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Knowledge Economy Dimensions
Constantin BRĂTIANU
The Bucharest Academy of Economic Studies, Romania
E-mail: cbratianu@yahoo.com
Violeta Mihaela DINCĂ
The Bucharest Academy of Economic Studies, Romania
E-mail: violetamihaeladinca@yahoo.fr
Abstract
The purpose of this paper is to present an analysis of the emergent knowledge
economy and its dimensions. The knowledge economy is based primarily on the
development of intangibles, and knowledge processing. The knowledge revolution is
changing the way we think and work, and the knowledge worker reflects the nature of
the new economic driving forces. The knowledge economy opens new directions, and
offers unprecedented opportunities to produce and sell on a mass scale, reduce costs,
and customize to the needs of consumers, all at the same time. The dimensions of this
new economy are the following: economic and institutional regime, education and
skills, information and communication infrastructure, and the innovation system. Based
on these dimensions, the World Bank Institute developed two important indices: the
Knowledge Index (KI), and the Knowledge Economy Index (KEI).
Keywords: intangible, knowledge, knowledge economy, knowledge economy
index
JEL classification: M10, M14
Introduction
Knowledge has always had a significant impact on the economic and social
development. However, only nowadays the number of knowledge workers and
knowledge embedding process in technologies, products and services increased
significantly. In the same time, globalization and the technological revolution of
the last few decades have made knowledge and the intellectual capital key drivers
of competitiveness and they are profoundly reshaping the patterns of the world’s
economic growth and activity (Roos, Pike & Fernstrom, 2005; Debowski, 2006;
Nicolescu & Nicolescu, 2006). For knowledge we shall consider the new dyad:
cognitive knowledge – emotional knowledge, where knowledge is viewed as a
mental and emotional representation and interpretation of the world we are living
in (Bratianu & Orzea, 2009).
In this paper we will first concentrate on outlining some of the most
important conceptual dimensions of the knowledge economy such as: emphasizing
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210
the importance of the knowledge revolution for the emergence of the knowledge
economy, deepening the notion of intangible, analyzing the concepts of data,
information and knowledge, and presenting the four basic dimensions of the
knowledge economy: 1) economic incentive and the institutional regime;
2) education and skills of the human resources; 3) information and communication
infrastructure; 4) innovation system. These four dimensions have been considered
by the World Bank Institute to be significant for the Knowledge Economy Index
(KEI), used to evaluate the emergence of the knowledge economy in different
countries.
1. The knowledge revolution
The knowledge economy is a term that refers either to: an economy of
knowledge focused on the production and management of knowledge in the frame
of economic constraints, or to a knowledge-based economy. In the second
meaning, more frequently used, it refers to the use of knowledge technologies
(such as knowledge engineering and knowledge management) to produce
economic benefits as well as job creation (Drucker, 1969). The phrase was
popularized if not invented by Peter Drucker as the title of Chapter 12 in his book
The Age of Discontinuity, published in 1969.The essential difference is that in a
knowledge economy, knowledge is a product, while in knowledge-based economy,
knowledge is a tool. However, this difference is not yet well distinguished in the
subject matter literature.
The background for the knowledge economy stands in the knowledge
revolution. The knowledge revolution refers to a global-scale paradigm shift that
many compare to the agricultural and industrial revolutions. It refers to a
fundamental socioeconomic change from: an industrially-based economy to a
knowledge or information-based one, from adding value by producing things
which is, ultimately limited to adding value by creating and using knowledge
which can grow indefinitely. The knowledge revolution sustains that the new
source of wealth is knowledge, and not labor, land, or financial capital. It is the
intangible, intellectual assets that must be managed (Nicolescu & Nicolescu, 2006).
Many authors maintain the idea that in the following decades, wealth, in the form
of physical assets will diminish, while wealth, in the form of knowledge assets will
increase. As Rifkin (2000) indicates that whereas the industrial age emphasized the
exchange of goods and services, the coming age will emphasize the exchange of
cognitive and emotional knowledge.
Intangibles have different meaning depending on the context. In sports,
intangibles typically refer to the value driver that differentiates one team’s
performance from another. In arts, intangibles commonly refer to the artists’
unique embodiment of substance and form. In business, intangibles are commonly
referred to as intangible assets, which are part of the intellectual capital. In
financial analysis, intangibles refer to the difference between the book value per
share and the share price, or the firm's accounting value and its publicly traded
Review of International Comparative Management Volume 11, Issue 2, May 2010 211
market value (established through the Stock Market, or through mergers,
acquisitions). In law, legally created intangibles are referred to as intellectual
property and include trademarks, patents, customer lists, and copyright.
Intangible assets are defined as identifiable non-monetary assets that
cannot be seen, touched or physically measured, which are created through time
and/or effort and that are identifiable as a separate asset. There are two primary
forms of intangibles - legal intangibles (such as trade secrets, copyrights, patents,
trademarks, and goodwill) and competitive intangibles (such as knowledge
activities (know-how, knowledge), collaboration activities, leverage activities, and
structural activities).
• From an organizational perspective, Amidon (Amidon, 2005) indicates
that the knowledge movement is reshaping how organizations are created, evolve,
mature, and evolve or die. It is reshaping how business is done, how economies
develop, and how societies prosper. Stewart (1997) points out that just as the
industrial revolution did not end agriculture because people have to eat, this
revolution will not end industry because we still need physical products. Also,
Jennex notices that brands and knowledge are becoming a source of value, not
unlike capital. Brands, for example, represent accumulated surplus value turned
into client loyalty, which translates into lower marketing costs, higher prices, or
larger market share for the owner organization (Davis & Meyer, 1998). In digital
markets, brands are an invaluable source of trust and orientation to consumers who
are looking for quality and security. Many organizations invest heavily in building
a reputation that is conveyed through a brand. Some businesses have even
outsourced almost all other activities just to maintain their focus on managing the
brand. In an internetworked economy, knowledge is a key intangible asset that
requires effort to develop and to protect (Jennex, 2008).
Figure 1 Industrial vs. digital age characteristics
Source: Jennex, M, (2008), Knowledge Management: Concepts, Methodologies, Tools, and
Applications, published by Information Science Reference, London
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212
The main causes of the knowledge revolution can be classified (Nicolescu
& Nicolescu, 2006) as follows:
• Technical and technological causes. Growth of informational,
communication processes. Growth of atomic level processes, through
nanotechnologies. Growth of living cells level processes, through biotechnology.
• Human causes. Changes in the level of preparation of HR,
quantitatively and qualitatively.
• Managerial causes. Efficiency results from the using degree of
resources such as: material, financial, informational knowledge at organization
level. The migration of competitive advantage away from tangible assets towards
intangible ones forces organizations to focus on generating, acquiring, transferring
and combining such assets to meet customer needs. In order to be successful in
these activities, firms and their managements must be entrepreneurial (Teece,
2000). This implies, according to Teece, that knowledge-intensive, entrepreneurial
firms must have: flexible boundaries; high-powered incentives, non-bureaucratic
structures, shallow hierarchies, and an innovative and entrepreneurial culture.
In short, the following suggestions are made for the design of knowledge-
intensive forms: reduce hierarchy, only provide the basic outline of production
structure, and transfer decisions to connect knowledge worker tasks from the
formal to the informal organization structure (Teece, 2000).
2. Knowledge and the knowledge worker
At the individual level, knowledge is created via cognitive processes such
as learning, while social systems (i.e., groups) generate knowledge through
collaborative interactions (Smith & Lyles, 2003). The factors taking part in the
knowledge creation process in an organization may come either from internal or
external sources. The knowledge creation process consists of the transformation
process of raw data into information. In this process, the human capital utilizes
technological tools enabling the collection and classification of knowledge. The
definition of concepts such as raw data, information, and knowledge is based on
the user’s perspective, by which the data is considered as raw facts, the information
is considered an organized set of data, and the knowledge is perceived as
meaningful information (Bhatt, 2001).
The idea on which this definition is based is the recursive relationship
between the raw data, information, and knowledge managed by the human capital,
which is able to determine irrelevant information and return it to its previous status
of raw data. Similarly, accumulated knowledge may be considered by the human
capital as irrelevant, and returned to a previous status. The raw data, information,
and knowledge are relative to each other. The raw data can become critical for a
certain individual, resulting in the changing of its status to that of information,
which is then combined as a basis for diagnosis and becomes knowledge
(Schwartz, 2000).
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Cohen and Levintal (1990) add that the ability of expanding the knowledge
base in an organization depends on the level of learning and on the previous
knowledge base of the individuals in the organization, which extend their ability to
obtain further knowledge (Schwartz, 2006). Our distinction between data,
information, and knowledge follows the mainstream conception found in current
literature (e.g. Davenport & Prusak, 1998). We view data as isolated recordings
that are often generated automatically and cannot be directly used to answer
questions. Information is connected, condensed, or generally processed data that
allows an individual to answer questions. Knowledge is what enables an individual
to ask relevant questions. It refers to the capability of an individual to solve
problems. Information only becomes knowledge if a person interprets that
information correctly, connects that piece of information with his or her prior
knowledge, and can apply it to problems or decisions (Alavi & Leidner, 2001).
It is important to distinguish between data, information, and knowledge.
The primary distinction between the three lies in the degree to which they are
organized and useful. Data are raw stimuli with little organization or ready utility
(Avali & Leidner, 2001). Data become information when they are processed and
organized in a systematic way. Information becomes knowledge when it is ready to
be used to orient action. In Davenport, Long, and Beers’ terms, “Knowledge is a
high value form of information that is ready to apply to decisions and actions”
(Davenport et al., 1998, p. 43). We see data, information and knowledge as parts of
a three-stage rocket (Schreiber et al., 2000). Knowledge assumes information, and
information in turn assumes data. The bottom layer is formed by data. Data are the
noises, scratches, images and other unstructured elements, out there in reality. If
the data are interpreted explicitly, we speak of information. If this information is
used by people in reasoning or in performing actions – i.e., if it is interpreted – we
have knowledge. This means that going from data, via information to knowledge,
degrees of freedom increase. The same data can be interpreted in many different
ways to serve as information. In a similar way, information can be interpreted in
many different ways to serve as knowledge. Someone receives data and
information, and with the aid of knowledge the person already possesses,
information becomes knowledge, which, in turn, can consequently complement or
change a person’s current knowledge. The crucial difference between information
and knowledge is interpretation and this interpretation is done with the human
mind. It implies a cognitive perspective on knowledge. Presently, humans are the
only carriers of knowledge. They are goal-oriented sign or symbol processing
systems (Schwartz, 2006). What is exclusive for humans as carriers of knowledge,
here, is different for information and data. In that situation, not only humans, but
also other kinds of actors (software agents) are involved.
With respect to the knowledge actors have, various divisions can be made.
The most important one is the distinction in knowledge content and knowledge
type. Knowledge content concerns what knowledge is about: about cars, about
physics, about making coffee, about computers or about coordination mechanisms.
Domains, fields and disciplines are examples of knowledge content. Postrel (1999)
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214
calls a knowledge domain a “singularly-linked cluster”, also named “discipline”.
Scientific fields are good examples of knowledge domains, for example medical
science, biology, chemistry or sociology (Schwartz, 2006).
In 1966, Peter Drucker described the difference between the manual
worker and the knowledge worker: a manual worker uses his hands to produce
„things”, while a knowledge worker uses his intelligence to produce ideas,
knowledge and information. The knowledge economy is a new concept which
refers to using knowledge to produce benefices (Nestian, 2009). Knowledge
workers in nowadays’ social groups are individuals who are being assessed for
their capacity to interpret information within a specific topic matter. They will
frequently make progresses within the general perception of that subject through
focused analysis, design and/or development. They make use of research skills to
specify problems and to find out alternatives. Supplied with their own expertise
and insight, they work to overtake those difficulties, aiming to influence company
decisions, priorities and strategies.
Knowledge workers may be met across a variety of information
technology roles, but also among professionals like teachers, lawyers, architects,
physicians, nurses, engineers and scientists. As businesses increase their
dependence on information technology, the number of fields in which knowledge
workers must operate has expanded dramatically.
Typical knowledge workers (especially R&D scientists and engineers) in
the age of knowledge economy must have some system at their disposal to create,
process and enhance their own knowledge. In some cases they would also need to
manage the knowledge of their co-workers (Thorp, 1998). Savage describes a
knowledge-focus as the third wave of human socio-economic development. The
first wave was the Agricultural Age with wealth defined as ownership of land. In
the second wave, the Industrial Age, wealth was based on ownership of Capital, i.e.
factories. In the Knowledge Age, wealth is based upon the ownership of knowledge
and the ability to use that knowledge to create or improve goods and services.
Product improvements include cost, durability, suitability, timeliness of delivery,
and security (Sheridan, 2008).
Due to the rapid global expansion of information-based transactions and
interactions being conducted via the internet, there has been an ever-increasing
demand for a workforce that is capable of performing these activities. Knowledge
Workers are now estimated to outnumber all other workers in North America by at
least a four to one margin (Sheridan, 2008). Knowledge workers bring advantages
for companies in a wide range of significant ways. These enclose: studying data to
set up relationships, valuing input in order to assess elaborated or conflicting
priorities, identifying and understanding trends, making connections, understanding
cause and effect, talent to brainstorm, thinking broadly (divergent thinking),
developing more focus (convergent thinking), creating a new capability, bringing
forth or modifying a strategy.
These knowledge worker involvements found themselves in contrast with
activities that they would typically not be asked to perform, including: transaction
Review of International Comparative Management Volume 11, Issue 2, May 2010 215
processing, routine tasks, simple prioritization of work. There is a set of
transitional tasks includes roles that are seemingly routine, but that require deep
technology, product, or customer knowledge to fulfill the function. These include:
providing technical or customer support, handling unique customer issues,
addressing open-ended inquiries (Thorp, 1998). Generally, if the knowledge can be
retained, knowledge worker contributions will serve to expand the knowledge
assets of a company. While it can be difficult to measure, this increases the overall
value of its intellectual capital. In cases where the knowledge assets have
commercial or monetary value, companies may create patents around their assets,
at which point the material becomes restricted intellectual property. In these
knowledge-intensive situations, knowledge workers play a direct, vital role in
increasing the financial value of a company (Cortada, 1998).
3. The main dimensions of the knowledge economy
One key aspect about the knowledge economy is that the economics are
not of scarcity, but rather of abundance. Unlike most resources that become
depleted when used, information and knowledge can be shared, and actually grow
through application.
Therefore the global world has arrived to consider knowledge and
technology as the heart and mind of the global economy. The countries that thrive
are those that encourage their people to develop the skills and competencies they
need to become better workers, managers, entrepreneurs, and innovators. Today’s
policy makers must extend their country’s existing strengths through careful
investments in education, institutional quality, and relevant technology. They must
create enterprises that are knowledgeable enough to recognize new competitive
opportunities—and skillful enough to convert those opportunities into wealth.
In short, they must build a knowledge economy. The model is not new. In
recent years, several economies, such as Chile, Finland, Ireland, Korea, Malaysia,
and Singapore have been its avatars. China and India are following the same path.
Why, then, have many developing countries been slow to identify the strands of
global knowledge that, when woven together with unique pieces of local
knowledge, will produce the tapestry of the knowledge economy? If the basic
components of the knowledge economy are readily available, why not appropriate
them for growth and innovation? The answer lies in limited awareness,
disincentives, and weak institutions. Together these challenges can keep the
knowledge economy from taking root, preventing countries from forging powerful
combinations of the best that the globe has to offer them and the best they have to
offer the rest of the globe.
In order to benchmark a country’s position compared with others in the
global knowledge economy, we use the Knowledge Indexes which are interactive
tools created by the World Bank Institute. The Knowledge Index (KI) is an
economic indicator prepared by the World Bank Institute to measure a country's
ability to generate, adopt and diffuse knowledge. Methodologically, the KI is the
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216
simple average of the normalized performance scores of a country or region on the
key variables in three Knowledge Economy dimensions: education and human
resources, the innovation system, and information and communication technology
(ICT). In a larger perspective, the Knowledge Economy Index (KEI) takes into
account whether the environment is conducive for knowledge to be used
effectively for economic development. It is an aggregate index that represents the
overall level of development of a country or region towards the Knowledge
Economy.
The KEI is calculated based on the average of the normalized performance
scores of a country or region according to the following four main dimensions of
the knowledge economy (World Bank Institute, 2007):
• Economic incentive and institutional regime. The country’s
economic and institutional regime must provide incentives for the efficient use of
existing knowledge, the acquisition of new knowledge, and the application of both
to economic activity in order to improve production, to raise quality, to innovate,
and to launch new enterprises.
• Education and skills of human resources. People need education and
skills development that enable them to create and share knowledge, and to use it well.
• Information and communication infrastructure. A dynamic
information infrastructure is needed to facilitate the effective communication,
dissemination, and processing of information.
• Innovation system. The country’s innovation system – firms, research
centers, universities, think tanks, consultants, and other organizations – must be
capable of tapping the growing stock of global knowledge, assimilating and
adapting it to local needs, and creating new technology that underpins the
development of new products and processes that can compete in export markets
and meet needs at home.
Based on these above dimensions, the World Bank Institute developed the
Knowledge Economy Index (KEI), which is a broad measure of the overall level of
preparedness of a country or region for the knowledge economy. The KEI
summarizes each country’s performance on 12 variables corresponding to the four
knowledge economy dimensions presented above. The KEI is constructed as the
simple average of the normalized values of those indicators, from 0 (weakest) to 10
(strongest).
Both developed and developing countries must consider their future in a
world system where knowledge is gold. To become successful knowledge
economies, countries must act simultaneously on their education base, their
innovation systems, and their information and communication technology
infrastructure, while also building a high-quality economic and institutional
regime. Strategies must be adapted to a country’s level of development, and
progress is usually gradual, but some countries have been able to achieve
spectacular progress in a decade (World Bank Institute, 2007).
Review of International Comparative Management Volume 11, Issue 2, May 2010 217
The 12 variables corresponding to the four dimensions
of the knowledge economy
Table 1
Dimensions Indicators
Economic and institutional regime Tariff and non-tariff barriers
Regulatory quality
Rule of law
Education and skill of population Adult literacy rate
Gross secondary enrollment rate
Gross tertiary enrollment rate
Information infrastructure Telephones per 1000 people
Computers per 1000 people
Internet users per 1000 people
Innovation system Royalty payments and receipts, US$ per person
Technical journal articles per million people
Patents granted to nationals by the US Patent and
Trademark Office per million people
In 2008, Denmark retains its leading position as the world’s most advanced
knowledge economy. With a 2008 KEI of 9.58, it ranked 1st place as it did in 1995.
Table 3 presents the rankings for 25 countries based on the Knowledge Economy
Index (KEI) 2008. Although its KEI ranking remains the same, Denmark saw
measurable improvement in the education: the education dimension index rising
from 9.61 ranking 9th in 1995 to 9.80 to rank 1st in 2008, and the education
dimension index growing from 9.57 ranking 3rd in 1995 to 9.66 second only to
Singapore in 2008. However its performance in the ICT dimension fell from the
5th position in 1995 to the 6th, and the innovation dimension remained at 4th place
compared with 1995 rankings.
The improvement in the education dimension is largely attributed to its
increase in tertiary enrollment rates. Its tertiary enrollment rate rose from 48.17
(normalized score 9.28) to 79.94 (normalized score 9.53). Despite large
improvements in telephone, computer and internet penetration, the normalized
scores of all three ICT variables fell, especially that for Internet penetration, which
fell from 9.43 in 1995 to the most recent of 9.07. The abatement of Denmark’s ICT
dimension reflects that other countries have made even larger improvements in
their ICT infrastructure over the same time period.
The Nordic countries remain among the best performers in the KEI.
Sweden is ranked 2nd, with Finland and Norway following closely at the 3rd and
5th places, respectively. The four KE dimensions in these countries are all well
developed in a balanced manner. These countries are characterized by their strong
performance in the education dimension - all rank within the top 7 places, and to a
lesser extent in the innovation and EIR dimensions – all rank within the top
13 spots.
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218
The countries’ ranking according to their KEI and KI performances
Table 2
Source: www.worldbank.org/wbi/k4d.
Conclusions
These last decades managerial focus shifted from the traditional factors of
production to knowledge processing. But knowledge is not something new, it has
been here for centuries, the only thing that changed was managers and companies’
perception on knowledge power to create wealth and value for society. The new
economy made knowledge the main raw material and the power of our brains the
intellectual capital of the companies. The knowledge workers became the main
driving forces of the new economy, and the importance of intangibles overcome
that of tangibles.
The conceptual dimensions of knowledge economy presented in this paper
revealed that this economy requires new ideas and approaches from policy makers,
managers and knowledge workers. Investments in education and training,
innovation and technological adoption, the information infrastructure, and a
conducive economic incentive and institutional regime are necessary for sustained
creation, adoption, adaptation and use of knowledge in domestic economic
production, which will consequently result in higher value added goods and
Review of International Comparative Management Volume 11, Issue 2, May 2010 219
services. This would tend to increase the probability of economic success, and
hence economic development, in the current highly competitive and globalized
world economy.
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