Coordinative Development of the Social Systems
by System Dynamics Modeling
Qingrui Xu, JinyangHua, Baoqun Fan
*Dept of Engineering Management, School of management, Zhejiang University, Yu
Quan Road, Hangzhou City, China, 310027 Email: huajinyang@sina.com.cn
Abstract:
To develop continuably, it’s important to keep the ecosystem balance. Coordinative
development between the Economic System, Science & Technology System(S&T) and
Education System, therefore, is also important, especially for China. It’s an important
national level policy decision issue.
This article first discusses the theory and mechanism of the sustainable and
coordinative development of the three complex systems. Then are the nature and
characteristics of the relationship between them analysed. Coordinative development
can greatly enhances the competitiveness of a country.
Based on above theoretical analysis, this article advances a method of multicreteria
optimization of coordinative development between the three complex systems.
The last, System Dynamics modeling is applied and policy analysis is made of growth
rate on three systems for China. A brief conclusion was hereby drawn on the
coordination of the development rate of S&T and Education. This conclusion was highly
appreciated by some senior executives in the ministries.
Keywords: ecosystem balance, coordinative development, economic system, S&T
system, education system, system dynamics, modeling approach, input
1 Introduction
At the tuming point of another
thousand ages, “Knowledge Economy”
has been at the beginning of inkling, and
the trend of global competition can not
reverse too. Under above background and
developing directions, how to grasp
promptly the opportunities provided by
knowledge economy, shorten the gap
with Developed Countries (DCs), and
increase international competitiveness of
firms, industries and nation has become
the great issues that China has to face at
the tuming point of 20 Century.
Bypast, the rapid development of
science and technology to develop
economy has brought the human a world
of advantage, but synchronously, the
abusive activity to environment has been
repaid with serious ecological problems
which become the impediment to develop
economy sustainably. So many factors
influence ecology as S&T, economy, as
above, and demology systems. The rising
of population not only consumes more
rescue, but also produces more waste for
environment to decompose (see figure 1).
Figure 1 the five-system interactive frame
Now people come to know, only under
sustainable environment can economy be
developed sustainably. A subject thus is
put forward on how to get environment
sustainable, which is coequal important,
if not more, with developing economy.
Since the activity of S&T and economy
has direct impact on environment, these
two systems are undoubtedly the most
important factors. Furthermore, as figure
1 shown, education can influence on
ecology by influencing the activity of
S&T, economy, and the population. So
we can draw the following conclusion as,
of the five systems, there exists a more
basic interaction between S&T, economy
and education. The coordinative
development of these three systems
becomes the precondition for ecology,
even for all five systems to he
sustainable.
On further thoughts, the solutions to all
above issues have consanguineous
relation with how S&T and education can
be bring into economy, and how
economy can support S&T and education
activities strongly. Therefore, there is
especial importance and theoretic value
for China to survey the coordinative
status among the three systems, and
probe into the solution to reform.
Furthermore, it is an important national
level policy decision issue. For instance,
coordinative development between the 3
complex systems greatly enhances the
competitiveness of the
Multiple-National-Companies (MNC),
especially in the United States in the
recent decades. Based on above reasons,
the residual part in this article will be
extended around the three systems,
including the modeling by system
dynamics.
2 the basic connotation of coordinative
development of STEE
2.1 the nature and characteristics of the
relationship between STEE
Knowledge becomes the principal
resource at the knowledge and global era,
and the most important mechanism is the
production, distribution, application and
diffusing of the knowledge. So, S&T and
education become the most direct and
pivotal activity to aim to it. But such
activity in any country is carried under a
sequential process, which need to face
with the role transition and function
adjusting. So it is important for S&T and
education themselves to coordinate to
take the new roles. On the other hand,
S&T and education are seriously
restricted by economic budget as well as
promoting economic development. So,
considering from the inner relationship,
the coordinative development among the
three systems become the sticking point
whether S&T and education can promote
economy and economy can improve the
operating quality.
2.2 the connotation of the coordinative
development among three systems
There is no structure without system,
and no system without structure, either.
The structure lies in every thing. On the
other hand, the structure is related closely
to another nature of system, which is
interaction. The interaction between the
factors in the system is carried through
the structure formed by the factors, and
the structure is the premise and base for
the interaction.
Realizing from such point of view, the
coordinative development of STEE can
include following meanings:
First, to realize coordinative
development, there must be inner
coordinative in each subsystem, viz. inner
structure is rational.
Secondly, on the base of rational inner
structure in subsystems, the interactions
between the subsystems are simulative
for each other in the process of getting to
its aim.
Thirdly, the ultimate aim of
coordinative development for three
systems is the harmony as a whole, which
concretely embodies in the optimization
of holistic effect and structure matching.
2.3. a mathematics model of
multicriteria optimization
Systemic analysis is a quantitative
method to deal with coordinative
development, which set up a model by
the optimization analysis method in the
condition of resource restricts. The big
system of STEE is composed of three
subsystems: S&T subsystem, education
subsystem, and economy subsystem,
which are marked by {ST}, {ED} and
{EC}, each subsystem is composed of
several factors. TE (Total Effect) defines
the whole effect of STEE, so TE is the
function of factors of subsystem, inner
structure of subsystem, interaction
between the subsystems, and interaction
among the three systems, viz.:
TE=f({ai},Si]i,TD, i=1,2,3
ai: the factors in the subsystem, i=1
refer to {ST}; i=2 refer to{ED}; i=3 refer
to {EC};
Si: the inner structure of subsystem;
li: the interaction between the
subsystems;
TI: interaction among three systems
Above four variables can be classified
by two kinds, ai and Si belong to
structure, Ii and TI belong to interaction.
So, the mathematical function of
coordinative development among STEE
can be figured as:
C=c(cl {ai},Si),c2(Ii),c3(TI))
cl({ai},Si) means rational inner
structure of subsystems;
c2(li) means positive
between the subsystems;
c3(TI) means harmony on the whole.
Thus, on the base of
x(0)=({ai(0)},Si(0),1i(0)), four-leveled
harmonizing and optimizing model can
be set up as following:
First level: the first step of sectional
harmonizing, rationalization of
subsystem structure, S(x),
Second level: the second step of
sectional harmonizing, positive
interaction between the subsystems, I(x),
Third level: the third step of sectional
harmonizing, positive interaction among
three systems, TI(x),
Forth level: harmonizing as a mass,
C(x),
Then, the optimize model can be
described as a four-nested model as
following(Figure 2).
Although it is difficult to work out this
model, but it reflect a systemic thought to
optimize step by step, and the logic
relationship for harmonizing to improve
step by step as well as the practical
approach to obtain the coordinative
development. As a tool to analyses the
STEE coordinative development, it can
provide directional and methodological
reference for harmonizing STEE.
interaction
2.4 a successful example of harmonious
development
Here, the Engineering Research Center
(ERC) is a successful example, which
typically testify the coordinative
development and integration of STEE.
ERC is a new cooperative form of
industry, school, and research, which is
based on university, hangs education and
Max C(x") =c(g,(S(x")), ¢, lx), @, (TI)
st g(x’) <0
C =C(xq,),$ =S(K 4). 1 SM y), TH STK)
Max TI(x+,)
st. Qf (xq) £0
C =C(y'),S =S(K*),1 =1y),TI STIX)
Max I(x})
s.t. J, (x5) $0
C =C(x§),$ =S(x5), 1 =Ilyg), TI =THx§)
Max S(x¢)
st. G (xs) $0
C =C(x“%), S$ =S(y"%), T =Iy*), TI =TH(x)
whenk =0,thenC (y*) =C(y"),S(y') =S(y") 1g") =xVT1y') =Ty”)
Figure 2 A Four-nested Model
scientific research together, cultivates
students during the research process, and
students can absorb _ instructive
experience in the cooperation practice.
Such cultivate model of ERC not only
provide mature technique and technology
to the enterprise, but also bring up
excellence talents with good adaptability
and strong research ability to serve the
development of S&T and economy.
3. The evaluation frame and international
comparison on the coordinative
development of STEE
3.1 the evaluation frame of the theory
and mechanism
According to the connotation of the
coordinative development of STEE, the
evaluation accordingly lies in such three
aspects:
(1) evaluating the rationality of
inner structure of subsystem, by structure
departure degree index and summed
structure departure degree index;
(2) evaluating the interaction
between the systems, by productivity
rising indexes and bridge indexes;
(3) | Evaluating the whole effect of
STEE, by position departure index. The
indexes are defined as:
The degree of structure
departure= |X, —X|]
Summed degree of structure
departure= 5(the degree of structure
departure departure of system i)
X, means the international place of
each index; X means the mean value of
intemational place of all the indexes.
i=1-3 respectively refers to the S&T
system, education system, and economy
system.
The less the index value of structure
departure degree and summed degree, the
more even the competence between the
factors.
Productivity means that certain input
can get more output because of
technology progress, |§ management
improvement, or scale economy, such on.
For one country, this index reflects the
increase of economic benefit and
improvement of matching between
systems. The bridge index comes from
such idea as the interaction between
systems pass through the in-between, and
several statistical and inquisitional
indexes, elected from indexes system of
intemational competence, can make up of
bridge index and evaluate the degree of
interaction and relation between systems.
Position departure degree =
|ST-ED|+|ST-EC|+[ED-EC|
Position departure degree describes the
relative difference of developmental
degree among the STEE, the value
reflects the developmental status and
change trend of coordinative degree of
STEE as a whole.
This evaluation index’s strongpoint lies
in that, for one country, we can work out
the degree of structure and position
departure and bridge index of past years,
which are tokens of the interaction
between systems, to describe the change
of coordinative developmental degree of
STEE in the country. For different
country, the comparison of such value
between countries can explain the degree
of native country relative to certain
country, and analyses primarily where the
weakness lies as well.
3.2 The international comparison on the
coordinative development of STEE
The relative evaluation is based on the
aforesaid evaluation index frame, and use
the rational factors of international
competence evaluation system for
reference. When comparing, the countries
can be separated into two groups, one is
the developed country group represented
by America and Japan, and another is the
rising country group represented by
Singapore and Korea’ Then the
evaluation frame can be applied to
intemational and respective comparison.
The conclusions include following
several facets: STEE in developed
countries are coordinative, which lies not
only in the rational inner structure and the
whole effect, but in the interaction and
integration between systems and high
degree of matching each other. Compared
with developed group, the harmonious
degree of the rising industrial countries
and regions is not enough, but not large.
The main challenge they faced with is to
adjusting the economic structure and
improving the adaptability of STEE
structure. Meanwhile, they need to
improve the interaction between systems.
The harmonious degree in developing
countries is low and the harmonious
status is poor. For China, it is not ideal in
all the three aspects. The harmonious
status is improved recently, but the
structure of S&T and education in fact
became more unreasonable, and the
matching degree with economy became
worse. It lies in the high degree of S&T
and education structure departure, the
high degree of summed structure
departure of STEE, the high degree of the
position departure of STEE, and the low
value of bridge index.
The inspiration we can get from the
comparison lies in that: economic benefit
in one country is related directly to
harmonious developmental degree of
STEE; there is two radical approaches to
improve the absonant status of STEE, one
is to optimize the structure of S&T and
education, the other is to improve the
bridge index, and promote the interaction
among systems to evolve as a symbioses.
4. System Dynamics model of
harmonious development among STEE in
China
4.1 The virtues of System Dynamics
approach to study _— harmonious
development
System Dynamics (for short, SD)
method is an effective one in describing
the structure, the interaction and
evaluative activity of complex systems,
since the structural relationship formed
by SD model decide directly on systemic
function. Namely, the dynamic model is
built upon inner structure, stream of
matter, stream of information, and their
feedback structure, then provide the
practical possibility for explaining the
systemic dynamic activity.
Comparing with theoretic optimization
method, SD method has following
strongpoint. (1) For non-linear complex
system, SD method can improve systemic
activity more roundly by transferring the
problem from outside system to inside
which changes the systemic structure and
activity model deeply. (2) Herein
systemic evolution activity is uncertain,
SD method can show the process
all-around through simulating and
improve effectively the certainty and
intuitivism. (3) More obviously, SD
method can deal with large number of
data which theoretic method can’t do.
4.2 The SD model of STEE
The model can be separated into
several models, including the whole
structure, the subsystem structure of S&T,
education, and economy.
In the whole model, the interaction and
multileveled feedback relationship among
three systems decide on the characteristic
of holistic activity. The whole structure of
the model is showed as figure 3.
There are three interrelated feedback
loops representing the interaction
between three systems. The loop I
describes the inter-promoted relationship
between education and economy. The
loop II describes the relationship between
S&T and economy, and the loop III
describes the one between S&T and
education.
On the basis of whole structure, we can
grasp the further causality in each
subsystem by systemic analysis approach,
which are showed as figure 3 to 5, and
get the respective SD flow chart
eventually.
4.3 the SD flow chart of the model
According to the structure of system
model above, the SD flow charts of the
model can be drawn out. Figure 6 is
about the economic subsystem and its
abbreviative meaning of the variables
listed in table 1, the others just follow it.
Figure 2 Whole structure relationship of interaction among STEE
Education
Input
National
Income
Figure 3 the causality of education subsystem
Higher | »| Higher
edu. talents
Student ‘PT eacher.
Education Second:
> ary
— Secondary
outlay. edu. 4 talents
Status of sf T
economic Primary | ___) Primary
development edu. labour force
Population
P) status J
Figure4 the causality of S&T subsystem
r| Economic status ;}——-> | Education system}
S&T outlay Structure of S&T talents|
a,
Apply.& develop. of tech. FR
aera
Tech Digest & Self-develop Scientific FR
Intrudu. absorb tech.
S&T outcome
Figure5 _ the causality of economy subsystem
quantity of labour force
Edu. subsystem
Quality of labour force
Tech.
Produ- Tech.
NI
content in #—
ctivity outcome /* | S&T subsystem
production
Figure 6 the SD flow chart of the economic system
COEN2. Utils:
COENISICOENL
ENT
ad COEN, TEDUCI
<AlE : ‘~« TEDUC2
. _ EDUCI
<TIRD>
TPDBDN RRN CMAR <RRN>
DE Son TCMAR2 = TCMARI
a~
_—_
DBDN IE
TCMAA2
_—~ aa
CMAA RAN
NAIEA y
TCMAAL
CMA’ PDBDN
AIIEA ae Se ee
ACOA ®
ed TAGROA
ce
CPUTN
Fcc _—_
r
~~ KK - sae
EDUC FD UC2
i. aye" TAGROR
pete RC te
a 5
Table 1
the corresponding of variables in economy subsystem model
ACD | Annual fixed assets discount
AGOA | Annual growth of economic input
AGOR | Annual growth of economic
consumption
AIIEA | Annual economic input
Cll The proportion of fixed assets to
economic input
CG Fixed assets
CMA | Annual growth rate of economic
A input restricted by resource
CPUT | Unit economic benefit of aggregate
N assets
DBDN | Economic Difference
Ni Economic input being the upper limit
of aggregate supply
N3 Pure consumption being the upper
limit of aggregate supply
NAIIE | Initial value of annual economic input
A
NI National income
PDBD | Realized economic difference
N
RC Pure consumption
TANC | Average time of fixed assets
G
TPDB | Lag time for society to realize
DN economic difference
ACI Annual input of fixed assets
AGRO | Annual growth rate of economic
A input
AGRO | Annual growth rate of economic
R consumption
ANCG | Annual growth of fixed assets
CC Annual average liquidity time of
current assets
CK1 Annual discount rate of fixed assets
CMAR | Annual growth rate of consumption
restricted by resource
CTCNI | Contribution of aggregate assets to
national income
DE Aggregate demand
N2 Economic input being the lower limit
of aggregate supply
N4 Pure consumption being the lower
limit of aggregate supply
NCG Initial value of fixed assets
NRC Initial value of pure consumption
RAN Proportion of economic input to
national income
RRN Proportion of pure consumption to
national income
TC Aggregate assets
wc Liquidity capital
5. The multicriteria optimization based on
SD model
5.1 the basic concept of optimization
method by SD
Here is another method by SD, which
fits well for policy analyzing. To evaluate
the solutions proposed, it goes by two
steps. First, elect some basic indexes in
order to make evaluation. Secondly,
compare the future value of indexes for
each solution by simulating, and attempt
to achieve the best possible result during
the dynamic process.
For STEE, education input and S&T
input may be regarded as devoted
variables, different input choice makes
different solution. Electing such indexes
as Gross national product (GDP)
reflecting economic level, number of
S&T personnel (STP) _ reflecting
educational level, total factor productivity
(TFP) reflecting S&T level. Thus GDP,
STP, TFP constitute basic index system
and can be used to evaluate the
harmonious degree of STEE. After
inputting the existing input data to SD
model, some index value for future will
produce, and the value group of GDP,
STP and TFP will differ from different
solution. Then we can compare the value
groups and get the best corresponding
solution, which we may act on.
5.2 the evaluating and optimizing
process of three indexes
There are four kinds of increase
patterns about the input of education and
S&T.
Pattern 1: the proportion of input to
GNP or NI is fixed and increases
following the economy,
Pattern 2: this proportion increases at a
fixed speed,
Pattern 3: the proportion increases at a
low speed first, then high-speed, in the
end the proportion holds the line.
Pattern 4: the proportion increase with
high-speed at first, then holds the line for
some time, then slow down until get to a
steady value.
Thus, there are 16 pattems combined as
Table 2 listed.
Table2 the 16 patterns combined by education input and S&T input
; ee Cinput | Pil i) P3 P4
Edu. inpul
Pi Pll P12 P13 P14
P2 P21 P22 P23 P24
P3 P31 P32 P33 P34
P4 P41 P42 P43 P44
Then, for each pattern, the simulation outcome of GDP, STP, TFP and the evaluation
of optimization can respectively be achieved as Table3-5.
Table 3 evaluation on index of GDP
Combination | 1997 / 2007 | 2017 | 2027 | 2037 | 2047 | Evaluation
pattern on
feasibility
Pil 75.3 | 87.5 88 82.5 68 72 :
P12 75.3 97 98 84 71 73
P13 75.3 93 153 145 93 108
P14 75.3 88 130 152 123 150 +
P21 75.3 150 175 163 133 147
P22 75.3 108 162 202 175 204 +
P23 75.3 123 162 198 198 213 ¢
P24 75.3 146 187 206 194 204 +
P31 75.3 119 198 213 160 180
P32 75.3 102 228 295 260 268 ++
P33 75.3 181 173 158 150 180
P34 75.3 133 250 273 240 245 ee
P41 75.3 92 154 177 165 194 +
P42 75.3 113 181 238 175 227 ¢
P43 75.3 98 135 192 200 177
P44 75.3 127 193 360 392 390 +++
Table4 __ evaluation on the index of STP
Combination} 1997 | 2007 | 2017 | 2027 | 2037 | 2047 | Evaluation
pattern on
feasibility
Pil 83.44 101 97.5 72 57 67 :
P12 83.44 111 117 100 80 86
P13 83.44 135 142 120 90 99 :
P14 83.44 113 137 153 140 155 +
Table 4 —_ evaluation on the index of STP (Continued)
P21 83.44 | 130 162 170 135 157 :
P22 83.44 | 122 155 175 142 165 +
P23 83.44 | 115 150 177 152 190 :
P24 83.44 | 170 158 170 167 173 +
P31 83.44 | 175 183 150 140 138 :
P32 83.44 | 117 208 248 233 238 ++
P33 83.44 | 198 215 170 123 156 :
P34 83.44 | 102 144 190 202 196 ++
P41 83.44 | 106 144 196 181 181 +
P42 83.44 | 138 168 185 188 168 :
P43 83.44 | 135 169 167 154 190 +
P44 83.44 90 220 327 323 340 ++
Table 5 evaluation on the index of TFP
Combination | 1997 | 2007 | 2017 | 2027 | 2037 | 2047] Evaluation
pattern on
feasibility
Pil 29.6 37 36 28 23 25 :
P12 29.6 44 48 35 23 26
P13 29.6 62 50 38 35 32
P14 29.6 52 58 55 42 45
P21 29.6 42 58 60 42 47 :
P22 29.6 50 65 70 42 70 +
P23 29.6 46 63 73 54 69 :
P24 29.6 44 65 80 80 77 +
P31 29.6 56 69 60 38 52 :
P32 29.6 35 82 88 70 82 +
P33 29.6 42 nD 70 52 60 :
P34 29.6 40 53 63 80 73 ++
P41 29.6 42 58 73 38 65 +
P42 29.6 60 68 65 63 65 :
P43 29.6 40 63 77 52 65 :
P44 29.6 33 46 63 80 80 +4
Based on above evaluation on single index respectively, the total evaluation may be
listed as Table 6.
Table 6 _total evaluation on three indexes
Pattem Pil | P12 P13 P14 P21 P22 P23 P24
evaluation - : : + : + : +
Pattem P31 | P32 P33 P34 P41 P42 P43 P44
evaluation * +++ = t+4+++ + * = t+t+t++
The simulating result suggests that P24, P32, P34 and P44 are feasible.
5.3 the policy meaning of the model
Since the actual condition in China lies that the development of S&T and education
lag badly behind the development of economy, which makes a high demand to S&T and
education, so to their input. Pattem 44 can be proved best one, and the concrete
distributive strategy of S&T and education input lies in the fifth column in Table 7.
Table 7 _ different demand among four feasible combination patterns
P24 P32 P34 P44
Distributi | FR: 2016’ 9%; FR: 2045’ | FR: 2045’ | FR: 2036’ 19%;
ve 2045’ 7.5%; 23%; 26%; 2045’ 18%;
strategy | AR: 2001’ 29%;]AR: 2010’) AR: 2045’ | AR: 29-30%;
in R&D 2045’ 24.5%; 28%; 38%; ED: 2045’ 52%;
ED: 2045’ 67.9%; 2045’ 34%; | ED: 2045’
ED: 2045’ 36%;
439%;
Distributi | PE: 2045’ 50% PE: 2021’ | PE: 2045’ | PE: 2010’ 39%;
ve ME: 29-30% 44%; 42% 2045’ 46%;
strategy | HE: 20% 2045’ 47%; | ME: 24% ME: 29-30%
in ME: 24% HE: 33% HE: 2016’ 29%;
education HE: 2036’ 2045’ 26%
29%; 2045’
28%
FR: fundamental research; AR: applied research; ED: experimental development; PE: primary
education; ME: middle education; HE: high education.
Furthermore, it is concluded by SD that education input had better 10 years ahead of
S&T input. The figure lies as following.
A gap of 10 years
Figure 7 education input ahead of S&T input development
Education input/GDP -ssssessssssssessessessessesseseenceceeseeceneencenseneceeeeeeeenee
R&D input/GDP
Summary
By SD we can draw a conclusion as
that, education input had better 10 years
ahead of S&T input in China. Such
arrangement on input can be in favor of
developing S&T, Economy and
Education harmoniously and sustainably,
so to Ecology. This conclusion was
highly appreciated by some senior
executives in the ministries.
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