communities seriously,
recognizing an “agency” in communities that
transforms knowledge and makes it circulate
actively. Thus, in our model no-thing is converted,
nor moved or transferred, but it is rather
acknowledged that some behaviors emerge, evolve
and spread over a community of people in virtue of
some processes. In the “Knowledge Stream Model”
we parcel these processes out in terms of
institutionalization, diffusion and socialization.
These phases can entail different articulations of
activities according to the nature and size of the
social structure in which they occur, but we claim
their function is scale- and domain-invariant. This
opens up a research strand focusing on the role and
functionalities of Knowledge Artifacts in enabling
and supporting those phases, that is focusing on
functionalities that support, e.g., group
brainstorming and argumentation, meaning
reconciliation, collective deliberation, appropriation,
learning and training, rather than Knowledge
representation and logic inference.
Future work will also encompass the application
of the model to concrete case studies, like the project
we describe in (Cabitza et al., 2014) where to show
its descriptive, rhetorical, inferential and applicative
power (Halverson et al., 2008).
REFERENCES
Argote, L., Darr, E., 2000. Repositories of knowledge in
franchise organizations: Individual, structural and
technological. The nature and dynamics of
organizational capabilities 82, 51–65.
Argote, L., Ingram, P., 2000. Knowledge transfer: A basis
for competitive advantage in firms. Organizational
behavior and human decision processes 82, 150–169.
Bereiter, C., 2002. Education and mind in the knowledge
age. L. Erlbaum Associates.
Bourdieu, P., Wacquant, L.J., 1992. Réponses: pour une
anthropologie réflexive. Seuil.
Brown, J.S., Duguid, P., 2001. Knowledge and
Organization. Organization Science 12, 198–213.
Burke, P., 2012. A social history of knowledge. Polity,
Cambridge.
Burman, J.T., 2012. The misunderstanding of memes:
TheKnowledge-streamModel-AComprehensiveModelforKnowledgeCirculationinCommunitiesofKnowledgeable
Practitioners
373
Biography of an unscientific object, 1976–1999.
Perspectives on Science 20, 75–104.
Cabitza, F., Cerroni, A., Simone, C., 2014. Knowledge
Artifacts Within Knowing Communities to Foster
Collective Knowledge, in: AVI 2014, 391–394.
Cabitza, F., Locoro, A., 2014. Between Form and
Perform: the Knowledge Artifact in Organizations and
IT Design, in: IS 2014.
Cerroni, A., 2006. Scienza e società della conoscenza.
Utet.
Cerroni, A., 2007. Individuals, knowledge and governance
in the 21st-century society. JCOM 6.
Cook, S.D.N., Brown, J.S., 1999. Bridging episte-
mologies: the generative dance between organizational
knowledge and organizational knowing. Organization
Science 10, 381–400.
D’eredita, M.A., Barreto, C., 2006. How does tacit
knowledge proliferate? An episode-based perspective.
Organization Studies 27, 1821–1841.
Davenport, T.H., Prusak, L., 1998. Working Knowledge:
How Organizations Manage What They Know.
Harvard Business Press.
Dawkins, R., 1999. The extended phenotype: The long
reach of the gene. Oxford Univ Press.
Dawkins, R., 2006. The selfish gene. Oxford Univ Press.
Dennett, D.C., 1990. Memes and the exploitation of
imagination. Journal of Aesthetics and Art Criticism
127–135.
Essers, J., Schreinemakers, J., 1997. Nonaka’s subjectivist
conception of knowledge in corporate knowledge
management. Knowledge Organization 24, 24–32.
Fine, G., 2003. Plato on knowledge and forms: selected
essays. Clarendon Press ; Oxford University Press.
Gourlay, S., 2004. Knowing as semiosis: steps towards a
reconceptualization of’tacit knowledge’, in:
Organizations as Knowledge Systems. Knowledge,
Learning and Dynamic Capabilities. Palgrave
Macmillan, 86–105.
Gourlay, S., 2006. Conceptualizing knowledge creation: a
critique of nonaka’s theory*. J of Manage Stud 43,
1415–1436.
Halverson, C., Ackerman, M., Erickson, T., Kellogg,
W.A. (Eds.), 2008. Resources, Co-Evolution and
Artifacts: Theory in CSCW, Springer.
Herrigel, E., 1999. Zen in the art of archery. Vintage
Books.
Heylighen, F., 1998. What makes a meme successful?
Selection criteria for cultural evolution.
Brown JS, Duguid P. 2001. Knowledge and Organization:
A Social-Practice Perspective. Organ Sci 12, 198–213.
Knorr-Cetina, K., 1999. Epistemic cultures: how the
sciences make knowledge
. Harvard University Press.
Latour, B., 1987. Science in Action: How to Follow
Scientists and Engineers Through Society. Open
University Press.
Ljungberg, J., 1997. Organizations and conversation.
From Workflow to Conversation 181.
Maturana, H.R., Varela, F.J., 1992. The Tree of
Knowledge: The Biological Roots of Human
Understanding. Shambhala Publications, Boston, MA.
Moradi, E., Saba, A., Azimi, S., Emami, R., 2012. The
Relationship between Organizational Culture and
Knowledge Management. Int J of Innovative Ideas 12.
Moritz, E., 1990. Memetic Science: I-General
Introduction. Journal of Ideas 1, 1–23.
Nonaka, I., 1994. A dynamic theory of organizational
knowledge creation. Organization Science 5, 14–37.
Nonaka, I., Takeuchi, H., 1995. The knowledge-creating
company: How Japanese companies create the
dynamics of innovation. Oxford University Press.
Nonaka, I., van Krogh, G., 2009. Tacit Knowledge and
Knowledge Conversion: Controversy and
Advancement in Organizational Knowledge Creation
Theory. Organization Science 20, 635 – 652.
Orlikowski, W.J., 2006. Material Knowing: The
Scaffolding of Human Knowledgeability. Eur J of
Inform Syst 15, 460–466.
Polanyi, M., 1983. The Tacit Dimension. Peter Smith,
Gloucester, USA.
Ribeiro, R., Collins, H., 2007. The bread-making machine:
Tacit knowledge and two types of action. Organ Stud
28, 1417–1433.
Schatzki, T.R., Knorr-Cetina, K., von Savigny, E., 2001.
The practice turn in contemporary theory. Psychology
Press.
Schmidt, K., 2012. The trouble with “tacit knowledge”.
CSCW 21, 163–225.
Schön, D.A., 1983. The reflective practitioner: How
professionals think in action. Basic books.
Speel, H.C., 1996. Memetics: On a conceptual framework
for cultural evolution. In The Evolution of Complexity,
Kluwer.
Stehr, N., 1994. Knowledge societies. Wiley Online.
Stehr, N., 2005. Society and Knowledge. Transaction Pub.
Stehr, N., others, 1992. Practical knowledge: Applying the
social sciences. Sage Publications Newbury Park, CA.
Suchman, A.L., 2011. Organizations as Machines,
Organizations as Conversations: Two Core Metaphors
and Their Consequences. Medical Care 49, S43–S48.
Tsoukas, H., 2003. Do we really Understand Tacit
Knowledge?, in Managing Knowledge: An Essential
Reader. SAGE, 357.
Tylor, E.B., 1871. Primitive culture: researches into the
development of mythology, philosophy, religion, art,
and custom. Murray.
Wenger, E., 1998. Communities of Practice: Learning,
Meaning, and Identity. Cambridge Univ Press.
KMIS2014-InternationalConferenceonKnowledgeManagementandInformationSharing
374
