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Chapter 7
Generic Knowledge Strategies
Ettore Bolisani and Constantin Bratianu
To cite this document:
Bolisani, E., and Bratianu, C. (2018). Generic knowledge strategies. In
Bolisani, E. and Bratianu, C. ( 2018). Emergent knowledge strategies: Stra-
tegic thinking in knowledge management (pp.147-174). Cham: Springer
International Publishing. DOI: 10.1007/978-3-319-60657-6_7.
Abstract
The purpose of this chapter is to introduce generic knowledge strategies,
which aim at increasing the level of organizational knowledge and creat-
ing the intangible infrastructure for company strategies and achieving
competitive advantage. The main characteristic of these generic strate-
gies is that they can be developed in any organization although their suc-
cess is related to a specific organizational context and a given business
environment. The ontology of these generic strategies comes from the
equilibrium dynamics of organizational knowledge and the correlation
with the known-unknowns matrix. The generic knowledge strategies pre-
sented in this chapter are the following: exploitation strategies, acquisi-
tion strategies, sharing strategies and exploration or knowledge creation
strategies. Exploitation knowledge strategies are designed in a similar way
with low cost business strategies and efficiency models. This
is a consequence of the fact that managers know what they know, which
means that they know very well their intangible resources. Acquisition
knowledge strategies are designed as a result of the identification of the
strategic knowledge gap. Sharing knowledge strategies are specific for
knowledge management and they contribute to increase the level of or-
ganizational knowledge by its diffusion within the whole organization. Ex-
ploration knowledge strategies focus on knowledge creation and on feed-
ing the innovation process.
2
7.1.Thinking Perspectives
7.1.1.Generic Business Perspectives
According to Oxford advanced learner’s dictionary “generic” means
“shared by, including or typical of a whole group of things; not specific”.
Essentially, “generic strategies” can be developed by any organization in
concordance with its vision and available resources and capabilities. From
the previous chapters we learned how complex and diverse is the field of
knowledge strategies and how compelling is to consider for further analy-
sis a multidimensional framework. Three main perspectives may be con-
sidered as possible initial dimensions of that framework: a) the Porter’s
generic business strategies; b) the known-unknown matrix, and c) the or-
ganizational knowledge dynamics. Our conceptual research demonstrates
that regardless of the initial starting point the final result converges to-
ward the same spectrum of generic knowledge strategies, even if the an-
gles of their perception might be a little different.
The concept of generic strategies has been introduced by Michael
Porter in his seminal book Competitive advantage: Creating and sustain-
ing superior performance (1985). Focusing on the competitive position a
firm might have, Porter considers that there are two fundamental ap-
proaches to competitive strategy: low cost and differentiation. The signif-
icance and evaluation of any strength or weakness a firm possesses is es-
sentially a function of its impact on the cost level and differentiation. “The
two basic types of competitive advantage combined with the scope of ac-
tivities for which a firm seeks to achieve them lead to three generic strat-
egies for achieving above-average performance in an industry: cost lead-
ership, differentiation, and focus. The focus strategy has two variants,
cost focus and differentiation focus” (Porter, 1985, p. 11). The cost lead-
ership and differentiation strategies are conceived for industry wide,
while the focus strategy is conceived for only a segment of that industry.
The firm that develops a cost leadership strategy aims to achieve compet-
itive advantage through a series of efficiency methods which lead to the
3
lowest cost per product or service on the market. The cost leadership
strategy implies mass production and a large volume of products and ser-
vices sold. These products have basic and functional features able to satis-
fy the customers from a very vital and practical perspective. That allows
the firm to become an above-the-average performer in its industry, and
as a consequence it will obtain higher returns than its below-the-average
competitors. In contrast to cost leadership strategy, the differentiation
strategy addresses people with new and different psychological needs. In
developing this strategy, the firm “selects one or more attributes that
many buyers in an industry perceive as important, and uniquely positions
itself to meet those needs. It is rewarded for its uniqueness with a premi-
um price” (Porter, 1985; p. 14).The differentiation can be thought in
product design, realization, or delivery system. Generating novelty and
embedding it into firm’s activities are the sources of any differentiation
strategy. While cost leadership and differentiation strategies can be de-
signed for a large industry range, focus strategy is designed only for a
segment or several segments of that industry. “By optimizing its strategy
for the target segments, the focuser seeks to achieve a competitive ad-
vantage in its target segments even though it does not possess a competi-
tive advantage overall” (Porter, 1985; p. 15).
To understand Michael Porter’s vision about strategy we must
add his remark that operational effectiveness is not a strategy. Although it
contributes to realize a cost leadership strategy, operational effectiveness
is based on short time thinking and decision making without any direct
impact on competitive strategy. Only through an integration process and
convergence pattern of thinking toward competition and competitors a
firm can achieve a sustainable competitive advantage by “performing dif-
ferent activities from rivals’ or performing similar activities in different
ways” (Porter, 1996; p. 3). That is valid when we consider both tangible
and intangible resources, although they have different behavior and ways
of being processed. When we map the cost leadership strategy from the
tangible resources domain onto the intangible resources domain we get
what March (1991) and Zack (1999) called exploitation strategy. Exploita-
tion of organizational knowledge means a good understanding of what
4
does exist at a certain moment within organization as cognitive, emotion-
al, and spiritual knowledge, in explicit and tacit forms. Also, it is about
knowing and using efficiently data, information, and knowledge stored in
the information systems. Exploitation stimulates knowledge codification,
sharing, dissemination, propagation and embedding. Exploitation means
to reduce knowledge waste and knowledge loss, by increasing knowledge
retention and knowledge reuse. When we map the differentiation strate-
gy from the tangible resources domain onto the intangible resources do-
main, we get the exploration strategy (March, 1991; Zack, 1999). Explora-
tion means to search for new knowledge and ways of increasing the level
of organizational knowledge. Knowledge management will stimulate, in
perspective, knowledge creation and knowledge acquisition from inside
the organization as well as from the external environment. Exploration
strategy is a key driving force for innovative firms. The focus strategy does
not have a direct equivalent in the field of knowledge, but it approaches
the disruptive innovation strategies. Although we started by considering
the business generic strategies defined by Michael Porter (1985), we have
to underline a big difference in the domain of intangible resources. Firms
should not choose between exploitation and exploration strategies but
should find a balance between them by developing a knowledge strategy
ambidexterity (Raischet al., 2009).
7.1.2The Known-Unknown Matrix
The answer formulated by the former Secretary of Defense Donald
Rumsfeld (2002) during the U.S. Department of Defense News briefing
has become quite famous: “Reports that say that something hasn’t hap-
pened are always interesting to me, because as we know, there are
known knowns; there are things we know we know. We also know there
are known unknowns; that is to say we know there are some things we do
not know. But there are also unknown unknowns – the ones we don’t
know we don’t know” (italics added). These expressions “known un-
knowns” and “unknown unknowns” generated a lot of critiques and de-
5
bates from many journalists, writers, language experts, philosophers and
people involved in economics and politics. However, these expressions re-
flect the known-unknown paradox that can be obtained by combining the
level of awareness of what we know with the degree of known in the ex-
ternal world in a matrix (Dalkir 2005). Figure 7.1 presents an illustration of
the known-unknown matrix with associated generic knowledge strate-
gies.
Figure 7.1 The known-unknown matrix
The matrix incorporates four states of knowledgeable domains that can
be phrased as follows:
I know what I know.
I know what I don’t know.
I don’t know what I know.
I don’t know what I don’t know.
I know what I know
Knowledge Exploita-
tion Strategy
I know what I
don’t know
Knowledge Ac-
quisition Strategy
I don’t know what
I know
Knowledge Shar-
ing Strategy
I don’t know what I
don’t know
Knowledge Explo-
ration Strategy
External World
Known Unknown
Knowing
Not Knowing
Level of Aware-
ness
6
The first two sentences reflect a static and finite world of knowledge, and
a deterministic way of thinking (Bratianu, 2007; 2015b). I know what I
know because I am certain about my knowledge. Since certainty can be
understood only in terms of conscious thinking, it results that I am con-
sidering my rational knowledge. The second sentence refers to the gap in
my knowledge with respect to a given finite and static world of
knowledge. I know what I don’t know because I know how much I am
supposed to know in this field, or in this life, about the external world.
These first two sentences, which synthesize the “known” do-
mains,substantially refer to explicit knowledge. The third domain is a little
more difficult to comprehend since it considers both explicit and tacit
knowledge. Since tacit knowledge reflects the experience we have it is
hard to be aware of how much we know. I know that I can use the
knowledge got through my experience but I don’t know what exactly I
know and how much I know. The fourth domain is about the infinity of
knowledge in the external world and our practical impossibility to be
aware of all of it. At the same time, it is about the absence of knowledge
concerning the probable future events and phenomena.
For each domain we can associate some generic knowledge strat-
egies each organization may develop in order to close the identified gaps
between the known and the unknown fields. If we project some strategic
objectives into the future and there is a strategic gap between where we
are and where we want to be, then we should be able to define an asso-
ciate knowledge gap which represents the “unknowns” from that matrix.
Thus, for the first domain, we can label “known-knowns” the develop-
ment of knowledge exploitation strategies which will enhance the effi-
ciency of data, information and knowledge processing. For the second
domain, we can label “known-unknowns” the case when we have to de-
velop knowledge acquisition strategies which will help us in acquiring the
knowledge we need in realizing the new products and services for achiev-
ing competitive advantage. The third domain can be labeled “unknown-
knowns”, and for it we need to implement knowledge sharing strategies
through which tacit knowledge can be externalized and shared with oth-
ers. The forth domain, that we may label “unknown-unknowns”, requires
7
knowledge creation which can be obtained through knowledge explora-
tion strategies.
7.1.3.Organizational Knowledge Dynamics
The perspective of organizational knowledge dynamics has been initiated
in Bratianu (2011), based on the metaphorical analysis of knowledge as
energy, and then developed in Bratianu et al. (2011) by using the Analytic
Hierarchy Process (AHP). Organizational knowledge is a semantic con-
struct designed to reflect the integrated individual knowledge fields of all
employees and the codified knowledge embedded in the procedures, rou-
tines, documents of intellectual properties, data bases and organizational
culture (Becerra-Fernandez and Sabherwal, 2010; Brown and Duguit,
1998; Davenport and Prusak, 2000; Nonaka and Takeuchi, 1995; Spender,
1996; Sveiby, 2001). According to the multi-field theory (Bratianu, 2015a),
organizational knowledge is a result of the work performed by nonlinear
integrators on the rational, emotional, and spiritual knowledge fields. The
most powerful nonlinear integrators are leadership, management, and
organizational culture. Management acts mostly on rational knowledge,
leadership acts mostly on emotional knowledge, and organizational cul-
ture on spiritual knowledge. Knowledge is created at individual level and
then through complex social processes it is amplified and structured at
the team and organizational levels (Nonakaand Takeuchi, 1995).
The knowledge-based theory of the firm (Nickerson and Zenger,
2004; Spender, 1996; Sveiby, 2001; Tsoukas, 1996) is conceived on the as-
sumption that any organization can be viewed as a system of distributed
knowledge, bounded by an interface which separates the internal fields of
knowledge from the external fields of knowledge. This assumption is also
shared by Schiuma (2009, p. 292), in his model of knowledge assets dy-
namics: “Every organization can be analyzed as a system made of
knowledge elements, that is knowledge resources that are to some extent
interdependent”. Figure 7.2 shows such a holistic view of the firm which
is open to knowledge transfer with respect to the business environment.
8
From a strategic perspective, the firm must be in dynamic equilibrium
with external fields of knowledge forces, and must have the capacity of
responding fast to the rapid and unpredictable changes in the turbulent
business environment. That means to achieve a positive variation of the
level of organizational knowledge, where organizational knowledge re-
sults from the balance between inward fluxes of knowledge, knowledge
creation and the outward fluxes of knowledge.
Figure 7.2 Organizational Knowledge Dynamics
This organizational knowledge dynamics is similar with the conservation
law of energy applied to an open system. However, there is an important
difference with respect to energy conservation since knowledge can be
created and can be destroyed while energy can only be transformed from
one form into another form. The organizational knowledge dynamics
evaluation is necessary in identifying the knowledge gap which is associ-
Knowledge
Acquisition
Knowledge
Loss
Knowledge Creation
Internal
field of
knowledge
External field
of knowledge
Knowledge
Exchange
Interface
Knowledge
Sharing
9
ated to the strategic gap with respect to strategic intention of the firm. As
showed by Zack (1999, p. 135), “underlying a firm’s strategic gap is a po-
tential knowledge gap. That is, given a gap between what a firm must do
to compete and what it can do, there may also be a gap between what
the firm must know to execute its strategy and what it does know”.
Knowledge strategies are designed to close this strategic knowledge gap
which is aligned with the business strategic gap. That “is essential for as-
suring that knowledge management efforts are being driven by and are
supporting the firm’s competitive strategy” (Zack 1999, p. 135). When in-
tangible resources are dominant and the firm is knowledge intensive,
knowledge strategy becomes the driving force of the company, as showed
in the previous chapters.
7.2Knowledge Exploitation Strategy
7.2.1Organizational Ambidexterity
The exploitation strategy might be considered an oxymoron. On one
hand, the concept of “exploitation” means to use efficiently the organiza-
tional resources for a short term gain, and on the other hand the concept
of “strategy” means long term thinking. Since time is a continuum, the
link between short term and long term thinking is done through a process
of continuous adaptation by a systematic exploitation of the existing or-
ganizational knowledge. “Exploitation includes such things as refinement,
choice, production, efficiency, selection, implementation, execution”
(March 1991, p. 71).Knowledge exploitation strategy implies a continuous
adaptation of the organization to the changeable business environment
by making use efficiently of all intangible resources and capabilities exist-
ing in organization. Even though there are contributions to the knowledge
field, they are incremental and contribute to the improvement of what
has already been done without any dramatic impact on competitive ad-
10
vantage. Peter Senge (1999, p. 14) considers that knowledge exploitation
can be seen as a “survival learning” process or “adaptive learning”. It is an
important process, but not sufficient for creating a competitive ad-
vantage: “Adaptive learning is important – indeed it is necessary. But for a
learning organization, adaptive learning must be joined by generative
learning, learning that enhances our capacity to create” (emphasis in orig-
inal).
Generative learning can be realized by an exploration strategy,
which means that an organization, aiming at achieving a competitive ad-
vantage, should create a balance between knowledge exploitation and
knowledge exploration strategies. Some authors call this dynamic capabil-
ity organizational ambidexterity (Andriopoulos and Lewis, 2009; Cao et
al., 2009; Raischet al., 2009).“The third tension relates to static versus dy-
namic perspectives on ambidexterity. Although some research suggests
that sequential attention should be paid to exploitation and exploration,
the majority of organizational ambidexterity research presents a range of
solutions that enables organizations to simultaneously pursue the two ac-
tivities” (Raischet al., 2009; p. 686). However, organizational ambidexteri-
ty is conditioned by the limited resources and capabilities which should
be allocated for implementing these two complementary strategies and
by the goal of shareholders of maximizing their profit for all investments
made. Also, it is well-known that returns from knowledge exploitation are
faster than those of knowledge exploration, and that they have a lower
degree of uncertainty. What is good for shareholders in a short run might
not be good for the whole organization in the long run. The strategic solu-
tion to this conflicting decision process is creating a dynamic equilibrium
between knowledge exploitation and knowledge exploration since both
of them are essential for the strategic positioning of organization (March,
1991; Raischet al., 2009). Moreover, results of knowledge exploitation
can be fed up in knowledge exploration, and outcomes of knowledge ex-
ploration can be improved incrementally by knowledge exploitation.
As a strategy, knowledge exploitation can be implemented
through a series of processes which have, as a common base, increasing
efficiency of using the known organizational knowledge for improving the
11
existing routines, procedures, products and services. It is the essence of
the known-knowns domain of the awareness matrix presented in Figure
7.1. In the following sections, we shall present two of the most successful
applications of this strategy, namely knowledge codification and
knowledge mapping.
7.2.2 Knowledge Codification
Knowledge codification implies transforming cognitive, emotional and
spiritual knowledge into messages that can be understood by all employ-
ees of a certain organization. It occurs inside the organization but its con-
sequences should be observed in both internal and external environment.
Knowledge codification enables knowledge communication, knowledge
use and reuse. Without data, information and knowledge codification
communication between people, between people and computers, be-
tween computers and intelligent technological artifacts, or between or-
ganizations and their external business environment, would have not
been possible. Codification is usually defined as a process of transforming
an idea into an object, using a code that can range from an abstract to a
metaphorical form. Starting from this assumption, knowledge codification
is presented as a process that supports “the inscription of knowledge in
symbolic forms” (Cacciatoriet al., 2012). If natural language, numbers or
analytical models are used as codes, then knowledge is converted into
declarative statements, documents, databases, lessons learnt reports and
best practices handbooks. If nonverbal language, images or graphical
models are used as codes, knowledge is codified into videos, practices
and conduits. The rich diversity of codes from natural to symbolic lan-
guages emphasizes the adaptable and contextual character of knowledge
codification. However, the choice of codification models and technologies
depends on the economic metrics and constrains. As emphasized by
Cowan et al. (2000, p.22), “In practice, the extent to which knowledge is
codified is determined by incentives: the costs and benefits of doing so.
12
For instance, many factors – such as, to take the simplest argument, the
high cost of codifying a certain type of knowledge – can decrease the in-
centives to go further, by lowering the private rate of return on codifica-
tion”.
For some authors, codification is more focused on formal
knowledge and its processing capability by a firm. For instance, Janicot
and Mignon (2012, p.6) define codification as “a process of storage, in-
dexation and distribution of formal knowledge independently of any con-
text. To complete this definition, the concept of codification can be
broadened to include standardization of knowledge”.
Knowledge codification constitutes an imperative for any organi-
zation which aims at achieving competitive advantage, especially for the
knowledge intensive business service firms. It integrates both human and
software agents with the dominant role played by people and not the
technology. Knowledge codification enables verbal and nonverbal com-
munication at individual and organizational levels. At individual level, ver-
bal codification is used during combination processes while nonverbal
codification appears during socialization processes as described by Nona-
ka and Takeuchi (1995) in the famous SECI model. Both verbal and non-
verbal messages resulting from codification express encrypted ideas, ex-
periences, beliefs and cultural values (Nonaka and Takeuchi, 1995;
Spender and Strong, 2014; Stacey 2001).
Explicit knowledge is, in itself, a result of a mental codification
process by using a natural language. Then, written knowledge is a result
of codification by using grammatical codes and cultural routines. Organi-
zational knowledge in its multiple forms is also a result of codification and
integration of all employees’ knowledge. It is a shared knowledge. Creat-
ing data, information and knowledge bases is possible only by using spe-
cific codes to structure, store and retrieve them: “rapid advancement in
software agent technology has allowed for embedding organizational da-
ta, routines and processes into routines, repositories and function-
creating opportunities for time-saving, duplication of effort, and con-
sistency through rule-based reasoning” (Datta and Acar, 2010; p. 48). All
the rules and constraints are based on a specific logic which essentially
13
represents a codifying process. However, coding data, information and
knowledge implies decoding, which means the intervention of the human
agents for their retrieval, reinterpretation and re-contextualization. In
knowledge codification, human and information intelligent agents are
synergistically bound as a result of systems thinking (Gharajedaghi, 2006;
Senge, 1999) and nonlinear processes (Bratianu, 2009; Gladwell, 2000).
Codification emerged as a necessity process for making possible commu-
nication in a social context, and as a means of increasing the cognitive
value of organizational knowledge. However, that depends on the trust
existing among people, among organization and its stakeholders in using
codified knowledge. As remarked by Scarso and Bolisani (2012, p. 19),
“the issue of trust is significant in KIBS-client interaction, especially when
customized services delivered by means of a sparring relationship are in-
volved”. We shall discuss more about trust in a further section presenting
the knowledge sharing strategy.
Considering the multi-field theory of knowledge (Bratianu, 2015a)
we have to consider not only rational or explicit knowledge but also emo-
tional and spiritual knowledge. From this perspective, two domains of
knowledge codification should be presented: dress codes and ethical
codes. A dress code is a set of requirements an organization may formu-
late with respect to the way its employees should wear to work. Dress
codes vary from organization to organization and range from formal to
business casual, or casual. At one extreme a dress code might imply a uni-
form while at the other there are only some suggestions for casual and
descent dress. A dress code incorporates rational, emotional and spiritual
knowledge in different proportions. For instance, in a hospital, medical
doctors usually have white colored dresses which mostly integrate ration-
al and emotional knowledge, while in a university, professors and stu-
dents wear, during special ceremonies, traditional caps and gowns which
mostly incorporate emotional and spiritual knowledge. Dress codes are
usually requested in firms where employees have interactions with cus-
tomers, like law firms, accounting firms, fast food restaurants, shopping
centers or airplanes. In workplaces where some employees interact with
customers or clients, and others do not have these business interactions,
14
organization may choose to have two different dress codes. IBM was fa-
mous not only for its computers but also for its organizational culture-
which requested a formal business attire: “It was well known throughout
business circles that IBM salespeople – or, for that matter, any IBM em-
ployee – wore very formal business attire. Tom Watson established this
rule when IBM was calling on corporate executives who – guess what –
wore dark suits and white shirts!” (Gerstner, 2003; p. 184). That dress
code resisted up until 1995 when the new CEO Gerstner, Jr. abolished it.
IBM is also an excellent example of the way the founder Thomas Watson
Sr. could impose the company his beliefs and values creating an organiza-
tional culture of respect, hard work, and ethical behavior. Reflecting on
that aspect, Gerstner Jr. (2003; p. 182) remarked: “I came to see in my
time at IBM, that culture isn’t just one aspect of the game – it is the game.
In the end, an organization is nothing more than the collective capacity of
its people to create value. Vision, strategy, marketing, financial manage-
ment – any management system, in fact – can set you on the right path
and carry you for a while. But no enterprise – whether in business, gov-
ernment, education, health care, or any area of human endeavor – will
succeed over the long haul if those elements aren’t part of its DNA” (em-
phasize in original). Shared values create a framework for the decision
making process which becomes a code of ethics for all employees. Ac-
cording to Collins English Dictionary, an ethical code is “a set of moral
principles used to govern the conduct of a profession”.
An ethical code for any organization represents a deep codifica-
tion process which involves all types and forms of knowledge and is
strongly interacting with its vision, mission, and strategizing process. For
IBM the basic beliefs representing the backbone of its ethical code formu-
lated by its founder and reinforced by Watson, Jr. are the following
(Gerstner Jr., 2003, p. 184):
Excellence in everything we do.
Superior customer service.
Respect for the individual.
15
A great organization is one with a great set of moral values which
are shared by all its employees. It is valid not only for firms but also for
not-for-profit organizations. A good example can be the world-class uni-
versities and their ethical codes. We shall illustrate this idea considering
one of the most prestigious universities in the world - Harvard University.
Since there are different formulations for different schools, we shall pre-
sent the principles of the academic community of The Harvard Kennedy
School posted on the official site of the university:
Respect for all members of our community and for the space we
share.
Professionalism in all things, including the pursuit of intellectual
and academic excellence.
The recognition of the value of different opinions in our "free
marketplace of ideas."
Individual accountability for actions inconsistent with this Code of
Conduct.
Members of the community have a personal responsibility to in-
tegrate this code into all aspects of their experience.
In conclusion of this section, we would like to emphasize again that
knowledge codification should not be limited only to explicit knowledge
and information systems. Codification is a complex process which inte-
grates in specific forms rational, emotional, and spiritual knowledge and
contributes directly to the increase of organizational effectiveness as a
dynamic capability able to produce and sustain the competitive ad-
vantage of the firm.
7.2.3 Knowledge Mapping
Knowledge exploitation as a strategy implies two essential conditions for
knowledge management: a) to have a realistic evaluation of organization-
al knowledge and its distribution through the whole organization; b) to
have the capability of using and re-using efficiently that available organi-
zational knowledge. The first condition reflects the managerial capacity of
16
evaluating the quantity, quality, distribution, and transferability of
knowledge resources in all their form. That means to accept that
knowledge is not uniform and homogeneous from a quality point of view
and that it is compelling to distinguish between procedural knowledge
and expertise, or between rational, emotional and spiritual knowledge.
Although there are some methods proposed to measure knowledge di-
rectly (BolisaniandOltramari, 2012; Vallejo-Alonso et al., 2011), or indi-
rectly by measuring the intellectual capital of an organization (Andriessen,
2004; Guthrie et al., 2012; Sveiby, 2010), the complexity of the problem
delays the creation of a metric able to provide acceptable results
(Bolisani, 2016). We will discuss more about this topic in Chapter 8.
Knowledge distribution is not uniform through an organization, since
knowledge resides mostly in people and they have different levels of edu-
cation and experience, and they are working in activity domains with dif-
ferent levels and types of knowledge. Transferability of knowledge de-
pends on the form of knowledge and different individual and
organizational barriers. While explicit knowledge can be transferred easily
from one part of organization to another, tacit knowledge remains em-
bodied in the employees’ experience and can be shared through socializa-
tion or conversion to explicit knowledge (Bratianu, 2015a; Nonaka and
Takeuchi, 1995).
The second condition of using and re-using the available organiza-
tional knowledge efficiently depends on the managerial intelligence and
the tools available. Knowledge mapping is a complex process that inte-
grates organizational intelligence, dynamic models and IT tools (Driesse-
net al., 2007; Kim et al., 2003; Lee and Fink, 2013; van den Berg and
Popescu, 2005). The result of this process is a knowledge map which be-
comes a navigating tool for organizational knowledge. “A knowledge map
portrays the sources, flows, constraints, and sinks (losses or stopping
points) of knowledge within an organization” (Liebowitz, 2005; p. 77).The
first generation of knowledge mapscontains maps whichare based on the
metaphor of knowledge as stock representing only databases and sources
of knowledge within the organization. These knowledge maps offer a
static representation of knowledge distribution and related topics (docu-
17
ments, operational information, people) for the use of knowledge seekers
and decision makers. From a very practical point of view, they are soft-
ware programs based on a certain taxonomy and structure of organiza-
tional knowledge, and a specific logic of coding, storing and retrieving da-
ta, information and knowledge. Also, they can identify people with some
profile (i.e. specific experience and expertise on given activity domains).
Knowledge maps can have a hierarchical or neural structure. In the first
case, the search is based on a top-down semantic search while, in the se-
cond case, the search is based on key words and neural-like branches. In-
stead of progressing linearly with the search from one level to another
structure level, the neural maps provide semantic connections like the ra-
diant thinking used in Mind Maps (Buzan and Buzan, 1993; p. 59): “The
Mind Map has four essential characteristics: a) the subject of attention is
crystallized in a central image; b) the main themes of the subject radiate
from the central image as branches; c) branches comprise a key image or
key word printed on associated line, and topics of lesser importance are
also represented as branches attached to higher branches; d) the branch-
es form a connected nodal structure”. The value of knowledge maps re-
sides in the global image of the available (explicit and tacit) knowledge in
organizations, and algorithms to find and use the needed knowledge.
Thus, knowledge maps help to re-use critical knowledge and increase the
exploitation efficiency.
The second generation of knowledge mapsis based on the con-
ceptual metaphor of knowledge as stocks-and-flows. A knowledge map of
this category representsthe sources of all types of knowledge with their
main attributes, and the flows of knowledge from one part of organiza-
tion toward another one. Kim et al. (2003, p. 36) define such a knowledge
map as “a diagrammatic representation or corporate knowledge, having
nodes as knowledge and links as the relationships between knowledge,
and knowledge specification or profile”. Thus, knowledge mapping
evolved to include not only sources of information and knowledge but al-
so the main knowledge flows within the organization. It is a mapping of
the Nonakian dynamics of organizational knowledge (Nonaka, 1994; No-
naka and Takeuchi, 1995). Knowledge flows are generated and structured
18
by business process flows. As Yooet al. (2007; p. 107) remark, “Knowledge
flows and business processes cannot be separated because knowledge is
inputted and outputted through business processes. Knowledge flows in-
herit the feature and appearance of corresponding business processes”.
A knowledge map consists of two components: a) diagram –
graphical representation of knowledge, having nodes and linkages; b)
specification – descriptive representation of knowledge. Knowledge maps
help employees to search easily for the available knowledge within organ-
ization and use it such that they can optimize the cognitive work and in-
crease productivity of knowledge processing. There are some clear ad-
vantages of building and using knowledge maps (Driessenet al., 2007; Kim
et al., 2003; Lee and Fink, 2013; O’Donnell et al., 2002):
Codification and formalization of all knowledge inventories within
an organization based on certain ontology and processing logic.
Increasing knowledge retention from experts who retire, by mak-
ing their expertise known and available to other knowledge seek-
ers.
Understanding of relationships between different knowledge
sources or between knowledge sources and knowledge users. Al-
so, easierunderstanding of cause and effect relationships.
Efficient navigation across the organizational knowledge fields
and reduction in cognitive load for knowledge seekers, due to
their holistic representation of relationships among complex con-
structs.
Stimulation of knowledge sharing and creation of communities of
practice based on common interests. That results in an increasein
the average level of organizational knowledge and in stimulated
innovation.
In a synthetic manner, Kim et al. (2003; p. 37) conclude: “The knowledge
map plays a key role in the KM project because it gives a knowledge pro-
file (knowledge warehouse), knowledge link (navigation aids among
knowledge), and expert finder”.
19
7.3 Knowledge Acquisition Strategy
7.3.1 Knowledge Acquisition
Knowledge acquisition means finding ways of increasing the level of or-
ganizational knowledge by purchasing knowledge from the external busi-
ness environment. In a strategic perspective this strategy contributes to
closing the knowledge gap (Zack, 1999) between what is available in the
firm and what is needed for achieving a strategic objective. Knowledge
acquisition is conceived as an alternative to knowledge creation, when
the firm’s human capital is not able to generate new knowledge or the
process of knowledge creation is beyond the financial resources of the
firm (Chasto nand Mangles 2000; Davenport and Prusak 2000; Hoe and
McShanne 2010). Usually, that situation happens when the firm is small
and makes efforts to develop new products and services. Knowledge ac-
quisition is a common strategy used by SMEs (Chan and Chao 2008;
Desouza and Awazu 2006; Durst and Edvardson 2012). Knowledge acqui-
sition in organizations spans a large spectrum of activities aiming in con-
cordance with the size of organization and its mission. It refers mostly to
cognitive knowledge since emotional and spiritual knowledge is generat-
ed internally by people and their cultural values.
It represents just one activity of a broader and more complex
process, as shown by Liao et al. (2010; p. 21): “Acquiring knowledge is the
first activity in the broader activity of accepting knowledge from the ex-
ternal environment and transforming it into a representation that can be
internalized, and/or used within the organization”.
Knowledge acquisition is a frequently used strategy for entrepre-
neurial firms. As Studdard and Munchus (2009; p. 243) remark, “one of
primary factors that hinder the formation and development of entrepre-
neurial firms is resource constrains. It is difficult for the entrepreneurial
firm to sufficiently generate and acquire internal and external
knowledge”. Knowledge acquisition can be done in various ways, from
buying access to scientific literature and knowledge bases, to hiring skilled
20
people. For designing knowledge strategies, firms can purchase expertise
from consulting companies and organize training programs for specific
needs by hiring experts. For all firms (regardless their size), whose strate-
gic intention is innovation, it is critical to acquire intellectual properties
rights by purchasing patents. A successful strategy for small firms to in-
crease knowledge acquisition with reasonable costs is to become part of
some knowledge or learning networks (Chaston and Mangles 2000).
Network knowledge transfer focuses mostly on explicit rational
knowledge. Emotional and spiritual knowledge has been used during the
negotiation and formation of the learning network. Without a conver-
gence of spiritual knowledge fields from member firms the construction
and operation of the network is almost impossible. Spiritual knowledge is
the driving force of the whole learning network, and emotional
knowledge from each firm may become the catalyst of the learning pro-
cess. It is interesting to note that learning processes are nonlinear, and
that the network effect on knowledge transfer increases exponentially
with the number of participants. Knowledge networks enlarge the bound-
ary of the organizational knowledge fields and create the need of finding
ways of integrating the internal and external knowledge. “With the
knowledge integration model the skillful coordination, collaboration, and
integration of vertical and horizontal boundaries promote the dynamic
knowledge integration process, and build strategic innovation capability”
(Kodama, 2011; p. xii). An alternative of becoming a part of a business
network is to create business alliances, which are forms of collaboration
“where two or more organizations share resources and activities to pur-
sue a strategy” (Johnson et al., 2011; p. 338). In such a business alliance,
one of the strategic partners can share its knowledge. Thus, a business al-
liance has a critical role in the process of knowledge acquisition because it
facilitates firm’s access to best practices and shared markets (Grant,
1996; Tsai, 2001).
Knowledge acquisition depends on the absorptive capacity of the
organization. The concept of absorptive capacity has been coined by Co-
hen and Levinthal (1990) and reflects the organization’s capability to val-
ue, assimilate and apply knowledge coming from external sources. When-
21
ever a firm has to establish the future business strategy or to elect the
most efficient manner of adapting to market demand, it analyzes the
business environment, it identifies and captures the critical knowledge,
and then it develops the necessary structures and systems for using the
acquired knowledge. Organizational absorptive capacity is based on indi-
viduals’ absorptive capacity, and their integration derives from a man-
agement effort and from the use of IT systems that are employed in the
firm. Based on its organizational absorptive capacity, a firm identifies the
knowledge that must be acquired, determines the most efficient way to
assimilate the selected knowledge and also balances the new knowledge
with the previous one.
7.3.2 Knowledge Capturing
Knowledge capturing is a process through which trained people can ex-
tract valuable knowledge from experts and embed it in databases or intel-
ligent software programs. Experts are individuals with a high level of
knowledge and understanding in a given field of activity. By integrating all
knowledge and experience, acquiredby performing a series of intellectual
activities,experts develop a significant expertisein time. This expertise is
not proportional with the number of years spent in the same do-
main,because it is not a linear entity. Expertise is a nonlinear intangible
which correlates with the variety of experiences and the quality of
knowledge integrated through hard work and intelligent processing. Ex-
pertise is an excellent example of integration of rational, emotional, and
spiritual knowledge, generated during a long period of time and stored as
experience in our memory. “The bottom line truth is that tacit knowledge
is not so much transferred as it is acquired and the process for acquiring
tacit knowledge requires personal experience. There are no shortcuts.
People don’t become experts by reading what others have written, they
become experts by doing” (Eucker, 2007; p. 12).
22
Expertise is related to experience, and through experience to
time, but not only quantitatively. Intensity of work and high motivation
are also important factors in becoming an expert. Research performed in
this field concluded that true expertise needs about ten thousands of
working hours on the same topic or focused on the same type of activity
(Levitin, 2006). Discussing about expertise Gladwell (2008, p. 45) under-
lines the same idea for the chess activity domain: “To become a chess
grandmaster also seems to take about ten years. (Only the legendary
Bobby Fischer got to that elite level in less than that amount of time: it
took him nine years.) And what’s ten years? Well, it’s roughly how long it
takes to put in ten thousands hours of hard practice. Ten thousands hours
is the magic number of greatness”.
Knowledge capturing from experts enables the realization of ex-
pert systems which are software tools to support decision making. “An
expert system can provide people with advice by replacing part of the
reasoning that is performed by experts. In fact, experts can use such a
system themselves to reduce workload when there is too much to do and
too little time” (Milton, 2007; p. 3).In essence, an expert system is com-
posed of a computable knowledge base of domain concepts and an inter-
face engine of procedural rules if-then. Many expert system developers
discovered that the difficulty is not to design and write a computer pro-
gram but to elicit knowledge from experts. There was a “knowledge ac-
quisition bottleneck” since knowledge engineers were able to create
computer programs but they have no training in capturing knowledge
from experts. To overcome their lack of experience in capturing
knowledge from experts, knowledge engineers developed some auto-
mated knowledge acquisition systems called “shells”. A shell is an interac-
tive computer program that contains a series of questions aiming at ex-
tracting knowledge directly from experts. That means that each shell can
be used only for a well-defined class of problems for which there is a sig-
nificant knowledge captured. Moreover, these expert systems deal only
with rational knowledge although any decision process is conditioned by
the integration of rational, emotional and spiritual knowledge (Bratianu,
2015a). Research performed in cognitive sciences concerning knowledge
23
capturing converged to a new activity called Cognitive Task Analysis (Clark
et al., 2008; Hoffman andLintern, 2006). Although there are several
methods of performing Cognitive Task Analysis, the main stages of the
process are essentially the same: a) search for and collect preliminary
knowledge; b) identify knowledge representation; c) use a combination of
knowledge elicitation methods; d) analyze, verify and interpret data ac-
quired; e) put the final result into an adequate format. The outcome of a
knowledge elicitation process is a knowledge base, a knowledge store, a
knowledge repository or an ontology. From Knowledge Management
point of view the main limitation of any expert system is the emphasis on
rational knowledge and on the if-then logic.
7.3.3 Knowledge Retention
Knowledge retention is the result of applying knowledge captured from
experienced workers who retire. As shown in Figure 7.2, organizational
knowledge should find a balance by compensating the knowledge loss
(due to people who leave the firm because they retire or are fired, for ex-
ample during an economic crisis). Especially when thousands of employ-
ees suddenly leave a company, the dynamic equilibrium of organizational
knowledge is severely destroyed. A famous example comes from Boeing
(DeLong 2004, p. 19): “After Boeing offered early retirement to 9,000 sen-
ior employees during a business downturn, an unexpected rush of new
commercial airplane orders left the company critically short of skilled
production workers. The knowledge lost from veteran employees com-
bined with the inexperience of their replacements threw the firm’s 737
and 747 assembly lines into chaos”. Another example is givenby DeLong
(2004) and concerns the impact of knowledge loss on organizational
knowledge dynamics of Delta Airlines. The company decided, during a
downsizing operation in 2001, to offer attractive packages to senior
workers for leaving the company. As a result, 11,000 employees voluntari-
ly left the company, including about 1,200 aviation maintenance techni-
24
cians, many with 20-30 years of experience at Delta Airlines. Although the
business of the company improved as a result of cost cutting with salaries,
the company later suffered from a severe knowledge loss, with negative
long term consequences.
Knowledge retention is a complex process through which organi-
zations can reduce knowledge loss. DeLong (2004) analyzes knowledge
retention strategies and group them into four main categories: a) human
resources, processes and practices; b) knowledge transfer practices; c)
knowledge recovery initiatives; and d) information technology applica-
tions to capture, store and share knowledge. In the first group we have all
the methods and mechanisms that human resource departments may use
to create a long-term approach for reducing the individual and organiza-
tional knowledge lossqualitatively and quantitatively. That means to im-
prove the system for evaluating employees’ competences and to analyze
where the organization is at risk with losing critical knowledge. That anal-
ysis should be complemented with an extensive career development and
managerial succession planning processes. Another issue related to
knowledge retention is the succession of departing leaders. Intelligent or-
ganizations create plans for leadership succession to make a slowly and
efficient transfer of knowledge from the leaders who retire towards the
new generation of leaders. That means to develop a process of intergen-
erational learning and to create a necessary culture for making it efficient
(Lefter et al., 2011; Tichy and Cohen, 2007). Great leaders like Jack Welch
of General Electric, Andy Grooves of Intel, and Roger Enrico of PepsiCo
spent a lot of their agenda’s time in teaching younger generations of
leaders. As Tichy recalls (2007; p. 56): “Jack Welch of General Electric is
one of the most dedicated teachers I know. For twenty years he has made
biweekly visits to GE’s Crotonville executive training center to enter into
dialogue with thousands of his employees each year. His schedule was al-
so filled with hundreds of video conferences, meetings, factory visits and
workshop sessions”. Also, Jack Welch designed a comprehensive program
to prepare the next CEO of GE when he will retire, and Jeff Immelt is the
proven success of this process.
25
7.4 Knowledge Sharing Strategy
7.4.1 Knowledge Sharing
Knowledge sharing is a strategy that increases the average level of organi-
zational knowledge and contributes directly to the increase of organiza-
tional entropy. Intelligent and creative organizations discovered that
achieving competitive advantage through innovation needs a higher level
of knowledge and a higher value for their organizational entropy. As a
process, knowledge sharing contributes to organizational knowledge cre-
ation from individuals’ knowledge. “Organization cannot create
knowledge on its own without the initiative of the individual and the in-
teraction that takes place within the group. Knowledge can be amplified
or crystallized at the group level through dialogue, discussion, experience
sharing, and observation” (Nonaka and Takeuchi, 1995; p. 13). Knowledge
sharing is a process by which an individual is willing to share his or her ex-
perience with others without expecting any financial reward out of it. It is
not an imposed activity by the managers like a working task, although it
could be stimulated by creating an organizational culture favorable to it.
Knowledge sharing involves activities of transforming or disseminating
knowledge from one person to another, to a group of people, or to a
whole organization. According to Cyr and Choo (2010; p. 825), knowledge
sharing in organizations may be viewed “as the behavior by which an in-
dividual voluntarily provides other members of the organization with ac-
cess to his or her knowledge and experiences. Knowledge sharing encom-
passes a broad range of behaviors that are complex and multi-faceted”.
Its importance comes from the fact that knowledge sharing links the indi-
vidual knowledge fields where knowledge is generated, to the organiza-
tional level where knowledge is applied and attains value.
The opposite attitude to knowledge sharing is knowledge hoard-
ing (Cyr and Choo, 2010) which reflects egoism, lack of trust in other peo-
ple and fear of losing power. Knowledge sharing is a voluntarily process
but it depends on many personal and organizational factors that may
26
stimulate it or may inhibit it. Szulanski (1995; 2000) extended the mean-
ing of the concept of stickiness introduced by von Hippel (1994) for in-
formation transfer within an organization to knowledge sharing and
transfer. “The assessment of the degree of difficulty experienced in a
transfer is likely to reflect the number and intensity of those distinct mo-
ments of difficulty. Other things equal, a transfer is more likely to be per-
ceived as difficult or sticky when efforts to resolve transfer problems be-
come noteworthy” (Szulansky, 2000; p. 11). Knowledge stickiness appears
especially in organizations where there is a culture of fierce individual
competition and a fear of losing a certain usefulness if one’s expertise is
shared to a group of people. At the limit, the person who shared his or
her experience is not of interest anymore and he or she can be fired at
any time. In organizations where there is a team culture and cooperation
is valued both by managers and employees, knowledge sharing is a cur-
rent practice. In such situations, there is a culture of trust and of reward-
ing for people who share their knowledge. Nonaka and Takeuchi (1995)
show that much of the business success of Japanese companies resides in
their organizational culture of team work and knowledge sharing.
Trust is a powerful concept that has been used in many fields of
activity, and defined in different ways. For instance, economists define
trust in terms of quantitative aspects which can be measured using eco-
nomic metrics, while psychologists define trust in terms of qualitative at-
tributes of trustors and trustees. Sociologists focus on the quality of rela-
tionship between people and on the social context that influences them.
One of the classic definitions which got some popularity has been formu-
lated by Gambetta (Castelfranchi and Falcone, 2010; p. 19): “Trust is the
subjective probability by which and individual, A, expects that another in-
dividual, B, performs a given action on which its welfare depends”. The
definition focuses on the subjective probability of an individual which
cannot be computed mathematically and reduces in practice to a person-
al belief. A more developed model of trust has been formulated by Mayer
et al. (1995). It switches the focus from the attributes of trustor to the
quality of the relationship between trustor and trustee and introduces
the aspect of vulnerability. In their view, trust is “the willingness of a par-
27
ty to be vulnerable to the actions of another party based on the expecta-
tion that the other will perform a particular action important to the trus-
tor, irrespective of the ability to monitor or control that other party”
(Mayer et al., 1995; p. 712). It is evident that trust is a complex concept
which integrates attributes of both trustor and trustee as well as the qual-
ity of their relationship in a given social context. Since the trustor be-
comes vulnerable to the possible negative consequences from the trus-
tee, we can now understand why, in an organizational culture with a low
level of trust, people are not willing to share their knowledge. Education,
training and solid rewording systems should be used for a long time in or-
ganizations to build the necessary climate of trust and to stimulate
knowledge sharing.
7.4.2 Communities of Practice
Communities of practice are not new ideas. They have been always pre-
sent in the human history under diverse forms and structures. For in-
stance, during the Middle Age, there were craft guilds that played similar
roles like today’s professional communities of practice. They disappeared
as a result of the industrial revolution, but communities of practice con-
tinued to develop in almost any aspect of human life. According to
Wenger et al. (2002; p. 4), “Communities of practice are groups of people
who shape a concern, a set of problems, or a passion about a topic, and
who deepen their knowledge and expertise in this area by interacting on
ongoing basis”. People who create these communities of practice can
work together in the same company or not. Their institutional affiliation is
not important. They find value in being together and sharing their ration-
al, emotional, and spiritual knowledge as well as their aspirations to
achieve some strategic objectives. Emotional and spiritual knowledge
have also an important role in creating the social gravity field since there
are no compulsory forces to act upon those who join a community of
practice. The high level of trust and the common cognitive interests stim-
ulate knowledge sharing and knowledge creation. Traditionally, communi-
28
ties of practice have often been groups of people who share face-to-face
their knowledge. More recently, communities of practicesalso tend to be-
come virtual networks where knowledge is shared by using all opportuni-
ties offered by advanced information systems and technologies (North
and Gueldenberg, 2011; O’Dell and Hubert, 2011; Pasher and Ronen,
2011).
Knowledge sharing in communities of practice stimulates learning
and knowledge creation. As a result, these communities of practice may
become knowledge or learning communities. North and Gueldenberg
(2011; p. 149) define a knowledge community as “a group of people exist-
ing over a relatively long period who have interest in a common domain
and want to develop and share knowledge together. Participation is vol-
untary and personal. Knowledge communities are formed around specific
topics”. Communities of practice may have short or long life cycles, they
may become a successful project or a failure. Like any social construct, a
successful community of practice needs to satisfy some requirements
(North and Gueldenberg, 2011):
A well-defined domain of knowledge sharing that is attractive to a
large spectrum of people.
A leader able to create an attraction field of interests around him
and a high level of social trust.
A critical mass of people gathering and sharing knowledge.
An agenda of events which can be improved continuously.
A rewording system such that the most active participants to feel
that their efforts are appreciated by the other members.
A website, newsletter or other publications. These are essential
for creating a dynamic communication between members of
community.
The leader plays an essential role in designing that community of practice
and attracting people as a result of his or her recognized expertise in that
knowledge sharing domain. The leader should be able to create the nec-
essary critical mass of participants and an interesting agenda of events
able to keep alive the community. In some online communities of prac-
tice, created by using some smart websites, the leaders do not appear di-
29
rectly, but their expertise has been embedded in the structure and func-
tionality of the online platforms.
It is interesting to see how great companies designed and imple-
mented knowledge sharing models and developed communities of prac-
tice. We shall consider for illustration the case of ConocoPhillips (O’Dell
and Hubert, 2011) which is an international, integrated energy company
and the third-largest oil and gas company in the United States. The com-
pany has about 30,000 employees working in over 30 countries.
“Knowledge sharing methods were adapted to promote functional excel-
lence and leverage knowledge across organization. Knowledge sharing
sponsorship is now organization-wide and supported by all business
streams” (O’Dell and Huber, 2011; p. 163). The company developed a cul-
ture able to support and stimulate knowledge sharing as a means of
learning for all employees. The company created more than 120 commu-
nities of practice known as networks of excellence. These communities
are aligned in their activities with the business processes contributing to
achieving competitive advantage. The experience obtained so far in run-
ning these networks of excellence reveal the following key success factors
(O’Dell and Hubert 2011; p. 166):
1. Leadership and sponsorship.
2. A clear business case with a well-defined knowledge domain.
3. Adequate resources and defined roles.
4. Member engagement.
5. Deliverables and activities.
6. The development of trusted relationships.
7. Knowledge transfer processes.
8. Supporting information technology.
9. A system for motivation, recognition of results, and rewards for
performance.
10. Network measurements for keeping track of each member activi-
ty.
The whole knowledge sharing system and all 120-plus networks of excel-
lence are managed by a team of six experts. “The team addresses strate-
gic goals and leverages resources across the organization. Working with
30
all business streams and functional units, it is responsible for maintaining
established networks and managing associated training, metrics, and por-
tal sites” (O’Dell and Hubert, 2011; p. 167). However, by far the most im-
portant result of the company vision in implementing that knowledge
sharing system is the development of a knowledge sharing culture, based
on mutual trust. To build trust, the company organizes face-to-face meet-
ings and networking where people get the feeling of being members of
the same community. However, there is the challenge of people working
in different geographical zones with different cultural values and time
zones. For instance, employees from western countries feel comfortable
with posting questions and comments, while employees from Asia-Pacific
region don’t feel that way since they have a team culture and find real dif-
ficult to single them out by asking questions. Leaders of each community
can try to find out solutions to overcome these cultural barriers.
7.5 Knowledge Exploration Strategy
7.5.1 Knowledge Creation
Although people enjoy living and working in a comfortable zone of
known-knowns, the new turbulent business landscape increasingly im-
poses to search for the unknown-unknowns zone, which features a high
levels of uncertainty and risks. Emergent strategies replace the deliberate
ones and knowledge exploration strategies replace the exploitation strat-
egies. “The essence of exploration is experimentation with new alterna-
tives. Its returns are uncertain, distant, and often negative” (March, 1991;
p. 85). Exploration means to search for new knowledge and ways of in-
creasing the level of organizational knowledge. Knowledge management
will stimulate knowledge creation and knowledge acquisitionin perspec-
tive, from inside the organization as well as from external environment.
Open innovation is already a well-established process of acquiring new
31
knowledge from external contributors. However, searching for new
knowledge is a costly strategy and the outcomes are not certain. The risks
associated to knowledge exploration are significantly higher than those
associated with knowledge exploitation of organizational knowledge. Top
management should be guided by a strong vision concerning the explora-
tion of new ventures to produce goods and services. Knowledge explora-
tion became a key strategy for innovative companies. Steve Jobs was such
a visionary leader who wanted to change the world. “Under Job’s leader-
ship, Apple has earned a reputation as one of the most innovative com-
panies in technology. Business Week in 2007 named Apple the most inno-
vative company in the world, beating Google, Toyota, Sony, Nokia,
Genentech, and a host of other A-list companies” (Kahney, 2008; p. 179).
The most important contribution of an exploration strategy is giv-
en by knowledge creation. According to the Data-Information-Knowledge-
Wisdom (DIKW) model, information is a result of processed data and
knowledge an outcome of the processed information (Davenport and
Prusak, 2000; Jashapara, 2011; Rowley, 2007). In this conceptual frame-
work, knowledge creation means information processing. However, the
domain of information processing belongs to information science where
information is the pivotal concept and it is defined based on Shannon
mathematical theory of communication (Bratianu, 2015a). Since there are
different perspectives in information science and in knowledge manage-
ment concerning the meaning of information, we shall confine our discus-
sion to the knowledge management approach, and we shall present the
main ideas of the famous Nonaka’s theory of knowledge creation dynam-
ics (Nonaka, 1994; Nonaka and Takeuchi, 1995; Nonaka et al., 2008). The
model is based on a series of knowledge transformations which can be
represented on a diagram defined by epistemological and ontological di-
mensions. The epistemological dimension reflects the individual contribu-
tion to knowledge creation, while the ontological dimension reflects the
social contribution. This way, Nonaka creates a synthesis between the
psychological and sociological perspectives of knowledge creation.
The core of the Nonaka’s theory of knowledge creation is the SECI
model, which is composed of four conversion processes of tacit and ex-
32
plicit knowledge (Nonaka, 1994). When people share common
goals,theycan form communities of practice, or communities of business
processes, which contribute to the amplification and development of new
knowledge. These communities define the ontological dimension of the
model. Now, considering this epistemological-ontological knowledge
space, “a spiral model of knowledge creation is proposed which shows
the relationship between the epistemological and ontological dimensions
of knowledge creation. This spiral illustrates the creation of a new con-
cept in terms of a continual dialogue between tacit and explicit
knowledge” (Nonaka 1994, p. 15).
Nonaka’s model shows the important role played by social inter-
actions and by the organizational framework of communication between
employees. That becomes critical in knowledge intensive business pro-
cesses (KIBP) where knowledge fluxes could attain high levels of intensity.
“Within KIBP, it is the human ability to interpret the information obtained
and transform the information to knowledge, thus providing the individu-
al with the opportunity to further develop their own intuition and innova-
tion based on KIBP experiences” (Little and Deokar, 2016; p. 861). From a
psychological perspective, this is a learning process integrating the past
experience and knowledge with their future expectations and the busi-
ness needs (Salmador and Florin, 2013). Individual learning transforms
through social interaction into a social learning process which amplified
up to the organizational level becomes organizational learning (Argote,
2013; Argyris, 1999; Crossan et al., 1999).
7.5.2 Knowledge Co-creation
Knowledge co-creation emerged as a new paradigm for understanding the
new cooperation processes in knowledge creationbetween firms and
their stakeholders. From a process of knowledge creation centered on the
firm’s R&D capability and embedding that knowledge in new products
and services, we face today a transition toward a process of knowledge
creation by the firm in partnership with its stakeholders. “Co-creation is
33
the process where more than one party systematically joins forces to in-
teract, learn and share information to create value” (Kennedy and Guz-
man, 2016; p. 313). These co-creation phenomena have changed the way
business strategies are designed and implemented (Kao et al., 2016; Mill-
spaugh and Kent, 2016; Paswan et al., 2014; Ramaswamy and Ozcan,
2013; Verleye, 2015). As a consequence, the process of value creation is
not centered on the firm anymore but on its working relationships with
customers and other stakeholders involved in the chain production. Con-
sumers want to be involved in a series of activities related to product de-
sign, production and marketing, activities done so far only by firms. As
Ramaswamy and Ozcan (2013, p. 7) remark, “In more and more firms,
strategy making has become a joint process of co-creative discovery, as
enterprises devise and develop new opportunities together with custom-
ers, partners and other stakeholders”.
The knowledge process now extends beyond the boundary of the
firm and integrates knowledge from the external business environment in
new and attractive ways for all participants. The co-creation phenomena
developed in an accelerated way especially in the service field, where ser-
vice dominant logic stimulates knowledge exchange and final consumers
enjoy having their expectations better fulfilled by the firms. This emerging
consumer empowerment is mediated efficiently by social media networks
(Kao et al., 2016; Kennedy and Guzman, 2016). The co-creation phenom-
enon increases the firm’s entropy very much,by reducing its full control
on the production process. That means that there is a need for a new
type of management able to give away some power to the participants in
the co-creation process but to keep the overall control on the chain of de-
signing, production and marketing activities. Kao et al. (2016) identify in a
generic co-creation process five significant stages: interact – creating at-
tractive conditions for interaction; engage – building user trust, loyalty
and a sense of belonging; propose – enhancing knowledge sharing and
users contribution; act – developing consensus and the participation to
collective innovation; realize – evaluation of the result of the co-creation
process.
34
Knowledge exploration strategy becomes essential in the turbu-
lent business environment since the sustainable competitive advantage
cannot be achieved by using the old success business formulas. New vi-
sions and explorations are necessary but not only within the internal
business environment; explorations should extend to the external busi-
ness environment where stakeholders can play an important role in
knowledge co-creation and value co-creation. Closed innovation should
be replaced by open innovation and customers should be part of that new
and rewarding process. That means a new type of leadership and strate-
gizing able to deal with a higher level of entropy and uncertainty.
Approaches to knowledge co-creation can be different, in relation
to the characteristics of product or services, to the attitude of companies,
and to their position in the value chain. Recent studies (Paiola et al., 2013)
have collected evidence of the different possible approaches of compa-
nies aiming at acquiring and exchanging knowledge with external busi-
ness partners, including suppliers and customers.
7.6 Conclusion
Knowledge acquisition strategy is useful for closing the knowledge gap
between what a firm knows and what it is needed to be known for
achieving competitive advantage. Knowledge acquisition comes as a first
choice when the organization does not have a critical mass for knowledge
creation or closing the knowledge gap requests both knowledge acquisi-
tion and knowledge creation. Knowledge acquisition implies purchasing
knowledge from the external business environment by using different
methods and practices. One of the most efficient methods is creating a
business network with other firms or becoming a part of such a network.
A network is an enabler for creating knowledge fluxes and an efficient
balance between those which cross the organization interface in both di-
rections (i.e. inward and outward). Knowledge acquisition is an attractive
strategy for SMEs and especially for those which are entrepreneurial and
35
innovative. The level of acquired knowledge depends on the absorptive
capacity of each organization, which integrates both human and technol-
ogy factors. Much of the organizational knowledge is stored within indi-
viduals who use it performing their tasks and playing the competition
roles. Experience and expertise of many people remain a valuable intel-
lectual capital potential without an efficient contribution to the new
products and services. The only solution to making all that knowledge
available throughout the organization is building a culture of trust and
stimulating knowledge sharing. That can be achieved by encouraging
people to participate in communities of practice where they can share
their experience with others and learn new knowledge from them at the
same time. Knowledge sharing embraces all forms of knowledge (i.e. ra-
tional, emotional, and spiritual knowledge). Finally, exploration strategy
comes with knowledge creation, so that firms can sustain their competi-
tive advantage in a turbulent business environment. Moreover, in design-
ing new products and services, firms open themselves toward their cus-
tomers and other stakeholders, to work together and co-create them.
Open innovation is replacing the old system of closed innovation, and
through co-creation,firms can use the potential knowledge residing in the
external business environment.
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