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On the Knowledge Economy
Knut Ingar Westeren
Nord-Trøndelag University College - Norway
Interest in the knowledge economy has increased
considerably in the last decade both among social
scientists and as a part of political processes across the
globe. One striking milestone on the political scene in
Europe is the Lisbon decision where the development
of a competitive economic policy for the European
Union was linked to the success of the development of
the knowledge economy. Similar trends are easily ob-
servable in other parts of the world and are becoming
an increasingly important part of industrial policy.
Academically, the concept of the knowledge econ-
omy is among the fastest growing areas of published
literature; accelerating rapidly during the last decade.
This story is, in a way, as old as the concept of orga-
nized production because the key to understanding
this phenomenon is to understand how people learn
from each other in a production situation. In economic
science we can track this back to Marshall (at least).
Indeed, this Special Issue on the Knowledge Economy
builds on topics found elsewhere. A thorough and
recent review of this literature can be found in Döring
and Schnellenbach (2006). In the articles of this Special
Issue, we extend key knowledge economy concepts
that include:
The concept of the knowledge economy – from
theoretical formulations to operationalization
The knowledge economy at the business level
Knowledge – regional development and policy
formulations
Many of these articles were first presented at the
Presidential Symposium at the Mid-Continent Region-
al Science Association 38th Annual Conference, Kansas
City June 7 – 9, 2007. The articles by Raspe & van Oort
and Trippl & Tödtling were added because of their
thematic focus and their extension of arguments put
forward in originally selected articles. With this issue,
our intent is to go one step further in analyses of the
knowledge economy by forwarding conceptual devel-
opments combined with empirical assessments.
1. The concept of the knowledge economy:
From theoretical to operational
In the article by Otto Raspe and Frank van Oort
entitled “Localized Knowledge Externalities in Re-
gional Economic Development and Firm Growth,”
knowledge is defined as the ability to recognize and
solve problems by collecting, selecting and interpret-
ing relevant information. Hence, a basic feature of the
knowledge economy is the use of knowledge in inter-
relationships among market actors to produce goods
and services, from the first idea to final products.
Raspe and van Oort develop eight measurable indica-
tors and analyze spatial patterns of the Dutch know-
ledge economy by grouping the indicators into three
factors:
1. „Knowledge workers‟ with indicators: ICT sensitiv-
ity, educational level, creative economy, and com-
municative skills
2. „Research and Development‟ („R&D‟) with indica-
tors: the density of high and medium tech firms
and the share of R&D employees
3. „Innovativeness‟ with indicators: technical and non-
technical innovations.
Spatial analysis of the Netherlands highlights
knowledge intensity of Dutch regions (municipalities)
from statistical scores of these three factors. This em-
pirical analysis extends the current literature by utiliz-
ing a theory-driven conceptualization of the know-
ledge economy with regional analysis based on statis-
tical data.
JRAP 38(2): 96-99. © 2008 MCRSA. All rights reserved.
An Introduction to the Special Issue 97
In addition, the authors applied employment data
for manufacturing and business services firms stem-
ming from a micro dataset of approximately 62.000
firms in the Netherlands during the period 2001-2006.
They analyzed how firm-level economic growth was
dependent on characteristics of the knowledge econ-
omy.
Results of the authors‟ work suggest that firms ex-
perienced higher growth rates when located in a re-
gion with a higher intensity of successfully innovative
firms or with a higher intensity of research and devel-
opment activities. Splitting the analysis into models of
manufacturing and business services allows the au-
thors to differentiate impacts. Results further suggest
that as 'knowledge workers' had no significant impact
on firm growth in general, they did foster growth in
business services. The authors also found that spillov-
er advantages were not related to specific industries,
but rather, were firm specific. Indeed, in some cases,
cluster regions grew faster than knowledge regions
In Hanas Cader‟s article entitled “The Evolution of
the Knowledge Economy”, the author builds from the
standard OECD definition of the knowledge economy
(like many of the other articles in this issue) and ex-
tends illustrative elements that improve its focus.
Cader discusses the distinction between two ways of
defining the knowledge economy:
Data-driven: Using the data that are available
(across regions/countries)
Conceptually-driven: For example, being based on
a model of knowledge acquisition and use, and re-
lationships to innovation and economic perfor-
mance
Cader examines industries in the U.S. economy to
assess their level of knowledge using, as an indicator,
the knowledge level of workers‟ occupations. He esti-
mates knowledge ratios for industries using data for
1991 and 2001. In this study, ten occupational types
were identified as representative of knowledge work-
ers. Results of this analysis suggest that some suppo-
sedly professional industries have been classified
downward with respect to knowledge level (e. g.
smelting and refining of nonferrous metals). Further,
many service industries have shifted upward on the
knowledge-intensity scale. Other industries that were
traditionally considered to be non-knowledge-
intensive industries were found to be knowledge-
intensive (e.g. child day care service and some person-
al care industries). While the data give few clear con-
clusions to what may be occurring, Cader‟s analysis
suggests that information technologies have helped to
routinize many functions previously preformed by
more highly-skilled professionals. The IT revolution is
often used as an exemplary argument for the rapid
growth of the knowledge economy. While in many
cases, this is realistic, its use also tracks effects related
to how knowledge is used in production processes.
The Cader study suggests that this effect can go in
both directions.
The article highlights the fact that we have expe-
rienced significant changes in the occupational struc-
ture of industries in recent years and that this is reflec-
tive of changes in the knowledge level. On the other
hand some industries have, relatively speaking, not
changed their position very much regarding occupa-
tional structure (e.g. different part of the machinery
industry). In such industries we see examples of suc-
cessful knowledge creating policies which strengthen
the firms‟ competitive position. This is just a reminder
that when conducting analyses which are data inten-
sive, one must be careful that the interpretations fol-
low the definitions.
2. The knowledge economy at the business
level
In the article entitled “Management and Learning
in the Knowledge Society,” Hans Siggaard Jensen rais-
es an important question: What are the main chal-
lenges for management of firms in the knowledge
economy? In response, Jensen discusses the new
forms of management, based on a central role for
knowledge production and finds that they are differ-
ent from to the conception of strategic management.
Knowledge management seeks to maximize the poten-
tial of the company to meet challenges and remain
flexible enough to foster relevant innovations.
Jensen also points out that the knowledge economy
is often led by researchers, innovators and designers.
In a sense, management and the strategies pursued by
managers are adapted to those who develop innova-
tive products. The knowledge creating capability is the
central resource of the company, its intellectual capi-
tal.
When it comes to knowledge and learning, firms
involved in knowledge based operations need to be
mindful that success hinges on:
Doing the task efficiently
Learning from the process of doing the task effi-
ciently
Successful knowledge-based firms develop new know-
ledge based on research, innovation and design that
actually secures the value creation of the company.
This runs counter to traditional thinking. In earlier
98 Westeren
industrial systems, authority flowed downwards from
management. In the knowledge economy, a reverse
form of authority exists because firms will not survive
if workers subjugate their knowledge for that of man-
agement. While management may possess specialist
knowledge, it often lacks the innovative knowledge of
the employees. In the knowledge economy we have
what we could call an inversion of authority.
My own article entitled “How to Define and Meas-
ure Knowledge for the Analysis of Competitiveness”
stems from discussions three years ago with a manag-
er of an oil rig company in Norway (Aker) who recog-
nized that the primary competitor in Spain (Dragados)
paid a 50% lower wage rate than at Aker. Despite this,
Aker won contracts in a highly competitive interna-
tional market. The manager was convinced that this
was due to the fact that Aker produced using a smar-
ter process; one driven by the development and appli-
cation of new knowledge. In the resulting applied
research, I developed a conceptual and empirical lin-
kage between knowledge and competitiveness.
As a basis for the analysis, the company‟s know-
ledge capital was assessed using the following catego-
ries:
Human capital: Defined as the knowledge the em-
ployee has and uses in the operations of the com-
pany. Often looked at as the employees‟ level of
education and expertise in the company.
Structural capital: Defined as the knowledge that is
left in the company when the employees have left,
e.g. patent rights, company routines, databases and
so on.
Relational capital: Defined as all human capital and
structural capital that are linked in networks with
all external relations the company has, for example
contracts with other companies to market channels
and so on.
Then the task was to determine the value of the
firm‟s knowledge capital accomplished in the follow-
ing way:
Identification: Here one must look at knowledge in
relation to the processes that are central for value
creation in the company.
Measurement: Here one must find a useful and op-
erational set of indicators of which to measure
knowledge capital.
Management: Here one must develop a manage-
ment system for the company that incorporates the
effect that knowledge capital has on achieving the
company‟s objectives: maximization of profits.
How indicators measure knowledge and how these
metrics can be extended to bridge the link between
knowledge and competitiveness provide focus for the
assessment. Included are several statements about
how important knowledge is for competitiveness yet
how limited the existing literature is with respect to
empirical examples; hence this article intends to con-
tribute just such an example and thus help fill the gap.
In the final article of this section entitled “Commu-
nity Knowledge: A Catalyst for Innovation”, Kjell-Åge
Gotvassli ties this into the community development
and tourism literature by examining three different
models that help in understanding entrepreneurial
activity and innovation. These include:
1. The individual/cognitive model
2. The “community” model
3. The system/network model.
Gotvassli extends knowledge-based concepts into
rural tourism development. Specifically, this case
study focuses on a Norwegian mountain setting as a
knowledge-based example in which a visit to the re-
gion is built around the wilderness experience-scape.
Interestingly, the keys to success of this hostel lie with-
in three knowledge-based factors:
1. Knowledge as a foundation for innovation. A good
learning environment forms the foundation for in-
terplay between theory and practice, material arti-
facts, senses, aesthetic signals, individual expe-
rience and social interplay.
2. A successful operation of networks. In addition to a
close and tight network of family, friends and col-
leagues, the manager has also developed a network
of external resource people, customers and public
institutions. These networks are characterised by
trust and interpersonal relationships. Long-term
relationships are important for creating a good
learning environment.
3. The individual approach. Local community managers
act as self-realisation entrepreneur.
Results of this case study suggest, in an interesting
fashion, that the emergence of the knowledge econo-
my is not solely a high tech urban phenomenon, but
exists in remote rural regions as well. Successful
knowledge management can be regionally generic and
extend to personal service sectors such as tourism.
An Introduction to the Special Issue 99
3. Knowledge – regional development and
policy formulations
The three papers in this section highlight studies
that focus on knowledge, regional development and
policy formulations. Characteristics of these three case
studies link knowledge creation and diffusion within
the contexts of:
Climate (as an amenity)
Culture
Clusters
In the article by Michaela Trippl and Franz
Tödtling entitled “From the Ivory Tower to the Mar-
ketplace: Knowledge Organizations in the Develop-
ment of Biotechnology Clusters” the authors examine
the recent trends of Austrian universities to move
from acting solely as academic institutions to serving
as regional economic engines. The authors reflect on
the variety of knowledge interactions that exist in the
Austrian economy, many of them in traditional sectors
Austrian universities play a key role in knowledge
intensive biotechnology clusters which have direct
and interactive forms of knowledge linkages. These
linkages are brought about by strong and formal uni-
versity-industry partnerships and academic spin-offs
in biotechnology.
At the national and regional levels, interaction
within the scientific system is found, indicating a ra-
ther intense local and national circulation of academic
knowledge. Policy interventions have been significant
for promoting closer relations between academic fa-
culties and firms. These policies act to foster a trans-
formation of scientific knowledge into marketable
products by forming academic spin-offs.
Dennis Hoffman and Timothy Hogan present an
article entitled “Sunbelt Growth and the Knowledge
Economy” in which they explore whether a know-
ledge economy drives economic growth. Empirically,
the authors develop explanatory growth models for
the portion of the Southwestern United States known
as “The Sunbelt. This region possesses what some
consider an ideal climate which serves as a built in
natural amenity. In this study, the authors search for a
link between college educated workforce and econom-
ic growth.
Their results suggest mixed results with simple
correlation statistics showing strong relationships be-
tween the share of college graduates and per capita
personal income. Further, they found a modest link
with employment growth but no statistically signifi-
cant correlation with income growth. Results further
suggested that expanding the ranks of college edu-
cated workers alone was insufficient to insure eco-
nomic success as some proponents of the knowledge
economy seem to believe.
Finally, the article by Meir Russ and Jeanette Jones
entitled “Regional Economic Development Indicators
for a Knowledge-Based Economy” takes up the dis-
cussion about creating and managing intellectual capi-
tal (IC) for regional economic development initiatives.
The unique aspect of this case is the development of a
framework and set of indicators for Northeast Wiscon-
sin; an economically peripheral region thought to be
knowledge deprived.
Russ and Jones provide results that suggest:
the importance of cultural change as a prerequisite
for accumulating intellectual capital in a know-
ledge deprived region.
that cluster councils can be effective in developing
an agreed upon set of indicators for their industry
cluster.
that policy should compensate for the lack of the
critical mass of knowledge assets through inter-
regional collaboration.
The stories presented in this special issue are, by
themselves, interesting. But viewing them collective-
ly, there are some common lessons to learn. Extending
OECD definitions related to the knowledge economy
in a more explicit and operational manner helps us
understand how creation and diffusion of knowledge
interacts with economic systems and other societal
phenomena. The empirical case studies that incorpo-
rate “knowledge policies”, knowledge process, and
variability in geographic and sector applications pro-
vide a deeper understanding of how knowledge is
involved in economic change. Overall, the intent be-
hind organizing this special issue of the Journal of Re-
gional Analysis and Policy was to contribute to a more
explicit understanding of the knowledge economy and
providing better operational applications. Enjoy!
References
Döring, T. and J. Schnellenbach. 2006. What do we
know about geographical knowledge spillovers
and regional growth?: A survey of the literature,
Regional Studies 40: 375-395.
