Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей
A system of factors (indices and indicators) and a new method of quantitative and qualitative evaluation are developed. This system, named “Sustainable Development Gauging Matrix” (SDGM) and data presented by reliable international organizations culminated in a Global Simulation regarding quality of...
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| author | Zgurovsky, M. Z. |
| author_facet | Zgurovsky, M. Z. |
| author_institution_txt_mv | [
{
"author": "M. Z. Zgurovsky",
"institution": null
}
] |
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| description | A system of factors (indices and indicators) and a new method of quantitative and qualitative evaluation are developed. This system, named “Sustainable Development Gauging Matrix” (SDGM) and data presented by reliable international organizations culminated in a Global Simulation regarding quality of life and security of the world population. Specifically, this study focuses on analysis of the Systematic Regularity of World Conflicts over the Course of Time. A prognosis is detailed of the next world conflict, labeled the "Conflict of XXI Century”, and an analysis is provided of its nature and main characteristics; duration, main phases of the conflict and intensity. This prognosis details a set of basic global threats that spawn this conflict. Using cluster analysis, its influence on different countries of the world is accurately defined. These results were obtained by applying the capabilities of the world data centers network as a tool for providing a variety of scientific interdisciplinary data. |
| first_indexed | 2025-07-17T10:22:41Z |
| format | Article |
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© M.Z. Zgurovsky, 2009
Системні дослідження та інформаційні технології, 2009, № 1 7
TIДC
ТЕОРЕТИЧНІ ТА ПРИКЛАДНІ ПРОБЛЕМИ І
МЕТОДИ СИСТЕМНОГО АНАЛІЗУ
UDC 519.711
GLOBAL ANALYSIS OF SUSTAINABLE DEVELOPMENT IN
CONTEXT OF QUALITY AND SECURITY OF HUMAN LIFE
M.Z. ZGUROVSKY
A system of factors (indices and indicators) and a new method of quantitative and
qualitative evaluation are developed. This system, named “Sustainable Development
Gauging Matrix” (SDGM) and data presented by reliable international organizations
culminated in a Global Simulation regarding quality of life and security of the world
population. Specifically, this study focuses on analysis of the Systematic Regularity
of World Conflicts over the Course of Time. A prognosis is detailed of the next
world conflict, labeled the "Conflict of XXI Century”, and an analysis is provided of
its nature and main characteristics; duration, main phases of the conflict and inten-
sity. This prognosis details a set of basic global threats that spawn this conflict. Us-
ing cluster analysis, its influence on different countries of the world is accurately de-
fined.. These results were obtained by applying the capabilities of the world data
centers network as a tool for providing a variety of scientific interdisciplinary data.
INTRODUCTION
We will consider the concept of “sustainable development” based on the theory of
noosphere created by Vladimir Vernadsky. In the middle of last century in his
work (Vernadsky, 1944) he declared that the Homo sapiens with his mind and
activities began strongly influence the natural development of the environment or
biosphere. The theory and practice has confirmed that after several decades the
noosphere doctrine proves to be a necessary platform for the development of the
“triune” concept of sustainable ecological, social and economic development. In
1996 the United Nations formulated this concept in the following way: “System
coordination of economic, ecological and human development in such a way that
from one generation to the other the quality and safety of life should not decrease,
the environmental conditions should not worsen and the social progress should
meet the needs of every person”.
This concept was generalized by a number of international organizations,
among them Rome Club, International Institute for Applied System Analysis
(IASA), Institute for System Research (USSR), International Federation of Insti-
tutes for Advanced Studies. The problems of environment and sustainable devel-
opment were discussed at the UN conferences and summits, (UN Summit, Rio de
Janeiro, 1992), (UN Summit, Johannesburg, 2002). Thus, the new concept has
united the three main components of the sustainable development: economic, eco-
M.Z. Zgurovsky
ISSN 1681–6048 System Research & Information Technologies, 2009, № 1 8
logical and social. It is recommended to carry out «Transition from One-
Dimensional Development to its Harmonization with Respect to Three constitu-
ents: {Economic; Ecological; Social/Institutional}. Thereby the purpose of this re-
search is working out a sustainable development measuring system based on the use of
interdisciplinary data characterizing each of its three dimensions. By using this measur-
ing system which we call Sustainable Development Gauging Matrix (SDGM) we carry
out global simulation of sustainable development in the context of quality of life and
security of population. Also we analyze the impact of the totality of global threats on
this development.
1. DEVELOPMENT OF SDGM MATHEMATICAL MODEL
We characterize sustainable development by two main constituents: security of
population ( secI ) and quality of their life ( qlI ), as fig. 1. Then the generalized
sustainable development measure (Index) may be presented by a quaternary {Q}
with imaginary scalar part j ( secI ), describing security of people and real vector
part ( qlI ), describing quality of life in the space with three dimensions: economic
( ecI ), ecological ( eI ) and social-institutional ( sI ):
qlsec}{ IIjQ += , (1)
⎩
⎨
⎧
=−
>
=
.)conflict(0ofvaluationzerofor1
,0ofvaluespositiverealfor1
sec
sec
I
I
j
In this space for each country we have the sustainable development radius-
vector ( sdI ) with the Euclidean norm:
2
s
2
e
2
ecsdsd IIIII ++= (2)
which we define as a sustainable development index ( sdI ). Quality of life compo-
nent (Iql) is the sustainable development vector ( sdI ) projection on the ideal vec-
tor with coordinates (1; 1; 1):
)(cos2
s
2
e
2
ecql α⋅++= IIII . (3)
Fig. 1. Quaternary Approach for Sustainable Development Representation
Sustainable Development
qlsec}{ IIjQ +=
Security of Population Quality of life
Global analysis of sustainable development in context of quality and security of human life
Системні дослідження та інформаційні технології, 2009, № 1 9
The angle (α ) is defined as a degree of harmonization:
⎟⎟
⎠
⎞
⎜⎜
⎝
⎛
≤≤
⎟⎟
⎟
⎠
⎞
⎜⎜
⎜
⎝
⎛
++
++
=
3
1cosarc0,
3
cosarc
2
s
2
e
2
ec
2
s
2
e
2
ec αα
III
III
(4)
as fig. 2.
Since simulation of security and quality of life is carried out using different
methods and different initial data it seems reasonable to fulfill it separately in
three stages. At the first stage we will carry out Data Analysis of Quality of Life
Component of Sustainability. In order to perform this simulation we have to select
of data by means of which each of three sustainable development dimensions can
be presented most adequately. These data are also to be prepared by reputable
international organizations or research centers annually on the permanent basis.
To present economic dimension two global data bases were used: Global
Competitiveness Index ( cI ), annually developed by the World Economic Forum
(The Global Competitiveness Report, 2007-2008), and Index of economic freedom
( efI ) developed by Heritage Foundation (The news of intellectual centre of Heri-
tage Foundation, 2008).
Ecological dimension (Iе) is defined by the well-known Environmental Per-
formance Index, which is annually formed by the Center on environmental
legislation and policy of Yele University together with Columbia University (EPI
Beta, 2007/2008).
Social dimension is formed by three global indices: Quality of life Index,
developed by the International Living organization (Quality of Life Index, 2008),
Human development index, annually calculated in the framework of United Na-
tions Development Program (Human Development Report, 2007/2008) and Index
of knowledge society, created by UN Department on economic and social devel-
opment (The publications of the United Nations on economic and social affairs —
UNDESA, 2005). All together these six indices are defined by 12 policy catego-
ries and 65 indicators and accumulated at the Ukrainian branch of World Data
center (WDC for Geoinformatics and Sustainable development, 2008).
Based on the description of interconnections between these factors, their
transformation to the unified computational platform, the mathematical model for
Quality of Life simulation, named “Sustainable Development Gauging Matrix”
(SDGM) was developed as fig. 3.
Fig. 2. Quality of Life Component ( qlI ) and Harmonization Degree (α)
(1, 1, 1)
α
sI
sdI
ecI
eI
Social/Institutional
Ecological
Economic
qlI
M.Z. Zgurovsky
ISSN 1681–6048 System Research & Information Technologies, 2009, № 1 10
This interdisciplinary model is a large scale matrix compression. It combines
data of various natures and reflects the balance between three inseparable spheres
of the society — economic, ecological and social/institutional. Under such condi-
tions all data, indicators and indices, which are included in the SDGM model, are
measured in different units and have various interpretations. This is why they are
reduced to the normal form in such a way that their changes and the changes of
their indices themselves were in the range from 0 to 1. In this case the lowest val-
ues of the above indicators will correspond to the numerical values close to 0, and
the highest — will approximate these values to 1. Such normalization allows one
to calculate each of the indices ecI , eI , sI and sdI in the form of an algebraical
compression of its constituents with the corresponding weighted coefficients. In
turn, the weighted coefficients in the calculation formula of the sustainable devel-
opment index ( sdI ) are chosen in such a way that allows one to provide the same
weights of economic, ecological and social measures in this index.
2. DATA ANALYSIS OF QUALITY OF LIFE COMPONENT OF
SUSTAINABILITY
The mathematical model SDGM was used for calculation of quality of life com-
ponents of sustainability for 2005–2008, which are represented in table 1 (col-
umns 4–9). These components are: the Euclidean norm of sustainable develop-
ment radius-vector ( sdI ), Harmonization Degree (α , column 6) and Quality of
Life Component ( qlI , column 5).
We see that among five leaders (Switzerland, New Zeeland, Finland, Swe-
den and Norway) there are no superpowers with dominating ideologies and
economies. The basic industries of these countries are not oriented at the usage of
considerable natural resources and cheap labor. These countries are leading in the
Fig. 3. Mathematical Model “Sustainable Development Gauging Matrix” (SDGM)
Economic dimension
22 Indicators,
3 Policy Categories
Ecological dimension
31 Indicators,
6 Policy Categories
Total: 65 Indicators,
12 Policy Categories
Social+Inst.
dimension
33 Indicators,
3 Policy Categories
qI
hdI
ksI
efI cI )(e EPIESII =
)(
),,(
,)(
kshdqs
e
cefec
IIIfI
EPIESIfI
IIfI
++=
=
+=
α,qlI
Global analysis of sustainable development in context of quality and security of human life
Системні дослідження та інформаційні технології, 2009, № 1 11
ecological dimension index. They are very active in innovation activities; invest
about 4 % of their GDP for R&D.
G8 countries are placed from the 6th to 23rd position by quality of life com-
ponent of sustainable development (except Russia). In particulars Canada ranks
6th position, France — 11th, Germany — 12th, Japan — 13th, United Kingdom —
16th, United States — 16th, Italy — 21st, Russia — 56th. Nevertheless they are
world leaders in GDP absolute values, but their quality characteristics of eco-
nomic development, renewal of natural resources and development of social capi-
tal move these countries in the second-third dozen.
T a b l e 1 . The results of sustainable development global simulation (dimen-
sionless quantities)
Sustainable
Development
Index
{Q}=jIsec+Iql
Quality of Life Component Security
Component Country
Rank {Q} Rank Iql α (rad) Ie Iec Is Rank Isec
1 2 3 4 5 6 7 8 9 10 11
Very High
Switzerland 1 3,275 1 1,462 0,1394 0,680 0,955 0,898 8 1,813
Canada 2 3,258 7 1,377 0,1127 0,668 0,866 0,851 1 1,881
Sweden 3 3,250 4 1,382 0,1564 0,629 0,931 0,833 2 1,868
Norway 4 3,244 5 1,380 0,1729 0,605 0,931 0,854 3 1,864
Finland 5 3,222 3 1,382 0,1378 0,649 0,914 0,831 5 1,840
New Zeland 6 3,218 2 1,383 0,1319 0,650 0,889 0,857 6 1,835
Australia 7 3,201 14 1,353 0,1089 0,669 0,798 0,876 4 1,849
Denmark 8 3,167 13 1,353 0,0970 0,674 0,840 0,830 7 1,814
Austria 9 3,148 11 1,357 0,1556 0,612 0,894 0,844 10 1,791
Luxemburg 10 3,139 15 1,350 0,1416 0,625 0,831 0,882 11 1,789
France 11 3,138 8 1,365 0,1799 0,586 0,878 0,901 14 1,773
Germany 12 3,133 9 1,364 0,1389 0,632 0,863 0,868 15 1,769
Japan 13 3,128 16 1,343 0,1282 0,634 0,845 0,847 12 1,785
Netherlands 14 3,124 18 1,324 0,1074 0,654 0,787 0,852 9 1,800
Ireland 15 3,109 17 1,326 0,0941 0,664 0,827 0,805 13 1,784
United
Kingdom 16 3,099 12 1,353 0,1054 0,668 0,863 0,813 20 1,746
United States 17 3,062 6 1,379 0,1050 0,687 0,810 0,891 32 1,683
Spain 18 3,054 19 1,309 0,1618 0,582 0,831 0,855 21 1,745
Belgium 19 3,043 21 1,293 0,1299 0,613 0,784 0,843 18 1,750
High
Portugal 20 3,035 25 1,283 0,1852 0,546 0,858 0,819 16 1,751
Italy 21 3,025 22 1,290 0,2004 0,531 0,842 0,861 23 1,735
Slovenia 22 3,020 29 1,270 0,1983 0,527 0,863 0,809 17 1,750
Costa Rica 23 3,017 27 1,278 0,2081 0,530 0,905 0,778 22 1,739
Chile 24 3,000 24 1,288 0,1082 0,638 0,834 0,759 27 1,712
M.Z. Zgurovsky
ISSN 1681–6048 System Research & Information Technologies, 2009, № 1 12
1 2 3 4 5 6 7 8 9 10 11
Lithuania 25 2,999 23 1,289 0,1602 0,579 0,862 0,791 29 1,710
Latvia 26 2,995 26 1,278 0,1801 0,562 0,888 0,763 25 1,718
Uruguay 27 2,995 33 1,246 0,1761 0,539 0,823 0,796 19 1,749
Hungary 28 2,992 31 1,263 0,1706 0,554 0,842 0,792 24 1,729
Slovakia 29 2,980 30 1,269 0,1666 0,566 0,860 0,772 28 1,711
Estonia 30 2,968 20 1,298 0,1240 0,626 0,852 0,770 35 1,670
Greece 31 2,939 36 1,224 0,1992 0,505 0,802 0,813 26 1,715
Czech
Republic 32 2,932 34 1,233 0,1391 0,572 0,768 0,796 31 1,699
Poland 33 2,910 41 1,211 0,1875 0,512 0,805 0,780 30 1,699
Medium
Israel 34 2,891 32 1,252 0,1284 0,591 0,796 0,781 39 1,639
Croatia 35 2,878 42 1,209 0,2193 0,483 0,846 0,765 36 1,669
Argentina 36 2,873 43 1,208 0,2276 0,469 0,818 0,805 37 1,665
Korea, South 37 2,866 28 1,270 0,1184 0,610 0,794 0,796 52 1,596
Bulgaria 38 2,861 45 1,188 0,1790 0,511 0,785 0,762 33 1,673
Malaysia 39 2,855 38 1,221 0,1509 0,578 0,840 0,696 44 1,635
Mexico 40 2,849 40 1,211 0,1568 0,545 0,798 0,755 41 1,638
Panama 41 2,845 39 1,218 0,1764 0,533 0,831 0,746 46 1,627
Albania 42 2,841 48 1,170 0,2089 0,491 0,840 0,696 34 1,671
Colombia 43 2,818 37 1,222 0,2121 0,512 0,883 0,721 51 1,596
Thailand 44 2,803 50 1,164 0,1442 0,553 0,792 0,671 40 1,639
Brazil 45 2,785 46 1,181 0,2135 0,479 0,827 0,740 49 1,604
Jamaica 46 2,782 54 1,145 0,1604 0,529 0,791 0,663 42 1,637
Tunisia 47 2,775 53 1,146 0,1570 0,526 0,781 0,678 45 1,629
Jordan 48 2,767 58 1,130 0,1457 0,531 0,765 0,662 43 1,637
Ecuador 49 2,749 47 1,173 0,2362 0,456 0,844 0,731 58 1,577
Bosnia and
Gerzegovina 50 2,744 61 1,123 0,2248 0,446 0,797 0,702 47 1,621
El Salvador 51 2,728 55 1,137 0,1381 0,549 0,772 0,648 53 1,591
Romania 52 2,717 56 1,136 0,1606 0,506 0,719 0,742 55 1,581
Turkey 53 2,705 59 1,128 0,1532 0,517 0,759 0,678 57 1,577
Georgia 54 2,700 49 1,167 0,1708 0,538 0,822 0,662 69 1,533
Ukraine 55 2,698 66 1,097 0,1979 0,455 0,741 0,704 50 1,601
Russia 56 2,692 57 1,131 0,2334 0,459 0,839 0,661 63 1,561
Peru 57 2,677 60 1,125 0,1682 0,511 0,781 0,657 65 1,552
Guatemala 58 2,670 67 1,096 0,1731 0,496 0,767 0,635 60 1,575
Moldova 59 2,653 76 1,068 0,1640 0,474 0,707 0,669 54 1,585
Egypt 60 2,651 73 1,074 0,1762 0,494 0,763 0,604 59 1,576
Viet Nam 61 2,650 83 1,040 0,1937 0,451 0,739 0,612 48 1,610
Philippines 62 2,646 65 1,099 0,1877 0,484 0,779 0,641 66 1,547
Trinidad &
Tobago 63 2,643 62 1,118 0,1100 0,545 0,704 0,687 71 1,525
Global analysis of sustainable development in context of quality and security of human life
Системні дослідження та інформаційні технології, 2009, № 1 13
1 2 3 4 5 6 7 8 9 10 11
Low
Armenia 64 2,629 52 1,147 0,1459 0,540 0,778 0,668 80 1,483
Namibia 65 2,625 77 1,062 0,1399 0,498 0,706 0,635 62 1,563
Morocco 66 2,605 80 1,048 0,1573 0,486 0,721 0,608 64 1,557
Nicaragua 67 2,596 75 1,069 0,1737 0,473 0,734 0,645 70 1,527
Botswana 68 2,595 74 1,074 0,0968 0,541 0,687 0,632 72 1,521
Venezuela 69 2,588 71 1,090 0,2557 0,407 0,800 0,681 77 1,497
Honduras 70 2,557 69 1,094 0,1659 0,496 0,754 0,645 82 1,463
Algeria 71 2,555 79 1,060 0,1962 0,474 0,770 0,592 78 1,495
Indonesia 72 2,547 87 1,009 0,1280 0,482 0,662 0,604 68 1,538
Azerbaijan 73 2,510 81 1,048 0,1621 0,480 0,722 0,613 83 1,462
Bolivia 74 2,498 86 1,010 0,1672 0,444 0,647 0,658 79 1,488
South Africa 75 2,496 70 1,091 0,1052 0,537 0,690 0,662 95 1,405
China 76 2,496 82 1,044 0,1343 0,488 0,651 0,669 85 1,452
Nepal 77 2,466 92 0,968 0,2085 0,443 0,721 0,512 76 1,498
India 78 2,459 94 0,950 0,0857 0,488 0,603 0,555 74 1,508
Kazakhstan 79 2,457 84 1,035 0,1037 0,510 0,650 0,632 89 1,423
Uzbekistan 80 2,439 91 0,984 0,1319 0,468 0,650 0,586 84 1,455
Tadjikistan 81 2,419 88 1,002 0,1965 0,441 0,723 0,572 91 1,417
Pakistan 82 2,397 100 0,887 0,1032 0,473 0,587 0,476 73 1,511
Senegal 83 2,368 95 0,924 0,1266 0,472 0,628 0,500 87 1,444
Kenya 84 2,362 93 0,967 0,1664 0,479 0,690 0,506 96 1,395
Tanzania 85 2,323 97 0,902 0,1588 0,460 0,639 0,464 90 1,421
Bangladesh 86 2,303 102 0,861 0,1462 0,402 0,580 0,509 88 1,442
Very Low
Benin 87 2,260 103 0,852 0,1001 0,450 0,561 0,464 94 1,408
Cambodia 88 2,237 101 0,874 0,0745 0,452 0,538 0,524 99 1,363
Zimbabwe 89 2,227 106 0,839 0,3260 0,293 0,693 0,467 97 1,389
Zambiya 90 2,206 105 0,849 0,0902 0,447 0,551 0,472 100 1,357
Nigeria 91 2,179 104 0,851 0,1018 0,462 0,562 0,450 103 1,328
Ethiopia 92 2,022 107 0,823 0,1671 0,430 0,588 0,408 104 1,199
Mozambique 93 1,982 108 0,805 0,1125 0,434 0,539 0,422 105 1,176
The BRIC countries (Brazil — 45th, Russia — 56th, India — 78th and China
— 76th) are characterized by rapid growth of their economies which reach 8-12 %
annually. In spite of this BRIC countries by the quality of life component of
sustainable development are ranked from the 45th position for Brazil to 78th
position for India. It is connected with low level of sustainable development
harmonization at the expense of priority economic development and at the same
time lagging in ecological and social fields.
In the lower part of the list there is a group of African countries (Benin —
87th, Cambodia — 88th, Zimbabwe — 89th, Zambia — 90th, Nigeria — 91st,
Ethiopia — 92th, Mozambique — 93th) which are in miserable conditions in
regard to almost all indicators of quality of life component of sustainable develop-
ment.
M.Z. Zgurovsky
ISSN 1681–6048 System Research & Information Technologies, 2009, № 1 14
The verification of adequacy of the SDGM model was accomplished by
matching of sustainable development and night lights world maps. The Nighttime
Lights of the World dataset contains the first satellite-based global inventory of
human settlements, derived from nighttime data from the (Defense
Meteorological Satellite Program — DMSP (2007), collecting at the network of
world data centers. It has made possible to check and to adjust adequacy of
SDGM model.
The important application of SDGM model connects with decisions making
at national level and policy development. For this purpose the 4-levels inverse
analysis procedure was developed as fig. 4.
In accordance with it for a particular country the sustainable development
data are analyzed based on sequentially passing the four levels from the top of the
triangle to its basis. During this “inverse” movement the “worst” values of sus-
tainable development factors are chosen for the given country. It allows to
Iec Ie Is
Isd
Fig. 4. Inverse Analysis Procedure
Quality
of life
A decent standard
of living
Basic
requirements
Efficiency
enhancers
Ecosystem
vitality
Economic
freedom
-Development of infrastructure
-Macroeconomic stability
-Мarket size
-Business freedom
-Freedom from government
-Labor freedom
-Marine protected area
-Intensive cropland
-Effective protection
-Risk conservation
-Burnt land area
-Irrigation stress
-Water qиality
-Water stress
-Economy
-GDP per capita
Critical
policy categories
Critical
indicator
Critical
dimensions
Economic
dimension
Ecologic
dimension
Fig. 5. Critical factors for Ukraine
Global analysis of sustainable development in context of quality and security of human life
Системні дослідження та інформаційні технології, 2009, № 1 15
“the space of critical indicators” necessary for making decisions aimed to
elaborate the strategy of the country’s sustainable development.
For example, the application of this inverse analysis procedure for Ukraine
makes it possible to obtain 2 critical dimensions of sustainable development, 6
critical policy categories and 16 critical indicators, as fig. 5. These critical factors
may be used by people taking political and managerial decisions.
3. ANALYSIS OF SEQURITY COMPONENT OF SUSTAINABILITY
Than we have analyzed the second component of sustainable development — se-
curity of people’s ‘life. This component in our research is presented by index Isec,
which has two statuses: a) Conflict status: =j imaginary unit; 0sec =I ; b) Regu-
lar development status: 1=j ; 0sec >I .
First consider case a) conflict status. The analysis of historical data on the
sequence of world conflicts which took place starting from 705 B. C. up to now
with the five year quantization interval has shown that in the analysed data six
consecutive evolutionary waves of world conflicts — nC are vividly recognized,
as fig. 6.
If the periods )( nCT of identified waves are divided by the greatest
common divisor kc which is equal approximately 85, then the periods may be pre-
sented in the form of a temporal series with coefficients sF , as table 2.
T a b l e 2 . Main characteristics of nC waves of world conflicts
nC Time )( nCT )( nCN TNCI n /)( = sF
1C 705 B.C.–
401 D.C. 1106 1218 101.1)( 1 =CI 137 =F
2C 402–1074 674 756 122.1)( 2 =CI 86 =F
3C 1075–1497 422 1618 981.3)( 3 =CI 55 =F
4C 1498–1749 252 1543 123.6)( 4 =CI 34 =F
5C 1750–1919 170 1485 735.8)( 5 =CI 23 =F
6C 1920–2007 87 1035 897.11)( 6 =CI 12 =F
)(7 FC 2008–2092 85 >1400 16)( 7 >CI 11 =F
Analyzing this series of numbers }1,2,3,5,8,13{=sF we see that it is a se-
quence of Fibonacci numbers with the “Golden section” equal 1.618. Since six
terms of sequence )(,),( 61 CTCT … respond to the law of Fibonacci series, we
come up with the hypothesis, that occurrence of world conflicts is subordinate to
this law. The intensity of conflicts )( nCI depends on a level of technological
evolution of the society and increases in time according to the hyperbolic law.
cn
n
n
n
n KF
CN
CT
CNCI
−
==
8
* )(
)(
)()( . (5)
M.Z. Zgurovsky
ISSN 1681–6048 System Research & Information Technologies, 2009, № 1 16
Fi
g.
6
. T
he
st
ru
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Global analysis of sustainable development in context of quality and security of human life
Системні дослідження та інформаційні технології, 2009, № 1 17
From the analysis of the revealed regularity we see that the next element of
this series will correspond to the seventh wave of world conflicts with the length
of the 80–85 years. We call it "the conflict of XXI century". This conflict has the
time interval approximately from 2010 to 2092 with the probable phases: 1 — the
10's years of XXI century — origin; 2 — the beginning 20's, the extremity of 40's
of XXI century — growth; 3 — 50's — of XXI century — the culmination, I *
)16( 7 >C ; 4 — the beginning of the 60's — the extremity; 70's of XXI century —
recession; 5 — 80's of XXI century — attenuation.
Now we pass to the analysis of the security status b): Regular Development
( 1=j ; 0sec >I ). For this status we analyze the risks of "the conflict of XXI cen-
tury" emergence. Based on the study of the totality of threats generating this con-
flict we will analyze its nature. We consider the 10 threats defined as the major
ones for the XXI-st century by UN, World Health Organization (WHO), Trans-
parency International and the UN Child Fund (UNISEF).
1. The first important threat is Global Reduction of Energy Resources,
which is stipulated by a rapid decrease of organic fuels resources, accompanied
by an increase of their consumption, first of all, in countries — economic giants.
In the beginning of the 20s of this century there will be the intersection of con-
sumption and production curves of energy produced from oil. Similar phenomena
will be observed for the balances "production-consumption" of the energy pro-
duced from gas — in the beginning of 30s and for uranium — in the beginning of
50s, respectively. Тtherefore, until the mankind have found sources which could
fully substitute organic fuels and nuclear power, the energy security both of a
separate country, and the world as a whole will decrease.
2. Gap between the Planet Bio capacity and ecological footprint is a sec-
ond global threat. By the mid of 2008 our planet’s population constitutes
6.65 billion people living in the territory of 510 million square kilometres. Its de-
mand in biosphere, or in the global ecological footprint, is 14.1 Billion global
hectares. Therefore, at present the global ecological footprint exceeds the bio ca-
pacities of the Earth by 5 Billion global hectares. It means that the planet’s re-
sources are being used up quicker than nature can recover them. By 2050 the gap
between the people’s needs and the Earth bio capacities will be 14 Billion global
hectares. This threat is strongly correlated with the changes of the planet’s popu-
lation demographic structure. For example, the greatest increase in the population
within the next fifty years is expected in the poorest regions of the world: in Af-
rica it will double, in Latin America and the Caribbean basin the population will
increase by 1.5 times, while in Europe it will decrease by 0.8 times.
3. Global warming as a next threat is the process of gradual rise of average
annual temperature of the Earth atmosphere and the World Ocean. As a result,
natural cataclysms would become more frequent, the harvests would become
poorer and many biological species may disappear. The major part of the
warming observed in the last 50 years is caused by human activity. First of all, it
is due to emissions of the gases causing greenhouse effect, such as carbon dioxide
(CO2) and methane (CH4).
4. According to World Health Organization and UNICEF, one more global
threat is connected with reducing access of people to clean potable water and
sanitary means. The fifth part of mankind (more than 1,1 billion people) has no
M.Z. Zgurovsky
ISSN 1681–6048 System Research & Information Technologies, 2009, № 1 18
access to potable water, and 2,4 billion person are not provided with minimum
sanitary conditions. Especially critical is the situation in urban regions of poor
countries.
5. The next global threat is Income Inequality. According to the World
Bank in 1973 the gap in profits between the richest and poorest countries was de-
fined as 40:1, and now it is 75:1. This threat is rather serious from the point of
view of growing number of conflicts in the world, spreading of corruption, terror-
ism, crimes, worsening of education, ecology and health care.
6. Among new threats to the mankind, World Health Organization (WHO)
points out such global diseases, as cancer, cardio diseases, cerebrovascular dis-
ease, HIV, tuberculosis and malaria in connection with their dramatic global
spreading. During the following twenty two years they expect a considerable
growth of mortality as a result of all global diseases, especially of cancer and
HIV.
7. Corruption becomes the next global threat. Now it’s a big obstacle to
economic growth and social evolution. It has become the major reason for poverty
and pulled up any positive transformations. Its "explosion" occurred at the end of
XX — beginning of XXI centuries in the course of the globalization. In the recent
years this phenomenon has been spreading into all countries of the world, and,
thus, corruption has gained global, international character. The forecast of
“Transparency International” shows the growth of corruption in the next three
years.
8. According to UNISEF infant Mortality is the next global threat.
11 million children under five years of age die annually all over the world. The
reasons are rooted in poverty resulting in mothers’ poor health, bad sanitary con-
ditions, infectious diseases and conflicts.
9. The next global threat, which we included in our model, is the vulner-
ability of the countries to the natural disasters. In our study we consider earth-
quakes, droughts, cyclones and floods as main natural disasters. In the simulation
we take into account the UNDP data on the total number of human losses result-
ing from the four above indicated natural disasters.
10. State Fragility is the last global threat, which we consider in the
course of simulation. It looks paradoxically, but after the end of Cold War the
new geopolitical system has been expanded by the big totality of unstable, unsuc-
cessful and poor countries. Weakening of restrictive mechanisms of bipolar world
stipulated escalation of the new wave of confrontations, terrorism, violence, terri-
torial claims and unequal development. Uncontrollable spreading of nuclear
weapons, wide-scale nuclear power production in such unbalanced world in-
creases a threat to sustainability and the global security of mankind. In this study
for quantitative estimation of this threat we use the State Fragility Index taken
from (Monty G. Marshall and Jack Goldstone, 2007).
Now we define the summarized impact of the totality of examined ten global
threats on different countries grounded on cluster analysis method with the pur-
pose of selecting groups of the countries with "close" performances of summa-
rized threats. To do it, for each country j , we shall put the vector rjT with the
coordinates which characterize the corresponding threats.
)NDSF,GW,WA,CP,CM,CD,GINI,FB,ES,(=rjT . (6)
Global analysis of sustainable development in context of quality and security of human life
Системні дослідження та інформаційні технології, 2009, № 1 19
Where ES — Energy Security; FB — Footprint and Biocapacity Balance;
GINI — Inequality; GD — Global Diseases; CM — Child Mortality; CP — Cor-
ruption Perception; WA — Water Access; GW — Global Warming; SF — State
Fragility; ND — Natural Disasters.
Initial data on each threat are taken from the mention above International or-
ganizations data bases. This data are normalized, so that its values vary over the
range (0–1).
]1,0[
ESES
ESES
1ES
minmax
min ⇒
−
−
−= ,
⇓
( )ND,SF,GW,WA,CP,CM,CD,GINI,FB,ES=rjT . (7)
After such normalization the security index secI for each country is defined
as the Minkovsky norm:
3
1
3
sec )(∑
=
==
n
j
rjrj TTI . (8)
Then relationship of order between clusters of countries has been introduced, as:
rjrkjk TTKK ≤⇔≺ . (9)
Actually the Security Index secI is the aggregated degree of remoteness of
the country j from the totality of ten presented threats. Here the maximum danger
for the country corresponds to 0sec =I in terms of closeness of the totality of
threats to a country, and the minimum danger corresponds to 1.
Global simulation with the application of the presented method shows, as ta-
ble 1 (columns 10, 11) that 10 most secure countries also have very high values of
the sustainable development index and degree of harmonization. Thanks to their
peaceful policy they are minimally involved in international conflicts and contro-
versies.
The positions of G8 countries, except Canada, in their security rating are dif-
ferent. It is explained by the lower degree of sustainable development harmoniza-
tion as compared with the first group of countries and their more aggressive eco-
nomic and political behavior in the world.
Post-socialist and BRIC countries are scattered in the ranking table of secu-
rity in connection with quite different internal situations and different groups of
external factors influencing them.
The most vulnerable countries from the point of view of their security are
characterized by low and very low values of the index of sustainable development
and degree of harmonization, high values of state fragility, bad ecological indica-
tors, very wide spreading of global diseases, corruption, and drastic inequality of
people.
To facilitate the analysis and make it easier we use the method of Principal
Compound Analysis (PCA) which allows reduce variables with many properties
to several hidden factors. Analysis shows that currently the most considerable
M.Z. Zgurovsky
ISSN 1681–6048 System Research & Information Technologies, 2009, № 1 20
threats for most countries are the reduction of energy security, worsening of bal-
ance between bio capacity and human demands and the growth of corruption.
Now, when we have the computed values of the quality of life index ( qlI )
and security index ( secI ), it is possible to compute the summarized quaternary of
sustainable development, as table 1 (columns 2, 3).
We see that leaders are countries with high degree of sustainable develop-
ment harmonization, good ecological indicators, high energy security, low values
of state fragility, low level of corruption. And vice versa, worsening of this group
of indicators lowers the ranking of countries in regard to quality and security of
life.
From the presented results of simulation and from the revealed regularity of
global conflicts occurrence important questions arise: why the seventh element of
Fibonacci series degenerates? What will happen with the world civilization in the
course of “the conflict of XXI century” and after it’s over? Maybe here is a clos-
ing cycle of some evolutionary chain 721 CCC →→→ … ?
The answer to these questions can be found in the works of two outstanding
scientists of the past century. In particular Vladimir Vernadsky wrote (Vernadsky,
1944): «In the geological history of biosphere human beings will have great fu-
ture, if they do not use their mind and labor for self-destruction». The other Rus-
sian scientist Nikita Moiseyev, the creator of the computer program for global
climate simulation “Nuclear winter” noted (Moiseyev, 2000): «If the mankind is
not going to radically change its behavior on the Planetary scale, then in the
middle of XXI century there may appear conditions under which people cannot
exist».
These conclusions were made for the mankind existence paradigm which
can be described by the formula “to meet people’s own interests”. If we assume
that the mankind will change the paradigm of its existence for another, for exam-
ple, for the paradigm of «harmonious coexistence». Then the systemic regularity
of world conflicts determined for the previous paradigm, obviously, will lose its
validity. Thus, the mankind will find new prospects for prolongation of its mis-
sion on the Planet. The main responsibility of scientists and, in particular, of the
participants of our conference is to make a contribution in this important goal.
CONCLUSION
The new Sustainable Development Gauging Matrix (SDGM) was developed and
argued. This tool allows to obtain quantitative estimations of the quality of life
component of sustainable development process depending on the groups of
economic, ecological, social and institutional indicators and datasets. The list of
most essential global threats to the future of mankind has been selected and
cluster analysis of dependence of sustainability on these threats is held. On the
basis of usage of SDGM model the foresight of the future global conflicting
has been executed. The created mathematical model allows to develop
recommendations regarding the ways of improving the standards of quality and
safety of life in particular countries and regions of the world by the global
computer simulation of sustainable development process.
Global analysis of sustainable development in context of quality and security of human life
Системні дослідження та інформаційні технології, 2009, № 1 21
REFERENCES
1. Vernadsky V.I. (1944). Few words about the noosphere. The progress of modern bi-
ology, 18(2), 113–120.
2. UN Summit, Rio de Janeiro (1992) from Word Wide Web: http://www.ihst.ru/~
biosphere/terminal/LokaL %20povestki.htm.
3. UN Summit, Johannesburg (2002) from Word Wide Web: http://revolution.allbest.ru
/ecology/000059941.html.
4. The Global Competitiveness Report (2007–2008), http://www.weforum.org/en/ini-
tiatives/gcp/Global%20Competitiveness%20Report/index.htm.
5. The news of intellectual centre of Heritage Foundation (2008) from Word Wide
Web: http://www.heritage.org/index/countries.cfm.
6. EPI Beta (2007/2008) from Word Wide Web: http://www.yale.edu/epi/files/
2008EPI Text.pdf .
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com/.
8. Human Development Report (2007/2008) from Word Wide Web: http://hdr.undp.
org/en/media/hdr 20072008 en complete.pdf.
9. The publications of the United Nations on economic and social affairs — UNDESA
(2005), UN publication № Е.04. ІІ.C.1, 2005.
10. WDC for Geoinformatics and Sustainable Development (2008) from Word Wide
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11. Defense Meteorological Satellite Program — DMSP (2007) from Word Wide Web:
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12. Monty G. Marshall and Jack Goldstone (2007). Global Report on Conflict, Govern-
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(17), 3–21.
13. Moiseyev N.N. (2000). To save the mankind on the Earth, Ecology and life 1 (03),
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Received 08.12.2008
From the Editorial Board: the article corresponds completely to submitted
manuscript.
|
| id | journaliasakpiua-article-108446 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T10:22:41Z |
| publishDate | 2009 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/5a/6524fc5a819894a83044d6c67e2be05a.pdf |
| spelling | journaliasakpiua-article-1084462018-04-06T12:35:46Z Global analysis of sustainable development in context of quality and security of human life Глобальный анализ устойчивого развития в контексте качества и безопасности жизни людей Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей Zgurovsky, M. Z. A system of factors (indices and indicators) and a new method of quantitative and qualitative evaluation are developed. This system, named “Sustainable Development Gauging Matrix” (SDGM) and data presented by reliable international organizations culminated in a Global Simulation regarding quality of life and security of the world population. Specifically, this study focuses on analysis of the Systematic Regularity of World Conflicts over the Course of Time. A prognosis is detailed of the next world conflict, labeled the "Conflict of XXI Century”, and an analysis is provided of its nature and main characteristics; duration, main phases of the conflict and intensity. This prognosis details a set of basic global threats that spawn this conflict. Using cluster analysis, its influence on different countries of the world is accurately defined. These results were obtained by applying the capabilities of the world data centers network as a tool for providing a variety of scientific interdisciplinary data. Предложена система факторов (индексов и индикаторов) и разработана новая метрика для измерения процессов устойчивого развития (SDGM) с целью глобального анализа указанных процессов в контексте качества и безопасности жизни населения мира. Для этого моделирования использованы данные, представленные авторитетными международными организациями. С применением SDGM исследовано влияние совокупности глобальных угроз и мировых конфликтов на устойчивое развитие. Сделана попытка предвидения следующего конфликта, названного «конфликтом XXI столетия», и выполнен анализ его природы и главных характеристик: продолжительности, основных фаз течения и интенсивности. Определена система глобальных угроз, порождающих этот конфликт. С использованием метода кластерного анализа определено влияние этих угроз на различные страны мира. Запропоновано систему факторів (індексів та індикаторів) і розроблено нову метрику для вимірювання процесів сталого розвитку (SDGM) з метою глобального моделювання зазначених процесів у контексті якості й безпеки життя населення світу. Для цього моделювання використано вихідні дані, представлені авторитетними міжнародними організаціями. Із застосуванням SDGM проведено дослідження впливу сукупності глобальних загроз і світових конфліктів на сталий розвиток. Зроблено спробу передбачення наступного конфлікту, названого «конфліктом XXI сторіччя», і виконано аналіз його природи й головних характеристик: тривалості, основних фаз плину та інтенсивності. Визначено систему глобальних загроз, які породжують цей конфлікт. З використанням методу кластерного аналізу визначено вплив цих загроз на різні країни світу. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2009-03-19 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/108446 System research and information technologies; No. 1 (2009); 7-21 Системные исследования и информационные технологии; № 1 (2009); 7-21 Системні дослідження та інформаційні технології; № 1 (2009); 7-21 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/108446/103403 Copyright (c) 2021 System research and information technologies |
| spellingShingle | Zgurovsky, M. Z. Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей |
| title | Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей |
| title_alt | Global analysis of sustainable development in context of quality and security of human life Глобальный анализ устойчивого развития в контексте качества и безопасности жизни людей |
| title_full | Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей |
| title_fullStr | Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей |
| title_full_unstemmed | Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей |
| title_short | Глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей |
| title_sort | глобальний аналіз сталого розвитку в контексті якості і безпеки життя людей |
| url | https://journal.iasa.kpi.ua/article/view/108446 |
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