Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 1/37 Chapter 3: System Dynamics Department of Social Informatics.

Slides:



Advertisements
Similar presentations
Chapter 1 Introduction to Modeling DECISION MODELING WITH MICROSOFT EXCEL Copyright 2001 Prentice Hall.
Advertisements

Process Design (Specification)
Towards an integrated South African Green Economy Model (SAGEM)
DECISION SUPPORT SYSTEM ARCHITECTURE: THE MODEL COMPONENT.
Flow Charts, Loop Structures
System Dynamics Modeling with STELLA software. Learning objective  After this class the students should be able to: Understand basic concepts of system.
Gautam Sanka. Analyze and Elucidate the behavior of complex systems Complex Systems Collection of interconnected elements (system) Behavior and Characteristics.
System Dynamics 1. What is System Dynamics  Computer simulation modeling for studying and managing complex feedback systems, such as business and other.
Do you know what it takes to manage global change wisely?
* Finally, along the lines of predicting system behavior, researchers may want to know what conditions will lead to an optimal outcome of some property.
University of Southern California Center for Systems and Software Engineering ©USC-CSSE1 3/18/08 (Systems and) Software Process Dynamics Ray Madachy USC.
Introduction to Modeling
Chapter 1 Software Development. Copyright © 2005 Pearson Addison-Wesley. All rights reserved. 1-2 Chapter Objectives Discuss the goals of software development.
© 2012 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license.
Dynamic Models Lecture 13. Dynamic Models: Introduction Dynamic models can describe how variables change over time or explain variation by appealing to.
Simple Linear Regression. Introduction In Chapters 17 to 19, we examine the relationship between interval variables via a mathematical equation. The motivation.
V.Liberzon /Spider Management Technologies/ People who lack sufficient practical experience in Project Management meet with.
Kinney ● Raiborn Cost Accounting: Foundations and Evolutions, 9e © 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied, duplicated,
Page 1 ISMT E-120 Introduction to Microsoft Access & Relational Databases The Influence of Software and Hardware Technologies on Business Productivity.
McGraw-Hill/Irwin© 2006 The McGraw-Hill Companies, Inc. All rights reserved.
Capital Budgeting Chapter 11.
Chapter 6: The Traditional Approach to Requirements
System Analysis Overview Document functional requirements by creating models Two concepts help identify functional requirements in the traditional approach.
System Analysis & Design Introduction: System Analysis and design course intents to help students understand its importance in developing systems that.
Public Policy Modeling Causal Loop Diagrams Friday, April 21, 2017
Emergy & Complex Systems Day 1, Lecture 1…. Energy Systems Diagramming Energy Systems Diagramming A Systems language...symbols, conventions and simulation…
1 Chapter No 3 ICT IN Science,Maths,Modeling, Simulation.
Do Now: 1) What is the general relationship between the flow of water into a bathtub and the amount of water that is in the tub? 2) If the person filling.
Computers Are Your Future Eleventh Edition Chapter 13: Systems Analysis & Design Copyright © 2011 Pearson Education, Inc. Publishing as Prentice Hall1.
Introduction System Dynamics Un instrument for System Thinking.
Term 2, 2011 Week 1. CONTENTS Types and purposes of graphic representations Spreadsheet software – Producing graphs from numerical data Mathematical functions.
Cost Behavior Analysis
-- BUSINESS PROPRIETARY --© 2007 viaSim 1 Archived File The file below has been archived for historical reference purposes only. The content and links.
Crosscutting Concepts Next Generation Science Standards.
3DCS Advanced Analyzer/Optimizer Module © Dimensional Control Systems Inc DCS Advanced Analyzer/Optimizer Equation Based Tolerance Analysis Quick.
Lecture 2 BSC 417/517. Today’s class Course website Schedule & topics for rest of semester Software tools and introductions Basic system components and.
Introduction to Science Informatics Lecture 1. What Is Science? a dependence on external verification; an expectation of reproducible results; a focus.
Operations Management using System Dynamics Part I.
CHAPTER 10: CORE MECHANICS Definitions and Mechanisms.
5 - 1 Copyright © 2006, The McGraw-Hill Companies, Inc. All rights reserved.
Comparing Political Systems. Why Compare? “Without comparisons to make, the mind does not know how to proceed.” Tocqueville “Man is by nature a social.
Risk and Capital Budgeting 13 Chapter Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin.
Cost-Volume-Profit Relationships Chapter 6 McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved.
Chapter McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Risk and Capital Budgeting 13.
1 Rockefeller College of Public Affairs and Policy University at Albany Tools for Systems Thinking and Modeling Dynamics: Graphs over time Structure:Causal-loop.
Bathtub Water Level Model
Basic building blocks of SD Levels (Stocks), Rates (Flows), Auxiliary variables and Arrows Essential building blocks Represent the way dynamic systems.
© 2014 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license.
An Introduction to Using Systems Thinking and STELLA in the Classroom
System Dynamics 3 CAP4800/5805 Systems Simulation.
6 Systems Analysis and Design in a Changing World, Fourth Edition.
Chapter 7 Part II Structuring System Process Requirements MIS 215 System Analysis and Design.
Asset accounting-29.pptx This course will give an overview of the following Workbreakdown Structure Network Project Builder Project Planning.
McGraw-Hill/Irwin Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 5 Modeling the Processes and Logic.
Value network analysis for complex service systems: Author : Juite Wang Jung-Yu Lai Li-Chun Hsiao Professor : Soe-Tsyr Daphne Yuan Presenter : Po-Wei Chiang.
Chapter 1: The Nature of Analytical Chemistry
Introduction to Modeling Technology Enhanced Inquiry Based Science Education.
SECURE TROPOS Michalis Pavlidis 8 May Seminar Agenda  Secure Tropos  History and Foundation  Tropos  Basics  Secure Tropos  Concepts / Modelling.
Software Architecture
Systems Thinking – Modeling a System
Chapter 6 System and Application Software
Software Engineering System Modeling Chapter 5 (Part 1) Dr.Doaa Sami
Introduction to Modeling Lab: Causal Loop & Stock and Flow Models
Chapter 6 System and Application Software
Chapter 6 System and Application Software
Scientific forecasting
Chapter 6 System and Application Software
Cost-Volume-Profit Relationships
Introduction to Decision Sciences
Software Architecture
Presentation transcript:

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 1/37 Chapter 3: System Dynamics Department of Social Informatics Graduate School of Informatics Kyoto University Kazuyuki Moriya Introduction to Field Informatics

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 2/37 What’s System Dynamics?  One of the numerical simulation techniques  Developed in the late 1950s by J.W.Forrester of the Massachusetts Institute of Technology  Applied the methodology for system analysis used in engineering to dynamically analyze systems in the field of business administration and social science.  An effective tool for simulating and analyzing complex systems in which various factors are interrelated

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 3/37 Simulation techniques  Deterministic Simulation A given input always leads to the same output under the mathematical model  Monte Carlo Method Using random numbers and probability to simulate problems.  Multi-agent simulation Simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 4/37 How to Apply SD to Environmental issue  Build a social model, in which some factors related to ecosystem and human activities are included, focusing on the flows of indicator substances (such as carbon dioxide that is considered as one of the causative factors of global warming).  By executing models, you can grasp the relationship among factors and the flows of indicator substances not only through numerical results but also by visualizing results with graphs.  SD can be used as a tool of decision making and policy examination, because it is easy to compare the results of various scenarios with SD models. ※ SD:System Dinamics

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 5/37 Application software  STELLA(isee systems inc) STELLA supports a very intuitive graphical user interface so that beginners can easily use to learn about SD. (paid)  Vensim Software free for educational use, has equivalent functions to STELLA. Available from the website at

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 6/37 Elements of model components  Stock A container where something is stored.  Flow A valve which controls the inflow to or the outflow from a stock.  Converter Used for defining the auxiliary variables and constants.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 7/37 Symbols: Stock, Flow and Converter Flow Stock Converter The flow of information among elements can be described by connecting stocks and flows to one another with connectors. ※ An Arrow( → ) stands for a connector.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 8/37 Saving model based on compound interest.  Stock : Deposit Account  Flow : Interest Income  Converter : Interest rate Deposit AccountInterest Income Interest Rate Year Deposit Account(Yen) 010, , , , , , Red Arrow: Connector Initial Value: 10,000 yen Interest rate: 5%

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 9/37 Equations in SD  Equation about Stock(Deposit Account) DA(t) = DA(t-dt) + II*dt  After one year DA(1) = DA(1-1) + II*1 = DA(0) + II II = Stock before update * IR = DA(0)*0.05 = 10,000*0.05 = 500 DA(1) = 10,000 + 500 = 10,500  Two years later, calculating in the same way II = 10,500*0.05 = 525 DA(2) = DA(1) + II = 10, = 11,025 DA: Deposit Account, II: Interest Income, IR: Interest Rate

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 10/37 Positive Feedback Loop (1)  The increase in the value of stock(DA) will cause the value of inflow(II) to rise. As a result, the value of stock(DA) in turn increases. Such a relationship is called positive feedback loop. Deposit Account(DA)Interest Income(II) Interest Rate(IR) DA ↑→ II ↑→ DA ↑→ II ↑ ・・・・

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 11/37 Positive Feedback Loop(2)  Trends of changing(increasing or decreasing) are the same directions between elements  There are cascading positive feedback loops among more than two elements. Salary raise Motivation increase Improved performance ++ +

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 12/37 Bathtub model  Converter “ Desired Level ” : 100liters  Stock “Bathtub” : initial value =0 liter  Converter “Water Level Difference” = Desired Level - Bathtub  Flow “Faucet” = Water Level Difference*0.4 BathtubFaucet Water Level Difference Desired Level In this model, the difference between Desired Level and the water volume in Bathtub is calculated.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 13/37 Executed result of Bathtub model

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 14/37 Negative Feedback Loop  Trends of changing(increasing or decreasing) are the opposite directions between elements  According to increasing the value of bathtub, “Water Level Difference” is decreased. As a result, flow rate of “Faucet” is gradually decreased.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 15/37 Causal Loop Diagram  Diagramming the interrelationships between elements in SD model  This diagram indicates whether system as a whole has a positive(or negative) feedback loop or not  Assign “+”, if the relationship between two elements is positive. Assign “-”, if that is negative.  Total count of “-” is odd number ⇒ negative feedback loop as a whole  Total count of “-” is even number ⇒ positive feedback loop as a whole

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 16/37 Example of Causal Loop Diagram (1) ー Positive Feedback Loop as a whole ー  Increase of “Motivation” results from “Salary” raising ( + )  Performance is improved by increasing of “Motivation” ( + )  Improving of “Performance” results in raising of “Salary”( + ) In this case “+” is three and “-” is zero. The total count of “-” is zero(even number). This diagram indicates there are positive feedback loop as a whole Salary Motivation Performance ++ +

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 17/37 Example of Causal Loop Diagram (2) ー Negative Feedback Loop as a whole ー  An increase of “Membership” results in decreasing of “Not Member”( - )  A decrease of “Not Member” results in decreasing of “New Member”( +: Response is the same direction)  An increase of “Membership” is more activity in membership recruitment. As a result, “New Member” increases(+)  Total count of “-” is one(odd number), so this diagram indicates negative feedback loop as a whole. New Member Membership Not Member + + + -

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 18/37 Example of Causal Loop Diagram (1) ー Positive Feedback Loop as a whole ー  Total count of “-” is two(even number). ⇒ This diagram indicates negative feedback loop as a whole Outstanding Subject New Subject Stress Work Efficiency Work Volume + + + - -

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 19/37 A local development model making efficient use of a rich natural environment An example of SD

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 20/37 Scenario  Assume that agriculture and tourism are the main local industries in the target region A making efficient use of its rich natural environment.  Tourists visiting the region A are looking forward to the various activities available in this rich natural environment. So, tourism significantly contributes to the local development of the region A.  Resort development is carried out to promote the vitality of the local economy in this region by attracting tourists.  However, overdevelopment results in environmental destruction, and the greater the number of visiting tourists, the more strain the natural environment has to sustain.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 21/37 Subjects based on scenario  Consider the relationship among “Rich Natural Environment”, “Tourist Attractiveness” and “Region Vitality” using SD.  Include “Sightseeing Load”, which represents the increase in the environmental load by increase in visiting tourists, and “Resort Development” for attracting tourists in the model.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 22/37 Assumptions of SD Model  The increase of “Region Vitality” stimulates the efforts of preservation of the natural environment.  The increase in “Tourist Attractiveness” results in the increase in “Region Vitality” results.  The increase in “Rich Natural Environment” result in the increase in “Tourist Attractiveness”.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 23/37 Causal Loop diagram Rich Natural Environmental Sightseeing Load Resort Development Region Vitality Tourist Attractiveness + + + + + --

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 24/37 Region Vitality Resort Development Increase Attractiveness Decrease Attractiveness Decrease Vitality Tourist Attractiveness Increase Vitality Sightseeing Load Rich Natural Environment Decrease Richness Increase Richiness

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 25/37 Values given to SD model(1)  “Rich Natural Environment”, “Tourist Attractiveness” and “Region Vitality” are abstract concepts, we assign 50 units as the initial values for these stocks.  unit is a fictitious unit system.  If one of the factors reaches over 50 units, it is considered to be in a desirable state, and in an undesirable state up to that point.  The magnitude of this fictitious unit system has a mathematical meaning.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 26/37 Values given to SD model(2)  “Increase Richness” is defined as depending on the state of “Region Vitality”.  If “Region Vitality” is more than 50 units, people are more interested in the preservation of the natural environment and it contributes 10 units to the increase of “Rich Natural Environment”, while it is less than 50 units, people cannot make efforts for the preservation of the natural environment.  “Decrease Richness” is determined by two convertors, “Sightseeing Load” and “Resort Development”.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 27/37 Values given to SD model(3)  “Increase Attractiveness” and “Decrease Attractiveness” depend on “Rich Natural Environment”.  “Rich Natural Environment” directly affects “Tourist Attractiveness”. If the state of “Rich Natural Environment” is more than 50 units, the value of “Increase Attractiveness” will be 10 units, while it is less than 50 units, “Decrease Attraction” will be 15 units.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 28/37 Values given to SD model(4)  “Increase Vitality” and the outflow from it “Decease Vitality” are assumed to depend on the state of “Tourist Attractiveness”.  If the state of “Tourist Attractiveness” is more than 50 units, “Increase Vitality” will be 15 units, while it is less than 50 units, “Decrease Vitality” will be 15 units.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 29/37 Values given to SD model(5)  “Resort Development” is defined as 1 unit if both “Tourist Attractiveness” and “Region Vitality” are more than 50 units  The motivation to develop resorts is enhanced not only when many tourists are visiting the region, but also when the vitality in the region is enough.  “Sightseeing Load” is defined as 1 unit if “Tourist Attractiveness” is more than 50 units.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 30/ year unit

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 31/37 Comparison among scenarios using SD  Examine what kind of consideration is possible using SD if you are asked to decide the best balance between the efforts of preservation of the natural environment and the resort development.  Assume that we will make some efforts for preserving the natural environment to maintain and improve Rich Natural Environment.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 32/37 Region Vitality Sightseeing Load Resort Development Increase Attractiveness Decrease Attractiveness Increase Vitality Decrease Vitality Preservation Coefficient Sightseeing Benefit Development Coefficient Tourist Attractiven ess Preservation Effort Increase Richness Decrease Richness Rich Natural Environment

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 33/37 Four Scenarios  Scenario 1: No efforts of environment preservation (Preservation Coefficient = 0 units) but with resort development (Development Coefficient = 5 units).  Scenario 2: Preservation Coefficient is set to 5 units but no resort development (Development Coefficient = 0 units).  Scenario 3: Both Preservation Coefficient and Development Coefficient are set to 5 units.  Scenario 4: Preservation Coefficient is set to 15 units and Development Coefficient is set to 5 units.

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 34/37 Result(Scenario 1) Preservation Coeff.=0units 、 Development Coeff.=5units

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 35/37 Result(Scenario 2) Preservation Coeff.=5units 、 Development Coeff.=0units

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 36/37 Result(Scenario 3) Preservation Coeff.=5units 、 Development Coeff.=5units

Copyright (C) 2010 Field Informatics Research Group. Kyoto University. All Rights Reserved. 37/37 Result(Scenario 4) Preservation Coeff.=15units 、 Development Coeff.=5units