iBusiness, 2011, 3, 213-219
doi:10.4236/ib.2011.32028 Published Online June 2011 (http://www.scirp.org/journal/ib)
Copyright © 2011 SciRes. iB
Resource Differentiation of Knowledge
Evgeny Popov, Maxim Vlasov*
Institute of Economics, Ural Branch of the Russian Academy of Sciences, Yekaterinburg, Russia.
Email: Mvlassov@mail.ru
Receive February 28th, 2011; revised April 14th, 2011; accepted April 27th, 2011.
ABSTRACT
The objective of the present research is classification of institutions for knowledge generation at a minimal economic
level and formulation of a strategy regarding knowledge generation, which would allow introducing modifications into
engineering processes. Based on the methodological apparatus for institutional economics, classification of economic
institutions for new knowledge generation at a minimal economic level has been accomplished. The author has con-
ducted an empirical study concerned with allocation of shares of new knowledge generation according to the degree of
change impact on production processes of economic entities. As a result of the research carried out by us the structure
of external and internal risks in the context of new knowledge generation has been determined; evaluation of risk factor
significance has been made; weighting coefficient values for each risk factor have been determined through expert es-
timation. The received results allow the enterprises to carry out an estimation, forecasting and planning of generation
of new knowledge.
Keywords: Knowledge Management, Knowledge Differentiation
1. Introduction
Onrush of market relations, generation of positive ten-
dencies towards economic growth and well-being of po-
pulation is grounded on all-round application of achieve-
ments referred to knowledge-based economy.
A fair number of researches are dedicated to resolution
of issues in the context of knowledge-based economy.
However, the mentioned researches are generally nar-
rowed down to consideration of knowledge-based econ-
omy in terms of instrumental approach and opportunities
for economic and mathematical modeling of innovation
development. The issues concerned with cost estimate
and generation of new knowledge remain unsolved.
Processes of generation of new knowledge imply consid-
erable risks, and that is ground for application of tech-
niques related to institutional economics.
Significance of knowledge for economics was first ac-
centuated by F. Hayek in the Nobel lecture of the prize
winners in economics. Hereafter the issues related to the
given field of economics were considered by well-known
researchers of economics in their scientific works. F.
Machlup substantiated significance of new knowledge
generation for development of production activity by e-
conomic agents. А. Marshall, one of the founders of neo-
classical economics, acknowledged significance of know-
ledge in economic processes; he believed that “know-
ledge is one of the most powerful production engines”. K.
Viig determined position of knowledge in a modern
company, and D. Stonehouse investigated conditions fa-
voring knowledge control system functioning. E. Broo-
king and Т. Stewart studied significance ofintellectual
capital for a company. P. Druker considered importance
of transition to knowledge management as a specific
strategic concept. I. Nonaka determined capability of an
economic entity to transform nonformalized knowledge
into formalized one as a fundamental criterion of as-
sessment regarding knowledge generation efficiency. R.
Solow suggested a type of relationship specifying the re-
sults of scientific and technological advance impact on
the results of introduction of innovations, which cause
engineering process change. F. Valenta introduced clas-
sification in terms of profoundness of changes made in a
production process. B. Twiss, carrying out research into
new knowledge generation issues, determined that 80-
90% of activity in the context of new knowledge genera-
tion are not economically efficient in terms of real mar-
ket activity.
The objective of the present research is classification
of institutions for knowledge generation at a minimal
economic level and formulation of a strategy regarding
knowledge generation, which would allow introducing
modifications into engineering processes.
Resource Differentiation of Knowledge
214
2. Differentiation of New Knowledge
Imbalance of actual and desired output of new knowl-
edge is attributed to the lack of elaborated methodologies
in Russian scientific literature that are referred to differ-
entiation of changes introduced by this knowledge into
production processes.
J. Shumpeter singled out the following typical changes
of production processes: application of innovative tech-
nologies and technological processes; introduction of new-
quality production; readjustment of industrial organiza-
tion and logistics [1].
Czech researcher F. Valenta introduced in his mono-
graph classification in terms of profoundness of changes
made in a production process: simple change of quality
specified by low material costs, lack of change-related
risks and, correspondingly, minor profit variance, with
initial system characters are not subject to change; more
profound process change concerned with more consider-
able investments and risks, which allows increasing pro-
duction activity profitability level, with all or most part
of system characters are subject to change, but the basic
structural concept is retained; major change in functional
properties of the system or its part, which modifies its
functional principle and imply considerable financial ex-
penditures and risks [2].
Introduction of new knowledge in the activity by eco-
nomic entities modifies production processes, and it re-
quires classification of new knowledge in terms of pro-
foundness of changes made. The author suggests the fol-
lowing differentiation of new knowledge in terms of pro-
foundness of changes made in production processes (Ta-
ble 1).
The author has conducted an empirical study con-
cerned with allocation of shares of new knowledge gen-
eration according to the degree of change impact on pro-
duction processes of economic entities (Figure 1).
Based on the analysis in Figure 1, the following con-
clusions can be drawn:
First, financing of new knowledge generation within
the scope less than 8% of profit and development of
quality new knowledge does not afford an opportunity
for economic entities to optimize technological processes
and gain significant profit as a result of new knowledge
introduction.
Second, substantial changes in technological processes
and profit from new knowledge introduction occur when
amount of financing of new knowledge generation is
more than 8% of profit; when the share of new knowl-
edge (which, if introduced, results in functional changes
in technological processes) is more than 30% of the total
volume of new knowledge introduced.
In the context of the present situation over the half of
Russian enterprises finance new knowledge of a quality
nature as a basic strategy for new knowledge generation,
which does not give rise to technological process change
and seizing the competitive edge, and, correspondingly,
growth of profits.
Strategy that affords opportunity to optimize the activ-
ity in terms of new knowledge generation and, corresp-
ondingly, to increase profit as a result of new knowledge
introduction, can be described by way of the following
structure:
0.28
0.43
0.29
q
s
f
dNK
dNK
dNK
(1)
where:
dNKq- share of qualitative new knowledge;
dNKs - share of structural new knowledge;
dNKf - share of functional new knowledge.
3. Internal and External Risks Concerned
with New Knowledge Generation
One should mention that new knowledge generation risks
are part of integral risks of economic entity operation.
New knowledge generation processes are, in most
cases, associated with considerable time lines between
decision-making regarding knowledge generation and in-
Table 1. Differentiation of new knowledge in terms of impact on technological process change.
Type of new
knowledge Impact on technological process change Share of the given type in total
volume of new knowledge Influence on profit
Qualitative
knowledge
Weak.
Immediate response to change in external environment.
Does not affect technological processes.
Share reduces with increase in new
knowledge generation dP = 0
Structural
knowledge
Moderate.
Change of structure of an economic entity.
Does not affect technological processes.
Share reduces with increase in new
knowledge generation dP = const < dTC
Functional
knowledge
Strong.
Change of technological processes.
Share grows with increase in new
knowledge generation dP > dTC
Note: dP - change in profit; dTC - costs referred to new knowledge generation.
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Resource Differentiation of Knowledge 215
Figure 1. Time history for profit (dP) to de pend upon allocation of new knowledge generation volumes according to degree of
impact on production processes (%). (NKq - qualitative change; NKs - structural change; NKf - fun ctional chang e).
troduction of new knowledge into economic activity.
Considerable span time predetermines uncertainty in terms
of prospective conditions for new knowledge introduc-
tion, which results in emergence of various risks related
to its generation.
A new knowledge generation risk is an estimate of
contradictions regarding prognostic and actual results of
activity referred to new knowledge generation.
Considering the fact that new knowledge generation is
one of business lines of enterprises, the risks related to
such activity should be subdivided according to their re-
lationship to an economic entity; subject to the field of
occurrence; to external and internal. External risks of
new knowledge generation include those with the source
in external environment in reference to the considered
object. Internal risks of new knowledge generation are
those occurred due to immediate activity by an economic
entity.
As a result of the research carried out by us the struc-
ture of external and internal risks in the context of new
knowledge generation has been determined; evaluation
of risk factor significance has been made; weighting co-
efficient values for each risk factor have been determ-
ined through expert estimation (Tables 2 and 3).
One should mention that internal risks are much more
significant for new knowledge generation than external
risks. According to the empirical study results, internal
risk weighting coefficient is 63.8%, external risks—36.2%.
4. Classification of Institutions for New
Knowledge Generation
So far as institution environment is a set of regulations
structuring an activity by economic entities and their in
teraction, then, in the context of institutional approach,
activity by economic entities is specified by transforma-
tion and transaction approaches. The first approach emp-
hasizes internal factor impact on activity by economic
entities. In turn, the transaction approach considers exter-
nal factor impact. Thus, in compliance with classification
of institutional theories by О. Willianson, classification
of institutions should primarily be accomplished in terms
of such criterion as “relationship to an economic entity”,
Table 2. Structure of internal risks in the context of new
knowledge gener ation.
Type of risks Weighting
coefficient, %
Low staff proficiency 17.80
Staff instability 11.26
Negative result of the activity 15.82
Lack of result within the established time limit 17.65
Unconformity of the results obtained with those
planned 20.92
Practical use impossibility 16.57
Total 100
Table 3. Structure of external risks in the context of new
knowledge gener ation.
Type of risks Weighting
coefficient, %
Divestiture by the market 27.42
Noncompetitiveness of new knowledge 28.76
Infringement of intellectual property 26.48
Availability of analogs in the global practice 17.34
Total 100
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Resource Differentiation of Knowledge
216
namely, internal and external institutions should be dis-
tinguished. Therefore, considering the fact that knowl-
edge generation is one of business lines by enterprises,
an initial criterion in terms of classification of insti-
tutions for new knowledge generation is their relation-
ship to an economic entity. Therewith, the first line pro-
vides analysis of enterprises and firms “on the inside”, i.е.
through a system of standards, agreements and contracts
specified by various management approaches to new
knowledge generation. The second line studies economic
organizations “on the outside”, i.е. it considers regula-
tions of economic entities’ interaction [3].
Application of modern economic approaches to activ-
ity by economic agents requires examination of a cate-
gory referred to market potential of an enterprise. In the
process of generation of an institutional structure of new
knowledge generation processes by economic entities on
the basis of market potential of the enterprise, the follow-
ing functions referred to endogenous institutions should
be singled out: management, use of resources, interaction
with third parties; for external institutions-relationship
with contractors, market condition influence. Functional
structure model of market potential of an enterprise is a
requisite criterion for classification of institutions for
new knowledge generation [4].
The block referred to institutions for management in-
cludes newly developed mission, strategy and objectives
of new knowledge generation. The given block is pre-
sented as a set of components relative to the system of
management: planning, organization, stimulation and con-
trol [5].
There is an established conception in the economic lit-
erature concerned with external uncontrolled factors of
enterprise’s macroenvironment; the conception includes
analysis into technological, economic, social and politi-
cal factors. The author of the present research considers
it essential to add analysis of environmental factors as
well [6]. A complex of the given factors generates the
block of institutions for external condition influence.
In order to understand a conception regarding probable
lines of development, an essence of institutional structure
of new knowledge generation activity by economic
agents at a minimal economic level, classification of
mini-economic institutions for new knowledge genera-
tion is required.
Elements of market potential of an enterprise can be
structured in terms of four management functions: plan-
ning, organization, stimulation and control, and in terms
of three scopes of activity by an enterprise: analytics,
production and communication [4].
To classify institutions for knowledge-based mini-
economy, the following approaches can be applied. One
of the approaches to classification is a method of posi-
tioning at a two-dimensional plane suggested by a French
professor О. Favereau [7]. The given method assumes
disposal of the available theoretical models and ap-
proaches at coordinates “internal market of an enter-
prise-external market” and “actual rationality of decision
-procedural rationality”. О. Williamson in his studies
suggests such a classification approach as generation of a
hierarchical system “hierarchy of goals” [3].
Since dominant features of institutions are endogen-
eity or exogeneity of their generation or application, and
the fact that the activity by the given institutions extends
over the activity by singular employees or the enterprise
as a whole, so it is exactly those features of minieco-
nomic institutions for new knowledge generation that
have to be employed as basic features for classification.
The elaborated classification of institutions for new
knowledge generation based on the criteria stated above
is demonstrated in Figure 2.
Thus, the analysis of the obtained fundamental theo-
retical and empirical results of the research carried out by
the authors, results in the following basic points.
First, classification of mini-economic institutions for
new knowledge generation accomplished on the basis of
the methodological apparatus for institutional economics
and applicable to a minimal economic level affords an
opportunity to reduce uncertainty in terms of analysis
and organization of new knowledge generation, in terms
of evaluation and prediction of development of the given
economy elements.
Second, development of institutions for new knowl-
edge generation as standards and regulations of organiza-
tion referred to it has an effect of considerable reduction
of costs and risks, which, being high, impede generation
of new knowledge at a required level, and, correspond-
ingly, satisfaction of needs in new knowledge by eco-
nomic entities.
Institutions for knowledge management are subject to
the established system of decision-making inside of a
particular economic entity. Regarding the issues related
to new knowledge generation, it is exactly the estab-
lished knowledge management standards at an enter-
prise—institutions for knowledge management—which
determine activity lines, necessity and capability of fi-
nancing new knowledge generation at an enterprise.
Endogenous institutions include standards of intera-
ction between economic agents, which are established
inside of a particular economic entity.
Exogenous institutions are standards established due
to external factors in reference to an enterprise.
5. External Effects
One should mention the fact that new knowledge that is
applied for technology and thus increases technological
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Resource Differentiation of Knowledge
Copyright © 2011 SciRes. iB
217
Figure 2. Classification of mini-economic institutions for new knowledge generation.
2) Principle of step-by-step solution. process efficiency has also external impact on other do-
mains where new knowledge is applied. A study into in-
novation activity by enterprises demonstrated the fact
that enhancement of the material base and technological
field of new knowledge appliance results in reduction of
negative impact on the environment, ecology and im-
provement of personal well-being.
In the given context we consider that substantiation of
efficiency regarding new knowledge generation activity
is possible by way of identification, assessment of re-
serves, especially in the context of development and in-
troduction of new knowledge into economic activity by
economic agents.
The technique referred to assessment of conjugation
effects in terms of new knowledge generation is based on
classification of new knowledge in terms of fields of ap-
pliance, identification of their potential, share, their inter-
relation, correlation and conjugation effect.
Particular importance in the given context is given to
institution for external factor assessment in terms of new
knowledge generation.
For substantiation of efficiency regarding conjugation
of activities related to new knowledge generation, the
following principles are applied: Conjugation effects in terms of new knowledge gen-
eration are most effective provided they are allowed for
in material production.
1) Evaluation of quantitative rates of a potential result
and required costs on the basis of indirect effect exposure.
Resource Differentiation of Knowledge
218
To substantiate the conjugation effect, the author relies
on a methodological statement concerned with the fact
that the highest efficiency can be achieved in case of
maximal conjugation of measures.
The institution for external factor assessment in terms
of new knowledge generation is a certain complex of tra-
ditions, habits and mechanisms of assessment of mutual
influence of new knowledge generation external effects
by economic entities. Significance of the given institu-
tion increases in case the required financing of new
knowledge generation is not provided. The essence of the
institution is in wide application of external effects in the
processes of new knowledge generation, dynamic re-
sponse to changes in external economic environment,
satiation of activity by economic entities with new know-
ledge.
An analysis of new technological knowledge influence
on other fields allowed estimating (according to the em-
piric research data) the following external effects in
terms of new knowledge generation (Table 4).
In other words, to produce 100% of technological
knowledge, up to 17% of economic and ecological, 9%
social, 4% (each) cultural and political knowledge are
generated simultaneously.
The analysis given in Table 4 demonstrates the fact
that external effects of production and introduction of
new technological knowledge with the lowest risk values
and maximal introduction coefficient afford an opportu-
nity to reduce considerably the risks referred to produc-
tion and introduction of new knowledge in conjugate
spheres with high risk coefficients, such as ecological,
political and social.
In the course of the research external effects of pro-
duction and introduction of new technological knowl-
edge into economic activity by economic entities in cor-
relation with other scopes of activity of economic entities
have been identified. Growth in production and introduc-
tion of new technological knowledge exerts an influence
on other scopes of activity and allows reducing the risks
related to production and introduction of new knowledge.
Thus, in the process of calculation of new knowledge
Table 4. External effects in terms of new knowledge genera-
tion in the field of technology according to the scopes of ap-
pliance.
Fields of new knowledge External effect
Economic 0.17
Social 0.09
Cultural 0.04
Political 0.04
Ecological 0.17
value and, correspondingly, an effect of new knowledge
introduction into economic activity, their influence on
other fields of activity is required to be taken into con-
sideration.
6. Conclusions
The research conducted by the author has yielded the fol-
lowing results:
First, differentiation of new knowledge in terms of
profundity of changes introduced into technological pro-
cesses has been accomplished, which is ground to con-
sider new knowledge generation processes from different
aspects of economic activity. A diagrammatic model of
new knowledge generation structure has been developed;
it allows optimal structuring of scientific and engineering
processes on the basis of their differentiation. By refer-
ence of numerical criteria analysis related to the structure
of the generated knowledge, guidelines regarding devel-
opment of a strategy of its generation have been set forth.
Second, the author identified the structure of external
and internal risks referred to new knowledge generation;
assessment of risk factor significance has been made;
weighing coefficient estimation for each risk factor has
been accomplished in an expert way.
In the issuance of the conducted research classification
of risks referred to new knowledge generation has been
implemented. Trends towards reduction of external and
internal risks referred to new knowledge generation have
been identified. In order to assess capabilities for predic-
tion of new knowledge generation risks and work out the
means to reduce them, the apparatus for institutional
economics was suggested.
Third, based on the methodological apparatus for insti-
tutional economics, classification of economic institu-
tions for new knowledge generation at a minimal eco-
nomic level has been accomplished. It affords an oppor-
tunity to reduce uncertainties in terms of new knowledge
generation, evaluation and prediction of development of
elements referred to a certain economy.
Fourth, external effects of new technological knowl-
edge introduction into economic domain and other
scopes of activity by an enterprise have been exposed.
Thus, external effects of new technological knowledge
generation make it possible to substantially meet require-
ments in ecological and social branches of knowledge.
Based on results obtained, enterprises are capable of
making evaluation, prediction and planning in reference
to new knowledge generation. The found means of re-
duction risks and costs referred to new knowledge gen-
eration are ground for its intensified introduction into
business activity, which predetermines innovation econ-
omy development.
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REFERENCES
[1] J. A. Schumpeter, “The Theory of Economics Develop-
ment,” George Alien & Unwin, London, 1952.
[2] F. Valenta, “Management of Innovations,” Progress,
Moscow, 1985.
[3] O. E. Williamson, “The Economic Institution of Capital-
ism: Firms, Markets, Relational Contracting,” Macmillan,
London, 1985.
[4] E. V. Popov, “Market Potential of the Firm,” Interna-
tional Advances in Economic Research, Vol. 10, No. 4,
2004, pp. 337-338. doi:10.1007/BF02295147
[5] R. Oldcorn, “Management Bases,” The Financial Press,
Moscow, 1999.
[6] P. Kotler, “Marketing Bases,” Мarketing Bases Progress,
Moscow, 1990.
[7] O. Favereau, “Organisation et Marché, Revue Française
d’Economie,” Hiver, Vol. 4, No. 1, 1989, pp. 65-96.