Handling Complex Societal Problems
Book of Abstracts, Volume 10
EUROSIM 2001 Congress
SHAPING FUTURE WITH SIMULATION
4th International EUROSIM
in cooperation with
Euro Working Group Complex Societal Problems
Dutch NOSMO Research Group on Simulation
26-29 June 2001
Delft University of Technology
Delft The Netherlands
coordination special track Dorien J. DeTombe
Corresponding address
Dr. Dorien J. DeTombe, Ph.D.
Chair Operational Research Euro Working Group Complex Societal Problems
P.O. Box. 3286, 1001 AB Amsterdam, The Netherlands, Europe
Tel: +31 20 6927526
E-Mail: DeTombe@lri.jur.uva.nl
http://www.geocities.com/doriendetombe
ISBN 90-5638-081-8
Handling Complex Societal Problems
EUROSIM 2001
Complex Societal Problems
More and more the world realizes that complex societal problems are very hard to handle, and the development of these kind of problems are difficult to predict. It becomes clear that these kinds of problems can no longer be handled by one government, by one actor or by one discipline alone. Handling these problems needs a worldwide cooperative approach including many actors and experts. It needs a multi actor- and a multi-disciplinary approach.
Examples of complex societal problems are the effects of climate change, that results in floods, avalanches and biological changes, the world wide industrial waste disposals, large healthcare threads due to malaria and AIDS, and the vulnerability of the society on computers, internet and stock exchange.
Methodology for complex societal problems focuses on methods and tools for handling these problems. It uses existing methods and tools and develops specialized methods and tools. In handling complex societal problems many methods and tools can be used, as data analyzing tools such as SPSS, knowledge acquisition tools such as interview techniques and decision support tools such as MCDA, GDSS and simulation. The main question in the field of methodology for handling complex societal problems is which method and tool can be used best to support the problem handling process, given the problems, the problem handlers, the moment in the problem handling process, and the money and time available.
The International Society on Methodology for Complex Societal Problems, with its Operational Research groups as the Euro Working Group 21 and several national groups, is a multidisciplinary group of scientists, who develop this field together. The field of Methodology for Complex Societal Problems organizes each year several special sessions on conferences.
This special session of the field of Methodology for Complex Societal Problems focuses on the use of simulation in handling complex societal problems.
Dr. Dorien DeTombe, Chair Operational Research Euro Working Group 21 on Methodology for Complex Societal Problems, The Netherlands, gives an introduction to the special session in ‘Using Simulation Models to Handle Complex Societal Problems’ on the use of simulation models to analyze the problem, to realize the feedback loops, and to try out several possible interventions (what–if situations). The simulation model makes it easier to discuss causes and effect of interventions and makes the decision-making process more transparent.
Dr. Cor van Dijkum, University of Utrecht, The Netherlands, focuses in ‘The validity of simulation to understand complex phenomena‘ on theoretical issues of confusion and divergence in definitions of simulation methods, methodologies and scientific worldviews in which different paradigms are used. This can be a challenge to develop new insights as well as a source of worry if there is a progression at all. In different periods of time different methods for simulation are in fashion. This makes it difficult to answers questions about validity In referring to the way the science of simulation can function in a interdisciplinary framework to understand and handle complexity the lecture tries to give some elementary answers to questions like ‘Is it possible to falsify those models? How can one compare the outcome of simulation models with data? What are adequate criteria of validation?’.
Dr. Iva Smit and Wim Smit of E&E Consultants, The Netherlands, discuss in their lecture about ‘Decision Support Systems in organizational Processes: What kind of Intelligence do we Need to Manage Knowledge’, that in problem handling rational (left brain) and irrational/ emotional (right brain) activities are needed. For problem handling all kind of knowledge is needed, among them tacit knowledge. Although Artificial Intelligence can not substitute human intelligence, it can in some cases complement the intelligence and can support the human effort by using expert systems (left brain support) as well as right brain support in data.
Prof. dr. Wu Yuying & Prof. dr. Yan Feng, Beijing Polytechnic University, China, discuss in their lecture titled ’The Sustainable Development of Enterprises in China’, a new approach of measuring the economic balance, including in the input-output analysis not only the material but also the use of labor, natural resources and waste, which should all be measure in energy.
Ir. Wim Smit, Jaap Hiddema and Dr. Iva Smit, of E&E Consultants, The Netherlands, and Falkirk, Scotland demonstrate in an article ‘The New Economy: A Study on Some Emerging Characteristics’ that the New Economy is governed by the same laws and relations as the traditional economy, and in both economies simulation can play a role.
Dr. Cathal Brugha, University College Dublin, Dublin, Ireland, focuses in A decision science model of thinking process for diagnosing mild distortions in one’s relationship with self, others and the world on models for decision in complexity.
Dr. Dorien DeTombe, Chair Operational Research Euro Working Group 21 on Methodology for Complex Societal Problems, The Netherlands, discuses in ‘Validation of the simulation models of complex societal problems for policy use’ on the too limited definition of validation in the field of methodology. This limited definition excludes the pre-research questions of validation.
Prof. dr. Makarenko, National Technical University of Ukraine, focuses in ‘Simulation Sciences in Shaping the Future. Challengers, Tools, Prospects and Dangers’, on the many hierarchical levels and related interconnections that makes it impossible to create a complete model of the world. However new approaches have been made in this area by the author to simulate the whole society on the different hierarchical levels, including global problems and the mental changes of the individual. In his lecture the author reviews also some existing simulation and modeling methods.
Dr. Werner Brucks, University of Zurich, Swiss, discusses in ‘The Psychological Integration of Resource Use Factors by Simulation: PIRUSIM’ the use of the simulation software PIRUSIM. This social scientific simulation is a framework model founded upon a theoretical idea that explains the individual's use of resources on the basis of established scientific findings. The core idea of the simulation model is social-ecological relevance, which means that for actors, social as well as ecological factors are relevant when they make decisions about using a resource. The simulation is micro analytic aggregative: the relevant processes are modeled at the level of the individual and then aggregate at the macro level of society as collective patterns of behavior.
Tutorial on ‘Handling Complex Societal Problems’ Dr. Dorien J. DeTombe
The tutorial consist of two parts:
Theory: In the theoretical part the main idea of the theory for handling complex societal problems will be explained with an introduction to the method Compram (Complex Problem Handling Method; DeTombe, 1994; DeTombe, 2001).
Practice: In the practical part we will explore in a hands-on workshop what this means concerning a real everyday life complex societal problem. We will start making a (simulation) model of the problem of an actual, not yet ‘solved’ complex societal problem.
See for more information about Methodology for Complex Societal Problems
Presentations
Presentation 1
Using Simulation Models to Handle Complex Societal Problems, an Introduction
Dr. Dorien J. DeTombe, Ph.D.
Chair Operational Research Euro Working Group Complex Societal Problems
P.O. Box. 3286, 1001 AB Amsterdam, The Netherlands, Europe
Tel: +31 20 6927526
E-Mail: DeTombe@lri.jur.uva.nl
http://www.geocities.com/doriendetombe
The societal problems the world is been confronted with will grow larger and more complex. The situations these problems provoke will be very hard to handle, due the complexity caused by the many phenomena and people involved. The development of the situations these problems provoke will be hard to predict. The many feedback loops can create unexpected and even chaotic situations. Examples of complex societal problems are the effects of climate change, that results in floods, avalanches and biological changes, the world wide industrial waste disposals, large healthcare threads due to malaria and AIDS, and the vulnerability of the society on computers, internet and stock exchange. Handling complex societal problems needs an integral multi-disciplinary approach, including experts of different fields and all the actors, such as governmental actors, organizational actors and Non-governmental (NGO’s) actors. Each actor has its own interest, own knowledge, own goals, power and emotions. The method Compram (DeTombe, 1994, 2000) is a framework that guides this handling process step by step. In several rounds experts and actors discuss their view on the problem and try to come to an agreement for interventions. This process will be carefully guided by a facilitator, who uses a seven-layer tool to support the communication process among the participants of the problem handling process (the experts and actors). In the seven-layer model the situation the problem provokes is expressed in different languages. Simulation is one of the languages to express the problem. The simulation model enable the participants in the problem handling process to analyze the problem, to realize the feedback loops, to see the development of the situation in time and to try out several possible interventions (what–if situations).
The simulation model makes it easier to discuss the causes, and effects of the interventions, and to analyze the complexity. In a complex societal problem in which causes and effects and the development in time can be indicated, a simulation tool can deepen the insights of the problem handlers in the problem and makes the decision making process for policy making more transparent.
Presentation 2
The Validity of Simulation to Understand Complex Phenomena
Dr. Cor van Dijkum, Department of Methodology & Statistics, Utrecht University, The Netherlands
E-mail: c.vandijkum@fss.uu.nl
Computer simulation seems to be a well-established scientific tool to generate knowledge about complex phenomena in our world. The sophistication of hard- and software made this success of computer simulation possible, and gave rise to valuable knowledge with which one can handle a variety of complex problems. Nevertheless, looking more closely to this knowledge, one also sees confusion and divergence in definitions of simulation methods, methodologies and scientific worldviews. As is the case in other fields of science different paradigms are used and what seems at first sight a coherent body of knowledge, appear to be at second sight "worlds apart" (Dijkum & Akkermans 1990). From the viewpoint of the history of science such a situation can be a breeding bed of a variety of research which at last can be combined in a fruitful scientific enterprise. The focus on linear differential equations for example created a wonderful starting point for mathematical research into non-linear differential equations. The neglect of possible stochastic component of differential equations and the focus on deterministic differential equations made it possible to develop a body of knowledge with which statisticians can at last start fascinating simulation studies into the world of stochastic phenomena.
Nevertheless, one can also worry about the fragmentation of knowledge and the slowness in the growth of the body of knowledge. One can wonder whether there is a progression at all and believe with some researchers of simulation (Sterman & Wittenberg 1999) that there is an arbitrary rise and fall of paradigms in which no true rationality is to be found. For believers in scientific rationality (Popper 1934, Lakatos 1970, Dijkum 1991) this belief undermines the credibility of simulation studies. Whenever such a worry was only theoretical one should not worry at all, but looking more closely to the practice of simulation studies one could get the idea that 'anything goes'. In different periods of time different methods for simulation are in fashion: system dynamics, object-oriented, distributed object oriented, agent based, fuzzy logic, soft system, multicriteria, petri net, a.s.o. .
Thereby very different programming languages and software are used with exotic names such as dynamo, simula, saps, xtpml, mascot, james, versim, moose, compose, prosit, mimose, acl. (see for example: Bargiela & Kerckhoffs 1998). There seem as many methods, methodologies and programming languages, as there are practices of simulation. Moreover when one question the validity of simulation models the answers are quite unsatisfactory. How can one for example judge the validity of climate models except then to refer to consensus between so-called experts? Is it possible to falsify those models? How can one compare the outcome of simulation models with data? What are adequate criteria of validation? How are quantitative and qualitative comparison balanced? How can one use advanced statistics to grasp uncertainty? It is quite clear that those questions are hard to answer in the practice and theory of simulation (Dijkum, DeTombe & Kuijk 1999).
In this paper it is tried to give some methodological answers to those elementary questions. That is done by: (1) updating the rationality idea of Popper and Lakatos into the framework of constructive realism (Dijkum, Zeeuw & Glanville 1998); (2) from within this framework the (re) definition of (for simulation) important concepts such as validation, system, dynamic system, social system, model, recursion, causal recursion, bonded graph, levels of aggregation, linear model, non-linear model, complex, stochastic (Dijkum 2000a); (3) illustrated by two examples of simulation of social systems (Kuijk, Mens-Verhulst, Dijkum & Lam 1998; Dijkum 2000b); (4) referring to the way the science of simulation can function in a interdisciplinary framework to understand and handle complexity (DeTombe 1994; Dijkum 2000c).
Presentation 3
Decision Support Systems in Organizational Processes: Which Kinds of Intelligence Do We Need to Manage Knowledge?
Dr. Iva Smit & Ir. Wim Smit E&E Consultants, Inc., Netterden, The NetherlandsE-mail: smitnet@wxs.nl
Dealing with the increasingly complex, tumultuous, and competitive environments in which organizations operate places high demands on human decision makers and on the machines that support them. Recent research shows that traditional models based on rational, analytical thinking do not sufficiently support decision making in such ill-defined, elusive situations, and that various kinds of intelligence are needed to effectively manage organizational processes. Rational intelligence, emotional intelligence, and artificial intelligence, as well as their synergy will be discussed in relation to the design and application of decision support and knowledge management systems.
Presentation 4
The Sustainable Development of Enterprises in China
Prof. Dr. Wu Yuying & Prof. dr. Yan Feng System Analysis Institute, Beijing Polytechnic University, Beijing, China,1 00022 E-mail: hlbao@solaris.bjpu.edu.cn wyyywm@263.net
The input-output analysis of economic balance in real estate or value form only considers the input and output of the material product section. The sustainable development considers the ecological system including population, economics, natural resources and environment.
The input-output analysis of sustainable development has to take them into consideration such as labor input, natural resource input, wastage brought along with the product output and the impact of wastage on the environment. The input-output tables in real estate or value form could not be applied directly in the analysis of sustainable development due to the complexity of the ecological system. The ecological system including population, economics, natural resources and environment should be measured in energy, therefore, the energy-type input-output table is the extension of that in the real estate or value form. The inputs of input-output table in energy form consist of not only the material product input, but also the human resource input and the natural resource input; its outputs consist of not only the material output, but also the wastage output and the impact of wastage on the environment. The energy-type input-output model, including population, economics, natural resources and environment, is given in the paper. The model is applied in the analysis of sustainable development of enterprises in China.
Presentation 5
The New Economy: A Study on some Emerging Characteristics
Ir. Wim Smit1, Jaap Hiddinga2, Dr. Iva Smit1 1E&E Consultants, Inc., Netterden, The Netherlands
2
Falkirk, Scotland, United KingdomThis paper attempts to summarize the prevailing characteristics of the New Economy, based on the abundant literature available on the subject. A comparison will be made between the traditional and the New Economy. Several of the emerging economic characteristics and the transitions that are currently taking place will be discussed in a wider historical and societal perspective.
Further, an approach for a simulation of the emerging trends will be presented and demonstrated on a simple (sub)model of an economic system, together with three business redesign processes, in which the model was applied. Finally, issues related to the validation, verification, and credibility of models simulating future events will be considered, and directions for potential future work will be indicated.
Presentation 6
A Decision Science Model of Thinking Process for Diagnosing Mild Distortions in One’s Relationship with Self, Others and the World
Dr. Cathal Brugha, President, The Management Science Society of Ireland
Department of Management Information Systems, Dublin Graduate School of Business,
Blackrock, County, University College Dublin, Belfield, Dublin 4, Ireland.
General Editor, International Transactions in Operational Research,
http://www.blackwellpublishers.co.uk/asp/journal.asp?ref=0969-6016&src=edt
http://mis.ucd.ie/staff/cbrugha/ Tel.+353-1-716-8132 (& Voicemail) Fax.+353-1-716-1120 Tel. +353-1-716-8854 (Editorial Assistant - Una Giltsoff) Email: Cathal.brugha@ucd.ie
Keywords: Decision Science, Behavioural Science, Experimental Psychology, Complex Societal Problems
Nomology is the science of the processes of the mind. Traditionally it has been used in philosophy and sociology. Recently it has been combined with decision science to synthesize at a meta-level well-known Oriental concepts such as Yin / Yang, and the I Ching, and Occidental (western) concepts described by Maslow and Jung, relating to personality, methodology selection, and the Systems Development Life Cycle in Information Systems.
Nomology shows that the main decision-making dimensions are Adjusting, Convincing and Committing. Adjusting is objective and balance-based and has two, four and eight aspects. Convincing and committing are subjective and relate more to processes and levels. Each has three aspects.
Nomology has been used to show the difference between Oriental and Occidental approaches to decision making. It is used to diagnose personality types; the system is similar to the Enneagram and Myers-Briggs typologies.
It has been used for decisions by groups to form nomological maps that describe where the group is at any time in its thinking in terms of the combinations of processes and levels. It is particularly amenable to structuring and framing decisions and to synthesizing data from qualitative research.
As a generic meta-framework it is used to evaluate new qualitative structures and insights into human behavior in a variety of different fields.
Although it is a descriptive system it can offer normative suggestions of what would be expected as the next step in a process or the remedy to an imbalance in behavior.
This presentation will emphasize ways of using the model to visualize thought processes, particularly those that emphasize relationships between the self, others and the world. Such visualizations are very helpful for getting an overview of where one stands with respect to a decision. This can apply across a variety of decisions from the micro with regard to one's personal choices to societal and intercultural change.
It is an integrated comprehensive model that can be used to predict how individuals, companies and cultures tend to behave based on their differences in personality and where they are in completing processes. Consequently, it provides the framework for building a simulation model for personal and group behavior that could be used to predict what decision-makers might do or should do in specific circumstances.
It locates well-known psychological issues such as depression and trust within the system. It focuses on mild imbalances and distortions and so is not focused on psychiatry; however it offers a base to research and understand abnormal behavior by comparing actual with simulated normal or typically expected behavior.
See http://mis.ucd.ie/staff/cbrugha/cbpaper.html for some abstracts of relevant papers.
Presentation 7
Validation of the Simulation Models of Complex Societal Problems for Policy Use
Dr. Dorien J. DeTombe, Ph.D.
Chair Operational Research Euro Working Group Complex Societal Problems
P.O. Box. 3286, 1001 AB Amsterdam, The Netherlands, Europe
Tel: +31 20 6927526
E-Mail: DeTombe@lri.jur.uva.nl
http://www.geocities.com/doriendetombe
Carying out research to handle real life problems demands that the outcome of the research is related to reality in such a way that the conclusions drawn on the basis of the research will have value in real life. A way to check how the research relates to reality is to analyze the way the research is done, including operationalizing the concepts, the way the data is analyzed, which phenomena are included and which models are used for representing the situation. This process is called validation of the research. The usual approach is to validate the research that has been performed. The research performed on real life situations reflects a selected part of the real world. Therefore validation should not only reflect the research performed, but also those parts, phenomena and variables that are excluded by the research.
Validation of the research performed is called inside validity and validation of the part that is excluded by the research is called outside validity. Outside validity that reflects the elements that have been excluded is called pre-outside validity.
The central question here is how is the selection made, why is this part left out the research and what are the consequences for the research outcome. At the other end of the research activity, after the research is done, the outcome of the research is presented in a research report. Post-outside validity refers to the way the outcome of the research is presented in relation to the performed research. How the research is used in policy making is called post-outside validity. A discussion with some ethical aspects.
Presentation 9
Simulation Sciences in Shaping Future. Challengers, Tools, Prospects and Dangers.
Prof. Dr. Alexander Makarenko National Technical University of Ukraine (KPI), Institute Applied System Analysis Pobedy avenue 36, 03056, Kiev, Ukraine E-mail: makalex@mmsa.ntu-kpi.kiev.ua
Not all recognises existing of challengers to the mankind and society should found solutions. But who make the decisions? On first glance them are leaders, chiefs of large firms, international organisations and so on. But the situation is more involved. Recent society became very complex object in many interconnections between elements. Mankind was developed in result of long evolution from primitive tribes. Such complexity follows to the situation when the leaders make solutions not arbitrary but on the base of accepted recently by society (or their part, for example by elite) norms, laws, beliefs and individual peculiarities of leaders.
Thus recent society is complex hierarchical object. Different individuals have different mental internal structures and play different roles. Because of many interconnections and hierarchical levels the whole society is very complex object and full modelling of them is unacceptable. Also under the question is the possibility of full modelling because evident presence of chance in processes. But recently new trends and prospects were proposed. Author hopes that his models (Makarenko, 1997, 1998, 1999, 2000) allow to forwards essentially simulation as for whole society as their parts and subprocesses. However the main issues of proposed report is analysis of all related to the simulation problems and their prospects.
First of all we discussed the recent problems and subjects of modelling. We should especially remarked global problems: sustainable development, progress measure, global geoeconomics and geopolitics, information technologies, global education, nature evolution and impact of simulation on the future shaping of society.
Secondly we consider the different people inquiry to modelling in dependence on their role in society hierarchy and on the possibility of implementation.
Another aspect of this problem is considering the simulation influence on the individual in dependence of their role and personal mentality. Such problems are considered in connections with global education, information technologies and social psychology problems. The increasing role of interdisciplinary in considering complex societal problems is discussed.
In connection with goals above the author propose the review of existing modelling and simulation methods, their development prospects, their recent influence on the decision making and their role in future and some examples of applications (including Ukraine experience). Some review of existing and possible future database is discussed. Also the problems of verification and acceptance by leaders are considered. Prospects and dangers of increasing role of simulation are discussed. In particular we consider the ethical problems connected with following from modelling power larger controllability of society. Possible fields of application of concepts are displayed. Some future research problems as the subject for collaboration is posed.
Presentation 10
The Psychological Integration of Resource Use Factors by Simulation: PIRUSIM
Dr. Wernher Brucks, lic. phil. University of Zurich, Department of Psychology, Division of Social Psychology
Plattenstrasse 14, CH-8032 Zurich, Switzerland fon +041-(0)1-634 21 18, fax +041-(0)1-634 49 31
brucks@sozpsy.unizh.ch http://www.psych.unizh.ch/sozpsy/sozpsy-gutscher.html
PIRUSIM is the "Psychological Integration of Resource Use Factors by Simulation". This social scientific simulation is a framework model founded upon a theoretical idea that explains an individual's use of resources on the basis of established scientific findings. For more than thirty years, there have been efforts in a variety of disciplines to identify the factors that determine human behavior in resource conflicts. If we wish to influence resource behavior in individuals or collectives, there is not much help to be gained from knowing the effects of single factors in isolation. Even if isolating the factors is the only way to increase our knowledge of them, the findings have to be integrated in the end if we are to understand the behavior in its totality. This simulation represents a first attempt to integrate the existing, up-to-now isolated findings in this field of research on the basis of psychological mechanisms. The simulation is thus a psychological theory of resource use.
Theoretical background
The core idea of the simulation model is social-ecological relevance. The concept of social-ecological relevance means that for actors, both social and ecological factors are relevant when they make decisions about using a resource.
Social-ecological relevance forms a single dimension. This means that the more relevance that the actor attributes to social factors, the less relevance will be attributed to ecological factors, and vice versa. All possible factors influencing an actor's use of a resource can be classified as either social or ecological. The social values or group identity of an actor, for example, belong to the social factors, while resource availability and ecological uncertainty are ecological factors.
Features of PIRUSIM
The simulation is microanalytic aggregative: the relevant processes are modeled at the level of the individual and then aggregate at the macrolevel of society as collective patterns of behavior. The simulation is event-oriented: it investigates changes in the social system that result from mutual influencing.
The simulation bases upon well-established empirical findings (multiply confirmed), so that the simulation can be validated. The simulation is deterministic. Random values are used only in forming the social network.
Data gathering
A special feature of PIRUSIM is that the simulation is data-driven. Solidly established findings from the field of dilemma research were
brought together with the aid of the theoretical concept of social-ecological relevance to form an integrated model of resource use.
Modelling
The empirical findings used were translated into mathematical equations and then grouped within the framework of the theoretical concept of social-ecological relevance to build the total model. Thanks to the structure of the model,various factors can be added to or removed from the model. This modular structure of the simulation allows investigation of specific research questions in the area of resource use.
Verification / validation
The validity of PIRUSIM was tested on two levels.
Verification tests a model by examining whether the simulation can reproduce the findings that were used to build the model. PIRUSIM replicates these findings qualitatively very well. Validation tests a model to see whether the simulation also has the capacity to represent new findings
correctly. PIRUSIM was found to qualitatively model the findings of a large-group experiment from the field of dilemma research well.
Visualisation / animation
PIRUSIM is a laboratory simulation, which means that no great effort was made to present the data using visual art or animations. The data can be presented in the form of tables, of course, and they can be imported into a database for further processing.
Influence areas
Using PIRUSIM, resource conflicts can be studied in a targeted manner, and solutions to the social-ecological dilemma can be found. Forexample, PIRUSIM has been used for concrete implementation in the planning and sustainableutilization of a commonly shared solar powerfacility.
Presentation 11
The Adjustment of Industrial Composition in China
Yan Feng Wu Yuying System Analysis Institute, Beijing Polytechnic University, Beijing, China,100022, Email:hlbao@solaris.bjpu.edu.cn wyyywm@263.net
The electronic commerce is emerging in China. With the advancement of electronic commerce, the industrial composition in China is changing rapidly. The industrial composition in the past is reviewed.The industrial composition at present is evaluated.The industrial composition in the future is predicted.
Tutorial
Handling Complex Societal Problems
EUROSIM 2001
Dr. Dorien J. DeTombe, Ph.D.Chair Operational Research Euro Working Group Complex Societal Problems
P.O. Box. 3286, 1001 AB Amsterdam, The Netherlands, Europe
Tel: +31 20 6927526
E-Mail: DeTombe@lri.jur.uva.nl
http://www.geocities.com/doriendetombe
The societal problems the world is confronted with will grow larger and more complex. The situations these problems provoke will be very hard to handle, due the complexity caused by the many phenomena and people involved. The development of the situations these problems provoke will be hard to predict. The many feedback loops can create unexpected and even chaotic situations. Examples of complex societal problems are the effects of climate change, that results in floods, avalanches and biological changes, the world wide industrial waste disposals, large healthcare threads due to malaria and AIDS, and the vulnerability of the society on computers, internet and stock exchange.
Handling complex societal problems needs an integral multi-disciplinary approach, including experts of different fields and all the actors, such as governmental actors, organizational actors and Non-governmental (NGO’s) actors. Each actor has its own interest, own knowledge, own goals, power and emotions. The method Compram (DeTombe, 1994, 2000) is a framework that guides this handling process step by step. In several rounds experts and actors discuss their view on the problem and try to come to an agreement for interventions. This process will be carefully guided by a facilitator, who uses a seven-layer tool to support the communication process among the participants of the problem handling process (the experts and actors). In the seven-layer model the situation the problem provokes is expressed in different languages. Simulation is one of the languages to express the problem. The simulation model enable the participants in the problem handling process to analyze the problem, to realize the feedback loops, to see the development of the situation in time and to try out several possible interventions (what–if situations). The simulation model makes it easier to discuss the causes, and effects of the interventions, and to analyze the complexity. In a complex societal problem in which causes and effects and the development in time can be indicated, a simulation tool can deepen the insights of the problem handlers in the problem and makes the decision making process for policy making more transparent.
The Tutorial ‘Handling Complex Societal Problems’ consists of two parts: a theoretical part and a practical part.
Theory: In the theoretical part the main idea of the theory for handling complex societal problems will be explained with an introduction to the method Compram (Complex Problem Handling Method; DeTombe, 1994; 2000).
Practice: In the practical part we will explore in a hands-on workshop what this means concerning a real everyday life complex societal problem. We will start making a (simulation) model of the problem of an actual, not yet ‘solved’ complex societal problem.
Structure & Goal Research Groups on Complex Societal Problems & Issues
Books of Complex societal Problems & Issues & Abstracts Books of conference presentations
Become a member of the research groups?
Methods of Complex Societal Problems & Issues: COMPRAM
For direct policy support in handling Complex Societal Problems & Issues
Foundation Greenhill & Waterfront
General corresp. address:
Dr. Dorien J. DeTombe, President
Chair International - , Euro - , West-Euro- & Dutch Operational Research Research Group Complex Societal Problems & Issues
P.O. Box. 3286, 1001 AB Amsterdam, The Netherlands, Europe Tel: +31 20 6927526 E-Mail: DeTombe@lri.jur.uva.nl
http://www.geocities.com/doriendetombe
©Dorien J. DeTombe, All rights reserved, update November 2003