PUBLIC ADMINISTRATION STUDIES AND TRAINING: NETWORKING IN THE CONTEXT OF HIGH TECHNOLOGY DEVELOPMENT

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Nov 18, 2013 (3 years and 9 months ago)

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PUBLIC ADMINISTRATION STUDIES AND TRAINING: NETWORKING IN THE
CONTEXT OF HIGH TECHNOLOGY DEVELOPMENT


Nikolaj Ambrusevič,

Vilnius Gediminas Technical University
,
Vilnius,

Lithuania

Assistant of
Department of International Economics and Management


Abstract
.

The author of the presented paper aims at bringing forward an overview of the theoretical a
s
pects of the
public administration studies and training networking in the contexts of high technology development. International
theories

and theoretical framework

for implementation and measurement

of
public administration studies and training
development networking
, such as

Knowledge System Model,
are represented here
.

Deeper investigation of methods of
public administration studies and training networking in the
context of high technology development, based on Triple
Helix Model
,

is provided here, too.

The author’s suggestion to investigate processes of
public administration studies
and training networking in the context of high technology development
, based on

co
operation between

three main
factors:
academy
,
business
,

and government



is raised. As a result,
correlation and regression analysis of expenditure
on research and development as the main factor of high technology development is provided. T
he author fores
ees some
guidelines for
implementation of public administration and training networking in the context of high technology
development by emphasizing the main role of b
usiness sector in the networking process
.


Introduction

Nowadays, the priority of economy

of the European Union in the conditions of recovery from the financial crisis is to
ensure growth by creating new jobs. This can only happen through continuous process of transformation of the
European Union into a dynamic knowledge
-
based economy by provi
ding excellent education, undertaking scientific
research, defining space for creativity and innovation. Thus, knowledge and innovation are primary factors for
competitiveness of European economy on the global market. This European transformation into a dy
namic knowledge
-
based economy has been the objective of the Lisbon agenda since 2000. In this framework, European Heads of State
and Government set the goal of increasing overall level of investment in research to 3 % of Gross Domestic Product by
the year
2010, and of raising the share of research funded by business sector. This certain goal and further steps of
successful knowledge
-
based economy, and especially, high technology development may be achievable only with
participation of integrated public admi
nistration studies and training networking system.

Public administration studies and training system are the main elements of strong and competitive environment
creation
,

required for the knowledge
-
based economy development. One of the most important condi
tions for a creation
of the useful public administration studies and training systems in the European Union
is the process

of networking.
The public administration studies and training systems ensures the processes of creation and implementation of
innovat
ions and are extremely important for high technology development according to the challenges in the new global
age.


1. International
t
heories of
p
ublic
a
dministration
s
tudies and
t
raining
s
ystems

Training refers to a planned effort by a company to facilit
ate employees’ learning of job
-
related competencies
(Kumpikaitė, Čiarnienė 2008). According to authors, these competencies include knowledge, skills, or behaviours that
are critical for successful job performance. The goal of training is for employees to m
aster the knowledge, skill, and
behaviours emphasized in training programs and to apply them to their day
-
to
-
day activities. According to Baldwin

et
al
. (1997), Martocchio, Baldwin (1997), Brinkenhoff, Apking (2001) the role of training has evolved from a
program
focused approach to a broader focus on learning and creating and sharing knowledge. Thus, while training continues to
involve programs to teach specific skills, there is an increasing emphasis on devising methods which emphasise broader
learning pa
rticularly through creating and sharing knowledge (Noe 2005).

Noe (2005) has identified six levels of technology
-
based training, listed below:

VI level: Electronic performance;

V level: Blended learning;

IV level: The delivery of computer
-
based training an
d Multimedia;

III level: Testing assessment;

II level: Online referencing;

I level: Communications.

The difference between the highest and lower levels of technology
-
based training is that at he higher levels learning is
more job
-
related and helps meet a b
usiness need (Kumpikaitė, Čiarnienė 2008).

Regarding Karl M. Wiig (2000), the role of public administration focuses on constant requirement to identify the
expected benefits of knowledge
-
based economy and work to achieve them. This is possible only in a ca
se of managed
knowledge
-
related actions and processes in four functional levels represented below:





























Fig.
1
. Four Functional Areas of Public Administration


No doubt, the main goal of public administration and public policy is to

create a public administration studies and
training systems, which would be not only governed by central and local institutions, but also would be integrated into
international networks. In this case, the priority of the public administration studies and
training systems development
consists on the problems of internationalization of the activities of universities and training institutions and the creation

of international networks of various regional, national and specialized higher education and training

organizations.

The importance of public administration studies and training systems is approved in the working papers of many
scientists and researchers. Studies of such scientists as Boyer, Arnable, Barre (1999) and others as well as strategically
signi
ficant documents of national and international organizations tend to focus on the importance of e
ducational and
training level
. The main ideas of importance of studies and training systems may be represented as the “knowledge
system” with the figures below
:



Fig.
2
. The “Knowledge System” Model

2. Knowledge system

Growth,

competitiv
e
ness,

job creation

1.Science
-
Technology
-
Industry

Educ
a
tion

Sc
i
ence

Techno
l
ogy

/
Innovations

Indu
s
try

Human resources/Labor market

Financial sys
tem

Governance
functions

„Staff“ functions

Operational
functions

Realization of the
value of knowledge

Monitor and
facilitate activity

Establish and update
knowledge infrastructure

Create,
renew, build,
organize knowledge
assets

Distribute and apply
knowledge assets
effectively

Survey and map the
regions knowledge
landscape

Determine
national
knowledge strategy
and specify educational
and other standards

Fund and authorize
knowledge
-
orientated
programs and activities

Implement incentives
to motivate knowledge
creation, sharing, use

Monitor knowledge
-
orientated programs
and activities

Provide basic,
vocational and
advanced learning
institutions

Provide knowledge
exchange network

Educate competent
teachers

Industrial parks
creation

Provide basic and
applied research
facilities

Educate and train
whole population to
high standards

Build knowledge in
libraries and automated
knowledge repositories

Facilitate industry
-
university and R&D
collaboration

Strengthen core
competencies and
guide students
on
future needs

Conduct cross
-
industry
research and
development

Prevent loss of
valuable knowledge
assets

Facilitate joint ventures
and other knowledge
sharing arrangements

Export knowledge
-
content products and
services

Provide employment of
competent people

Ascertain availability
of well
-
educated
people to satisfy
employment needs

Academic public



Industry



Government


The “
K
nowledge
S
ystem”
M
odel shows the relationship between the main actors of knowledge
-
based economy, i.e.
enterprises, universities, government and other public research institutions,

and the variety of some specific factors such
as the industry structure, the education and training system, the human resources and the labour market, the financial
system, etc. It is possible to identify the main building blocks of a “
K
nowledge
S
ystem”.
In this system, science,
technology or innovations and industry are central but not sufficient to ensure economic growth, competitiveness and
job creation. The education and training system, human resources and the labour market, and the financial system a
ll
have a substantial impact on the performance of the chain ‘Science
-
Technology
-
Industry’. From this perspective, the
performance of an economy depends not only on how the individual institutions perform, but also on how they interact
with each other as e
lements of a collective system of knowledge creation. Such interactions between various institutions
are possible with well
-
developed integrated public administration studies and training system, which ensures connection
between all three elements: science
, technology and industry.


2. Overview of the
t
heoretical
m
odels of
h
igh
t
ec
h
nology
d
evelopment

The main theoretical models of high technology development were created over the last decade of the previous century.
The most popular Triple H
e
lix Model of hi
gh technology represents a spiral model of innovation that captures multiple
reci
p
rocal relationships at different points in the process of knowledge capitalization (Etzkowitz 2002). The model
consists on three autonomous helices and determines processes r
elated to innovation and high technology development
by cooperation b
e
tween the academic soc
i
ety, public institutions and the business sector. The first dimension of the
Tr
i
ple Helix Model is internal transformation in each of the helices, such as the deve
lopment of lateral ties among
companies through strategic alliances or an assumption of an economic development mission by universities. The
second is the infl
u
ence of one helix upon another. The third dime
n
sion is the creation of a new overlay of trilater
al
networks and organizations from the inte
r
action among the three helices, which supports high
-
technology development.















Fig. 3. Triple Helix Model


Viale and Campodall'Orto (2002), Etzkowitz (2002), Gulbrandsen and Levitt (2000), and Wes
s
ner

(1999) agree that the
Triple Helix Model d
e
notes the university
-
industry
-
government relatio
n
ship as one of the relatively equal, yet
independent, instit
u
tional spheres which overlap and take the role of the other.

In the last decade scientists started a
d
d
ressing the different aspects of university
-
industry
-
government cooperation.
Their majority studies the importance of education and qualific
a
tion of the labo
u
r force. This is approved in the working
papers of many scientists and researchers, such as Boyer
et al
. (1999), Etzkowitz (2002), Casas, Go
r
tari and Santos
(2000), and Leydesdorff (2005), as well as strategically significant documents of n
a
tional and international
organizations that tend to focus on the importance of educational and trai
n
ing level of
high technology development.
The main ideas of importance of educational level and qualif
i
cation of labo
u
r force may be explained as the deeper
interaction between three elements of the Triple Helix Model.

From this perspective, the performance of an econo
my depends not only on how the indivi
d
ual institutions perform, but
also on how they i
n
teract with each other as elements of a collective system of knowledge creation. Such interactions
between various institutions are possible within the well
-
developed ed
ucational and training sy
s
tem, which ensures the
inter
-
connection between all three elements: science, technology and indu
s
try.

Group of scientists such as Potočnik, Ako, Courtois (2008) after analysis of the possibilities of embedding of the
processes of
networking in one of the sectors of high technology, in the sector of business of informational technology,
has established that process is influenced by:



the impact of technological development, which enables domination of the created system on the market
;



sells, showing the level of customers and suppliers interest of innovation;

Network
equipment

Network

operator

Application
provider

Application
developer

Portal

Enabling
technology

Content

provider

Device

Virtual

operator

-

t
echnology value chain

-

ser
vice

value chain

-

application

value chain



reliability of partnership, showing the vitality of the project.





















Fig. 4. Embedding the Processes of Networking in IT Business Sector


Successful implementati
on of networking model requires four main elements (Wrobel,

2008):



Thriving ecosystem.

Business does not grow in vacuums, but in the co
-
operational environment of suppliers,
researchers and customers, thus, the partnership of business sector and scientific

laboratories should be
secured;



Financial backing.

Innovations require money for starting capital and deeply engaged investors are critically
important;



Big open market.

The enterprise needs plenty of room for its activity, sometimes, there is necessary
to use
modification of existing niches or customer segments;



Support of big corporations.

For many cases, it is easier to develop business in shelter of big companies that
create their own ecosystem. In all four levels impact of public administration is si
gnificant.

Individual scientists propose to take into account additional factors that influence innovation
-
oriented networking
between business and science. In opinion of
Alexander von Gabain (2008) traditional element of „positioning“ or
„location“ should

be replaced by the element of „qualified personnel or staff“.
This is explained by the specifics
dependence of the business
-
oriented innovation and high
-
quality technology on well
-
skilled staff.

This
idea is disclosed
to the researcher's three assumptions

in a process of developing and integrating innovations company: scientific
platform; well
-
trained team, the ability to deliver on promises. Finnish researcher
Risto Siilismaa (2008)
reminds about
the important role of public administration in the processe
s of proper formulation of the law basis and providing support
to ensure effective innovation design and installation by providing appropriate studies and training.


3
.
High
t
echnology
d
evelopment:
i
mportance of R&D

Scientific literature provides two main
approaches of understanding and classification of high tec
h
nology sector. One
group of authors, such as Gardner, Johnson, Lee, Wilkinson (2000), S
a
hadev and Jayachandran (2004), ascribes high
technology industries according to the extent of funds, allocate
d for research and d
e
velopment in each sector:



High technology industries (aerospace, co
m
puters, office equipment, electronic communic
a
tion,
pharmaceut
i
cal industry);



Medium/susceptible to high technology industry (scientific instruments, electronic equipm
ent, m
o
tor vehicles,
chemical industry, non
-
electrical m
a
chinery and equipment);



Receptive to the knowledge of high technology sectors (post and telecommunications, co
m
puters and related
activities, research and deve
l
opment).

The other group of scientists,

such as Geisler (2002), Heertje (2001), Scheel (2002), Sigurdson and Li
-
Ping Cheng
(2001), rel
a
tively divides the sector of high technology into three groups, a
c
cording to their susceptibility to sc
i
ence,
which determines the development and production of

inn
o
vative technological solutions:



Technology of high scientific susceptibility (aerospace technology, computer technology, medical technology,
chemical technology, co
m
munication technologies, pharmacology, techno
l
ogy of accurate instruments and
machiner
y indu
s
try);



Technology of medium scientific susceptibility (shipbuilding, ground transportation, industry of pol
y
mers,
glass, st
one, colo
u
red metals and alloys);



Technology of low scientific susceptibility (oil refinery, metallurgical industry, light indu
stry, wood
processing, paper industry).

The Organization of Economic Development and Cooperation (OECD) recognizes those high technology industry
areas, where research and d
e
ve
l
opment are significant in promoting sales of final outputs such as: air industr
y, the
pharmace
u
tical industry, computers and office equipment, communication tools, and the scientific (medical, precision
measurement
, optical) measures (L
oshky 2009).

According to the National Science Foundation of the United States of America, there is

no single preferred method for
identifying high technology i
n
dustries (National Science Foundation, 2009). Therefore, the National Science Fundation
ind
i
cates two main criteria necessary for development of high technology se
c
tor:



Skilled labo
u
r force whic
h is understood as occ
u
pational employment, and the percentage of pa
r
ticular
occupations within industries change over time, reflecting upon the changes in employment growth, as

well as
the business structure;



Research intensity, where data is derived from

studies of publicly traded companies is known as R&D dollars
as a percent of total sales.

Due to objects multiplicity, the typology of high technology is multi
-
faceted, but the key fe
a
tures that distinguish high
technology sector are the following: the su
sceptibility of science, nece
s
sity of skilled labo
u
r force and research intensity

(R&D)
.

Since 2007 the Seventh Framework programme for research and technological deve
l
opment (FP7) has been the EU’s
main instrument for funding research in Europe. The main
aims of FP7 have been to increase Europe’s growth,
co
m
petitiveness and employment (Eurostat yearbook 2008). Research and development lies at the heart of the EU’s
strategy to become the most compet
i
tive and dynamic knowledge
-
based eco
n
omy; for instance, on
e of the goals was to
incre
a
se R&D e
x
penditure to at least 3.0

% of GDP by 2010.


4
.

Analysis of
a
cademy,

b
usiness and
g
overnment
n
etworking in
h
igh
t
echnology
d
evelopment
:
c
orrelation and
r
egression
a
nalysis

In order to evaluate networking of three main e
lements



business, government and academy


of high technology
development correlation

and regression

analysis of data of EU
-
27 countries, Japan and USA was performed.
Use the
c
orrelation transformer to determine the extent to which changes in the value o
f an attribute (GDP expenditure on
R&D) are associated with changes in another attribute (expenditure on business enterprise sector, expenditure on
government sector, expenditure on higher education sector, expenditure on private non
-
profit enterprises). T
he data for
a correlation analysis consists of five input columns. Each column contains values for one of the attributes of interest.


Table 1.
Input
-
Data of
C
orrelation and
R
egression
A
nalysis


GDP on
R&D, % (Y)

Business
sector, Bln.
EUR(X
1
)

Government
s
ector, Mln.
EUR (X
2
)

Higher education
sector, Mln.
EUR (X
3
)

Private non
-
profit
enterprises, Mln.
EUR (X
4
)

EU
-
27

1,84

135,716

28777

46666

1968

Belgium

1,83

3,934

500

1291

72

Bularia

0,48

0,031

78

12

1

Czech

1,54

1,165

309

279

7

Denmark

2,43

3,56

360

13
96

32

Germany

2,51

40,531

8100

9600

0

Estonia

1,2

0,067

20

61

3

Ireland

1,32

1,56

145

601

0

Greece

0,57

0,367

254

585

16

Spain

1,22

6,558

1971

3266

21

France

2,12

24,081

6546

6875

480

Italy

1,15

7,856

2701

4712

330

Cyprus

0,4

0,014

18

26

5

Latvia

0,67

0,057

17

39

0

Lithuania

0,76

0,053

44

94

0

Luxembourg

1,46

0,422

63

12

0

Hungary

1

0,435

228

219

0

Malta

0,55

0,017

1

9

0

Netherlands

1,74

5,392

1261

0

0

Austria

2,45

4,284

325

1689

26

Poland

0,56

0,477

560

469

7

Portugal

0,77

0,462

176

425

13
8

Romania

0,42

0,215

144

79

6

Slovenia

1,59

0,293

119

73

1

Slovakia

0,49

0,093

71

52

0

Finland

3,45

4,108

539

1079

36

Sweden

3,73

8,754

525

2387

25

United Kingdom

1,75

19,611

3361

8144

712

Croatia

0,8

0,109

79

109

0

Turkey

0,75

0,774

264

1249

0

Ic
eland

2,78

0,187

86

80

11

Norway

1,49

2,13

637

1229

0

Switzerland

2,9

6,257

91

1943

194

Japan

3,2

91,277

9795

15012

2212

USA

2,62

192,591

30471

39095

11635

Source: Eurostat Yearbook 2008.


The correlation coefficient
r

is a measure of the linear relat
ionship between two attributes or columns of data. The value
of
r

can range from
-
1 to +1 and is independent of the units of measurement. A value of
r

near 0 indicates little
correlation between attributes; a value near +1 or
-
1 indicates a high level of c
orrelation.

When two attributes have a positive correlation coefficient, an increase in the value of one attribute indicates a likely
increase in the value of the second attribute. A correlation coefficient of less than 0 indicates a negative correlation.

That is, when one attribute shows an increase in value, the other attribute tends to show a decrease.

All correlation coefficients show linear relationship between columns of data. All of them are positive. That means, that
the possible values of
x

and
y

all lie on a straight line with a positive slope:


Table 2. Data of
C
orrelation
C
oefficients

r
1

r
2

r
3

r
4

0,36546785

0,299647268

0,30605

0,266403


T
-
value is the observed value of the T
-
statistic that is used to test that two attributes are correlated. A

T
-
value near 0 is
evidence that there is no correlation between the attributes. A T
-
value far from 0 (either positive or negative) is that
there is correlation between the attributes.

To see if this T
-
value is significant or not, there is necessary to co
mpare T
-
value with T
-
statistic. Only bigger value than
T
-
statistic showing T
-
value are significant.


Table 3. Data of T
-
value and T
-
statistic

T
1

T
2

T
3

T
4

2,255477986

1,804247575

1,846738

1,587749




T
-
statistic




2,034515


Since only the T
1
-
value obta
ined is bigger than the statistical T
-
value, there is a significant relationship between
expenditure on R&D and expenditure on business sector.


Use the Regression transformer to identify the relationships between a dependent variable and one independent
v
ariable, and to show how closely they are correlated.

Calculations demonstrate:


Table 4. Data of
R
egression
A
nalysis



X
1

a
0

1,423220379

a
i

0,008390074


The relationship between
expenditure on R&D and expenditure on business sector should be expressed

by following
equation:




Y=1,423220379+0,008390074*X
1

In order t
o see if this equation is significant or not, there is necessary to compare Fisher coefficient F with F
-
critical.

Fisher coefficients are following:


Table 5. Data of Fisher
C
oefficients

F
1

F
critical

5,087180948

1,782509201


Since F
-
value obtained is bigger than the critical Fisher coefficient’s F
critical
-
value, there is a significant equation
showing relationship between expenditure on R&D and

expenditure on business sector:
Y=1,423220379
+0,008390074*X
1
.


In conclusion relationship between expenditure on R&D and expenditure on business sector should be expressed by
following:

-50
0
50
100
150
200
250
0
0,5
1
1,5
2
2,5
3
3,5
4


Fig. 5. Linear
R
elationship between
E
xpenditure on R&D

(horizontal, in %

of GDP
)

and
E
xpenditure on
B
usiness
S
ec
tor

(vertical, in Bln. EUR)


Equation shows, that expenditure on business sector positively increases GDP expenditure on R&D. Each unit of
expenditure on business sector, expressed in Bln. EUR, increases GDP expenditure on R&D with
0,008390074 rate.


5. F
indings

and conclusion



Correla
tion and regression analysis

show
s
, that between the main factor of high technology development


expenditure on R&D and expenditure on business sector exists linear and strong relationship. This requires
focusing

on the use o
f methods in public administration studies and training in business area.



The results of analysis and theoretical guidelines of high technology development established, that business
sector is the core element of high technology sector development regardin
g to the essence of Triple Helix
Model. Thus, possibilities for public administration studies and training networking in business area are
extremely important.



This is an interesting finding that raises serious questions as how to stimulate public administ
ration studies and
training in business area. As such, further research is needed to explore current and required levels of public
administration studies and training in business sector for high technology development.

In conclusion:



Lack of attention to t
he problem of public administration studies and training systems may be the main reason
for the loosing the opportunity for the European Union to become a leading global knowledge
-
based economy.



New challenges in public administration studies and training
system development under condition of new
global age require creation of competitive background for knowledge
-
based economy by processes of
continuous development of networks orientated into science
-
industry
-
technology cooperation.



International experience
, practice, cooperation and networking accumulate progressive development of public
administration studies and training systems. The solutions of establishment, development and implementation
of national and international network systems become the driving

forces of high technology sectors
development.



The importance of well
-
trained labour force encourages the requirements for the improvement of public
training, studies and qualification quality. The process of integration of scientific research elements in
to
processes of training and qualification improvement assumed to be very important on this stage of high
technology networking development.



Business sector is the core element of high technology sector development regarding to the essence of Triple
Helix
Model. Thus, possibilities for public administration studies and training networking in business area are
extremely important.



The results of analysis and the theoretical overview of measurements of public administration studies and
training provides basic

guidelines for networking creation in business sector:



to ascertain availability of well
-
educated people to satisfy employment needs;



to provide basic, vocational and advanced learning institutions;



to provide basic and applied research facilities;



to con
duct cross
-
industry research and development;



to facilitate industry
-
university and R&D collaboration;



to provide knowledge exchange network;



and, finally, to stimulate industrial parks creation.



The education and training system, human resources and the l
abour market, and the financial system all have a
substantial impact on the performance of the chain ‘Science
-
Technology
-
Industry’
, important for high
technology development.
From this perspective, the performance of an economy depends not only on how the
indivi
d
ual institutions perform, but also on how they i
n
teract with each other as elements of a collective system
of knowledge creation. Such interactions between various institutions are possible within the well
-
developed
educational and training sy
s
tem,
which ensures the inter
-
connection between all three elements: science,
technology and indu
s
try.


References:


1.

Aho
,

E
sko
. 2008
.

Rising to the challenge
. Born to grow. How to harness Europe‘
s most innovative entrepreneurs

-

to create jobs and
prosperity
.

Sc
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