Jenkins, Allan, "Bringing Systems Thinking to a General Audience", 1985

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Bringing Systems Thinking To
A General Audience

Allan Jenkins
University of Nebraska-Lincoln

ABSTRACT
The long term success of System Dynamics is largely dependent upon the
dissemination of systems thinking to a considerable segment of the general
public. A strategy for exposing a non-academic, adult audience to the basic
characteristics of systems is developed, using the ADAPT Learning Cycle,
System Dynamics, and the Social Fabric Matrix.

INTRODUCTION

I know that the great tragedies of history often fascinate men with
approaching horror. Paralyzed, they cannot make up their minds to
do anything but wait. So they wait and one day Gorgon devours them.
But I should like to convince you that the spell can be broken, and
that there is only an illusion of impotence, that strength of heart,
intelligence and courage are enough to stop fate and sometimes
reverse it. One has merely to will this, not blindly, but with a
firm and reasoned will.
Albert Camus

Qur track record to date in solving complex policy problems could easily
explain the paralysis exhibited by so many decision-makers at all levels.
Aware of the policy failures of the past, constantly confronted by new
problems which invariably arise as unanticipated consequences of earlier
actions, armed with limited information and inappropriate methodologies,
decision-makers are understandably hesitant to embark upon bold new ventures.
Furthermore, the most important policy problems are inherently complex,
involving multiple stakeholders holding conflicting values, so alternatives
and outcomes are impossible to order transitively.

Under’ these circumstances, the traditional analytic approach, which decomposes
problems into separate elements which are regarded as independent entities, is
inappropriate. Complex problems require a holistic approach in deriving
policy prescriptions. Unfortunately, this is easy to say, but difficult to
accomplish.

Recent developments in the various systems methodologies now provide an
alternative to the traditional analytic approach, At the same time, a variety
of recent policy actions - the PIK program, increased funding for drug
enforcement activities, military aid for the Contras - indicates that a
systems viewpoint has not penetrated into many major policy decisions, Policy
actions are still targeted at particular symptoms rather than at modifying the
structure of the system which generated the problem.

'
From the above, it seems that a relevant task for systems scientists is the
development and refinement of methodological tools which will enable
decision-makers to routinely use systems thinking in developing policy
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prescriptions. However, decision-makers should not be seen as the only
audience for these tools and techniques. For, as Forrester noted:

(Modelers assume). . . that the world is run by policy-makers,
apparently referring to people in government. For the great issues
now being considered in world modeling, the present people in
government are of little consequence. They do not have the power to
reverse long-standing tradition. They will not be in office long
enough to deal with the issues raised by world modeling. . . the
audience for the work must be the public in general. In today's
social structures, only in the role of the individual as a private
citizen does a person take a long-range view of the future,
(Forrester, 1981, pp. 22-3).

The scientist must be an educator, distilling the general principles of system
thinking into a manageable package, whose salient points can be readily
transmitted to a non-academic audience. The time constraints facing this
audience, as well as the level of intellectual investment required to use a
systems approach have to be considered. System dynamics can be an important
tool in this educational process, and at the same time can also benefit from
the use of other techniques which expose a wider audience to the benefits of
adopting a systems perspective.

This paper will briefly outline some basic notions about effective education
for adults, discuss the contributions which system dynamics can make to the
immediate education of this audience, and will introduce the Social Fabric
Matrix as a complimentary vehicle for bringing systems thinking to a general
audience,

ANDRAGOGY - THE EDUCATION OF ADULTS

The institutionalized process of education in the Western world is based upon
the monastic schools of the Middle Ages. The teaching monks transmitted the
reading and writing skills necessary to use and transcribe the sacred books,
as well as molding the personal development of the novices so they would
become obedient, effective servants of the church. From this monk-novice
arrangement, the tradition of pedagogy - literally, the art of teaching
children - spread to the secular schools of Europe, and hence to the Americas.

Recently, educators have begun to realize that the assumptions which hold for
the teaching of children may not be applicable to the teaching of adults.
Thus, andragogy - the art of teaching adults - is receiving increasing
attention. The literature does not suggest that there is any fundamental
difference in the way that children and adults “learn” - or internalize new
information. (Ingalls, 1973). Instead, the focus is upon the differences which
emerge in the learning process as an individual matures.

The foremost proponent of a separate approach for andragogy, Malcom Knowles,
has identified four basic concepts which illuminate the differences between
teaching children and teaching adults.

First, a person necessarily goes through changes in self-concept as he
matures, moving from the total dependency of an infant to the increasing
self-directedness of an adult. Traditional teaching, in which the teacher
makes the decisions about material, pace, class structure, and testing
procedures violates the autonomy of an adult. When adults discover that they
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are being treated like children, they allow the teacher to take responsibility
for their learning, and as passive participants, learn relatively little.

Second, an adult has accumulated a variety of experiences which represent an
important learning resource. The adult is thus able to relate new information
to previous experiences, seeing the value of the new information to his own
particular situation. The use of lectures, set presentations, and rigid
assignments ignores the value of these experiences. Discussion, laboratory
work, simulation, field experience and other action-learning techniques are
more appropriate in adult learning.

Third, the adult's readiness to learn is not a product of his biological
development or academic pressure. Instead, it is a function of the tasks
required in the performance of his role as a worker, manager, parent, group
leader - whatever his various roles might be.

Fourth, for the adult, the orientation to learning is problem-centered, and
his time. perspective is immediate. The adult wants to learn something which
is helpful in solving a problem which has been encountered. He wants to apply
the new knowledge immediately. (Knowles, 1973, pp. 45-90).

Recognizing these characteristics of adult learners, what type of teaching
strategy should be employed in bringing the basic concepts of systems thinking
to a non-academic adult audience? A standard class-room lecture is clearly
inappropriate. So is a typical consultant's presentation, even with its sharp
graphics and polished delivery. In both of these situations, the audience is
passive.

A manageable active-learning strategy for general audiences can be constructed
using three complimentary notions: the Learning Cycle, the Social Fabric
Matrix, and System Dynamics. In the following sections, these ideas will be
explained, and will be integrated into an active learning strategy.

THE ADAPT LEARNING CYCLE

At the University of Nebraska-Lincoln, a special program has been devised to
assist freshmen in their cognitive development. The ADAPT project is a
multidisciplinary program aimed at improving students ability to perceive
patterns, then to conceptualize from these recognized patterns. To accomplish
this task, faculty members have devised a basic strategy known as the ADAPT
Learning Cycle, a Piagetian-based educational approach. The program is based
upon the Piagetian notion that the development of cognition and thought is an
evolutionary process. For each individual, this process moves from the

- ability to use symbols to represent events, to the ability to classify diverse
objects, to the ability to conceptualize beyond directly representable
realities. (Piaget, 1970, pp. 30-3).

An ADAPT Learning Cycle is composed of three phases - Exploration, Invention,
and Application.

In the Exploration phase, participants are asked to recall, and share past
concrete experiences. The instructor supplies encouragement, asks open-ended
questions, and suggests alternatives. For example, to underscore the
importance of the systems approach, the instructor could ask the group for
examples of policy actions which created unanticipated consequences -
anti-poverty programs which have created a permanent poverty class, short-term
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business actions which hurt long-run firm viability, the introduction of new
technology which has created whole new sets of problems. (Would puritanical
Henry Ford have introduced the Model A if he had known how automobiles would
affect teenagers' sex habits?)

The real world experiences offered by the group become the basis for
generalizing about the foundational concepts of systems thinking. This
process of generalization is the Invention phase of the ADAPT Learning Cycle.
Giving hints, and asking questions, the instructor guides the group in the
identification of the general characteristics of the systems which had been
discussed. From previous work done through system dynamics modeling, a number
of significant system characteristics have been identified. While it is
unlikely that any group would arrive at these same generalizations on their
own, the instructor can guide the discussion to the following general
statements about systems, as identified by Forrester:

1.  Counterintuitive behavior - intuition and judgment may work in
understanding simple systems, where cause and effect are closely
related, but intuitive solutions to problems of complex systems are
wrong most of the time.

2.  Insensitivity to changes in system parameters - large changes in
the constants in a system have little influence because of
compensating system behavior.

3. Resistance to policy changes - stems from the first two
characteristics.

4, Influential pressure points occurring in unexpected places = the
system is sensitive to changes in some parameters, but their
location is not immediately evident. Hence, policy changes may
result in pressures unexpectedly radiating throughout the system
from obscure points.

5. . Corrective programs counteracted by the system's behavior -
internal system dynamics can overwhelm a policy which does not
modify the structure of the system.

6. Reactions to policy changes are different in the long-run than
in the short-run - short-term solutions are apt to lead to long-run
deterioration.

7. Drift to low performance - counterintuitive behavior and
short-term expediency lead to detrimental policy actions. If a
short-run solution has some positive effect, more of the same is
applied, which is detrimental in the long run.

(From DeGreene, 1973, pp. 65-6).

After completing the Exploration and Invention stages, the group has an
introductory understanding of some of the problems presented by the complexity
of a typical system. The Application phase allows the group to apply this new
knowledge in addressing some problem from a systems perspective. If the group
has sufficient time and resources, a system dynamics modeling simulation could
be undertaken. However, for the general audiences which are the focus of this
paper, it is unlikely that the participants would invest the time and energy
required for such a project.

Given these constraints, system dynamics may not be a particularly effective
tool in the introduction of applied systems thinking for a general audience.

For, while system dynamics is a useful tool in understanding complexity, it is
also characteristically complex. Even for a simple system, the flow chart and
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DYNAMO equations will overpower the uninitiated. It would be difficult to
pursue the active-learning strategy which is appropriate for adults without a
substantial commitment of time and energy.

Weil's actual experiences in the practical application of system dynamics
modeling for various clients is illustrative here. In the first project
undertaken, there was little client involvement. Few of the policy
recommendations were implemented. Ten years later, client involvement was
stressed, with more satisfying results (Weil, 1980, pp. 271-90).

Unfortunately, the level of commitment in time and money required for the
intensive client involvement drastically reduces the number of those who are
able to participate in the process. Therefore, in’ introducing systems
thinking to the widest possible audience methods other than system dynamics
may be more appropriate. One possible alternative would be the construction
of a Social Fabric Matrix, which is explained in the following section.

THE SOCIAL FABRIC MATRIX

The Social Fabric Matrix, first introduced by Greg Hayden, is drawn from the
institutionalist paradigm in economics. (Hayden, 1982, pp. 637-662). The
institutionalists are an amorphous group of non-orthodox economists who draw
upon the works of Veblen, Commons, and Dewey for their world-view, While it
is dangerous to generalize about any diverse group, typically the
institutionalists are characterized as being analytically pragmatic, focusing
upon the evolutionary nature of the economy rather than upon traditional
equilibrium analysis. The economy is seen as a social institution, constantly
changing as new technologies, defined in the broadest sense of all skills,
knowledge, and tools, continually alter relationships and offer new
possibilities.

As part of their effort to broaden the scope of economic science,
institutionalists have argued that it is necessary to view the economy with a
holistic perspective. Borrowing the term "holism" from Jan Christian Smuts,
whose book on the subject was published in 1926, the institutionalists built a
world-view which emphasized the dynamic interrelatedness of both biological
and physical systems.

The idea of holism was so central that Allan Gruchy argued that the entire
school would best be described as "Holistic Economics" since that term "called
attention to what is most characteristic in the new economics: Its interest
in studying the economic system as an evolving, unified whole or synthesis, in
the light of which the system's parts take on their full meaning.” (Gruchy,
1948, p.vii). While Gruchy's suggested appellation did not supplant
"Institutionalism" as the generic term for the entire school, the importance
of holism to the school has not diminished over time. Thus, in a recent
article, Petr includes the holistic approach as one of the ten fundamental
institutionalist ideas. (Petr, 1984, pp.1-17).

The adoption of holism as a fundamental concept brought a considerable set of
problems to the early Institutionalists however, since they had no
methodological tools which were adequate to deal with the complexity inherent
in such an approach. Thus, institutionalists have shown considerable interest
in the various systems methodologies which are now being developed.

The Social Fabric Matrix is an attempt to integrate a relatively simple system
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technique - an impact matrix - with the foundational notions of the
institutionalist paradigm. According to this paradigm, situations arise out
of the complex interactions of social institutions, technology, and the
environment. Underlying these interactions are a relatively stable set of
basic cultural values, supported by a multitude of norms. Continuing change
and conflict, not movement toward an equilibrium, are the anticipated outcomes
at all times.

The problem facing the institutionalist researcher was the same problem facing
those who are uninitiated in systems education - how to deal with the
complexity of the situation being considered.. The matrix allows the system
to be broken into a manageable level of complexity, without losing sight of
the inter-connectedness of the various components. An example, using the
matrix to explore Nebraska's energy system will prove illuminating.

The basic institutionalist notions, arrayed in a matrix, appear as Figure 1.

Figure 1 - Foundational Relationships

Receiving
Components

Delivering
Components

Institutions
Technology

Institutions
Technology
Environment

Values

Environment

Values

The identification of more specific components depend upon the situation of
interest to the group. What institutions are important to this issue? What
technological conditions? Which environmental factors are important? What
values are relevant? An adult group, through its real-world experience, can
decide these questions without having any specialized systems knowledge.
Different groups may choose different components, just as different system
modelers may choose different variables. One example of a matrix for the
Nebraska energy system is shown in Figure 2.

The process of specification could continue if necessary. For example,
consumers could be separated into residential, commercial, industrial,
transportation, agricultural, governmental, and electric utility sectors.
Water could be fresh, saline, flowing, falling, underground, polluted, or
impounded. As an active-learning event, the group will decide upon the
appropriate level of specificity.

There may well be controversy about the inclusion, or exclusion, of particular
elements. The instructor should encourage such situations, for the discussion
which follows will clarify the role of each element in the matrix.

Controversy can also be related to the problems of complexity, which can
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Figure 2 - Second Level Relationships”

Receiving Institutions | Technology | Environment
Components
2
elel 2 2
plaid] g|2] 3
4 3
si} a] a] 8/3 | # Slglé
si 812! g/é | lalalg
Delivering 8)s} a} 4/8 | ssiaicje
|__Components,
Goverments 1{2] 3 4 5.
2 | Consumers 6} T{ 8 9 10
4 | suppliers 1} 12] 13 1h 15
| Bxieting
$
& | peeaispiag 16 | 17| 18 19 20
Climate
2
@ | Heter
§ | tana ai |22 | 23 2h 25
= | Flora
& Treune
Notes:

* Values components omitted due to space considerations

1 - Different levelsof government deliver problens, legal
controls, and incentives to other levels of goverment.

2 - Governments deliver income, legal controls, and incentives.

3 - Governments deliver payments, legal controls, and incentives.

4 - Governments deliver controls on the development and use of

- Governments protect, or fail to protect, the environment.

~ Consumers deliver complaints, legitimacy, and challenges.

~ Consumers have consumption patterns which affect other

consumers.

- Consumers deliver payments and service needs.

~ Consumers deliver a demand pattern for different technologies.

- Consumers require environmental resources.

- Suppliers deliver complaints, legitimacy, and court challenges.

- Suppliers deliver energy and other services.

- Suppliers deliver energy, payments, and competition to other

suppliers.

~ Suppliers deliver a demand for different technologies.

~ Suppliers deliver demand for environmental resources.

- Technology delivers problems to governments.

1T - Technology delivers efficiency relationships, and unexpected
problems.

18 - Technology delivers efficiency relationships, and unexpected
problems.

19 ~ Technology delivers the basis for new technologies.

20 ~ Téchnology delivers pollution.

21 ~ Enviroment delivers complex problems to the government.

22 - Environment delivers resources, influence on demand, and finite
limits.

23 - Environment delivers resources, influences production patterns,
and finite limits.

2h - Environment delivers conditions which affect the efficiency,
applicability, and life of technology.

25 - Environment is intertwined, with ecological relationships

among all of its components.

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reinforce the systems generalizations that were identified in the Invention
phase.

As Figure 2 indicates, the focus is upon the "deliveries" which are made from
one component to another in the matrix. These deliveries indicate impacts or
influence, which may or may not represent causal relationships. For example,
a specific piece of government regulation may cause utilities to act in a
prescribed manner. On the other hand, the fact that utilities deliver energy
to consumers does not "cause" consumers to consume this energy. The matrix is
concerned with cumulative causation, the interaction of many components which
ultimately generate an action.

The information in the boxes may take any form that is applicable to the
problem being discussed, there is no need to convert every box to a common
denominator. One box may contain "hard" information on the total dollar flows
from consumers to suppliers, the next may contain a qualitative statement
about public perception of regulatory effectiveness, the next may contain
energy efficiency information on new consumer appliances, the next on rates of
cancer near atomic energy facilities. The degree of detail depends upon the
knowledge of the group, the level of information needed, and the commitment to
perform the required research.

As an introductory tool, this flexibility is valuable to the matrix. For
example, it may be desirable to simply use the matrix as a visual aid in
showing system complexity. The group could use its knowledge to identify the
components. For those relationships where a delivery is made, a 1 could be
placed in the appropriate cell. If there is no direct delivery, a 0 would be
entered. The resulting pattern of 1's and O's would give a visual image of
system complexity to the group, without requiring a major commitment of time
or money. This recognition of complexity could then guide the group in
obtaining the information which is most pertinent to the issue.

The Social Fabric Matrix appears to be a useful tool in bringing systems
thinking to a general audience. It requires no specialized systems knowledge,
and is flexible enough to adapt to group needs without requiring an extensive
commitment. Importantly, it incorporates an active-learning strategy which
allows the group to utilize real-world experiences. Because the technique
does not require specialized skills in modeling, it can be used immediately by
the group members.

Using the matrix in approaching problems from a systems perspective does have
a noticeable limitation - there is no mechanism for tracing changes in the
system over time. Through the matrix, one can see that changes in technology,
for example, will have impacts on several different cells. However, there is
no way to discover the magnitude of those changes, how pervasive they will be
throughout the system, or how long-lasting those changes will be. Therefore,
the matrix alone is not sufficient to give a dynamic view of system behavior.

This weakness in the matrix is of course the great strength of system
dynamics. One could argue that the two ideas are quite complementary. The
matrix is a good, active methodological tool capable of introducing
non-specialist audiences to the necessity of approaching problems with a
systems viewpoint. It provides a method of analysis utilizing a system
perspective without requiring specialized modeling skills. It is easy to use,
and since it doesn't require computer time, is very inexpensive.
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A side-by-side comparison of the two methods in Figure 3 shows their
complementary nature, for the weakness of one is the strength of the other.

Figure 3
SOCIAL FABRIC MATRIX SYSTEM DYNAMICS
STRENGTHS WEAKNESSES
1. EASILY UNDERSTOOD BY USERS COMPLICATED, REQUIRES COMMITMENT
2, IMMEDIATE USER PARTICIPATION REQUIRES TRAINING, WHICH IS NOT
ALWAYS AVAILABLE
3. FLEXIBLE, AMENABLE TO A SUCCESSFUL APPLICATIONS REQUIRE
VARIETY OF COMMITMENTS CONSIDERABLE COMMITMENT
4, VISUALLY CONCISE VISUALLY, CAN CONFUSE A GENERAL
AUDIENCE
5. REQUIRES NO PRIOR SYSTEMS BASED UPON CAUSAL LOOP RELATION-
KNOWLEDGE SHIPS WHICH ARE UNFAMILAR TO THE
AUDIENCE
WEAKNESSES STRENGTHS
1, STATIC APPROACH DYNAMIC APPROACH
2. NO WAY TO TRACE IMPACT SIMULATION OF VARIOUS SCENARIOS
OF POLICY PROPOSALS
3. NOT DIRECTLY TRANSFERABLE DYNAMO LANGUAGE
TO COMPUTER OPERATIONS
4. AMBIGUOUS LANGUAGE POSSIBLE REQUIRES SPECIFIC MODELING
IN DESCRIPTION OF COMPONENTS STATEMENTS
5. VISUALLY IMPRESSIVE

In those cases where the group chooses to go beyond the matrix, a system
dynamics model could be constructed. While the variables in this model would
not match the components identified in the matrix, the modelers would still
benefit from its construction. First, active participation in developing the
matrix would give many members of the organization an introductory lesson in
systems thinking, thus performing a valuable "consciousness-raising" activity.
Also, some of the information contained in the matrix could be incorporated
into the dynamic model. For example, the matrix might contain information on
the efficiency ratings of old and new appliances. The modeler could
incorporate this information into his work very easily. Construction of the
matrix should give clients a sense of the complexity facing the modeler,
which, through increased understanding, should make them more responsive to
the modeler's requests for information. From this short discussion, the
potential value of the matrix as an educational tool in building systems
thinking is apparent.

CONCLUSION

The transition to a "systems age" seems well under way, but progress is not
evenly distributed. Refinements in methodology, and application of the new
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methods to specific problems has understandably drawn the lion's share of
attention from systems scientists. While system dynamics has made tremendous
strides in describing system characteristics, there are warning clouds on the
horizon.

All too often, when the modeler leaves, the system thinking leaves as well.
Or, as Senge says: "The benefits of even highly successful applications often
prove only temporary, as policymakers drift back into old ways of thinking and
operating." Even more chilling is his later statement: "Although one or two
managers close to the consulting team may develop a new way of looking at a
specific problem, such a shift rarely extends to other problems, and I know of
no case where it has occurred pervasively within an organization." (Senge,
1984, p. 88).

One could argue that the practitioners of system dynamics may have overlooked
the importance of the long-term development of systems thinking by focusing on
the short-term expediency of “answering the client's questions." By now, we
know what happens to a system when short-term expediency takes precedence over
long-term needs.

It is unreasonable to expect the general public to become systems experts, yet
it is also impossible to see how system dynamics can have any real impact
until the systems perspective is widely adopted. System scientists need to
use effective educational tools like the Social Fabric Matrix to increase
public awareness, thus aiding that long-term shift toward systems thinking
that is so important to our future.

The ultimate end . . . is not knowledge, but action. To be half
right on time may be more important than to obtain the whole truth
too late.

Aristotle
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REFERENCES

Bayraktar, B.A, H. Muller-Merbach, J.E. Roberts and M.G. Simpson, eds.
Education in Systems Science , London: Taylor and Francis, Ltd, 1979.

DeGreene, Kenyon B. Sociotechnical Systems , Englewood Cliffs, N.J. :
Prentice-Hall, 1973.

Dunn, William N. Public Policy Analysis , Englewood Cliffs, N.J. :
Prentice-Hall, 1981.

Forrester, Jay W. "National Modeling in the Global Context," System Dynamics
Group Working Paper D-3325, 1981.

Gruchy, Allan G. Modern Economic Thought , New York: Prentice-Hall, 1948.

Hayden, F. Gregory, "The Social Fabric Matrix," Journal of Economic Issues ,
Volume 16, Number 3, September, 1982, pp. 637-662.

Ingalls, John D. A Trainers Guide to Andragogy , Washington: U.S,
Department of Health, Education, and Welfare, 1973.

Knowles, Malcom S. The Adult Learner: A Neglected Species , Houston: Gulf
Publishing, 1973.

Knowles, Malcom S. Informal Adult Education , New York: Associated Press,
1950.

Paulre, Bernard E. ed. System Dynamics and the Analysis of Change ,

Amsterdam: North-Holland Publishing Company, 1981.

Petr, Jerry, "Fundamentals of an Institutionalist Perspective on Economic
Policy," Journal of Economic Issues , Volume 18, Number 2, March, 1984, pp.
1-17.

Piaget, Jean, Science of Education and the Psychology of the Child , New
York: Viking Press, 1970.

Randers, Jorgen, ed. Elements of the System Dynamics Method , Cambridge, MA:
The MIT Press, 1980.

Senge, Peter M. "System Dynamics as an Artifact for the Systems Age,"
Dynamica , Volume 10, Part II Winter, 1984, pp. 84-89.

Smuts, Jan Christian, Holism and Evolution , New York: The MacMillan
Company, 1926.

Wolstenholme, E.F. "System Dynamics: A System Methodology or a System
Modeling Technique," Dynamica , Volume 9, Part II Winter, 1983, pp. 84-90.
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Sharing the presentation with Allan Jenkins:

F. Gregory Hayden

Professor of Economics

University of Nebraska-Lincoln
College of Business Administration
CBA 343

Lincoln, Nebraska 68588-0489