Economic Complex Networks
a holarchy of evolving sectors
Economic Complex Networks
a holarchy of evolving sectors
Proefschrift
ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,
op gezag van de Rector Magnificus Prof.ir. K.C.A.M. Luyben, voorzitter van het College voor Promoties,
in het openbaar te verdedigen op maandag 11 november 2013 om 15.00 uur
door Edgar Ferdinand Marcel van BOVEN HTS ingenieur elektrotechniek
geboren te Kloetinge
Dit proefschrift is goedgekeurd door de promotor: Prof.dr.ir. N.H.G. Baken
Samenstelling promotiecommissie:
Rector Magnificus, Voorzitter
Prof.dr.ir. N.H.G. Baken, Technische Universiteit Delft, promotor
Prof.dr. B.M. Balk, Erasmus Universiteit (Rotterdam School of Management) Prof.dr.ir. J.A. van den Brakel, Universiteit Maastricht
Prof.dr.ir. P.F.A. Van Mieghem, Technische Universiteit Delft Prof.dr.ir. R.E. Kooij, Technische Universiteit Delft Dr.ir. H. Wang, Technische Universiteit Delft Dr.ir. R. Hekmat, KPN Royal
ISBN 978-94-6186-201-3
This Research was funded by KPN Royal.
Keywords: Complex Networks, Economic Activity Classification System, Econophysics, Functions, Holon, Input-Output table, Sector, Telecommunications, Trans-sector Innovation.
Copyright © 2013 by E.F.M. van Boven
All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording or by any information storage and retrieval system, without written permission from the author. Printed in The Netherlands
to Olga
Acknowledgements
At the point of finishing this project I would like to thank the colleagues, acquaintances and family for all their support, inspiration and willingness to share knowledge and experience. Fortunate with the many people who have contributed to this adventure, firstly I express my gratitude to the community that facilitated my research. Thank you Professor Nico Baken for the rare kind of freedom that allowed for thinking at a global scale and far ahead in time, Ger Behonek for opening KPN’s doors to this research, Regine von Stieglitz for the trustful conjunction of decision makers, Joost Farwerck for agreeing and Edwin Jongejans for safeguarding the finalisation of the research against all odds.
Becoming a NAS member, I am particularly indebted to Professor Piet Van Mieghem guiding my first steps in complex network science (and encouraging me to let economic data speak) and Huijuan Wang reaching out to connect our research domains (which seemed so difficult to bridge). Sharing your knowledge and wisdom, inspired towards uncovering some of the secrets of weighted economic
networks. I sincerely hope our endeavour has not come to an end as we seem to be at the verge of a next step in econophysics.
I thank Antònio Pinto Suarez Madureira for teaming up. Initially, being alone together, we noticed that our trans-sector challenges were quite different from what our PhD colleagues at NAS were doing. Our discussions helped us find our ways, agreeing that whatever we would publish, it should be clear. Looking back, it is impossible to express my luck entering Statistics Netherlands for an explorative meeting chaired by Eric Wassink early January 2008. The willingness of key experts to participate in a research initiative, has led to more than five years of knowledge sharing, indispensable multi-disciplinary interaction and aid in navigating through massive amounts of statistical publications. I thank Hans van Hooff (currently the very last Dutch methodologist active in economic activity classification systems) for actively sharing your experience, the great many vivid conversations, phone calls and lengthy chains of email. I am grateful and thank Taeke Takema for explaining and providing the Dutch Input-Output tables that constituted the fundament for the network analysis.Finally, the Statistics Netherlands
connection has led to the involvement of Professor Jan van den Brakel and Professor Bert Balk leading to the inclusion of the German economic network in the research yielding valuable insights from comparing Germany and the Netherlands. I thank you both for your feedback and for participating in the promotion committee.
Furthermore, I thank the committee members Ramin Hekmat for co-publishing, encouraging the vital sectors study (and your crystal-clear lectures on graph theory) and Professor Rob Kooij for joining the analysis team on telecom functions and for our inspiring interaction since the late 90s.
I express my gratitude to the NAS members Ebisa Negeri, Christian Doerr, Fernando Kuipers, Yue Lu, Siyu Tang, Javier Hernandez, Anteneh Beshir, Cong Li, Ruud van de Bovenkamp, Almerima Jamakovic, Milena Janic, Jasmina Omic, Wynand Winterbach, Norbert Blenn, Tom Kleiberg and (from WMC) Professor Jos Weber, Jinglong Zou and (from TBM) Marc de Reuver and Professor Harry Bouwman for your support, sharing your knowledge and passing on relevant publications.
I thank Bingjie Fu in particular for translating the Chinese economic activity classification system and Wendy Murtinu for your crucial operational support, helping me through that mountain of action items. Marlies van Steenbergen, Noor Huijboom, Rob Reitsma and Rogier Noldus, thank you for strengthening my confidence. Indeed, a PhD project can be done part-time, complementing our challenging work “outside” the university. At the campus one can experience a second or (in my case) a third youth. Learning from a decade of interaction with more than a hundred young master talents is an
unprecedented phenomenon. From this community, the contributions of Jos Berière, Lars de Jonge, Wim van de Lagemaat, Shahin Mesgar Zadeh, Carolyn Simmonds Zuñiga, Aarabi Krishnakumar and Mohammad Hosseini deserve highlighting. Beyond expectations the thousands of working hours on your
Master thesis projects have clearly boosted the knowledge in and around the research team of Professor Nico Baken. This I witnessed and never shall I forget the intensity and the insights that each of your adventurous theses have brought. Hopefully each of you can spread or carry our work towards the 22nd century.
Together we learnt that successful dissemination of ideas worth spreading, requires the art of storytelling and visualisation. Hereby I thank Jim Stolze, Randolph Plomp and Yolanda Bakker who master this dimension and helped to communicate the messages from a labyrinth of trans-sector content.
For co-publishing and sparring I thank Annemieke de Korte, Ludmila Menert, Frank den Hartog, Rob Reitsma, Bert Feunekes and the following telecom professionals currently active within KPN: John Hoffmans for participating in the analysis of telecom functions and your support on crucial
moments, Harm Mulder for showing how to deal with a mission impossible and quoting Dilbert to keep spirits up, Nico van Belleghem for giving ICT support and frolicking towards those rare moments of success, and Willem Hollemans for your clear sketching and analysing the effects of contemporary (ICT) governance.
Furthermore I thank the KPN colleagues Pieter Veenstra for mastering the forces necessary to set things in motion before anyone else notices, Jack Tuyt for your prophecies, Stefan Satijn & Tim Ensing for load balancing our LCM work over our precious time, René Fehling for rendering your magic and creativity, Marieke Fijnvandraat for shedding light on the black hole of contemporary decision making, Coen Pegels for sharing interesting publications accompanied by personal connotations, Martin Janssen for sharing telecom market data and ancient telecom literature, Peter Maarten Westerhout for showing how to give the most powerful ET4-034 lecture, Jan Garnier & Ig Nieuwenhuis for your uncompromising feedback and sharing your vast experience, Wouter de Vries for your lucid analytics, Ed Sloot for filtering
contemporary management jargon, Marko Krcevinac for pointing out some fundamentals about mankind, Marten Rooimans for your music and elegantly formulated observations, Bert Blom for encouraging me while traveling, Rob Poland & Frans Bak for the in depth reflections in the safety of our office and Han Naber for safeguarding my disk drive and pointing out that there exists a life outside work.
I would like to acknowledge the former KPN colleagues Marco Kind, Sander Tolsma and Franklin Selgert for their contributions to the research.
I thank Peter Quatfass for our lengthy discussions especially during our cycling weekends, Frans Stoffijn for revealing F4CC (the ultimate isomorphism) and Ad de Vogel for your wise and sometimes hilarious propositions such as “Niet iedere volzin is zinvol”. Thank you Ludmila Menert for pointing out the same in other words: “Less is more”. During the final stage of my research this advice proved to be crucial. Writing down in clear language what grew in seven years is difficult, in particular for engineers like me that strive for completeness and precision.
I thank Kees Koster for explaining the meaning of key terminology from ancient Greek and Latin sources and Erik de Vries ever supportive, active and vivid since we met in the early 80s.
To Marc de Crom I am indebted, particularly for your indispensable comments on my attempts to approximate clear English wording. Thank you for feeding me and “paranymphing” together with Hans on St. Martin’s Day (11-11), that very day of sharing.
Finally I complete my acknowledgements by thanking Olga for your endless patience, support and devotion. When you were allowed to enter the Netherlands in 2006, my dual work was already on-going, scarcely leaving room for us both. Especially the great loss in our family coming across during the finalisation of my dissertation, made us look ahead. Looking forward to the years to come, to enjoy life together.
Edgar van Boven
Table of contents
Chapter 1 Introduction ………. 1.1 Problem statement ………... 1.2 Literature overview ………. 1.3 Research objective ……….. 1.4 Research questions .………. 1.5 Research domains and relevance ………. 1.6 Methodology ……… 1.7 Structure ………..Chapter 2 Theoretical framework .………..
2.1 Theoretical Environment ………. 2.2 Classification systems ………. 2.3 Sector related models and their structure .………... 2.3.1 Leontief Economic Model ……….. 2.3.2 Value Chain concept ………... 2.3.3 Integral Network Architecture method & model ……… 2.3.4 STOF method & model ……….. 2.3.5 Open Systems Interconnection reference model .………... 2.3.6 New Generation Operations Software and Systems ………….. 2.3.7 ITU-T G.80x ……….. 2.3.8 Framework for Cure and Care ……… 2.3.9 IEC 61850 ……….. 2.3.10 Overview related models ……… 2.4 Holons and Holarchy ………... 2.5 Hypotheses ……….. 2.6 Conclusions ………...………
Chapter 3 Sectors, economic activity classification systems and their evolution ……. 3.1 What defines a sector and which ones can be distinguished? ………. 3.2 Inventory and comparison of economic activity classification systems …. 3.3 Evolution of sectors and economic activity classification systems ..…….. 3.4 Which functions characterise a sector? ………... 3.5 Conclusions ………. 11 11 12 14 14 15 17 19 21 21 26 29 30 32 33 34 35 36 37 39 40 41 42 44 45 46 46 50 55 60 63 8
Chapter 4 Sector network analysis ……….……. 4.1 Classification systems visualised as networks .……….. 4.2 Input-Output tables ..………... 4.3 Analysis methodology of monetary flows from recorded statistical data .. 4.3.1 The first case study ..……… 4.3.2 The second case study .……… 4.4 Comparing the German and Dutch economies as networks ..……….
4.4.1 Quantitative aspects .……… 4.4.2 Hierarchical aspects ………. 4.4.3 Distributions ……… 4.4.4 Correlations .……… 4.5 Labour force trends ………. 4.6 Vital sectors in a sector network context ……… 4.7 Conclusions ……… 4.7.1 Conclusions from the data analyses .……… 4.7.2 Intuitive conclusions ………
Chapter 5 Modelling the sector network ………
5.1 Contributions to theory ……….. 5.2 The sector network model ..……… 5.3 Alternatives and application of the models ……… 5.4 Conclusions ………
Chapter 6 Trans-sector innovation and isomorphisms .………..….. 6.1 Isomorphisms ………. 6.2 Results from a Trans-sector Innovation idea generation experiment .…… 6.3 Service bundle 2020 ...……… 6.4 Trans-sector Innovation combinations .……….. 6.5 Conclusions .………
Chapter 7 The telecommunications related sector .……….….. 7.1 Communications value offered to the sector network ………
7.1.1 The OECD alternative aggregation .……… 7.1.2 Definitions related to communications .………. 7.2 The functions of telecommunications .……… 7.3 A telecommunications hierarchical graph ..……… 7.4 A contemporary double paradox ……….
7.4.1 The responsibility paradox .………... 7.4.2 The communications business paradox ……..………... 7.5 Conclusions ……… 64 65 66 71 71 73 76 77 82 88 92 99 103 110 110 114 118 118 122 128 129 130 130 131 135 138 142 144 144 145 148 150 152 154 155 157 162 9
Chapter 8 Conclusions .……….……….…….….. 8.1 Main findings ……….. 8.2 Hypothesis testing ……….. 8.3 Recommendations for future work ……….
8.3.1 Towards the next revision of ISIC .……….. 8.3.2 Towards unravelling the definitional perspectives of sectors …. 8.3.3 Economic network research ………....
Summary .……….……….……….…….….... Nederlandstalige samenvatting ……….……….…….…….. Curriculum vitae .……….……….…….……….… References ..……….……….……….……….. Appendices ..……….……….……….…….… Publications .……….. Definitions ...………. Economic Activity Classification Systems .………..
ISIC rev. 4 (United Nations) ....………. ANZSIC rev. 1 (Australia and New Zealand) .……….. ICNEA 2011 (Republic of China) ...……….………. SIC of ROC 2002 (Republic of China) .………. JSIC rev. 12 (Japan) .………. NAICS 2012 (US, Canada and Mexico) ...………. OKVED 2010 (Russian Federation) ………. Observations from the World Input-Output Database 2012 ………. Telecommunications functions ………. Repository of assessed models ………. Symbols and Acronyms ..………..
164 165 176 178 178 180 180 182 183 185 186 198 198 200 226 226 240 241 242 243 244 245 246 248 256 261 10
Chapter 1
Introduction
1.1 Problem statementMost systems consist of connected sub-systems. This allows for viewing, perceiving and studying systems from a network perspective. Tangible examples of real networks are power-grids, roads, railways and telecommunications networks.
In general, a network consists of a set of nodes interconnected by a set of links. Advances in various disciplines of science have provided evidence that networks can be distinguished on different scales [Barabási,2003],[Jamakovic,2008] and aggregation levels. Large systems of elements (nodes)
and their interactions or relations (links) can be represented as complex networks[Van Mieghem,2011].
In this sense a national economy can be considered to be a complex network. Our society and economy have been decomposed into a network of networks that consists of interdependent sectors
[Leontief,1936],[Bryson et al.,2006],[Miller&Blair,2009]. Phrased in complex network terminology: the sectors of an
economic network are inter-linked nodes that together constitute a sector network.
Roughly 11.000 years ago, the beginning of a major transition in human history took place. Nomadic families became colonists settling down in the first villages. This transition initiated the process of functional decomposition, also referred to as the division of labour [Kinneging,p227-240,2005].
Specialists took over vital and non-vital tasks previously performed by each family. As a result, productivity scaled up and the division of labour became an irreversible fact of life. In the work of Adam Smith (An Inquiry into the Nature and Causes of the Wealth of Nations)and Anne-Robert Jacques Turgot (Réflexions sur la Formation et la distribution des Richesses) [Hoyng,2011] the notion
of the division of labour has been formulated and widely accepted as a fundament of economic science. At national level, [Hidalgo&Hausmann,2009] state that level of the division of labour is limited by
the size of a country’s economy. The bigger the market, the more its participants can specialise and the deeper the division of labour that can be achieved.
Outsourcing of tasks/functions is primarily based on trust relations [Fukuyama,1995] and supported by
transactions. As money was gradually introduced[Pringle,1998], this trusted value symbol has
simplified the exchange of value in a standardised way. Both the process of specialisation and the trusted ability to transact, has enlarged efficiency and thereby the scale of economy and society, continuously reshaping the sectors and their ever changing boundaries. In parallel, the evolution of physical transportation and communication arrangements have significantly reduced travel time and the cost of bridging distance and time, enabling the growth of economy and society all the way from local to global. Furthermore our economic and social activities have become less tied to geographical, organisational and political boundaries [Friedman,2005].
The limitations of our collective competency [Pearson,2006] and means to oversee, understand and
govern the sector network (its dynamics, its structure, its resources and its interdependencies) are reflected in global system crashes such as the Internet bubble crash (2000 – 2003). Obviously, the current financial and economic crisis that announced itself in 2007[Teulings et al.,2011], constitutes an
unprecedented example and is now entering the sixth year of its existence. Though many
explanations of its origin have been given, finding a way out of this crisis does not seem in reach. The need for an innovative approach to invention, tooling and orchestration at sector network level is getting stronger as the recent crisis proves to have a devastating impact on the welfare and well-being of a substantial part of the world population [Obama,2009]. The US government Financial Crisis
Inquiry Commission[US FCIC,pxvii,2011]concluded that this crisis was caused by the failure of many
different actors and could have been avoided if a trans-sector orchestration arrangement would have been in place (regarding the sectors of finance, government, real estate and household). In this thesis the term trans-sector refers to innovation, transactions, collaboration and orchestration
involving actors originating from two or more sectors. Although at enterprise level an orchestration need is evident too, the prime difference between orchestration at enterprise level versus sector level is that orchestration at sector level explicitly addresses the public domain while at enterprise level it is limited to the business domain. When examining steps to find a way out of the crisis by realising innovations and optimisations in a trans-sector manner, we need a thorough understanding of the different sectors, their interdependencies and the trends that influence their evolution [Ángeles Serrano et al.,2007],[Helbing,2013]. A trans-sector approach from a network perspective can play a significant
role here and possibly complex network theory may prove to be a helpful tool[Schweitzer,2009]. These
approaches and the economic data sets, generously provided by Statistics Netherlands and Statistics Germany, have enabled this thesis’ complex network research of the German and Dutch sector network at various overlay levels.
The main problem addressed in this thesis is the lack of understanding of the components, the structure and developments within and between sectors. The current inability to orchestrate the sector network as a whole illustrates this problem. This thesis endeavours to give a contribution to the understanding of our contemporary sector network by gathering knowledge on the structure, composition, functions, properties and dynamics of our current economic system and by applying complex network theory.
1.2 Literature overview
Concerning innovation and collaboration, an abundant spectrum of literature is available. However, at the beginning of this thesis project in 2006, few publications were available that touched on the subject of trans-sector innovation. Bryson et al performed a literature review and proposed a framework for understanding cross-sector collaboration (published in “The Design and
Implementation of Cross-Sector Collaborations: Propositions from the Literature”, 2006). Bryson
et al provided 21 propositions concerning cross-sector collaboration with focus on complex public problems and public value. The authors present their view on this topic in which they argue that
“organisations will only collaborate when they cannot get what they want without collaborating. In effective cross-sector collaborations organisational participants have to fail into their role in the collaboration”. The authors state that “in the United States the presumption is that we will let markets (for-profit sectors) work until they fail. Only in that case government intervention is allowed as a last resort to try fixing the failure”.
A public-value-failure-model introduced in [Bozeman,2002] underlines the need to consider public
values irrespective of market efficiency.According to Bozeman public-value-failure occurs when: - core public values are not reflected in social relations, either in the market or in public policy, - neither the market nor the public sector provides goods and services required to achieve core public values.
The adjectives cross-sector [Roodink,2011] and trans-sector both appear in the literature to address the
same concept but cannot be clearly distinguished. The adjective trans originates from Latin and has a broader array of meanings compared to cross. Within the context of innovation the adjective cross may associate somewhat more to the meaning through things while the meaning of the adjective
trans seems to associate somewhat more to bridging things (e.g. trans-Atlantic and cross-country).
Relating to trans-sector innovation, value chains [Porter,1985], value networks [de Reuver,2009] , joined-up
ICT innovation [Huijboom,2010] and multi-actor business models [Bouwman,2008] are and have been
researched intensely. In 2011, Madureira has provided a literature survey and proposed a Holonic Framework (HF)to account for the value of digital information networks, relating to trans-sector innovation with focus on the perspective of network evolution. The HF identifies 13 capabilities, which are defined as procedures that a holon [Koestler,1967] can use to navigate through streams of
information flowing through networks that potentially bring value. The HF can be used to explain evolutionary change in policy making, economy and biology.
From the early 20th century on, many research initiatives have been devoted to studying economic systems e.g. by means of Input-Output matrices [Leontief,1936],[Miller&Blair,2009] andeconomic activity
classification systems [ISIC,2008],[SBI,2009],[van den Brakel,2010].
The International Standard Industrial Classification of All Economic Activities (ISIC) provided by the United Nations Statistics Division, proved to be a prevalent source for this thesis, enhancing the study of sectors from various viewpoints.
Interestingly, blending the research disciplines of complex networks (complex systems) and economic systems is relatively new and provides a viable and scientifically attractive combination commonly coined as economic networks. In 2009, Schweitzer et al stated in the paper Economic
Networks: What do we know and what do we need to know? that economic networks and their
dynamics is an emergent field of research and identifies a knowledge gap addressed in this thesis’ research. Schweitzer underlines the importance of the combination of massive data analysis, time series analysis, complexity theory and simulation with analytical tools that have been developed by game theory, graph and matrix theory
This thesis requires a selection of vocabulary from various scientific fields. Chapter 2 discusses the central nomenclature of this thesis and accounts for the proposed selection serving for a limited amount of newly introduced vocabulary. The main views that have influenced the selection of the nomenclature are a) network view, b) hierarchy, c) economic activity classification and functional view. This for example resulted in the frequent appearance of the terms a) node and link, b) holon and sub-system, c) enterprise, organisation, actor, activity cluster, unique functions and non-unique
functions which together constitute the sub-central nomenclature of this thesis respectively.
Concerning functions, abundant literature is available [ITU-T G.80x],[Bunge,1979],[Barnes,1982]. The functions
of economic (sub-)systems are considered relevant within the scope of this thesis, because of their strong interrelatedness with (economic) activities and the fact that these functions can be studied in a more abstract sense, apart from the objects in which functions can be implemented.
In his treatise on basic philosophy, Bunge touches on recognition and characterisation of sectors and their sub-systems. He considers society as a system with the following properties:
- Some members do labour, thus transforming the environment,
- Every member shares information, services or goods with some other members of the same community.
[Bunge,p194,1979] mentions two classical doctrines (holism versus individualism) dividing social
philosophers over the nature of institutions and the proper way of studying them. Bunge claims that his systemic theory serves neither of these doctrines where to his opinion the individualistic view sees society as an aggregate of individuals, and the holistic view sees society as a mystic totality
hovering above the individuals’ humble membership [Bunge,p241,1979]. Alternatively, Bunge regards
human society as a system composed of persons bounded by social relations. Section 2.1 explains in more detail how his theory connects sectors, systems, networks and functions.
Concerning the functions of digital information networks, extensive research, standardisation and modelling initiatives [ITU-T,1995],[OSI,1985],[eTOM,2002],[NGOSS,2004] took place, triggered by the need of
telecom operators to interconnect their networks at different hierarchical levels. Section 2.3 and the Appendix Repository of assessed models discuss these related models in more detail. The
telecommunications related sub-set of functions is considered relevant within the scope of this thesis as well, mainly because of their relative short existence and their substantial impact on the recent societal and economic developments.
This thesis adds a trans-sector contribution to a gap in the literature. This gap regards our
(orchestration of) contemporary networked economies by providing insight and overview from a multi-disciplinary approach that combines the research of functions in economic sectors, analysis of sector network value flows and lessons learnt from telecommunications related developments.
1.3 Research objective
This thesis’ first aim is to contribute to the understanding of developments in real economic systems by applying advances and tooling from the field of complex networks on time series of sector network related statistical data.
Initially, this research requires knowledge about economic activity classification systems, Input-Output analysis and the individual nodes of the sector network. Studying sector related models and the functions of sectors is imperative.
Subsequently, the second aim is to design a novel sector network model and a sector model (generically applicable to any sector) both reflecting the main findings of this thesis work. Thirdly, this project aims to enrich the area of complex networks with new insights derived from studying real economic networks and the monetary flows between their nodes. From these flows the complex network properties of the Dutch and German sector network are researched in order to understand and compare their structure, their clustering and their development over time.
Additionally, this research enables comparing economic networks to other types of real networks. From a valorisation perspective, the fourth aim of this project is to:
- provide a (model-based) view on the classification methodology of economic activities that can help future international coordinated revisions of these classifications on the one hand, and the use of these classifications for classifying individual cases on the other hand. - provide a set of inter-sector isomorphisms,
- generate promising trans-sector innovation ideas and understand the patterns and similarities, - visualise and explain the thesis results by means of animations and presentations for a broad (non-academic) target group.
1.4 Research questions
Three research questions (RQs) have been selected out of many possible research directions that address the research objectives. RQ2 builds on a fundament provided by RQ1 and subsequently RQ3 builds on RQ2. Figure 3 in section 1.7 elucidates the inter-relatedness of RQs, SQs, chapters and sections.
The first RQ and its six SQs address a) the definition of a sector, b) the current and historical sector inventory and c) the sector modelling part of the analysis:
RQ1 What defines a sector and which ones can be distinguished? SQ1a Which functions characterise a sector?
SQ1b Which specific and generic telecommunications related functions can be found? SQ1c Which relevant sector related data is available?
SQ1d Which economic activity classification systems exist? SQ1e How did the sectors evolve?
SQ1f Can we derive a generic sector model and what does it look like?
The second RQ and its three SQs address a) the sector network definition, b) the comparison of the sector networks’ characteristics/properties with those of an inventory of other types of complex networks and c) the sector network modelling part of the analysis:
RQ2 What is a sector network and how did it evolve?
SQ2a Does the sector network constitute a complex network?
SQ2b What are the main observations, properties and characteristics derived from sector network related data?
SQ2c Can we derive a generic sector network model and what does it look like?
The third RQ and its two SQs address trans-sector innovation examples, derived patterns and isomorphisms:
RQ3 Which promising trans-sector innovation examples can be identified? SQ3a Which main isomorphisms can we detect among the sectors?
SQ3b Can we profit and find value when we transfer sector specific knowledge, capabilities, insights and experience among the sectors? And more specifically; what does such a transfer mean for the telecommunications related sector?
The central theme in this thesis’ research is the complex network of economic sectors. All actors active in this complex system have become increasingly dependent on digital communications. Especially the facts that the telecommunications related sector provides this connective value and economies have become intensely networked, have led to incorporating a specific effort in this thesis’ research design, formulated in SQ1b and SQ3b.
1.5 Research domains and relevance
This section describes this thesis’ research domains and relevance. This thesis involves and intersects three research domains:
I. Classification systems and Input-Output tables (economic systems), II. Complex networks and graph theory,
III. Sector related models and functional analysis.
Figure 1: overview research domains and intersections
Answering the research questions requires interdisciplinary research. The nature and size of this thesis’ subject is broad in itself as it touches on an entire economy. In order to avoid a study about everything, the scope of work had to be narrowed down substantially while bearing in mind both the academic and valorisation related research objectives. Contributing to the understanding of
Ι. Classification Systems & Input-Output Matrices ΙΙ. Complex Networks & Graph Theory Network • Topology • Measures • Properties • Classification • Characterisation Classification Systems of Socio-economic Activities e.g. ISIC, NACE, SBI, NAICS, OKVED
Functions Sector Network Model
ΙΙΙ. Sector Related Models & Functional Analysis Division of Labour Data Analysis • Input-Output tables • Working People
Evolution over time
• Classification Systems revisions • Recording of Monetary Input-Output data
Network Hierarchy Clustering Weighted Networks • Link weight • Self loop Model • Holon • Portfolio • Telecom • Functional • Vital sector Matrix Analysis Visualisation Isomorphisms Layered Graphs Nodes & Links
Layering • Hierarchy / Holarchy • Interdependencies Trans-sector Innovation • Experiments • Similarities • Patterns Economic Networks D A C B 15
economic systems by applying advances from the field of complex networks involves at least these two different domains that together capture economic networks.
Finally, the modelling part of this thesis required a third additional domain that qualitatively supports and completes the sector network analysis. During the initial stage of this thesis project a functional perspective was incorporated. Economic activity classification systems indeed provide the names of the nodes (activity clusters) in the network and describe their value add, but do not explicitly address their specific nature and the uniqueness of their functioning.A functional
analysis of the International Standard Industrial Classification of All Economic Activities revision 4
[ISIC,2008] and a set of telecommunications related functions was carried out adding a qualitative view
to the complex network analysis of the Input-Output tables that tends to be more quantitative in nature. In chapter 2 the choice to add functional units of research is accounted for in more detail. Figure 1 captures the research subjects and their relations mapped on the three research domains. Besides the trans-sector idea generation experiment (domain III), the main relevance of this thesis lies within the intersections of the three research domains.
As stated, the sector model is a sub-ordinate part of the sector network model and aims to be generically applicable to any sector. In order to model the sector network, it is of help to first understand more about the nodes of the network (e.g. the studies that concentrated on classification systems and the distinction between vital and non-vital sectors). Here after the novelty of this thesis’ contributions are summarised per research domain intersection.
A. Contributions intersection {I ∩ II} \ {III} regarding data analysis:
Network properties and evolution of the Dutch and German economy are captured and compared by means of a newly developed complex network analysis method. In two case studies advances from the field of complex networks were applied to large economic systems and the (dis)similarities between economic systems and other types of real-world complex networks were explored. The analysis and comparison was carried out by means of several network constructs derived from Dutch and German time series of monetary data.
B. Contributions intersection {I ∩ III} \ {II} regarding functions and isomorphisms:
An inventory is given of all sector functions (status quo 2009) derived from ISIC rev.4 and telecommunications related models and standards. Functional comparison of adjacent sectors resulted in a list of the unique functions per sector. Finally, a set of meta-functions is derived that is generically applicable to all sectors and their constituents.
Isomorphisms are detected by means of a trans-sector innovation idea generation experiment and the service bundle 2020 interviews. Achieving more in-depth insights about trans-sector isomorphisms can contribute to solving current sector problems by offering concepts from other sectors.
C. Contributions intersection {II ∩ III} \ {I} regarding application of graph theory on sectors: Findings about sector network interdependencies and hierarchy are captured in layered graphs. Two examples are constructed:
- a vital sector graph,
- a telecommunications related graph.
D. Contributions intersection {I ∩ II ∩ III} regarding sector network modelling and visualisations: This intersection merges the outcome of this thesis’ research constituents into a novel sector network model (that includes the sector model). The sector network model is elucidated by various graphs / visualisations:
- derived from the monetary flows recorded in the Input-Output tables,
- showing the network structures of the Dutch classification systems SBI 1993 and SBI 2008, - revealing vital sector interdependencies.
Sector network properties, observations and conclusions are derived from data analysis and visual inspection of the generated graphs.
1.6 Methodology
This section describes this thesis’ research design and lists its sequential steps. A mixed method research [Smyth,2006] has been carried out combining the analysis of both qualitative and quantitative
sources. The research objectives and the research design (figure 2) were gradually determined, discovering research limitations and taking into account that:
- some statistical monetary data is proprietary (e.g. data about individual enterprises),
- time constraints force a limitation of the number of research partners, initiatives and relations as it is not feasible to intensively interact with experts from all sectors.
Senior experts originating from the following organisations have contributed to this thesis’ research sharing their knowledge, skills, insights, overview and data: Statistics Netherlands, KPN Royal, Toscani, TNO, Tolsma consulting, Statistisches Bundesamt Wiesbaden Germany, the TRANS consortium and the Dutch Research Delta.
Academic cooperation took place with staff members and graduate students of the Delft University of Technology, faculty Electrical Engineering, Mathematics and Computer Science and the faculty of Technical Policy Management, contributing to this research project in large number.
The research duration of seven years (2006 - 2012) required a spread of the literature review. When performed solely at the beginning of the project, more recent insights from novel publications would have been missed. During the initial stage, only a few sources could be traced about trans-sector innovation. Here after, in a chronological sequence the main parts of the research and the high level research design are described.
Figure 2: methodological structure / research approach Literature Review Preliminary Research Questions, Goals & Hypotheses
Analysis of functions and data Agreed
Research Proposal
Synthesis research parts Iterative Experiment
• Functions of telecommunications • Vital sectors and labour force • Dutch & German Input-Output tables Trans-sector idea generation and collection Recognition of patterns and isomorphisms Immersion in Environment & Conceptual Assignment Expert Workshops
Sector network modeling
2003 - 2006
2006 2007
Theoretical Framework
• Definitions and related models • Research domain description • Classification Systems 2008 – 2011 Reflection & Sanity check 2007 – 2011 2007 - 2010 Research Output 2013 2012 - 2013 Research re-focus 2009 2011 - 2013 2006 - 2007 Functional analysis ISIC Explanatory notes
& &
In May 2006, a stakeholder agreement formally acknowledged the research assignment*. This assignment (based on the outcome of a preceding three year orientation, an immersion in the environment of the research topic and a condensed domain study), resulted in a preliminary research proposal and hypotheses. Stated as a general rule of method, all envisaged research parts should follow the sequence; a) define, b) inventory and c) analyse. A next realisation step d)
compose innovation instantiations, was declared out of research scope for feasibility reasons.
In 2007, the agreed on research proposal initiated a high level sector related definitional study and an inventory of classification systems carried out in order to understand what a sector is. From the perspective of theoretical classification principles, classification systems were compared
qualitatively and sector related models were selected for further study.
In 2008, besides sector network visualisation efforts, an analysis was started regarding the functional inventory of sectors, taking the concept of transactions as a specific example.
In 2009, a functional analysis of the telecommunications related sector was carried out (including layering, generic/specific functions and functional model assessment). An intermediate research evaluation resulted in a re-focus of the research directions and fine tuning of the research questions and sub-questions. As the initial research parts were mainly qualitative in nature, here after stronger effort was put on balancing the quantitative and qualitative research contributions more equally (adding data analysis cases and the set-up of the corresponding analysis methods).
In 2010, the first quantitative case study concerning the Dutch Input-Output tables was carried out in cooperation with Statistics Netherlands experts. Additionally, the workshops in which these experts and complex network scientists from the Delft University of Technology have interacted, were of great importance validating the results and reviewing the research methodology.
Vital sectors and their vital infrastructures were included in the research and distinguished from non-vital sectors by means of network analysis and visualisations from their monetary flows. In parallel, shifts in the Dutch distribution of the jobs of employees were examined and the service
bundle 2020 interviews were carried out, revealing innovation trends and patterns.
In 2011, the construction of the sector model and sector network model took place (which included comparison and assessment of the related models). A reflection on the 2010 research outcome at the Erasmus University resulted in a second quantitative case study allowing for the comparison of the Dutch and German economic networks from their 1987-2007 monetary Input-Output table data. In 2012, remaining work was completed by analysing:
- the ISIC rev.4 explanatory notes regarding the unique functions of sectors,
- quantitative shifts in the size of the Dutch labour force, enterprises and non-profit organisations, - the link density of the German and Dutch sector network at four different overlays derived from the 1987-2007 monetary Input-Output table data.
Early 2013, a set of network properties was derived from the 1995-2009 time series in [WIOD,2012]**.
Finally a synthesis of the conclusions, of which some intuitive, connected all units of research.
(*) A beneficial side effect of a PhD project duration of seven years (instead of the more common four years), is the possibility to involve a substantial number of students contributing to parts of the research. The size and relevance of the outcome of the Trans-sector Innovation idea generation experiment (involving 114 master students) has been positively influenced by the above-average duration. In parallel, this time spread enabled the cooperation with seven master students in internships and MSc graduation projects related to this thesis.
(**) The time series of 40 countries captured in the World Input Output Database were published in the course of 2012.
1.7 Structure
This section describes the structure of this thesis. Figure 3 summarises which chapters and sections answer this thesis’ RQs and SQs. It is worth noting that the closing of the larger sections also gives its specific and more elaborate conclusions while the conclusions taken from the smaller sections are given in the final conclusive section of each chapter.
Chapter 2 describes the theoretical environment of this thesis. It discusses the backgrounds of large systems analysis, holon theory, economic activity classification systems, Input-Output analysis and accounts for the selection of the central nomenclature. Definitions of the related vocabulary are collected in the Appendix (from various viewpoints). Regarding the selected sector related models, their added value, application area, purpose, structure and similarities are compared and discussed. Section 2.5 contains this thesis’ three hypotheses.
Chapter 3 covers RQ1 and its SQs 1a, 1c, 1d and 1e, focussing on the analysis of individual sectors, economic activity classification systems and their history (mainly 1930 – 2008). Besides comparing the main (dis)similarities of these systems, the functions per sector were identified from the
explanatory notes of ISIC revision 4 (see section 3.4). Concerning the functions of the telecommunications related sector, chapter 7 gives additional results.
Chapter 4 covers RQ2, SQ2a and SQ2b, focussing on the analysis of the sector network. This chapter contains the design and results of the two quantitative analysis case studies. Furthermore, sector network visualisations from various viewpoints are presented and trends observed in the Dutch labour force are included. A complex network exercise is provided that builds on the results of a program carried out by the Dutch Ministry of the Interior and Kingdom Relations addressing the vital sectors and vital infrastructures.
Chapter 5 presents the construction of the sector model (SQ1f) and subsequently the sector network model (SQ2c). Furthermore chapter 5 summarises this thesis’ contribution to theory.
Chapter 6 focuses on trans-sector isomorphisms answering SQ3a and the generic part of RQ3 and SQ3b. This chapter exemplifies the main results and the patterns that were observed during a Trans-sector Innovation idea generation experiment and the service bundle 2020 interviews.
Chapter 7 covers the telecommunications specific part of RQ1 (SQ1b) and RQ3 (SQ3b) and
focuses on the unique value offered by the telecommunications related sector. Section 7.2 gives the results of the analysis of the telecommunications related functions, answering SQ1b.
In section 7.3 the dependencies and hierarchy of current telecommunications platforms are
examined and visualised. Section 7.4 discusses the trans-sector paradox applicable to contemporary telecommunications and completes the answer toSQ3b.
Chapter 8 discusses the research results and joins the main conclusions from the chapters 2-7. Section 8.1 summarises the answers to the research questions and sub-questions. Section 8.2 assesses whether this thesis’ three hypotheses hold. Finally, recommendations for future work are suggested in section 8.3.
Figure 3: overview which chapters and sections answer the research questions and sub-questions
Table 1 shows which chapters and sections contain the content of this thesis’ most relevant publications. The Appendix Publications lists all publications (journal papers, conference papers, conference presentations/visualisations/animations, poster sessions and the master theses) that contributed to this thesis.
Table 1: how the main publications relate to the chapters and sections RQ1 What defines a sector and which ones can be distinguished?
SQ 1a Which functions characterise a sector?
SQ 1b Which specific and generic telecommunications related functions can be found? SQ 1c Which relevant sector related data is available?
SQ 1d Which economic activity classification systems exist? SQ 1e How did the sectors evolve?
SQ 1f Can we derive a generic sector model and what does it look like? RQ2 What is a sector network and how did it evolve? SQ 2a Does the sector network constitute a complex network?
SQ 2b What are the main observations, properties and characteristics derived from sector network related data?
SQ 2c Can we derive a generic sector network model and what does it look like?
RQ3 Which promising trans-sector innovation examples can be identified? SQ 3a Which main isomorphisms can we detect among the sectors?
SQ 3b Can we profit and find value when we transfer sector specific knowledge, capabilities, insights and experience among the sectors?
And more specifically;
What does such a transfer mean for the telecommunications related sector?
Chapter Section 3 4 5 6 5 7 6 6 3 3 3 4 4 3 7 7.23.4 3.2 3.2, 3.3 3.3 5.2 5.2 4.1 - 4.6 4.4 7.4 6.1, 6.2 6.1, 6.4
Publications Chapter . Section
Unravelling 21st Century Riddles – 1.1, 5.1, 5.2, 6.1, 7.1
Universal Network Visions from a Human Perspective
Animation Smart Living 1.1, 3.1, 6.3, 6.4, 7.4
Virtual Mobility enabling Multi dimensional life 1.1, 6.4, 7.1, 7.4
Renaissance of the Incumbents, Network Visions 1.1, 3.1, 3.4, 5.1, 6.4, 7.4 from a Human Perspective
Multi-weighted Monetary Transaction Network 4.2, 4.3, 4.4, 5.1, 5.2
Trusted Transactions Transforming your Life 3.2, 3.3, 3.4, 5.1, 5.2, 7.1, 7.2
Towards Systematic Development of 6.2, 6.3, 6.4, 7.4
Trans-sector Digital Innovation
Chapter 2
Theoretical framework
This chapter aims to provide the theoretical background of this thesis (in section 2.1 and 2.2) and contributes to connecting the terms function, network, sector and system. Together these four terms constitute the central nomenclature of this thesis. The notion of a holarchy is introduced in section 2.4 capturing hierarchical and recursive aspects of networks and Economic Activity Classification Systems. This thesis’ three initial hypotheses (H1-H3) are given in section 2.5 and from the research output section 8.2 discusses whether these hypotheses hold.
Economic Activity Classification Systems, Input-Output tables, graph theory and related models are considered to be the tooling of this thesis’ work. From the literature, this chapter discusses examples of related models, their aims and compares their structure (in section 2.3).
2.1 Theoretical Environment
Philosophers, active in the scientific field of ontology, have tried to define which types of objects exist in reality [Barnes,p40,1982] by means of human language and mathematics [Bunge,1979],[Gleick,p28-50,2011].
In a stepwise sense, James Gleick captures the levels of ontological and definitial complexity by means of the road of abstraction paved by literacy: from things to words, from words to categories, from categories to metaphor and logic [Gleick,p39,2011].A word gives a name to an object. By means of
commonly accepted names anything can be identified, pointed at, defined, distinguished, classified and included in day-to-day speech.
Aristotle enriched the ontological theory adopting Plato’s systematic and axiomatic approach though disagreeing with Plato’s principal view [Eidos (meaning forms)] on how conceptual and real objects
relate. While introducing various new classification systems of objects [Categoriae], Aristotle
discriminated real from conceptual substances. In order to solve this discriminative problem, he proposed to follow the demarcations provided by the classification of the disciplines of science. He classified the objects or substances studied in natural science as real and objects that are for
example studied in mathematics as conceptual. Aristotle considered natural science to comprise botany, zoology, psychology, meteorology, chemistry and physics. As a result, all animals, plants and man-made artefacts were classified as real. According to Aristotle, luminaries like the sun, the moon etcetera are real as well. Two characteristicsare always applicable to any real object; over time it can change and/or (be) move(d) [Aristotle,Physica],[Barnes,p44,1982]. Conceptual objects on the other
hand, do not always have these two characteristics. An example of such a conceptual object is a numeral that is not subject to change.
In complex network theory the adjectives real or real-world are commonly used in order to address various types of networks. In this field of research it is widely accepted that the adjective real means that a studied network exists in physical reality. Although viable synonyms for real can be
concrete or material [Bunge,1979], for sake of simplicity and compliance with complex networks
terminology, the attributes real versus conceptual are distinguished in this thesis.
This section discusses this thesis central nomenclature* regarding its different meanings, main relations, definitions and etymology. [Webster,1993] proved to be a relevant source because it dates the
earliest recorded use in English language and traces back the appearance of a word to the earliest language in which it is attested. Concerning nomenclature originating from ancient Greek and Latin, more detailed backgrounds were taken from [Liddell&Scott,1968] and [Lewis&Short,1980] respectively.
(*) In addition to this thesis’ central nomenclature (function, network, sector and system), the Appendix Definitions provides a repository of meanings, definitions and references regarding the entire nomenclature of this thesis.
function (1533) from Latin “functio” meaning performance or execution [Lewis&Short,p792,1980]:
1) professional or official position (occupation)
2) the action for which a person or thing is specially fitted or used, or for which a thing exists 3) any of a group of related actions contributing to a larger action
The primary meaning of the Greek noun “ergon” [Liddell & Scott,p683 IV.1,1968] is work or deed
(something that is done). In a text originating from the 5th century BC, Thucydides uses the noun
“ergon” in the meaning of a function (being the first recorded use in a naval context).
network (1560) [Webster,p780,1993]:
1) a fabric or structure of chords or wires that cross at regular intervals and are knotted or secured at the crossings
2) a system of lines or channels resembling a network 3a) an interconnected or interrelated chain, group, or system
3b) a system of computers, terminals, and databases connected by communications lines From these meanings the first clearly associates to matrices.
sector (1570) from Latinmeaning one who cuts or cuts off, a cutter [Lewis&Short,p1654,1980]:
1a) a geometric figure bounded by two radii and the included arc of a circle 1c) an area or portion resembling a sector
1d) a social, economic or political sub-division of society (greater cooperation between the public and private sectors)
system (1603) from Greek “systema” meaningtotal, crowdorunion [Liddell&Scott,p1735,1968]:
1) a regularly interacting or interdependent group of items forming a unified whole 2) an organized set of doctrines, ideas, or principles
3a) an organized or established procedure
3b) a manner of classifying, symbolizing, or schematizing (a taxonomic system) 4) harmonious arrangement or pattern
From the selection of meanings mentioned above can be observed that the term(s): - function, sector and system existed more than 2000 years ago, while the term network has emerged relatively recent, regardless the various meanings these terms can have, - system was used in Greek*and can be considered the eldest of all four,
- network can be defined by means of the term system (ad 2, 3a & 3b), while a system can be presented, depicted or viewed as a network,
- system in its taxonomic meaning (ad 3b) comprises all types of classifications, - sector, system and network are used to address objects that can be real or conceptual,
- function is conceptual. A function can describe an activity/action which a person, a group or an object can perform. Further more a function can describe a state of being. Functions are often described by means of verbs and can be mapped hierarchically (ad 3),
- sector, used as a verb, relates to the process of dividing and classifying without any overlap. The term system can comprise networks and sectors due to its large conceptual reach (and history). Furthermore, a system can have one or more functions. An overview of system related literature is given in table 2 that relates systems to various application areas and fields of science. Accordingly, table 2 summarises some of the aspects that are relevant for this thesis that can be of help
explaining the theoretical background of functions, networks, sectors and systems. From ancient sources some fundamentals are selected which are still considered valid today. Contemporary theorists, philosophers and scientists from various disciplines have studied the concepts of these four terms and their relations, building on the work of their predecessors.
(*) [Sloterdijk,p183,2011]mentions that in the pre-socratic period some archaic Greek verbs have transformed into nouns. For example the verb “sophronein” meaning to be prudent changed into the noun ”sophrsynè“ meaning the virtue
of thoughtfulness. Interestingly, the noun “systema” [Liddell&Scott,p1735,1968] originates from thearchaic verb
“sunìstemi” meaning uniting or put together [Liddell&Scott,p1718,1968].
Table 2: historical sources, their application areas and relevant aspects for this thesis
The above listed sources also shed light on the difficulty to distinguish systems and networks. Networks explicitly consist of a set of interconnected nodes and links [Euler,1735]. Systems consist of
interconnected sub-systems or nodes however, a sub-set of limited sized systems can be envisaged as single nodes. Nicolas Léonard Sadi Carnot (who developed a thermodynamic concept of a system in the natural sciences) and Rudolf Clausius (who established the first two laws of
thermodynamics) studied various types of thermodynamic systems including steam machines. The term system can be used to describe a reservoir containing water/steam that can perform labour. Use of the term network to describe such a heat system seems a less obvious association. Theoretically, applying a network context to a heat system would require defining the water molecules as the nodes interlinked by van der Waals forces. In this sense, defining a weather system as a network can be considered as a comparable case. Another example of a system that is difficult to view as a network, is the convention of writing down music [Chrodegang,8th century]. Representing a music score as a
network would e.g. require defining the music notes as nodes that are linked by time sequence. As stated, a complex network can be defined as a large system of elements (nodes) and their interactions or relations (links). From this view, the set of networks can be considered to be part of the set of systems.
The term system has a long history, which can be traced back at least to Plato and Aristotle [Poetica], [De Generatione Animalium,740 A-20],[Liddell&Scott,p1735,1968]. Plato suggested that it could be possible to present
all knowledge as one single axiom based science system [Barnes,p42,1982]. Aristotle did not believe one
set of axioms could be the fundament of all knowledge because of the obvious independence of various fields of science. Each scientific domain deals with different objects, has a different
language and only shows limited overlap with neighbouring domains. Aristotle however did notice analogies among the various scientific domains. Though domain specific axioms and principles are different, similarities can be observed; the formal scientific structure is the same for each science
[Metaphysica XII 4,1070a31-3]. When considering sectors, a parallel can be proposed in line with Aristotle’s
inference about the domains of science, because sector specific objects, language and principles tend to be different as well.
As stated, during the era of Plato and Aristotle, an object view was commonly practiced in philosophy/ontology. Over time, several philosophical views were added and accepted (clearly influenced by discussions and advances in physics). For example Christiaan Huygens proposed a wave theory of light followed by Isaac Newton who proposed a corpuscular theory of light. In the late 19th century James Clerk Maxwell explained light as the propagation of electromagnetic waves [Wikipedia]. During the early 1900s, classical fundamentals in physics were revised e.g. the classical
ideas about absolute space, absolute time, absolute matter and absolute energy [Bor,2010].
Source Area Aspects relevant for this thesis
Aristotle 384-322BC Historia Animalium IV natural science, zoology classification systems and relevance of functions Categoriae phylosophy, ontology classification (of the "katègoria") of things/entities Physica natural science two characteristics of objects of natural science Metaphysica XII 4, 1070 a31-3 phylosophy, ontology analogies between different scientific domains Ethica Nicomachea phylosophy, ethics reflection on (how) "to transcend"
Euclid of Alexandria 325-265BC Elements geometry description of an n-dimensional geometrical system Chrodegang 712 - 766 Chant Messin music, liturgy system of writing down music (directive Gregory I) Leonhard Euler 1707-1783 Königsberg problem mathematics, physics graph theory, network view on scientific problems Nicolas Carnot 1796-1832 Reflections on the Motive Pow er of Fire natural science 2nd law of thermodynamics (working substance) Rudolf Clausius 1822-1888 Über die bew egende Kraft der Wärme natural science 1st & 2nd law of thermodynamics (working body) Ludwig v.Bertalanffy 1901-1972 General System Theory biology, generic unifying system definition
Arthur Koestler 1905-1983 Ghost in the machine politics, generic concept of a holon (recoined from ancient Greek) Wasily Leontief 1905-1999 Open & closed mathematical model economy, mathematics sector modeling, matrix input-output analysis Claude Shannon 1916-2001 A Mathematical Theory of Communication information theory definition and measure of information Mario Bunge 1919 - Treatise on Basic Philosophy phylosophy, mathematics mathematical & functional approach of sectors Philosopher / Scientist
In 1900, Max Planck defined energy packages. In 1905, Albert Einstein formulated the relation between energy and matter. Here after Werner Karl Heisenberg and Niels Henrik David Bohr formulated the uncertainty principle in quantum mechanics. In 1924, Louis-Victor de Broglie formulated the wave-particle duality hypothesis that all matter (not just light) has a wave-like nature as well.
Inspired by these advances in physics, new views were introduced in philosophy [Gleick,p178,2011]. For
example, adding a process view can be attributed to philosophers like William James (according to Alfred North Whitehead in Science of the Modern World). Subsequently, adding a time view can be attributed to Henri-Louis Bergson (1950s). As a result, philosophers started to recognise the temporal character of reality. Adding the view that an observation can influence an object to change, can be attributed to Whitehead. A summary from a process thinker who embraces the previous inferences could be as [Bor,2010]* puts it: “In the end, material objects are compressed energy subject to continuous change and motion” .
Systems Theory
During the 20th century, theorists/philosophers developed generalised system models captured by means of Systems Theory, originating from the General System Theory (GST) in which one of its founders Karl Ludwig von Bertalanffy defined system as “elements in standing relationship”
[Wikipedia]. System types have been classified from various perspectives, views and research
disciplines. Comparison of various system classifications shows a widely accepted discrimination between:
1. natural systems versus man-made systems (that are designed to work): - where natural systems are always physically real,
- while man-made systems can be either conceptual or real.
2. bounded systems versus unbounded systems [ITU T G80x], for example a network of pipelines is a
bounded system, while a radio bearer is an unbounded system. 3. open systems versus closed systems:
- where open systems (common cases) exchange energy, matter and information with their environment,
- while closed systems (rare cases) are considered to only exchange energy [Wikipedia].
Formulating a generic definition for closed systems proved to be difficult. As a result, some variety has been proposed, ranging from relatively closed systems to isolated systems that exchange nothing at all (the latter being a purely theoretical case).
The GST or systemics studies the principles and properties common to all (complex) systems irrespective of their particular constitution and the specific nature of their component elements and their relations[Bunge,p3,1979]. According to Bunge “the approach of the GST can be useful to address common objectives and solving problems in different fields”. Furthermore, he states that the study
of networks is part of the GST, which can be applicable to any kind of network also contributing to discover similarities between systems and to deal with their complexity. However, a disadvantage of the systemic approach is the tendency to de-emphasis specific peculiarities of the components of
a studied system. His Treatise on Basic Philosophy consists of eight volumes in nine parts. In
Ontology II, A world of systems, vol. 4, Bunge characterises his world view as systemic and states about systems:
- the universe is not a heap of things but a thing composed of interconnected things – i.e. a system, - a system, then, is a complex object, the components of which are interrelated rather than loose. - some things are not systems, assuming that there are elementary things (things without parts), - there are some concepts and structural principles that seem to hold for all systems,
- there are some modelling strategies that seem to work everywhere.
(*) Original Dutch phrasing proposed by philosopher Jan Bor: “Materiële objecten zijn uiteindelijk samengevatte
energie die in een voortdurende toestand van verandering en beweging is”.
Regarding Popper’s “world 3” he states that it mixes both conceptual and concrete objects (for instance a system consisting of theories and books). Bunge avoids these mixed systems because to his knowledge; “No theory specifies the manner whereby conceptual items could combine with
concrete ones”. For example: “Mathematical theories specify the way conceptual items combine, and ontological theories take care of the combination of concrete items. If the components are conceptual, so is the system. If the components are concrete or material, then they constitute a concrete or material system”. Thus, Bunge recognises two system kingdoms only. He concludes;
either conceptual or concrete, “a system may be said to have a definite composition (C), a definite
environment (E), and a definite structure (S)”.
From a systemist perspective, hereafter some of his definitional views [Bunge,p188-193,1979] are given.
These views interrelate human society, its members, systems, sub-systems, sectors and functions (interchanging the terms community and society):
1. Every human society is characterised by means of 10 properties. Three examples are: - some members do labour, thus transform parts of their environment (postulate 4.26 (i)), - some members manage the activities of others (from 4.26 (iii)),
- every member shares information, services or goods with some other members of the same community (from 4.26 (vii)).
2. Every human society has a number of sectors (postulate 5.2): - every member belongs to at least two sectors of it,
- no individual belongs to all sectors at the same time,
- every society can be analysed into a number of sectors and, in particular, sub-systems. 3. There is some division of labour in every society.
4. All sub-systems have at least three functions/activities in common: - consuming or transforming energy,
- producing waste products,
- communicating with other sub-systems of the community,
5. There are no systems without functions. The functions of a system define what the system does. Every function is related to a system that does the functioning, but the user of a system defines the function.
To these definitional views Bunge adds a mathematical representation and introduces mathematical symbols and definitions (terms of concepts):
σ a human society, where ∑ = {σ1, σ2, …, σm} is the set of human societies, where
human society is an example of a concrete system (definition 5.1) σ’ a social sub-system of a human society,
S(σ) set of all social sub-systems of human society σ (definition 5.4) S set of social relations: information, goods, services and management T set of transformation relations
S U T the structure of σ equal to the disjoint union of the two sets of relations S and T
(definition 5.1)
G(σ) the generic function(s) of the sub-systems of σ (these functions are common to all the social sub-systems in and they are part of the structure of each σ’).
F F-system, where F is short for the set of function(s) characterising the member sub-systems in contradistinction to others. F is a set of the disjoint union of the two sets social relations S or transformation relations T thus F ⊂ S U T
F (σ) F-sector of human society σ
FS (σ) the specific functions of the F-sector of σ. These functions are in the structure of each
sub-system σ’ but not in G(σ). FS (σ) are the specific functions of the F-sector of σ.
These functions are in the structure of each sub-system σ’ but not in G (σ).
