System Dynamics Interest Meeting Life Science Community Initiative

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System Dynamics Interest Meeting Life Science
Community Initiative

• 18 October 2007

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System Dynamics Modeling Interest MeetingAgenda

• Importance of Mental Models
• Describing Modeling To Non-Modelers
• Steps of the Modeling Process
• Causal Loop Diagramming Fundamentals
• Representative Academic Programs
• Principles for Successful Use of System Dynamics
• Validation and Model Testing

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• Importance of Mental Models

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System Dynamics Modeling Interest Meeting Where
does majority of information exist?
System Dynamics and the Lessons of 35 Years By
Jay W. Forrester
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System Dynamics Modeling Interest Meeting
Motivation Net Benefits?

• Mental Models .
• Hold critical project information
• Difficult to surface, share, challenge, and
  improve

Risk
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• Describing Modeling To Non-Modelers

Dan Goldner, Ventana Systems Inc
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Questions about simulation
What is it?

• How will it help me?
• What will it cost?
• How long will it take?
• How far can I trust it?

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Business School in America
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• Steps of the Modeling Process

Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman
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System Dynamics Modeling Interest MeetingSteps
of the Modeling Process
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System Dynamics Modeling Interest MeetingSteps
of the Modeling Process
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System Dynamics Modeling Interest MeetingSteps
of the Modeling Process
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 1. Problem Articulation (Boundary Selection)
• Theme selection What is the problem? Why is
  it a problem?
• Key variables What are the key variables and
  concepts we must consider?
• Time horizon How far in the future should we
  consider? How far back in the past lie the roots
  of the problem?
• Dynamic problem definition (reference modes)
  What is the historical behavior of the key
  concepts and variables? What might their
  behavior be in the future.

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System Dynamics Modeling Interest MeetingSteps
of the Modeling Process
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 2. Formulation of Dynamic Hypothesis
• Initial hypothesis generation What are
  current theories of the problematic behavior?
• Endogenous focus Formulate a dynamic
  hypothesis that explains the dynamics as
  endogenous consequences of the feedback
  structure.
• Mapping Develop maps of causal structure
  based on initial hypotheses, key variables,
  reference modes, and other available data, using
  tools such as
• Model boundary diagrams,
• Subsystem diagrams,
• Causal loop diagrams,
• Stock and flow maps,
• Policy structure diagrams,
• Other facilitation tools.

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System Dynamics Modeling Interest MeetingSteps
of the Modeling Process
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 3. Formulation of a Simulation Model
• Specification of structure, decision rules.
• Estimation of parameters, behavioral
  relationships, and initial conditions.
• Tests for consistency with the purpose and
  boundary.

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System Dynamics Modeling Interest MeetingSteps
of the Modeling Process
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 4. Testing
• Comparison to reference modes Does the model
  reproduce the prob-lem behavior adequately for
  your purpose?
• Robustness under extreme conditions Does the
  model behave realis-tically when stressed by
  extreme conditions?
• Sensitivity How does the model behave given
  uncertainty in parame-ters, initial conditions,
  model boundary, and aggregation?
• . . . Many other tests (see chapter 21).

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System Dynamics Modeling Interest MeetingSteps
of the Modeling Process
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 5. Policy Design and Evaluation
• Scenario specification What environmental
  conditions might arise?
• Policy design What new decision rules,
  strategies, and structures might be tried in the
  real world? How can they be represented in the
  model?
• "What if . . ." analysis What are the effects
  of the policies?
• Sensitivity analysis How robust are the
  policy recommendations under different scenarios
  and given uncertainties?
• Interactions of policies Do the policies
  interact? Are there synergies or compensatory
  responses?

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• Causal Loop Diagramming Fundamentals

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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
time
remaining
Work
Remaining

schedule
pressure
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
task
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming Fundamentals
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Causal Loop Diagramming
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• Principles for Successful Use of System Dynamics

Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman
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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 1. Develop a model to solve a particular problem,
  not to model the system.
• A model must have a clear purpose and that
  purpose must be to solve the problem of concern
  to the client. Modelers must exclude all factors
  not relevant to the problem to ensure the project
  scope is feasible and the results timely. The
  goal is to improve the performance of the system
  as defined by the client. Focus on results.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 2. Modeling should be integrated into a project
  from the beginning.
• The value of the modeling process begins early
  on, in the problem definition phase. The
  modeling process helps focus diagnosis on the
  structure of the system rather than blaming
  problems on the people making decisions in that
  structure.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 3. Be skeptical about the value of modeling and
  force the "why do we need it" discussion at the
  start of the project.
• There are many problems for which system dynamics
  is not useful. Carefully consider whether system
  dynamics is the right technique for the problem.
  Modelers should welcome difficult questions from
  the clients about how the process works and how
  it might help them with their problem. The
  earlier these issues are discussed, the better.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 4. System dynamics does not stand alone.
• Use other tools and methods as appropriate. Most
  modeling projects are part of a larger effort
  involving traditional strategic and operational
  analysis, including benchmarking, statistical
  work, market research, etc. Effective modeling
  rests on a strong base of data and understanding
  of the issues. Modeling works best as a
  complement to other tools, not as a substitute.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 5. Focus on implementation from the start of the
  project.
• Implementation must start on the first day of the
  project. Constantly ask, How will the model help
  the client make decisions? Use the model to set
  priorities and determine the sequence of policy
  implementation. Use the model to answer the
  question, How do we get there from here?
  Carefully consider the real world issues involved
  in pulling various policy levers. Quantify the
  full range of costs and benefits of policies, not
  only those already reported by existing
  accounting systems.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 6. Modeling works best as an iterative process of
  joint inquiry between client and consultant.
• Modeling is a process of discovery. The goal is
  to reach new understanding of how the problem
  arises and then use that understanding to design
  high leverage policies for improvement. Modeling
  should not be used as a tool for advocacy. Don't
  build a client's prior opinion about what should
  be done into a model. Use workshops where the
  clients can test the model themselves, in real
  time.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 7. Avoid black box modeling.
• Models built out of the sight of the client will
  never lead to change in deeply held mental models
  and therefore will not change client behavior.
  Involve the clients as early and as deeply as
  possible. Show them the model. Encourage them
  to suggest and run their own tests and to
  criticize the model. Work with them to resolve
  their criticisms to their satisfaction.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 8. Validation is a continuous process of testing
  and building confidence in the model.
• Models are not validated after they are completed
  nor by any one test such as their ability to fit
  historical data. Clients (and modelers) build
  confidence in the utility of a model gradually,
  by constantly confronting the model with data and
  expert opinion-their own and others'. Through
  this process both model and expert opinions will
  change and deepen. Seek out opportunities to
  challenge the model's ability to replicate a
  diverse range of historical experiences.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 9. Get a preliminary model working as soon as
  possible. Add detail only as necessary.
• Develop a working simulation model as soon as
  possible. Don't try to develop a comprehensive
  conceptual model prior to the development of a
  simulation model. Conceptual models are only
  hypotheses and must be tested. Formalization and
  simulation often uncover flaws in conceptual maps
  and lead to improved understanding. The results
  of simulation experiments inform conceptual
  understanding and help build confidence in the
  results. Early results provide immediate value
  to clients and justify continued investment of
  their time.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 10. A broad model boundary is more important than
  a great deal of detail.
• Models must strike a balance between a useful,
  operational representation of the structures and
  policy levers available to the clients while
  capturing the feedbacks generally unaccounted for
  in their mental models. In general, the dynamics
  of a system emerge from the interactions of the
  components in the system-capturing those
  feedbacks is more important than a lot of detail
  in representing the components themselves.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 11. Use expert modelers, not novices.
• While the software available for modeling is
  easily mastered by a high school student or CEO,
  modeling is not computer programming. You cannot
  develop a qualitative diagram and then hand it
  off to a programmer for coding into a simulation
  model. Modeling requires a disciplined approach
  and an understanding of business, skills
  developed through study and experience. Get the
  expert assistance you need. Use the project as
  an opportunity to develop the skills of others on
  the team and in the client organization.

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System Dynamics Modeling Interest
MeetingPrinciples for Successful Use of System
Dynamics
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 12. Implementation does not end with a single
  project.
• Modeling work continues to have impact long after
  the initial project is over. Models can be
  applied to similar issues in other settings.
  Modelers develop expertise they can apply to
  related problems in other pars of the
  organization. They may move into new positions
  and new organizations, taking the insights they
  gained and, sometimes, a new way of thinking,
  with them. Implementation is a long-term process
  of personal, organizational, and social change.

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• Validation and Model Testing

Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman
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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 1. Boundary Adequacy
• Purpose
• Are the important concepts for addressing the
  problem endogenous to the model?
• Does the behavior of the model change
  significantly when boundary assumptions are
  relaxed?
• Do the policy recommendations change when the
  model boundary is extended?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 2. Structure Assessment
• Purpose
• Is the model structure consistent with relevant
  descriptive knowledge of the system?
• Is the level of aggregation appropriate?
• Does the model conform to basic physical laws
  such as conversation laws?
• Do the decision rules capture the behavior of the
  actors in the system?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 3. Dimensional Consistency
• Purpose
• Is each equation dimensionally consistent without
  the use of parameters having no real world
  meaning?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 4. Parameter Assessment
• Purpose
• Are the parameter values consistent with relevant
  descriptive and numberical knowledge of the
  system?
• Do all parameters have real world counterparts?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 5. Extreme Conditions
• Purpose
• Does each equation make sense even when its
  inputs take on extreme values?
• Does the model respond plausibly when subjected
  to extreme policies, shocks, and parameters?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 6. Integration Error
• Purpose
• Are the results sensitive to the choice of time
  step or numberical integration method?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 7. Behavior Reproduction
• Purpose
• Does the model reproduce the behavior of interest
  in the system (qualitatively and quantitatively)?
• Does it endogenously generate the sysmptoms of
  difficulty motivating the study?
• Does the model generate the various modes of
  behavior observed in the real system?
• Do the frequencies and phase relationships among
  the variables match the date?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 8. Behavior Anomaly
• Purpose
• Do anomalous behaviors result when assumptions of
  the model are changed or deleted?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 9. Family Member
• Purpose
• Can the model generate the behavior observed in
  other instances of the same system?
• Tools and Procedures See text.

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System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 10. Surprise Behavior
• Purpose
• Does the model generate previously unobserved or
  unrecognized behavior?
• Does the model successfully anticipate the
  response of the system to novel conditions?
• Tools and Procedures See text.

63
System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 11. Sensitivity Analysis
• Purpose
• Numerical sensitivity Do the numberical values
  change significantly ..
• Behavioral sensistivity Do the modes of
  behavior generated by the model change
  significantly ..
• Policy sensistivity Do the policy implications
  change significantly ..
• . when assumptions about parameters, boundary,
  and aggregation are varied over the plausible
  range of uncertainty?
• Tools and Procedures See text.

64
System Dynamics Modeling Interest
MeetingValidation and Model Testing
Business Dynamics Systems Thinking and Modeling
for a Complex World, John Sterman

• 12. System Improvement
• Purpose
• Did the modeling process help change the system
  for the better?

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• Representative Academic Programs

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System Dynamics Modeling Interest MeetingThe
System Dynamics Group Bergen, Norway
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System Dynamics Modeling Interest MeetingThe
System Dynamics Group Bergen, Norway
What is System Dynamics? In a few words .The
purpose of System Dynamics is to help people make
better decisions when confronted with complex,
dynamic systems. The field provides a philosophy
and tools to model and analyze dynamic systems.
Equally important, the field provides techniques
and tools to investigate current decision making
and to help decision makers learn. The modeling
language is intuitive and it is common for all
kinds of applications be they in medicine,
economics, management etc. This makes System
Dynamics an ideal tool for interdisciplinary
work, and it makes learning more efficient
because basic system structures tend to repeat
themselves from one field of application to
another.
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System Dynamics Modeling Interest MeetingZackery
Dept. of Civil Engineering, TAM
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System Dynamics Modeling Interest MeetingTimothy
R B Taylor, Ph.D. Candidate, TAM

• Influence of Expert Domain Knowledge on Public
• Policy and Natural Systems 1
• Dissertation Proposal
• DRAFT 6/27/07
• Timothy R.B. Taylor
• Ph.D. Candidate
• Texas AM University
• Zachry Department of Civil Engineering
• Construction Engineering and Management Program
• Advisor David N. Ford

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System Dynamics Modeling Interest MeetingTimothy
R B Taylor, Ph.D. Candidate, TAM

• Abstract
• Interactions between society and natural systems
  can be beneficial or harmful to society. Society
  benefits from natural systems by being provided
  with the basic necessities of life (air, water,
  and food). However, recent events such as
  Hurricanes Rita and Katrina and the Asian Tsunami
  demonstrate the harmful impacts natural systems
  can have on society. Domain knowledge is
  developed from observation of natural and
  societal systems. Domain knowledge is contained
  within scientific knowledge and engineering
  knowledge. Scientific knowledge is gained through
  observation of natural and societal systems.
  Engineering knowledge is developed from
  scientific knowledge and is used to manipulate
  natural and societal systems. In the past two
  centuries scientific and engineering knowledge
  has produced technologies that affect the
  interaction between societal and natural systems.
  For example increased scientific knowledge of
  stratospheric ozone identified an increased
  cancer risk due to the depletion of stratospheric
  ozone caused by CFCs and other industrial
  emissions. Although scientists and engineers are
  in positions to advise on policies to address
  problems involving societal/natural system
  interactions, they are not always successful. The
  proposed research seeks to develop an improved
  understanding of the dynamic interactions between
  society, natural systems, scientific and
  engineering knowledge, and public policy. The
  proposed research will offer insight to
  scientists and engineers on effectively
  influencing public policy on these issues and
  will offer insight to policy makers on how to
  incorporate scientific and engineering knowledge
  into effective public policies.
• 1 Portions of the text have been taken from
  Integrated Natural Hazard Risk Management
  Modeling the Interactions of Nature, Science,
  Society, and Public Policy by Vedlitz,
  Lindquist, and Ford (2007). However, the
  development and description of the research
  program is the work of the author. The author can
  provide specific information.

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System Dynamics Modeling Interest MeetingThe
System Dynamics Group Bergen, Norway
Figure 4 Interaction of natural and societal
systems, public policy, scientific and
engineering knowledge, and technology
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System Dynamics Modeling Interest MeetingThe
System Dynamics Group Bergen, Norway
Figure 6 Expanded nuclear industry example
described using the dynamic hypothesis
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System Dynamics Modeling Interest MeetingThe
System Dynamics Group Bergen, Norway
Figure 8 Expanded stratospheric ozone example
described using the dynamic hypothesis
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System Dynamics Modeling Interest MeetingSchool
and Earth and Environmental Sciences
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System Dynamics Modeling Interest
MeetingRockefeller College of Public Affairs
Policy
Initiative for System Dynamics in the Public
Sector Rod MacDonald, Director The Initiative
for System Dynamics in the Public Sector develops
system dynamics computer simulation models of
specific problems identified by government
agencies and nonprofits. These models are used to
test scenarios and develop understanding about
the possible implications of different policies
and programs prior to implementation. Studies for
the Division of Disability Determinations, The
Governors Traffic Safety Committee and Home
Health Care Association of New York are among the
Initiatives recent projects as well as providing
training for Office of the State Comptroller and
Regional School Support Centers . Current
projects include an examination of scenarios
regarding the implementation of technology on the
criminal justice system for the National
Institute of Justice.
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System Dynamics Modeling Interest MeetingWater
Resources Management Program - UNLV
Dr. Krystyna A. Stave, Associate Professor The
water resources management program in the College
of Sciences is a flexible, interdisciplinary
course of study leading to a master of science
degree. It is a technically and scientifically
based program that blends the physical aspects of
the hydrologic sciences with policy and
management issues. The program, recommended for
those with undergraduate degrees in physical,
biological, natural sciences and engineering,
social sciences, management, environmental
studies, or related disciplines, encourages
multidisciplinary study and research with
participating faculty at UNLV from the colleges
of Sciences, Business, Urban Affairs,
Engineering, and Liberal Arts, the Boyd School of
Law, as well as participating faculty from the
Desert Research Institute and federal, state, or
local agencies.
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System Dynamics Modeling Interest MeetingWater
Resources Management Program - UNLV
Dr. Krystyna A. Stave, Associate Professor I
use a systems approach to study relationships
between people and the biophysical environment,
drawing on social ecology to examine the ways
that a person's biosocial context affects the way
she or he perceives and interprets environmental
conditions, defines environmental problems, and
develops ideas about how the environment should
be used and managed, and on hydrology and
ecosystem ecology to trace the effects of human
activity through the biophysical system. I teach
courses in system dynamics modeling, social
ecology, and environmental problem-solving. My
research focus is to improve stakeholder
participation in environmental decision-making.
This includes environmental education to increase
public awareness and understanding of
environmental issues and the development of
computer simulation models to support
decision-making.
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Description Elements Benefits
( necessary to progress to a Virtual World )

• Representative Elements
• A report consisting of text, Vensim software
  conceptual diagrams, graphs, etc.
• Model sectors for key stakeholders
• Information and physical flows
• Goals
• Policies
• Boundaries included and excluded
• Causality between key variables
• Interaction between key variables
• Feedback loop
• identification
• operation
• polarity
• Variable definitions and units

• Representative Benefits
• A basis to reason about
• range of potential performance
• drivers of normal and abnormal performance
• feedback loop strength and time-based dominance
• monitoring and control points
• data collection needs
• tradeoffs
• robust policies
• appropriate project design
• scope of potential virtual world
• Improved focus, scientific reasoning,
  communication, and influence within and between
  teams, executives, partners, contractors,
  lenders, etc.
• Improved knowledge retention and transfer

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Virtual World Elements Benefits
( incremental to Description elements and
benefits )

• Representative Elements
• A transparent, internally consistent, integrated,
  and verifiable Vensim software computer model
  that
• represents and simulates description
• checks units and equations
• includes a wide range of analysis tools, e.g.,
  causal tracing, feedback loop identification,
  deterministic and stochastic information, etc.
• produces time-series data
• allows comparison of historical to model behavior
• allows controlled experiments
• User interface that shields user from unnecessary
  complexity while allowing quick scenario
  configuration and analysis
• Optimization and Monte-Carlo analysis
• Stand-alone PC and BP Intranet Biz-Sims

• Representative Benefits
• A basis to validate
• range of potential performance
• drivers of normal and abnormal performance
• feedback loop strength and time-based dominance
• monitoring and control points
• data collection needs
• tradeoffs
• robust policies
• appropriate project design
• Reduced risk of implementation failure through
  use of role reversal gaming
• A means to satisfy assurance inquiries
• Useful for helping new project managers quickly
  gain years of experience

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Why is System Dynamics distinctive?

• What features make business dynamics models
  distinctive?
• how humans actually make decisions (versus how
  they say they make them)
• delays
• feedback
• non linear relationships
• validation process
• tightly coupled and integrated
• actions of others
• historical data matching
• process design and management policies

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