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An Environmental Laboratory for the Social Sciences
Edited By:
Peter W. House
Philip D. Patterson
U.S. Environmental Protection Agency
Washington, D.C. 20460
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Preface
The concept of a social science laboratory was
another of those "buzz" words which appear to
mean everything and at the same time nothing.
When a group of us began to advocate such an idea
for universities and colleges in late 1969; it was
immediately accepted in a fuzzy sort of way. Our
focus for the laboratory was to be a generalizable
computer based model.
Water resource planners have been accustomed
to developing and using computer models that focus
to a large extent on the water subsystem of the
entire river basin or regional system. This focus has
been so strong that the models have not been able
to deal simultaneously with a wide number of con-
cerns that are directly or indirectly related to water
resource planning, such as the effect of pollution
regulations on employment of different segments of
the labor force, employment by different segments
of the business and government community, percent
of incomes spent for various types of water uses,
externalities (market values of homes, land use
activity, assessed value of land, etc.) associated
with water quality and use, and the financing of
alternative water resource plans. In short, previous
water models have not been models of an entire
regional system with the water subsystem realistically
interacting with all the other major subsystems.
The RIVER BASIN MODEL is a water resource
model, but it is also a labor market model, a com-
mercial allocation model, a migration-housing
model, a land use and assessment model, a govern-
ment operations model, and several more. It is a
regional systems model. It deals with a full range
of factors that impact on the water subsystem and
a wide range of factors that are in turn affected by
water resource planning decisions.
The RIVER BASIN MODEL deals with groups
of people, corporations, and government depart-
ments as they interact with one another within a
spatially defined environment. It differs from other
water models in that it generates much of the data
used as inputs to water models as a result of com-
plementary processes that are a part of the regional
system. For example, a typical water model might
need inputs as to where industries are located, how
much they earn, what their tax payments are, and
how many people they employ.
In other words these are normally exogenous in-
puts to the model. The RIVER BASIN MODEL
makes these and other factors that relate to the local
water subsystem endogenously determined factors
that are either human inputs or generated by com-
puter simulations.
The RIVER BASIN MODEL recognizes that
many concerns of the water resource planner may
be handled only within the confines of a holistic
model of the regional system. To deal with the
economic, social, and governmental impacts of water
resource planning calls for a model that incorporates
and simulates the interaction of many subsystems
other than that for water. Some of these subsystems
are directly related to the water subsystem while
others are related in only an indirect way. The
RIVER BASIN MODEL is an attempt to represent
in an operational model all of these major sub-
systems, and thereby place water resource planning
within its realistic perspective.
Users of the model are given control over all
the resources of the local area being represented.
Some of the local activities withdraw water directly
from the water system and return their effluent to
that system (either treated or not). Most of the
businesses and population of the local system use
municipally supplied water which also must be with-
drawn from the local water system and treated if
necessary. The municipal treatment of sewage is
a decision that is made in light of local considera-
tions, such as cost, pollution levels, intergovern-
mental cooperation, etc.
The RIVER BASIN MODEL is oriented toward
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user requirements such as generality of representa-
tion, flexibility of change, ease of inputs, and read-
ability of output. The model provides, among other
things, great detail on the quality of the local water
system, the pollution generated by industrial,
municipal, and water sources. It also illustrates the
impact of pollution on treatment costs, health, rec-
reation activity, and social dissatisfaction.
A wide range of decisions and their consequences
may be illustrated by the model. For example, in
the economic sector the impacts of response to
water pollution regulations, fines, comprehensive
planning, and quality of the local water system may
be shown. In the social sector, the effect on leisure
time of pollution, political pressure agains polluters,
and loss of jobs because of plant closings can be
represented. The impacts of many government
decisions may be shown: comprehensive water
management programs, changing utility district
boundaries, intergovernmental cooperation and
many more.
Operating programs of the RIVER BASIN
MODEL computer package illustrate the impact
that the water system has on such phenomena as
housing selection, employment, time allocation and
the activity patterns that result, and government
budgetary activity (revenue collection and disburse-
ment). The users of the model may make a wide
range of private and public policy decisions which
affect the simulations for each of these phenomena
and more. The detailed and summary computer
output reveals the interactions of these decisions
and the collective impact they have on the environ-
mental quality of the represented area.
The RIVER BASIN MODEL, given its present
data base, does not, however, represent the work-
ings of an actual regional system with enough
accuracy to be used as a predictive device. It was
built using aggregated representations of people,
businesses, and government activities. Its primary
purpose is to give a holistic view of the workings of
a hypothetical regional system and its water sub-
system and to allow its users to interact in a dynamic
decision-making environment.
For nearly four years work was done on a com-
puter-based model which could be used both for
research and training purposes. When it was thought
that this end was accomplished Envirometrics Inc.
approached the National Science Foundation for a
research grant.
Upon approval, the grant was used to test the
concept of a general social science lab by having
several disciplines use the same model to teach their
extrant courses.
Part of this report is the result of that experiment.
The story and results are told directly by each pro-
fessor, except for more overall comments I made
myself.
In terms of the current program of the Environ-
mental Studies Division of EPA, the model and its
availability to all represents a two-edged experiment.
The first facet is related to the design and experimen-
tation of a large scale holistic model for research.
The CITY or RIVER BASIN MODEL, is some-
what unique in its size and comprehensiveness and
serves as a useful starting point for such an ex-
cercise. Secondly, there are the concomitant ques-
tions of user acceptance of these large scale models.
Part of our studies will document and analyze this
process since the model is presently in the public
domain, as is most of its documentation and is
currently being distributed through a network of 10
regional centers in the U.S. and several abroad.
The general usefulness of this lab is for each
reader to decide. Our thanks go to those professors
who tested the laboratory concept and who present
a guide for others.
IV
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Contents
PART ONE
Page
Chapter I—INTRODUCTION 1
Chapter It—BRIEF DESCRIPTION OF THE MODEL 3
The Represented Area (The Local System) 3
Activities . .. ".....". ,.. •. 5
Water Component ". 8
The RIVER BASIN MODEL as a Systemic Model 8
Chapter HI—USES AND USERS OF TWE MODEL 9
Using the Model 9
Model Features 11
Chapter IV—MODEL OUTPUT 12
Maps '....• 12
Tabular Computer Output 14
Migration 14
The Water System 17
Indicators 17
The RIVER BASIN MODEL as a Set of Regional Accounts 17
Chapter V-^MODEL INPUTS 21
Initial Director Inputs 21
Player Inputs 21
Periodic Director Inputs 24
Summary ', 24
Chapter VI—EXPLANATION OF THE WATER COMPONENT 26
Water Quality Ratings 26
Water Use ,..-.'. 26
Pollution Generation and Monitoring 26
Effects of the Water Quality Index 28
Chapter VII—THE COMPUTER PROGRAMS 31
Migration-Housing 31
Water Quality Calculations and Effects 31
Depreciation 32
Employment 32
Transportation .,...: .....' 32
School Allocation .. .• 32
Time Allocation 33
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Page
Commercial - 33
Bookkeeping '. 33
Chapter VIII—SUMMARY OF THE RIVER BASIN MODEL DESIGN 34
Design Assumptions 34
Basic Building Blocks 34
PART TWO
Chapter IX—THE RESEARCH PROJECT 39
Chapter X—DARTMOUTH:—BLUE CITY ON A GREEN LANDSCAPE—
John Sommer 41
Introduction 41
Course Descriptions 41
The Dynamics of the Model's Use 43
Introduction 43
Trend of Play 43
Economic Sector 43
Data Analysis , 46
Correlations 46
Government Sector 47
General Trends of Play 48
Conclusions 53
Chapter XI—AMERICAN:—CITY MODEL USAGE FOR COURSES IN REAL
ESTATE AND URBAN ECONOMIC DEVELOPMENT—Maury Seldin 55
Background and Development 55
Course Development 57
Course Objectives 58
Course Structure 59
Familiarization with the Model 60
Trend of Play 60
Economic Base 61
Business Cycle 61
Demographic Analysis 61
Housing Market Analysis 61
Appraisal 62
Land Use Studies 62
Interaction of Students 62
Conclusions 63
Chapter XII—GEORGETOWN:—CITY MODEL AT GEORGETOWN—
Philip Patterson 64
Introduction 64
Personal Background 64
Course Description and Class Composition 64
The Course 65
Purpose of the Course 65
Course Structure 55
The Play of the Model 66
Overview 66
General and Departmental Indicators 66
Frequency of Decisions 69
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Page
The Economic Sector 70
The Social Sector 70
The Government Sector 71
Summary 71
Conclusions 71
Recommendations 72
Suggestions 73
Chapter XIII—MANKATO STATE:—CITY MODEL USAGE IN THE URBAN
STUDIES INSTITUTE—Robert Barrett 75
Introduction 75
The Course 76
Organization of Players 77
Game Results 77
Concluding Observations 81
Chapter XIV—MEMPHIS STATE:—THE CITY MODEL EXPERIENCE—
Robert Dean 83
Introduction 83
The Course 84
Dynamics of Play 84
Conclusions , 86
Chapter XV—CONCLUSION 90
Objectives of the Study 91
Findings and Recommendations 91
APPENDIX
Appendix A—RIVER BASIN MANUALS SCENARIOS 93
Appendix B—RIVER BASIN MANUALS AVAILABILITY 102
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PART I
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CHAPTER I
Introduction
Today, social science education is in the midst
of a severe cultural lag. Its students, responding to
the needs of our society, are interested in becoming
active participants in the solutions of our social ills.
They appear to prefer this activist role to the more
traditional one of the passive scientist who studies
the system from afar. Unfortunately, although our
educational institutions will at least begin to prepare
students for the latter, they usually do not possess
techniques for preparing them for constructive par-
ticipation hi day to day affairs.
Possibly a partial explanation of this failing can
be found hi the evolved structure of the educational
institutions themselves. Unfortunately, there is little
for the historian and anthropologist to use to re-
create the path of evolution through the ages. Con-
sequently, we shall be forced to hypothesize the
growth of this institution in Western Civilization.
When the number of people gathered together in
a group or clan is small, and when the technology
they have at their disposal is primitive, the society
(depending on the niggardliness of nature) is usually
forced to spend large amounts of its energy in
matters of survival per se and therefore spends little
hi speculative or educational activities. The young
men or women, when time comes for them to par-
ticipate actively hi the group's survival, are ap-
prenticed to older members of their own sex
(normally in their own kinship group) to learn by
mimic the techniques they will use throughout life.
It is not until the technology improves and the
group's number increases, that specialization in
education is able to come about.
For our convenience, let us picture this evolving
rudimentary formal educational system as being
divided into two distinct categories. The first, a
manual-technical classification which includes a
teaching of all of the skills required to support the
culture in its day to day existence. In the case of
teaching these skills it would appear that the more
routinized the skills required and the greater the
number needed to perform the operations, the more
likely it is for the task to be turned over to some
form of formal educational institution rather than
to be apprenticed to single individuals. Subsumed
under this category could be such training opera-
tions as manual trade schools, guilds, military
academies, and so forth.
A second category can be broadly classified as
philosophy. This group of studies was instituted to
cater to the needs of the ruling and wealthy classes.
Since there was little chance that the young of these
groups would ever need to perform manual labor,
they were taught how to govern and how to address
themselves to the more abstract problems of life.
Often these schools specialized in religious training
or in the arts such as music and painting.
Classes in both schools were likely to be small,
and the amount of accumulated tribal knowledge to
be passed on to the young was relatively light. The
seminar and laboratory (shop) could be widely used,
resulting in a great deal of personal attention for the
student. Further, secondary sources such as books
were scarce so that the student could not be totally
separated from everyday experience; his laboratory
had to be his world—as interpreted by his teacher,
of course.
As educational institutions became more crowded
and as the accumulated knowledge of a society in-
creased, the schools had to search for methods of
educating its students in a more streamlined fashion.
For example, many of the frescoes on the walls and
ceilings of the 13th and 14th century buildings in
Europe were painted by a master and his students.
Such a practice is possible only if the number of
students is small and the master can see to each
in an apprentice fashion. For many decades we
attempted to maintain this concept of master-student
by separating the vast number of students seeking
knowledge into undergraduate and graduate levels.
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The lower level catered to its clientel through mass-
produced learning situations. Only the best from this
level were allowed to be taught in a tutorial sense.
Ancillary with the overcrowding of the edu-
cational sphere has been the evolution of the
researcher. As more and more students demanded
the benefits of an education, die demands placed
on the teacher increased to provide unique tutorial
discussions of the day to day environment. Further,
more and more teachers discovered a continuing
demand for a few of their seminars (based on their
own experience and observations) to the end that
there was both a desire and a demand for wide-
spread distribution of their teaching. Soon, the dual
phenomena of an expanding day to day environment
and the teacher's capability of explaining it, led to
the creation of a middleman, the researcher. The
researcher attempted to antiseptically describe and
relate a number of different environments and facets
thereof to be used by the teacher and his students in
place of first hand experience. In short, we evolved
a body of men whose specialty is the distribution of
observations of the real environment in such a fash-
ion as to provide an artificial, but rich situation for
the teacher and the student as they go about the
study of philosophy.
It appears that this trend, although seemingly
logically arrived at from a historical point of view,
has worked to the disadvantage of the modern
student. In truth, today's graduate student is the
victim of both overcrowding of our educational
facilities and the loss of a tutorial teacher. His teach-
ers have taken the road of the researcher as the most
rewarding and have abandoned him to read their
musing rather than join in the study. Although his
predecessors had the distinct advantage of practical
studies under a master, he finds himself relegated
to the role of the former undergraduate as his
numbers have grown to a point where it is im-
possible for modern educational facilities to handle
him as a unique individual. Since, as noted earlier,
our educational institutions led the student to expect
some degree of private attention and activistically
oriented research as he progresses in his education,
the lack of these ingredients leads to a great deal of
frustration. The solution at first blush appears quite
simple. All that is required is to reverse the evolu-
tionary tendency so that the modern student can
participate in real life problems under the tutelage
of a guiding teacher.
Unfortunately, self-evident as such a solution
might be, we are constrained by the fact that it is
impossible for all of the vast number of students of
social science (part of modern day philosophy) to
be unleashed upon the day to day world. What is
needed is an educational technique which will revert
to a more personalized education and at the same
time allow society to remain undisturbed by the
learning process. Models of the sort described here
are a step in this direction.
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CHAPTER II
Brief Description of the Model
In a sense, the RIVER BASIN MODEL* is a
misnomer, because if one places an emphasis on
"River" it leads one to believe that the model is
primarily concerned with water management. The
emphasis should be placed on "River Basin", and
that term should be interpreted in its broadest con-
text as meaning a geographical area of land. Through
its two major components— human interaction and
computer simulation—the model represents the
economic, social, and governmental activity that
takes place within the geographical boundaries de-
fined by the river basin or, more simply, by a group
of contiguous counties.
The model is unlike most other simulation or
human interaction models. It was not designed to
accomplish any one specific purpose. Rather it was
designed to let its users represent the major eco-
nomic, social, and government interests that cause
a regional system to function and change. As part
of the functioning of this regional system, water
is demanded by industries and municipal water sup-
pliers and pollution is generated by manufacturing
and commercial activities, by people, and by farm
activities.
The model is a computer-assisted decision-making
tool, in which a number of computer programs
simulate major processes that take place in any
local system such as migration, housing selection,
employment, transportation, shopping patterns, the
actual allocation of leisure time, and water quality
determination. Users of the model provide inputs
to these programs on behalf of business activities in
the economic sector, government departments in the
government sector, and population groups in the
social sector.
*The previous version of the RIVER BASIN MODEL
was known as the CITY MODEL. The RBM contains all
of this model plus numerous additions. The experiments in
the schools were carried out on CITY III. RBM is CITY
IV.
Normally, the users of the model are assigned
decision-making responsibility for businesses, popu-
lation units, and government departments in a gam-
ing format. This means that users become members
of teams or decision-making units that are assigned
control of:
• Economic Assets: cash, land, manufacturing
plants, commercial activities, and/or resi-
dences.
• Social Assets: population units that are
designated as high income, middle income,
and/or low income.
• Government Assets: power of the budget,
taxing and assessing authority, service re-
sponsibility, and planning power.
The computer print-outs in a given time period
provide a detailed description of the regional area
represented by the model, and the users of the model
evaluate this status as individuals, as team members,
and collectively to define problems, establish ob-
jectives, develop strategies, implement plans, and
react to feedback from the new computer printout
for the next time period. Figure 1 shows the aggre-
gate interactions between the users and the computer
portion of the model.
THE REPRESENTED AREA (THE LOCAL
SYSTEM)
Since the RIVER BASIN MODEL is a holistic
decision-making model for a geographical area that
has been pre-loaded into the computer, the choice
of the initial regional configuration to be represented
is very important.
The model deals with any geographical area and
many of its associated economic, social, govern-
mental, and water resource characteristics. Many of
these characteristics are represented on a grid map
that measures 25 square parcels of land on a side.
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Figure 1.—INTERRELATIONSHIPS IN THE MODEL
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u.
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COMPREHEND THE
STATUS OF
BOTH THE CITY
AND PARTICULAR
AREAS OF CONTROL
» MAKE DECISIONS TO
CHANGE STATUS
• DEVELOP
STRATEGIES
ECONOMIC SECTOR
PURCHASE LAND
DEVELOP LAND
OPERATE BUSINESSES
TRANSFER MONEY
OR PROPERTY
INVEST
BOYCOTT
SOCIAL SECTOR
• VOTE
• ALLOCATE TIME
• BOYCOTT
• SET TIME-DOLLAR
VALUE
GOVERNMENT SECTOR
TAX
APPROPRIATE BUDGETS
OPERATE DEPARTMENTS
RESPOND TO SOCIAL
AND ECONOMIC
SECTORS
COMBINE THE ACTIONS, DECISIONS, AND INTERRELATIONSHIPS
TO CREATE A SIMULATED METROPOLITAN SYSTEM.
BOOKKEEPING
FUNCTIONS
• OUTSIDE SYSTEM
INFLUENCES
ASSIGNMENT
PROCESSES
All of the 625 possible land parcels are of equal is known, the length of a parcel side may be de-
size, so the length of a parcel side determines what termined.
overall geographical size area may be represented.
^^ ^^ & » &
Or conversely, once the total area to be represented
The latter approach was used to set the initial
parcel side lengths for the model. It was decided
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early in the project to represent the Cuyahoga River
Basin area as one of the two initial starting con-
figurations turned over to EPA.
The Cuyahoga River Basin is located within a six
county area that also happens to be continguous
with the Cleveland and Akron Standard Metropoli-
tan Statistical Areas. To fit that six county area on
the 25 by 25 grid resulted in a choice of 2Vi miles
for the length of a parcel side for that particular
load configuration. Thus each square was equated to
6.25 square miles in area.
The length of a parcel side may be changed rather
easily when the model is loaded, but a realistic range
of lengths would be from about. 1 to 4 miles and a
number of other model parameters should be simul-
taneously altered to correspond with the areal scale
change. (See Appendix for other configurations).
Figure 2 shows a map of the economic activity
represented by the model for the Cleveland-Akron
area. The area is actually called RAYWID CITY
in order not to mislead users of the model that a
full-fledged attempt had been made to represent that
actual area.
The users of the RIVER BASIN MODEL are
assigned responsibility for allocating all of the major
economic, social, governmental, and water resources
for the local system (the area and its activities
represented on the grid map) on a year to year
basis. The director of the model (the person con-
ducting the run of the model) makes a number of
decisions for the major decision-makers that are
outside the local system. A number of computer
programs are also available to simulate part of the
actions between this local system and the rest of the
world.
The initial starting position will show a particular
set of allocations of the local system's resources and
their effects on the status of the local area. The
users of the model evaluate their own particular
status within the local system as well as the status
of the area as a whole. They then interact with one
another in a dynamic decision-making environment
in which they collectively have control over the local
water quality decisions that will be made, imple-
mented, and reacted to. Some of the model users
may have apparently only marginal interest in the
local water quality issues because they are pre-
occupied with running schools, building roads, earn-
ing incomes, producing manufactured goods, build-
ing housing, and supplying local goods and services.
Others may have more interest as they attempt to
be elected into public office, run the planning de-
partment, collect taxes, recreate, and develop a gen-
erally pleasant environment for their new residential
subdivisions. Still others might have a direct and
pressing interest in the local water quantity and
quality as they attempt to set and enforce water
quality standards, supply municipal water, use sur-
face water in their production process, and benefit
from major water-based recreation areas.
In short, the entire local system (at a certain
level of detail) is represented by the model and its
users, and water decisions are placed within their
realistic context of having different importance to
different individuals as a function of their occupa-
tion, location, resources, and personal inclinations.
ACTIVITIES
The major activities represented in the model may
be divided into three major sectors (economic,
social, and governmental) and one major subsector
(the water component). Each of these sectors has
a number of activities that interact with the activities
of the other sectors.
The major economic activity is the business opera-
tion. Four broad types of businesses are represented
in the model: basic industry (manufacturing mostly)
that produces goods for export to national markets,
service industries that supply goods and services to
local system buyers, residential developers and op-
erators who make housing available to the local
population, and farming activity which often con-
sumes the majority of the land in a region.
Figure 3 shows the detailed economic activities
that fall under each of these four broad headings.
The economic assets of the local system are divided
up among economic teams for their management. In
addition to businesses, vacant land, cash, and stock
ownership may be given to teams for their use as
they see fit. Teams may be set up in such a way
that they are specialized (have only heavy industry,
only residences, only land, etc.) or diversified (a
mixture of several types of assets).
The Social Sector has one basic resource and
that is people. The local system's population is
divided into clusters of 500 people (or some other
size if a program change is made) that are called
population units (Pi's). These Pi's are further char-
acterized by an income class (high, middle, or low),
average educational level, average savings, number
of registered voters, etc. Associated with income
class are a number of specific characteristics such
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as number of workers, number of students, and
many preference functions.
Social Teams are created by giving a team de-
cision control for all the Pi's of a given class on
specified parcels. A good number of the actions
taken by Pi's during the course of a year in the local
system are determined by computer allocation
models, but the social teams may affect these by
making time allocation, boycott, cash transfer, and
vote decisions for the Pi's under their control.
A significant part of the RIVER BASIN MODEL
centers around how Pi's function within the local
•system during the course of each round of play
which represents one year of time in the local area.
FIGURE 3-^-Economic Activities in the RIVER
BASIN MODEL
Basic Industry (sells output at markets outside the local
system)
Manufacturing (roughly equivalent to the 2-digit SIC
code industries)
FL — Furniture and Lumber
SG — Stone, Clay, and Glass
MP — Primary Metals
MF — Fabricated Metals
NL — Nonelectrical Machinery
EL — Electrical Machinery
TE — Transportation Equipment
FO — Food
TA — Textiles, Apparel, and Leather
PA — Paper
CR — Chemical, Plastics and Rubber
Non-Manufacturing
NS — National Services (such as insurance, research,
etc.)
Local Commercial (sells output competitively to local sys-
tem demanders)
BG — Business Goods
BS — Business Services
PG — Personal Goods
PS — Personal Services
Residential (provide housing space)
RA — Single Family
RB — Garden Apartments (6 times the housing space
as RA housing)
RC — High-rise Apartments (25 times the housing
space as RA)
Agricultural (consume land and use varying amounts of
fertilizer)
Fl — Fruit & Nut
F2 — Vegetable
F3 — Other Field Crops
F4 — Cash Grain
F5 — Tobacco
F6 — Cotton
F7 — Poultry
F8 — Dairy
F9 — Livestock
F10 — Ranchers
Fll — General
Figure 4 shows the actions of Pi's as they are
affected by the major operating programs.
The Government Sector is comprised of decision-
makers who are responsible for a wide variety of
public activities: budget making (appropriations and
revenues), land and building assessment, education,
municipal services, transportation, planning and
zoning, and utilities. The latter activity contains
within it the water office that is responsible for the
supply of public water. The Water Quality Office
may be a part of this department or a separate
agency.
FIGURE 4—Example of How Population Units Are
Affected by the Major Operating Programs of
the Model
Major Operating
Programs
Effect on Population Unit
Migration
Water System
Depreciation .
Employment .
Transportation
School Allocation
Park Allocation
Time Allocation
Commercial Allocation
.Pi's move to the local system,
find and change housing within
the local system, leave the local
system.
. Poor water quality increases dis-
satisfaction and high coliform
count increases health costs and
time lost due to illness.
.Housing that depreciates be-
comes less attractive in the mi-
gration process.
. Pi's are assigned to full and part
time jobs that maximize net in-
come (salary minus transporta-
tion costs), employers search for
best educated workers.
. Pi's travel to work by the mode
and route that minimizes total
costs (dollar plus time), Pi's
travel to shopping along die
minimum cost routes
.Students of Pi's are assigned to
public or private schools based
upon the quality of public
schools.
.Pi's are assigned to parks within
a specified distance of where they
live.
. Involuntary expenditures of lei-
sure time are calculated as a
function of the success of getting
part time jobs, public adult edu-
cation and the time spent on
transportation.
. Pi's are assigned to stores at
which the total costs are mini-
mized (price plus transportation
to the store).
-------
WATER COMPONENT
The water component is a subsector that, in a
sense, cuts across the other three sectors or is a
part of each. For example, some of the industrial
activities in the economic sector use surface water
in their production process and all other economic
businesses have some need for municipally supplied
water. Population units in the social sector use water
as a function of their income class and the type
of housing they inhabit. In the government sector,
the Utility Department is responsible for supplying
the municipal water needs of the residents of its
jurisdiction.
Each of the surface water users requires a speci-
fied quality of water and must either treat the water
they intake or purchase water from a source outside
of the local system. Every water user adds some
pollutants to the water it returns to the water system.
If left untreated, these water discharges may lower
the quality of water of the body of water into which
they are dumped. Since water users and polluters
are located in a geographical space, activities up-
stream and downstream are affected differently by
the dynamically created water quality conditions.
THE RIVER BASIN MODEL AS A SYSTEMIC
MODEL
The RIVER BASIN MODEL may be charac-
terized as a systemic model. That is, it is a model of
the interactive workings of the system it represents.
The RIVER BASIN MODEL is not a predictive,
projective, or normative model. It does not predict
a future state of the area represented, although it
does show the immediate status of the urban area
given all the resources of the system and the policies
attached to the use of those resources. Therefore, it
is an impact model (one year at a time) concerned
with resource allocation.
The RIVER BASIN MODEL is not a projection
model because it does not extrapolate present cir-
cumstances and relationships into the future. In
other words, the user of the model does not "turn it
on" and generate a set of future states for the area
represented. The model cycles in one year incre-
ments, and in a sense, it could be used for projection
if the user made the year to year decisions for the
urban area for a twenty or thirty year time period.
But because of the broad scope of the model and the
wide range of decisions that are based upon the
results of previous decisions in the economic, social,
and government sectors, this particular use of the
model should not be looked on as a simple task.
Furthermore, the RIVER BASIN MODEL is not
a normative or optimizing model. It will not itself
generate optimal policy decisions. The model pro-
duces a thorough set of indicators and measures of
the regional status at discrete points in time (the
end of each year) and it is up to the user of the
model to apply his own set of objective and sub-
jective criteria to evaluate the absolute or relative
quality of the environment. For example, the model
will generate measures of water quality along
stretches of the river, pollution dumped by various
activities, local water deficiencies, poor schools,
economic rates of return, housing quality, municipal
services quality, social dissatisfaction, etc. and the
user of the model must determine the values to be
placed on these measures in the process of making
policy decisions regarding the use of the regional
resources in future years.
A systemic urban model such as the RIVER
BASIN MODEL endeavors to represent the work-
ings of a regional system and its major subsystems.
This is done by selecting the major activities that
comprise the urban system (people in households,
businesses, and government agencies) and represent-
ing me actions that they pursue on a year to year
basis. Population groups reside in housing, earn
incomes, purchase goods and services, take part in
leisure activities, utilize government and institutional
services, transport themselves as they interact with
activities that are spatially separated from their
places of residence, and use water. Businesses pur-
chase goods and services, hire labor, require utilities,
produce output, sell output, pay taxes, invest earn-
ings, use the transportation subsystem, use water,
and generate pollutants that may be treated. Govern-
ment agencies receive funds, purchase necessary
goods and service, hire labor, provide service, and
set policy. Most of the departments compete with
the water quality office for a slice of the local budget.
-------
CHAPTER III
Uses and Users of the Model
Broadly speaking, there are two types of users of
the model when it is employed using a gaming for-
mat: the director and the players.
In each use of the model the director sets the
major purpose for which the model will be em-
ployed. Usually the specific group of players he has
in mind will determine his choice of the executive
options, such as the starting regional configuration
and any initial inputs to modify this basic configura-
tion.
As shown in Figure 5, the director may affect the
simulated region before play begins by selecting the
basic configuration and making changes in it. He
may also affect the year to year outside influences on
the local system by, among other things, acting as
the Federal and State governments with regard to
granting aid and imposing regulations. For example,
the director could act as an outside government that
imposes rigid water quality standards. He could
also act as a higher-level government that grants
financial aid for the construction of waste treatment
facilities, for comprehensive water resource plan-
ning, for enforcement and monitoring, etc. The fol-
lowing list is a sample of the executive options
available to a director.
Choice of Initial Configuration: TWO CITY or
RAYWIDCITY
Initial Decisions:
• Change Economic Team Holdings—many
possibilities.
• Change Social Team Holdings—many possi-
bilities.
• Change Government Service Levels—give
schools and/or municipal services higher or
lower use indexes.
• Change Local Tax Structures—many possi-
bilities.
• Change Salaries, Prices and/or Rents.
• Change Maintenance Levels.
To achieve:
• More or less team specialization or more or
less equitable starting positions among
teams.
• Create more or less neighborhood and/or
single-class control.
• Make neighborhood attractiveness vary by
altering the quality of public services.
• Shift to or away from dependence upon
property, sales, and/or income taxes.
• Alter rates of return to economic sector or
savings for social sector.
• Make area as a whole or parts of it more or
less deteriorated.
USING THE MODEL
The RIVER BASIN MODEL is a tool that has
utility which is dependent upon the quantity and
quality of data loaded into its files, the executive
options employed by the director, and the technique
used to evaluate the city status and generate inputs
to the model. These three types of inputs to the
model are illustrated in Figure 5.
Users will use the tool in a way that they find
best suits their purposes. It is a flexible model that
will take on different forms in the hands of different
users. The RIVER BASIN MODEL provides a
framework that is common for all regional decision-
makers (much as a chemistry lab and the associated
chemistry theory provide users of the lab with equal
access to the facilities and accumulated knowledge).
It allows the decision-maker to use this framework
and the computer programs associated with it to
achieve a wide range of objectives (much as the
chemist may use the lab for instructional, research
or production purposes).
Although the RIVER BASIN MODEL as pres-
ently developed will not satisfy every need of the
decision-maker, it does allow him the opportunity to
deal with a large number of regional phenomena
which up to now he has not been able to deal with
in a simulated and collapsed-time environment.
-------
Figure 5.—ILLUSTRATIONS OF INITIAL AND CONTINUAL INPUTS
TO THE RIVER BASIN MODEL
DESIGNATION OF INITIAL
CITY STATUSo
REAL CITY
DATA
HYPOTHETICAL
CITY DATA
SELECTION OF
EXECUTIVE OPTIONSo
MODULES
USED
PARAMETERS
USED
TECHNIQUE FOR
EVALUATION OF CITY STATUSt
SIMULATION
MAN-
MACHINE
GAME
FORMAT
CITY STATUSt
ECONOMIC
INPUTS
INPUTS
INPUTS
,'T
SOCIAL
GOVERNMENTAL
WATER SYSTEM
0
0
*
z
5i
ID
K
III
10
-------
Users of the model are given control over all the
resources of the local area being represented. Some
of the local activities use the water subsystem while
others do not. As a result of this, the water quantity
and quality is of varying importance to'the various
activities represented by the model.
The RIVER BASIN MODEL is oriented toward
user requirements such as generality of representa-
tion, flexibility of change, ease of inputs, and read-
ability of output. The model provides, among other
things, detail on the repercussions of various water
quantity and quality levels and on the effects of
water resource decisions on people and business
activities. It also illustrates the impact of other de-
cisions on the water subsystem itself.
A wide range of decisions and their consequences
may be illustrated by the model. For example, in
the economic sector the impacts of pollution regula-
tion decisions may be shown. In the social sector,
the effect on housing selection, employment, shop-
ping, and leisure activities are influenced by water
resource policies. The impacts of many government
decisions may be shown: comprehensive planning
programs, quality of life improvements, and many
more.
The users of the model may make a wide range
of private and public policy decisions which affect
the water subsystem and others. The detailed and
summary computer output reveals the interactions
of these decisions and the collective impact they
have on the environmental quality of the represented
area. Since each cycle of the model represents the
passage of a year of time in the area being repre-
sented, the model may be run for as many cycles as
the users find desirable.
MODEL FEATURES
User interaction in the RIVER BASIN MODEL:
• Requires fewer model assumptions on the
part of the designer than most previous
models because the users provide much of
the nonquantifiable relationships and inputs
to the represented system.
• Allows realistic human interaction and re-
action.
• Allows political repercussions associated
with water resource decisions, reversal of
policy, etc.
• Allows human involvement in the decision
process.
The RIVER BASIN MODEL deals with:
• External Inputs—area characteristics, in-
cluding the present water subsystem and
quality levels.
• Internal Inputs—wide range of water re-
source, economic, social, and government
decisions.
• Internal Outputs—changes in the resources
of the individual decision-makers.
• External Outputs—changes in the area char-
acteristics, allocations, assignments, match-
ing of supply and demand, insufficiency of
government services, and complete status of
the water subsystem.
The RIVER BASIN MODEL is useful to citizens
as well as planners because the model output is
designed in such a way that it is comprehensive,
easy to understand, and quick to retrieve. Thus,
regardless of the sophistication of the user, the model
will provide the necessary level of information upon
which evaluations can be made and decisions can
be generated.
The cycles of the model (each set of computer
output) represent one year in the life of the area
represented by the model. Users provide the evalua-
tion of the current status of the area (in its eco-
nomic, social, governmental, spatial, and water
quantity and quality dimensions). Through a wide
range of decision alternatives, they are able to de-
vise strategies and implement policies, in an attempt
to achieve any set of goals or objectives they devise,
as individuals or collectively.
These decision inputs may be generated in a
simulation environment (in which a single user or
group of users such as water resource planners are
given control over all the resources of the local
system) or in a game environment (in which in-
dividual users such as local officials, students and/or
citizens are given control over various resources in
the local system).
The RIVER BASIN MODEL has been designed
in a modular fashion, so that new modules may be
added or existing ones replaced or modified at mini-
mal expense. This modularity means that it is rela-
tively easy to:
• Redefine the model (change parameters and
coefficients).
• Load various regions.
This modular feature of the RIVER BASIN
MODEL allows it to be truly evolutionary, thus
making it a framework that can continually be
improved and modified for specific uses.
11
-------
CHAPTER IV
Model Output
The model describes and interrelates many of
the actual economic, social, and governmental activi-
ties that comprise regional areas. The metropolitan
area represented by the model is described by three
types of computer output: maps, tabular statistics,
and indicators.
MAPS
The maps show the spatial characteristics of the
represented area. The tabular output shows general
information of interest to the users of the model as
well as specific data concerning businesses in the
economic sector, groups of people in the social sec-
tor, and government departments in the government
sector. The indicators are measures such as the
economic rate of return, the social dissatisfaction
level, the quality of local government services, and
water quality indicators.
Of the dozens of maps, the Economic Status Map
(Figure 6) stands out as the one of single most
importance. Any represented area may be defined
by spatially locating land use activities, the highway
network and the water system in any desired pattern
on the grid map. Although this map does not show
the local water system, there are a number of maps
that do.
All physical objects (industries, stores, housing,
schools, government facilities, roads, rivers, and
treatment plants) are located in a specified section
of the regional area. Most facilities are located on
parcels of land (identified by two even coordinate
numbers). Roads are located (conceptually) along
the boundaries (sides) of the square land parcels
(identified by an even-odd or odd-even number).
A road on the map actually represents all the major
and minor roads that connect an origin and a desti-
nation at each end of the transportation link. Trans-
portation terminals are located at the corners of
parcels (identified by two odd-numbered co-
ordinates).
Other local system phenomena are also spatially
located. Population units are housed in residences
on parcels, service districts and farms are defined in
terms of contiguous parcels of land. Figure 7 is a list
of the map output separated into ten categories.
12
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**********************************************
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70 72 7t 76 78 80 82 84 86 88 90 92 94 96 98 100 102 104 106 108 110 112 114 116 118
PARCEL ICZT
TOP LEFT: 0»»EB
TOP BIGHT: ZOIIBG
RIDDLE: LAUD USE ABD LEVEL
BOTign LEFT: OTILITI LETBI
BOTtOB BISHT: % OBDETLPD LAID
PABCBL EDGES
.. .. BOJDBBD
— || TIPS 1 BO All
== BB TYPE 2 BOAD
IB II TTPE 3 BOAD
00 OO JOBISDICTIOB BOUIDABT
IBTBBS1CTIORS
ZOSIHG LAID OS* ZglXIG OSB
*
i
«
TIPE
TYPE
TIPE
1
2
3
TBBHIIAL
TEBBIBAL
TEBBIHAL
«
10
20
21
22
23
30
31
32
Alt
AIT
HI,
HI
LI
CI
IS.
US
BG
OSE _^
BOSIBESS
LI,CI
BG,3S,PG,PS
33
34
35
40
41
42
43
50
BS
PG
PS
BA.BB,
BA
BB
BC
PABKLt
BC
.ID
13
-------
FIGURE 7—Map Output Generated for Each Cycle of Operation
Map Category
Map Number
Map Name
Commercial
Government
Service
Water System
Farms
Property Values
Land Use and
Regulations
Parks
Social
Characteristics
Physical
Characteristics
Government
Facilities
10.1
10.2
10.3
10.4
10.5
10.6
10.7
10.8
10.9
10.10
10.11
10.12
10.13
10.14
10.15
10.16
10.17
10.18
10.19
10.20
10.21
10.22
10.23
10.24
10.25
10.26
Personal Goods Allocation Map
Personal Services Allocation Map
Business Commercial Allocation Map
Municipal Service
School Map
Utility Map
Water Usage Map
Water Quality Map
Municipal Treatment
Municipal Intake and Outflow Point Map
Surface Water Map
Farm Runoff Map
River Basin Flood Plain Map
Farm Map
Farm Assessed and Market Value
Market Value Map
Assessed Value Map
Economic Status Map
Highway Map
Planning and Zoning Map
Parkland Usage Map
Socio-Economic Distribution Map
Demographic Map
Social Decision-Maker Map
Topographical Restriction Map
Government Status Map
Map
TABULAR COMPUTER OUTPUT
The economic, social, and government teams re-
ceive computer output that describes the details of
the resources over which they have decision-making
power. In addition to this team-specific information,
general and summary statistics describing the repre-
sented area are available as common information to
all teams. A list of all the tabular output is shown in
Figure 8.
To provide examples of the tabular output, the
following descriptions of migration and the water
system are provided.
Migration
The basic population grouping in the model is the
population unit (PI). A PI is designated as being a
member of a socio-economic class (H, M, or L).
Pi's move into, within, and out of the local system
in response to available employment opportunities,
housing quantity and quality, and a number of other
factors. Figure 9 shows a sample of the summary
migration statistics for an area and a portion of the
detailed statistics.
The Migration-Housing computer routine cal-
culates dissatisfaction (environmental and personal);
develops a pool of movers comprised of the popula-
tion displaced by housing demolition, a percent of
the most dissatisfied, a percent of the total popula-
tion (random movers), natural population growth,
and the in-migrants; and moves the members of this
pool into housing that has adequate capacity and
quality.
A certain percentage of each income class that
are either unemployed or underemployed outmigrate
from the local system. Other movers who cannot
find adequate local housing also become outmi-
grants.
Referring to Figure 9, the Pi's living in the resi-
dences (or considering to live in the residences) on
parcel 9422 see a health index of 50 (the higher the
index the worse the situation). The time indexes are
calculated only for the income classes actually living
on the parcel. For example, on parcel 9422 there
were PM groups living there and because of the
distance and mode used to travel to work, 25 units
of dissatisfaction were added to the personal index.
Another 59 units were added to the index because
of the amount of leisure time that was spent in in-
voluntary pursuits.
14
-------
FIGURE 8—Tabular Output
Output Category
Code Number
Output Name
Migration
Water System
Employment
Commercial
Allocation
« • *
Social
Sector
Economic
4* *
Sector
Social and
Economic Summaries
Government Detail
Summary Statistics
1.1
1.2
1.3
1.4
1.5
1.6
2.1
2.2
2.3
2.4
3.1
3.2
3.3
3.4
3.S
3.6
3.7
4.1
4.2
4.3
4.4
4.5
4.6
- 30
4.7
5.1
5.2
50%
.3
6.1
6.2
Jf M
6.3
^ -
6.4
IF &
6.5
6.6
6.7
6.8
6.9
7.1
7.2
7 A
.3
7.4
7.5
7.6
mf mm
7.7
8.1
4% J%
8.2
A *%
8.3
8mt
.5
8.6
8m*
.7
8.8
8.9
8.10
8.11
8.12
8.13
8.14
8.15
8.16
8.17
8.18
8.19
8.20
9.1
^Environmental Indexes
Personal Indexes
Dissatisfaction Cutoffs
Migration Detail
Migration Statistics
Migration Summary
Water User Effluent Content
River Quality During Surface Water Process
Water User Costs and Consumption
Coliform and Pollution Index Values
Employment Selection Information for PL Class
Employment Selection Information for PM Class
Employment Selection Information for PH Class
Part-Time Work Allocation for PH Class
Part-Time Work Allocation for PM Class
Part-Time Work Allocation for PL Class
Employment Summary
Personal Goods Allocation Summary
Personal Services Allocation Summary
Business Goods Allocation Summary
Business Services Allocation Summary
Government Contracts
Terminal Demand and Supply Table
. Terminal Allocation Map
Dollar Value of Time
Social Decision-Maker Output
Social Boycotts
Farm Output
Residence Output
Basic Industry Output
Commercial Output
Economic Boycott Status
New Construction Table
Land Summary
Loan Statement
Financial Summary
Number of Levels of Economic Activity
d: Controlled by Teams
Employment Centers
Economic Control Summary for Teams
Social Control Summary for Teams
Social Control Summary Totals
Economic Graphs for Teams
Social Graphs for Teams
Assessment Report
Water Department Reports
Sampling Station Report: Point Source Quality
Sampling Station Report: Ambient Quality
Utility Department Report
Utility Department Finances
Municipal Services Department Report
Municipal Services Department Finances
Municipal Services Department Construction Table
Planning and Zoning Department Report
School Department Report
School Department Finances
School Department Construction Table
Highway Department Finances
Highway Department Construction Table
Rail Company Report
Bus Company Report
Chairman Department Finances
Tax Summary
Financial Summary
Demographic and Economic Statistics
15
-------
TIOCITI
PSBSOIAL IIDBX8S
FIGURE 9
BOOID 2
BBAITS ill DEI
LOCATIOB
CBOIDIIG BACIBBIA
as EFFECT EFFECT EFFECT TOTAL
CLASS
TBAISP.
TIBE
IHOL.
I IBB
•9«22
9622
9822
10022
25
25
25
25
25
0
0
0
50
25
25
9IDDLE
101
LOI
LOI
25
25
65
105
0 59
0 76
0 68
0 60
134
126
158,
150
IBDBXES
**************
******************************
RODBD 2
BEIGBBOBBOOD INDEI
LOCATIOB
9»22
9622
POLLOTIOI B
IIDBI CLASS
-7 LOI
BIDDLE
BIOS
-15 108
HI DOLE
HIGH
ESIDE8CB
QOALITT
19
39
49
It
64
74
BEIT
0
0
0
0
0
0
as >
100
100
100
100
100
100
SCHOOL
0
0
0
0
0
0
IBLFABB
OR TUBS
12
24
24
16
18
18
TOTAL
131
163
173
160
182
192
EHFIBOiaEITAL
IBDBI
124
156
166
145
167
177
***********************************************************************************************************************************
TIOCHI
BIGBATIOH DETAIL BOOIO 2
***********************************************************************************************************************************
SOCIAL BUBBEB
DECISION OF
PABCEL OBIBR TIPE BASES PI'S CLASS
QOALITI OF BOBBEB
LIFE ' BOVED
FBOfl/TO
PABCEL
BEASOB FOB
BOTIIG
9422
LOI
DIDDLE
0
290
1 CABS PROB 10030
1 BEIT TO 10826
DISPLACEBEST
DISPLACES*!!
9828
9626
9622 D BA 1
9822 G BA 2
LOt
LOI
271
286
1 CAIE FBOB
10024
DISPLACEBE IT
9630
BIGBATIOI BI TIPE
BIGBATIOB DOE 10 OIBBPLOiailT
LOB CLASS
FBOI/TO JOB-1 JOB-2 JOS-3 OUTSIDE
JOB-1 0000
JOB-2 0004
JOB-3 0000
OOTSIDE 0000
BIGBATIOB DDE 10 BIDIBEBPLOTBEIT
LOI CLASS
FBOB/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 0000
JOB-2 0000
JOH-3 0000
OOTSIDB 0000
BIGBATIOI DIE TO BOBILITI
LOI CLASS
FBOB/TO JOB-1 JOB-2 JOB-3 OUTSIDE
JDB-1 0000
JOB-2 0000
JOS-3 0000
OOTSIDE 0000
BIGRATIOI DOE TO PEBSOJAL DISSAT.
LOI CLASS
FBOB/TO JDB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 0000
JOB-2 0 15 0 6
JOB-3 0000
OOTSIDE 0000
BIGBATIOI DOE TO DISPLACBJEIT
LOI CLASS
FBOB/TO JDB-1 JOB-2 JOB-3 OOTSIDE
JDB-1 0000
JOB-2 1400
JDI-3 0000
OOTSIDE 0000
BIGBATIOI DOE TO IATOBAL GBOITB
LOI CLASS
PBOB/TO JOB-1 JOS-2 JOB-3 OUTSIDE
JOB-1 0000
JOB-2 0000
JOB-3 0000
OOTSIDE 0200
IISBATIOI DOE TO IB-BIGIATIOB
LOI CLASS
nOt/tO JOB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 0000
JOB-2 0000
JOB-3 0000
OUTSIDE 2 11 0 32
aiDDLE CLASS
FBOa/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JDB-1 0000
JOB-2 0000
JOB-3 0000
OOTSIDE 0000
BIDDLE CLASS
PHOB/TO JOB-1 JOR-2 JOB-3 OOTSIDB
JOB-1 0003
JOB-2 0002
JOB-3 0000
OOTSIDE 0000
BIDDLE CLASS
FBOI/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 2300
JOB-2 1000
JOB-3 0000
OOTSIDE 0000
BIDDLE CLASS
FBOB/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOS-1 6600
JOB-2 0000
JOB-3 0000
OOTSIDE 0000
BIDDLE CLASS
rBOB/TO JDB-1 JOB-2 JOB-3 OOTSIDE
JOE-1 0500
JOB-2 0300
JOB-3 0000
OOTSIDE 0000
BIDDLE CLASS
FBOI/TO JOB-1 JOB-2 JDB-3 OUTSIDE
JOB-1 0 0 00
JOB-2 0000
JUB-3 0000
OOTSIDB 2100
BIDDLE CUSS
FBOfl/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 0000
JOI-2 0000
JOB-3 0900
OOTSIDE 2000
BIBB CLASS
FBOB/TO JIl-1 JOB-2 JDB-3 OOTSIDE
JDB-1 0000
JOB-2 0000
JUB-3 0000
OOTSIDE 0000
HIGH CLASS
FBOa/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 0002
JOB-2 0001
JOB-3 0000
OOTSIDE 0000
BIGB CLASS
FBOB/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOS-1 2 1 00
JOB-2 4000
JOB-3 0000
OOTSIDE 0000
BIGB CLASS
FBOB/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 19 1 0 0
JOB-2 0000
JDB-3 0000
OOTSIDB 0000
BIGB CUSS
FBOB/TO JOB-1 JOB-2 JOB-3 OOTSIDB
JOB-1 03 0 0
JOB-2 1000
JOB-3 0000
OOTSIDE 0 0 0 A
BIGB CLASS
FBOB/TO JDB-1 JOB-2 JOB-3 OOTSIDE
JDB-1 0000
JOB-2 0000
JOB-3 0000
OOTSIDE 0300
BIGB CUSS
FBOB/TO JOB-1 JOB-2 JOB-3 OOTSIDE
JOB-1 0000
JOB-2 0000
JDB-3 0000
OOTSIDI 2000
16
-------
Note that there are six items that comprise the
environmental index and their contributions to that
index are listed in the output. The number of popula-
tion units that move to and from each residential
parcel and their reasons for moving are also shown
in the output.
The purpose of showing Figure 9 is not to explain
how the migration process works but to illustrate
that the full results of the process are illustrated on
tabular computer output that can be of great as-
sistance to the users of the model in then* decision-
making.
nomic sector are net worth for teams and rates of
return on individual investments. Major indicators
in the social sector are the per capita personal
incomes and the quality of life indexes. Major
government indicators are the service use indexes
for schools, parks, and municipal services and con-
gestion of highways. Major indicators in the local
water system are the water quality ratings.
Figure 11 shows the average quality of life index
for the population units (by class) controlled by a
social team. Figure 12 shows the Water Quality
Map for TWO CITY in Round 2.
The Water System
Figure 10 shows some tabular computer output
for a local system river (River 2). This output
shows the location of each segment of the river, the
quality rating and major pollutant, the time period
in the water's passage through a parcel, the amount
of each of the seven pollutant types, and the volume
of the water.
Once again, it is not important that the reader
fully understand this information at this time. It is
illustrated here only for the purpose of showing the
type of tabular computer output generated each
round as part of the model operation.*
INDICATORS
The model output is also expressed in some in-
stances by indicators. Major indicators in the eco-
*Information of this type is presented in great detail in
the fourteen manuals which accompany the model computer
program.
THE RIVER BASIN MODEL AS A SET OF
REGIONAL ACCOUNTS
Since the RIVER BASIN MODEL is a model of
an entire regional system, there is the requirement
that accounts balance within the local system. For
example, every expenditure for one activity is an
income for another activity. Similarly, local sales and
income from services rendered are actually derived
by totaling the expenditures made by the Pi's or
business activities for these goods and/or services.
Therefore, the impact of water quality and cost
decisions on the financial accounts for various popu-
lation and business groups and by location can be
followed over time. Not only are water usage figures
calculated, but also expenditures for water, pollution
treatment and fines. In short, the RIVER BASIN
MODEL is a systems accounting framework as well
as an integration of many market models within a
spatial context.
17
-------
LOCATION
11234
11234
11234
11234
11234
11234
11236
11236
11236
11236
11236
11238
11238
11238
11238
11238
11038
11038
11038
11038
11038
11040
11040
11040
11040
11040
11042
11042
11042
11042
11042
10842
10842
10842
10842
10842
10642
10642
10642
10642
10642
10644
10644
10644
10644
10644
10646
MUNICIPAL
10646
10646
10646
10646
10648
10648
10648
10648
10648
10448
10448
10448
10448
10448
10248
10248
10248
10248
10248
10048
10048
10048
10048
10048
RAYKIO CITY «*»/»^jj
RIVER QUALITY DURING SURFACE HATER PROCESS: RIVER 3 .«.«««««.
QUALITY
10
10
10
10
91
88
78
78
78
0
88
78
78
78
0
88
88
88
88
0
88
88
88
88
0
88
63
63
63
10
63
63
63
63
0
63
63
63
63
0
63
63
63
63
0
63
63
INTAKE P
63
63
91
92
92
92
92
81
92
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92
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91
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TIME
FROM OTHER PARCELS
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
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AFTER AGING
BEFORE BIO CHANGE
AFTER BID CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
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AFTER AGING
OINTt UTILITY DISTRICT
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE BIO CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
AFTER AGING
BEFORE 810 CHANGE
AFTER BIO CHANGE
EFFLUENT ADDED
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BOD
IX 1001
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-------
Figure 11.—SAMPLE OF QUALITY OF LIFE OUTPUT FOR POPULATION GROUPS
ROUND 1
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—QUALITY OF LIFE INDEX-
—QUALITY OF LIFE INDEX—
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20
-------
CHAPTER V
Model Inputs
Three types of model inputs should be dis-
tinguished: initial director inputs, player inputs, and
continual director inputs.
INITIAL DIRECTOR INPUTS
Some of the initial director inputs were discussed
under the chapter on users of the model. Briefly, he
can choose a prespecified (two at this time) starting
configuration. With this configuration he may make
any number of changes to alter the starting scenario.
Or, he can load into the computer a starting con-
figuration that he has fashioned out of real or hypo-
thetical data.
The initial starting position of the model is very
flexible in several ways. First, any desired initial
land use pattern may be represented. Thus, a model
run could begin with development ranging from a
blank board to a fully occupied land area. Also,
from one to fifteen separate local governments can
be represented.
Second, the population classes placed into hous-
ing, rents charged at housing, prices charged at
stores, salaries offered by employers, taxes charged
by local governments, etc. can be set in an infinite
number of patterns. For example, the five population
classes could be distributed among the housing stock
in such a way that there was much or little income
segregation, overcrowding or under-occupancy, etc.
Or any transportation subsystem configuration could
be represented.
Third, the control over the economic, social, and
governmental resources of the represented area can
be allocated among users of the model in any way
desired. For example, if a single person were using
the model for research or simulation purposes, all
of the economic assets could be placed under the
control of a single corporation. If the model is being
used for citizen participation or educational pur-
poses, the director of the model might choose to
have the resources of the community allocated in
such a way that some corporations own only one
type of economic activity (industry, commercial
establishments, residences, or land) or several types
of activities (a mix of industrial, commercial, resi-
dential, and vacant land).
The economic, social, and government sector
computer output describes the details of the re-
sources in these sectors. In addition to this specific
information, general and summary statistics describ-
ing the represented area are available as information
common to all the model users.
Model users provide the evaluation of the status
of the area as a whole and of the individual sector
resources in particular, develop goals and objectives,
formulate strategies, and make decisions for the
coming calendar year. All the information on the
computer print-outs describes the represented area
at one point in the year. All decisions that are made
take effect at that time and their impact is not seen
until the decisions are processed through the com-
puter and a new status is generated for the next year.
A subset of the initial director decisions are those
that relate to the local water system. The director
through the load program may create a region that
has any mix of water quantity and quality charac-
teristics. For example, a region could be configured
that had very low quality water and no treatment
facilities at the start of play. Or an initial starting
point could be developed that had all the pollution
created by activities in one jurisdiction have its
major detrimental effects on activities and people
in a downstream jurisdiction.
PLAYER INPUTS
Players have available to them a wide number of
possible formal decisions (ones that require process-
21
-------
ing by the computer) and they have an infinite
number of informal decision options open to them.
The formal decisions available to the players are
summarized in Figure 13 under the three sector
headings.
A subset of the player decisions are those that
relate to the local water system. Economic decision-
makers may build waste treatment facilities for their
industries that dump into the local water system.
They may also cut back operating levels of busi-
nesses in order to reduce the pollution they generate.
These two decisions do not fully indicate the impact
that the water component has or may have on the
specific sections of the local system because of
inadequate water supply, high municipal water costs,
poor surface water quality, poor transportation ac-
cess caused by the absence of bridges to cross a
river, etc.
FIGURE 13—Decisions Available To Users of the Model
1. Economic Decision-Makers
buy and sell land
set rents
set prices
set salaries
set maintenance levels
lend money
borrow money
buy and sell conservative stocks
buy and sell speculative stocks
build and demolish three types of residences, twelve
types of basic industries, and four types of com-
mercial establishments
• contract with construction industries
• transfer money to other economic and social and
government decision-makers
• boycott commercial establishments
• construct chlorination, primary, secondary and ter-
tiary effluent treatment facilities at basic industries
• change the operating level of a business (without
demolishing the building)
• set the amount of water which is recycled at basic
industries
• construct residences which use ground water
• operate farms
2. Social Decision-Makers
• allocate time to extra work, education, politics and
recreation
• boycott work locations, commercial establishments,
and modes of travel
• vote for elected officials
• set the dollar value of time travelling to work
• transfer money to other social, economic and govern-
ment decision-makers
3. Government Decision-Makers
grant appropriations
grant subsidies
transfer money to other government and social and
economic decision-makers
set welfare payments
set tax rates
float bonds
assess land and buildings
buy and sell land
set the number of job openings in government
set the maintenance level of government facilities
set government service districts
request Federal-State aid
set the salaries offered government workers
build and demolish schools
build and demolish municipal service plants
contract with construction industries
grant contracts with local goods and services es-
tablishments for government purchases
set the amount of public adult education offered by
the government
construct and demolish roads
construct and demolish terminals
zone land
build and demolish public institutional land uses
provide parkland
install utility service
set prices for utility service
construct and demolish utility plants
locate bus routes
buy and sell buses
set bus and rail fares
build rail lines
build rail stations
buy and sell rail rolling stock
locate rapid rail routes
set the amount of service on bus and rail routes
set prices for private use of publicly-provided water
construct and demolish primary, secondary, and ter-
tiary sewage treatment plants
construct and demolish water intake treatment plants
locate municipal water intake points
locate municipal sewage outflow points
locate water sampling stations
set dam priorities
change a business's operating level (without de-
molishing the building)
• construct and demolish bridges across rivers
Social sector decision-makers may be very much
affected by the quantity and quality of water in the
local system, but they make no direct water de-
cisions. They do vote for elected officials, however,
and to the extent that water issues are an important
local concern, the social sector might influence water
resource decision-making a great deal indirectly
through the ballot box. These votes might be for
water related referenda as well as for political
officers.
The Utility Department in each jurisdiction
(through its Water Office) has a number of decisions
that it may make. It sets the price of municipal
water for different types of buyers. It may construct
22
-------
intake and outflow treatment plants and locate them
to best advantage taking into account water supply
and quality, downstream activities, land'..costs, and
local sentiment. It may choose where in the local
water system to remove water for public consump-
tion and where to dump the municipal wastes.
Furthermore, the water resources decision-maker
may fund and locate sampling stations (ambient or
point source) and set dam operating priorities (to
favor recreation, flood control, and/or pollution con-
trol). Other government departments compete with
the Utility Department for local citizen support and
possibly for outside government financial assistance.
The Highway Department is affected directly by the
local water system in that it costs more to put high-
ways across parcels that contain rivers. This higher
cost represents the added expense of building bridges
and tunnels.
Figure 14 shows an example of a completed team
decision form and the computer "Edits" of a set of
decisions for a round of the model. Since collectively
the teams comprise most of the major local decision-
makers of the represented area, most of the change
that will take place from one round to the next will
be a function of the number and type of decisions
generated by the teams. The major decisions not
made by the teams are those made either by com-
puter simulators which represent the outside system
impacts on the local system or by the director who
may act as higher level governments or as Mother
Nature and cause floods, earthquakes, and/or other
forms of natural disaster.
Teams will often note that the decisions of other
teams have significant effect on their own output,
especially on the indicators. For example, the water
quality rating for a particular section of the river
might increase tremendously because of the creation
of more housing with no increase in the municipal
treatment facilities. Rates of return might drop be-
cause of increased local tax rates or assessments,
higher maintenance costs or service charges, in-
creased competition, etc. Or housing dissatisfaction
might increase because the housing stock has de-
teriorated, rents have gone up, or local government
services have decreased in quality.
The interactions among the various components
of the urban system that cause these interrelated
movements of decisions and indicators is generated
Figure 1.4.—SAMPLE OF INPUTS AND EDITS
INPUTS
Decision Decision
Code ' Maker
$
EDITS
$OUBLD/-A/7012,RB,0,1,50,60,0,145* NO UTILITIES
REQUIRES LEVEL 1 UTILITY SERVICE ONLY HAS LEVEL 0
$OUBLD/-F/8430,RA,6,4*
$FSA/»SC1/2,9030*
AID REQUEST OF SCI FOR 9030 GRANTED
23
-------
by several major simulations contained within the
computer program of the model. The model is in-
different as to how the inputs are generated. That
is, the inputs could be generated as a result of a
game format or by a single model user. The game
format could be capitalistic and democratic in nature
or socialistic.
PERIODIC DIRECTOR INPUTS
The director may act as the outside system by
controlling land purchases, loans, cash transfers,
exogenous employment, federal aid, the business
cycle, and the effects of Mother Nature. These
effects on the local system require computer inputs
on the part of the director. A number of other
influences he may exert on the local system and its
decision-makers are handled in the gameroom and
need no interface with the computer. For example,
the director could impose higher government regula-
tions on the local system in the form of water
quality standards, school quality, or municipal
service standards. The director could also change
player assignments (switch players among several
teams), make some computer information inacces-
sible (or acquired only at high cost), prevent or
encourage team interaction by their physical place-
ment in the gameroom, require rounds to be played
in a specified amount of real clock time, or a number
of other things.
Each director will find that he can affect the play
a great deal and force the local system to deal with
problems created by him if he wishes to exercise
some of these director options. On the other hand,
the director is not forced to make any of these
periodic inputs. The model will continue to function
without his use of these prerogative director de-
cisions.
SUMMARY
Figure 15 summarizes the user inputs to the
model. This figure shows the interaction of the user
(as director or participant) of the model with the
game component and with the phases of the model.
First, as part of "Model Definition" the director has
the option to define parts of the model (parcel size,
jurisdiction boundaries, population-scale, etc.). Sec-
ond, as part of the "Data Base Input" he can input
two types of data—parameter values for the op-
erating programs (for example, coefficients for mi-
gration, typical construction costs, normal units of
production for industries, etc.) and the number and
location of population units and activities (for ex-
ample, residences and the social class of the oc-
cupants, businesses, government buildings, roads,
bodies of water, etc.).
The director makes these decisions once, and
they define the starting configuration of the system
to be represented. The geographical scope of the
region represented by the director is a function of
the parcel size and the number of parcels used to
represent the system. Thus, a single county or a
multi-county river basin area could be represented.
The director also has the option to make no de-
cisions and instead start with one of the two pre-
specified hypothetical configurations.
As a third type of decision ("Teams"), the
director may affect the game format by the allocation
of resources to economic, social, and governmental
decision-making bodies that are called teams. A
final type of director influence is one that he may
choose to exert any time during the operation of the
model. By making inputs to the model (using the
same input format as the participants), the director
can control the outside system influences on the local
system (federal-state aid, business cycle, federal
regulations, etc.) and some local phenomena (flood-
ing, federal employment, etc.).
The participants of the model are members of
teams, and through the teams they become the
decision-makers of the local system. As decision-
makers, the participants establish individual and
collective goals, create any needed institutions (such
as a legal system, mass media, unions, etc.), evaluate
the status of the local system and its constituent
parts, and make decisions for the period of time
represented by a cycle of the model (one year).
These decisions are input at the "Data Implemen-
tation" phase of the model, and they interact with
one another and with the present status of the sys-
tem to create a new status of the system. The new
status is illustrated on the computer output, which
then serves as the basis for new evaluation on the
part of the decision-makers and a new cycle of game
play.
24
-------
Figure 15.—INTERACTION BETWEEN THE USER AND THE RIVER BASIN MODEL
USER
PARTICIPANTS
GAME COMPONENT
TEAMS
DECISION-MAKERS
OBJECTIVES
LEGAL SYSTEM
MASS MEDIA
ETC.
DIRECTOR
MODEL PHASES
MODEL DEFINITION
DATA BASE INPUT
DATA IMPLEMENTATION
INITIALIZATION
MODEL OPERATION
POST MODEL OPERATION
OUTPUT
25
-------
CHAPTER VI
Explanation of the Water Component
To illustrate the interaction among the various
modules that comprise the model, the water com-
ponent will be described in a very brief fashion.
The water component can be looked at as a module
that is plugged into the other major modules of the
regional model. This module could be changed
without changing other parts of the model (and vice
versa) as long as the links among the modules were
modified accordingly. Figure 16 shows the major
linkages between the water module and the other
modules and sectors that comprise the RIVER
BASIN MODEL.
WATER QUALITY RATINGS
In order to summarize and simplify the concept
of "water quality" in the model, an index of water
quality has been created. The value of this water
quality index at any location in the system is de-
termined by the concentrations of the seven pollutant
categories. The higher the quality rating, the lower
the quality of the water.
The average quality rating of water on a parcel is
calculated each round by taking the highest index
caused by any of the seven pollutants dealt with by
the model. Figure 17 shows the water quality level
generated by concentrations of each of the pol-
lutants. An explanation of the table is also included
in the figure.
Each parcel of land that contains surface water
(lakes or rivers) has a water quality index calculated
for it. The water quality raring for a parcel affects
the treatment cost paid by users of that water. The
quality rating also affects the pollution index, the
rate of depreciation for some developments, the
utility of the water, and major recreation activity.
The Water Quality Map (Figure 18) shows the
water quality rating for each parcel of land that has
surface water, the direction of flow of rivers, the
location of economic activities (including farms),
and the individual pollutant responsible for the water
quality rating.
WATER USE
All private economic activities require water as
part of their normal operation. Some of the manu-
facturing activities are surface water users, and they
must intake water from the parcels on which they
are located. All of the other activities use munici-
pally supplied water (except those few residences
which have private water supplies).
Surface water users pay for the cost of treating
the water they take from the local water system.
Municipal water users pay the price charged by the
Utility Department. The Utility Department must
construct intake facilities and treat the water if
necessary to supply the water needs of each utility
district.
POLLUTION GENERATION AND
MONITORING
All economic activities return their used water to
the local water system. Surface water users may opt
to treat all or part of the water they return to the
system with one of four types of treatment. The
other economic activities return their water to the
water system via the outflow point of the utility
district in which they reside.
The Water Office of the Utility Department may
determine through the operation of sampling sta-
tions the detailed components of the water quality
rating for any water parcel (the ambient water
quality) or for any point source of water outflow
26
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Figure 16.—INTERACTION BETWEEN THE WATER MOUDLE AND OTHER
PARTS OF THE RIVER BASIN MODEL
pollution index
t
water quality rating
available water
Flooding
water standards
penalties
col if orm index
construction costs and
land requirement
cost of operation-
extra cost to cross bodies
of water
recreation
Migration-Housing Module
residential water use
—ft Depreciation Module
Farm Ope ration
- fertilizer
Business Operation
water costs
intake treatment
outflow treatment
fines
- pollution
Social Operation
water costs
time allocation (sickness)
- pollution
Utility Department
water supply
operating costs
intake points
intake plants
intake treatment
waste disposal
outflow points
outflow plants
pollution
- sampling stations
Highway Department
road construction
Major Recreation Areas
Operation
27
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FIGURE 17—Definition of the Nine Comprehensive Water Quality Levels
Water Quality Levels
Pollutant Types
BOD (LBS/MG)
Chlorides (LBS/MG)
Nutrients (LBS/MG) .
Coliform
Bacteria (parts per MG)
Temperature
Oil & Floating Solids
High Level Wastes
10
5
25
2
0
o
0
20
10
50
6
0
o
0
30
15
100
12
1
o
o
40
20
200
20
2
o
o
60
30
400
40
4
o
o
100
40
800
70
7
>o
0
150
60
1600
120
10
>o
0
300
80
3200
160
14
>o
>o
> 300
> 80
>3200
> 160
> 14
> o
> o
Explanation of the Table
In order to determine the water quality level or index of given amounts of water, take the concentrations of each of the seven pollutant
categories and calculate the water quality level based upon each pollutant separately. For example, a BOD concentration of 25 LBS/MG would
yield an index of 3, coliform bacteria of 169 parts per MG would yield an index of 9, and the presence of oil and floating solids would allow
the water quality to be no better than 6. The worst (highest) water quality index that was calculated using the pollutant types separately, is
assigned to the given amount of water. If the water on parcel x had the three pollutants described above, it would be assigned water quality
index of 9.
Looked at another way, water quality level 4 is attained when a body of water has concentrations of BOD that exceed 30 but fall below
41, coliform bacteria concentrations above 12 but below 21, etc.
(from surface water industries or from the municipal
outflow point).
Surface water using industries and the municipal
water offices may treat their water outflow to reduce
its concentrations of pollutants.
EFFECTS OF THE WATER QUALITY INDEX
The Water Quality Index on a parcel of land has
direct effects on the following factors:
• Treatment costs of water withdrawn from
that parcel by the Water Department.
• Treatment cost of water withdrawn by an
industrial surface water user on that parcel.
• The amount of personal consumption ema-
nating from Major Recreation Areas located
on or near that parcel.
• The pollution index for that parcel.
The Pollution Index is a part of the Environ-
mental Index which is used as a basis for determin-
ing the attractiveness of a residential parcel of land
for potential in-migrants. A high Pollution Index
also affects the probability of population units mov-
ing away from a residential parcel.
The Health Index for a parcel of land influences
the amount of money spent by population units for
health services and the amount of time lost from
leisure activities. It also affects the Personal Index,
which in turn influences the amount of dissatisfac-
tion experienced by population units on a parcel.
The Health Index for a parcel of land is based upon
the concentration of coliform bacteria in the water.
This is the only case in which a single component of
the water quality index is handled separately.
All of the dissatisfaction indexes and quality of
life indexes are calculated in such a way that a high
value indicates high dissatisfaction or low quality
of life. In Figure 19 the components of the Quality
of Life Index are illustrated. For each of the indexes,
the corresponding dissatisfaction term is provided in
parentheses.
Note that both of the components of the Environ-
ment Index are indexes which are based entirely
upon locational quality factors outside the direct
control of the social decision-makers. For example,
social teams can only indirectly affect water quality,
school quality and local tax rates.
The Personal Index, on the other hand, is com-
prised of two indexes, one of which is based on
locational quality factors while the other is based
upon time allocation decisions that are largely within
the control of the social decision-maker.
28
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RAYWID CITY
** FIGURE 18'*«"«»**»»««»«*«
HATER QUALITY MAP
:*******************
ROUND 0
70
98 100 102 104 106
*************
110 112 114 116 118
12
14
16
IS
20
22
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
59
60
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1 1 1 1 1
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RA18I3S 3|NI 4|MP 1IMF 3IPG 3
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TE 3IRB13IBS 4IFO 1IRCI1IRC12
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CR 1< F 51 f SI F 51
1 < 1 1 1 1 34
< 1 1 1
ISG 1IR810IPS 41 1 AV< DIRECTION OF FLOW
NO MATER FLOWING
BETWEEN PARCELS
29
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Figure 19.—COMPONENTS OF THE QUALITY OF LIFE INDEX
Pollution Index
(Pollution Dissatisfaction)
Dependent Upon
• Water Quality Rating
Neighborhood Index
(Neighborhood Dissatisfaction)
Dependent Upon
• Housing Quality
• Rent Charged
• School Quality
• MS Quality
• Tax Rates or Welfare Payment
Health Index
(Health Dissatisfaction)
Dependent Upon
• Coliform Count
• Residential Crowding
• MS Quality
Environmental Index
(Environmental
Dissatisfaction)
i
Quality of Life
Index (Total
Dissatisfaction)
Time Index
(Dissatisfaction with
Time Allocation)
Dependent Upon
• Involuntary Time
• Transportation Time
• Recreation Time
1
Personal Index
(Personal
Dissatisfaction)
30
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CHAPTER VII
The Computer Programs of
the RIVER BASIN MODEL
Each cycle or round of the model consists of
users evaluating the status of the local system, inter-
acting with one another, making decisions, inputing
these decisions to the computer, and running the
computer program to generate a new status for
the local system.
Regardless of what decisions are input, the model
executes the same major operating programs in the
following sequence:
Migration-Housing
Water Quality Calculations and Effects
Depreciation
Employment
Transportation
School Allocation
Tune Allocation
Commercial
Bookkeeping
MIGRATION-HOUSING
The basic population grouping in the model is the
population unit (PI). A PI is designated as being a
member of a socio-economic class. The one thing
the three classes have in common is that 500 people
comprise a PI. Pi's move into, within, and out of
the local system in response to available employ-
ment opportunities, housing quantity and quality,
and a number of other factors.
This computer routine calculates dissatisfaction
(environmental and personal); develops a pool of
movers comprised of the population displaced by
housing demolition, a percent of the most dissatis-
fied, a percent of the total population (random
movers), natural population growth, and the in-
migrants; and moves the members of this pool into
housing that has adequate capacity and quality. A
certain percentage of each income class that are
either unemployed or underemployed outmigrate
from the local system. Other movers who cannot
find adequate local housing also become outmi-
grants.
Water quality affects migration through the en-
vironmental dissatisfaction (housing near polluted
water becomes less attractive) and through the per-
sonal dissatisfaction (bad health resulting from
nearby polluted water increases the probability of
moving).
WATER QUALITY CALCULATION AND
EFFECTS
The water quality on each parcel of land that
contains water is calculated by combining the pollu-
tion flowing into the parcel from up to three up-
stream sources (water from adjacent parcels) with
the quantity of water on the parcel. This mixing
process generates a water quality index for water
on that parcel for all users on that parcel (industries,
municipal water systems, and major recreation
areas). That portion of the water which is not with-
drawn has a certain amount of pollution disappear
based upon the rate of flow of the water. All water
returned to the water system on that parcel (in-
dustrial waste, municipal outflow, and farm run-off)
is combined with the water not withdrawn, and a
calculation of the total amount of pollution sent to
the next parcel downstream.
This process is performed for each parcel of land
that contains a moving body of water. The opera-
tion of industries, municipal water systems, farms,
and dams affect the water quality along different
stretches of a river. The water quality then affects
next year's migration and this year's depreciation
31
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and commercial activity (via major recreation areas)
as indicated in the following sections.
DEPRECIATION
Buildings and roads depreciate in value and utility
each year as a function of the passage of time
(obsolescence), the amount of use they receive
(wear and tear), and the quality of local municipal
services (especially police and fire protection).
Local decision makers may choose to maintain a
constant value for their developments by expending
the required amounts of money for maintenance.
This routine depreciates all developments and cal-
culates maintenance expenditures.
Three additional water-related factors can also
contribute to the rate of annual depreciation of
developments. First, industries that draw water di-
rectly from nearby water supplies have an additional
depreciation that is in proportion to the water
quality rating of the water they use. Second, for
utility districts that have insufficient supplies of
water, there is an additional depreciation that re-.
fleets above average fire damage due to inadequate
water for fire fighting purposes. Third, develop-
ments may experience increased depreciation as a
result of flood damage. This damage is related to
the severity of the flood (input by the director), the
type of building, its location in the flood plain, and
the flood control priority of dams for the river basin
(if there are any).
EMPLOYMENT
All Pi's in the local system compete with one
another for jobs in the local labor market. Likewise,
all employers compete to hire workers with the
highest education levels. There are two types of
employment—full-time and part-time.
The full-time employment routine assigns popula-
tion units (high income first and best educated first)
to full time jobs based on the assumption that
workers will attempt to maximize their net salary
(salary received minus transportation costs using
last year's transportation cost figures). Pi's will take
jobs in the next lower class if none are available in
their class. The part-time employment routine as-
signs part-time workers (80 time units in part-time
work equals one full-time job) to part-time jobs on
the basis of best education first. The number of
time units allocated to part-time jobs is set for each
group of Pi's on a parcel by the social decision-
makers. If time is allocated for part-time work, but
not enough part-time jobs exist, the dissatisfaction
of the Pi's is increased.
If plants that are causing water pollution are shut
down or forced to curtail output, then the reduction,
in the required labor force will have its repercussions
throughout the system. The employment routine
treats the former employees of the shut down plant
as unemployed at the start of the routine and assigns
them to other jobs if extra jobs are available in the
local system.
TRANSPORTATION
Pi's that are employed are assigned to a mode of
travel and to a specific route by this computer
routine. Taking the origins (homes as determined
in migration) and the destinations (jobs as de-
termined in employment) this allocator assigns
workers to transportation mode and routes in an
effort to minimize total transportation costs (dollar
costs plus the dollar value of time spent) subject
to the constraints imposed by public transit capacity,
road congestion, and transportation boycotts.
Each employer may offer a unique salary; Pi's
from a single parcel may be employed at several
different locations, and three transportation modes
(auto, bus, and rapid rail) may be considered.
Government decision-makers may affect the trans-
portation access (and thereby indirectly affect em-
ployment choices) by choosing where to build roads
of different capacities, where to run bus lines, what
fare to charge, and where to build and operate rapid
rail service.
SCHOOL ALLOCATION
Each PI contains a number of school age children
who attend public schools, if the public schools are
available and meet quality criteria that differ by
income class. This routine assigns students by class
(low class first) to public schools or private schools
based upon school quality criteria (quality of plant
and equipment, quality of teachers, and the student-
teacher ratio) and capacity of the school serving
their district. Population units who send their chil-
dren to private schools as a result of local public
school deficiencies must bear the cost of such private
education.
32
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Another school allocation routine assigns adults
from Pi's to public adult education programs in
proportion to the amount of leisure time allocated
by Pi's to such programs. The local education au-
thority provides public adult education programs by
hiring teachers and using existing educational facili-
ties. If Pi's are not able to spend as much in adult
public education programs as they wanted, then
their personal dissatisfaction increases.
TIME ALLOCATION
For each PI grouping, time spent in transportation
is deducted from a total of 100 units; then time
spent in part-time employment is deducted; public
adult education time is deducted; private adult
education costs are determined and the time is
deducted; voter registration is changed as a result
of the time spent in politics and the time is deducted;
and time is deducted for time spent in recreation,
and consumption of PG and PS is increased above
the normal amount. The remaining time is labeled
"involuntary" time, which contributes to the level
of dissatisfaction calculated for the following year.
COMMERCIAL
*»
Each PI grouping must purchase units of personal
goods and units of personal services each year.
Establishments that sell personal goods and personal
services must sell exclusively to local system de-
manders. These establishments compete with one
another through locational advantages and by prices
for a unit of goods or services sold. In the com-
mercial routine, the purchases (normal and rec-
reation-related) of the population groups on a
parcel and residential maintenance expenditures are
allocated to personal goods and personal services
establishments using the criteria that establishments
have a limited capacity and that shoppers attempt
to minimize total costs (sale price plus transporta-
tion charges).
In a similar fashion, purchasers of business goods
and business services must buy annually from BG
and BS establishments. These establishments com-
pete with one another to supply the local demand.
In the commercial routine, the purchases of busi-
nesses (including personal goods and personal
services establishments) for normal operation and
for maintenance are allocated to business goods and
business services establishments based upon the
same criteria as above (an infinite-capacity outside
supplier sells goods and services at prices in excess
of normal local prices).
The amount of purchases from local personal
goods and services establishments is affected by the
normal amount of business generated by Major
Recreation Areas and the present quality rating of
the water bodies serving those recreation areas.
Thus, consumption at local stores will rise some-
what with good water quality and fall with poor
water quality. This consumption is assumed to be
made by tourists from outside the local system.
BOOKKEEPING
This routine makes all the final calculations of
incomes and expenditures and of indicators for use
in the detailed computer output to the economic
activities and teams, the social decision-makers, the
government departments, and the summary statistics.
33
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CHAPTER VII!
Summary of the
RIVER BASIN MODEL Design
DESIGN ASSUMPTIONS
The basic design assumption of the model is that
if the major activities that take place within a
regional area are represented and related to one
another, then the actual demands for water quantity
and quality will result from the operation of these
activities. Furthermore, the realistic way in which
water resource decisions and their impacts affect
the urban system can only be represented in a
holistic model that incorporates public and private
decision-making.
The major decision-making actors are business
(the economic sector), the local population (the
social sector) and public policy makers (the gov-
ernment sector). They interrelate with one another
in a physical and institutional environment that takes
into consideration spatial relationships, ties to a
larger outside system, and allocates goods, services,
labor, incomes, etc. by a number of market opera-
tions.
The major markets are:
Interrelationships with the Outside System
Migration and Housing
Employment and Transportation
Commercial and Transportation
Time Allocation
Public Goods and Services
Allocation of Financial Resources
Demand for and Supply of Water
The four basic building blocks of the model are
business types, population units, government func-
tions, and parcels of land. All of these factors are
dealt with in a micro manner. That is, an individual
population unit (representing a given number of
people with loaded or derived characteristics) finds
housing at a specific location, is employed by a
specific employer (if in fact it is employed), shops
at designated locations, etc.
BASIC BUILDING BLOCKS
Much of the design effort associated with the
development of the RIVER BASIN MODEL was
spent developing general and usable concepts of
land parcels, business activities, population units
and government functions. A general concept is
required so that any area in the continental United
States can be represented. The concepts must be
usable in the sense that the users of the model are
able to understand the basic system relationships of
the model and the statistical output generated by
the computer within a relatively short period of
time.
Parcels of Land
The geographical area represented by the model
will be comprised of land parcels. A parcel of land
has the following characteristics:
» A place from which distance to other parcels
is measured.
• A size (number of acres or square miles), a
shape (square) and a unique identification
number (pair of coordinates).
• A number of constituent percents of land.
• A single owner of the privately owned
portion of the parcel.
• A single zoning classification.
• A single private land use.
All geographical areas (such as political jurisdic-
tions, special districts, river basins, flood plains, etc.)
are defined in terms of full parcels of land.
34
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An important characteristic of the sum of all the
parcels, which define the map boundaries, is that
they define the geographical limits of the local
system. All activities and decision-makers that are
outside of the regional boundaries comprise the out-
side system. There may be some activities (Fed-
eral installations and state institutions) and some
decision-makers (at the Federal and state level) that
are physically within the boundaries of the region.
These activities and their employment impacts are
part of the local system, but their policy is made as
part of the outside system (exogenous).
Business Activity
The RIVER BASIN MODEL contains business
activity within four categories: manufacturing, com-
mercial, residential, and farms. Within each of these
categories there may be many specific business types.
For example, eleven types of manufacturing may be
represented, five types of commercial, three types of
residences and five types of farms. Business activities
must be located on parcels of land. The production
function for each manufacturing and commercial
business is dependent upon the quantity and quality
of plant and equipment, and the amount of labor
hired.
35
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PART II
-------
CHAPTER IX
The Research Project
To test the utility of the techniques developed in
the RIVER BASIN MODEL (and its sister CITY
MODEL), a study was implemented which made
use of the model for educational purposes (rather
than research or policy making) in a variety of dis-
ciplines and university situations.
The brief summary above should suffice to give
the reader an overall impression of the model. The
next chapter will focus on the meetings held with the
participants.
The study design chosen consisted of picking a
half dozen professors from different universities who
were specialists hi distinct disciplines. It was further
decided that the model would be.run for a full year,
meaning that each professor would have an oppor-
tunity to run the model at least twice. Finally, there
was an attempt made to use the model on both
undergraduate and graduate classes and with varying
numbers of students. The professors and universities
included:
• John Sommer (Geography), Dartmouth
• Maury Selden (Urban Real Estate), Ameri-
can
• Philip Patterson (Urban Economics),
Georgetown
• Robert Barrett (Urban Affairs), Mankato
State
• Robert Dean (Urban and Regional Studies)
Memphis State
• Allen Feldt* (Human Ecology) Cornell
The actual running of the model was to be carried
out by Envirometrics' staffers while the conduct-
ing of the model was to be done at each university.
Contact was by phone, mail, and through full par-
ticipant meetings in Washington.
*Due to some unexpected demands on his time, Pro-
lessor Feldt was not able to fully participate.
Support for this project was provided by National Sci-
ence Foundation Grant Number Y008433.
For the first and second meetings with the par-
ticipants we met to discuss problems with the study
and to try to discover methods of improving the
runs. The third meeting was summarial and merely
focused on wrapping up the task itself.
The discussions were carried out very informally
with a representative of NSF present.1 Following
are some of the topics discussed and conclusions
reached.
A. There did not appear to be any easy method
of introducing,the material contained in the model.
We loaned the participants two film documentaries
of the games produced by NBC. Further, we made
available a number of slides and tried to teach the
participants how to introduce the model.
As a result, the first few months of the run were
a tribute to the tenacity and integrity of the pro-
fessors as they stumbled and fought their way
through the model with the students. The second
time around was considerably easier as the profes-
sors devised their own teaching formats and per-
sonalized the introductory lectures. One professor
devised his own visuals of CITY and his students
produced a video tape designed to teach the model.
B. All of the participant professors had to change
the reading lists assigned to their courses. They
found that the syllabus used previously was no
longer adequate to incorporate the breadth of sub-
ject matter covered with the Laboratory.
C. They all found that the model ran best when
the political leader was dynamic and aggressive.
Also, unless the professor began to make active use
of the model to demonstrate theories or to allow
innovative decision-making, the students became
bored because they had learned many of the
mechanics of the model by the third or fourth round.
D. The students tended to take over the lab as a
source of self-study. One theme became clear: there
should be a central laboratory which would allow
39
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students and professors continuous access to the
model, regardless of course.
E. The users felt that there was a need for more
information which was not provided by the model.
Consequently, everyone used a form of mass media,
including one or more newspapers and a video tape.
F. The model was too much for the professors to
run themselves; consequently, each professor had to
obtain help from the participating students or faculty
or assign one of their graduate students to the
project.
G. All of the users found that the model ran
better the second time if a general goal or strategy
for the students was pre-assigned.
H. There were a number of difficulties with mis-
understood or mispunched input cards on one hand
and poor turn-around on the other.
I. There was a general need for a visual of some
sort to be used by the players so that they could
see the impact of their decisions.
J. At the end of the first meeting, the users dis-
covered that they had only played the game from
one of an infinite number of possible starting posi-
tions. They all opted to continue with the same
starting position rather than a new one, however,
since they did not feel confident enough to tackle a
quantum jump in complexity so early in the game.
One professor did continue his city development
rather than begin again.
K. The professors all ended with a feeling that
use of the model would be a part of the next year's
courses and that it would not be difficult to run.
The amount of time that they were required to
expend to learn the model was considerable. In
fact, one or two said they might not have taken
part in the project had they known that it would
have taken so much time. However, at the end of
the project, they felt that the time expenditure was
well worthwhile.
L. An environmental laboratory is to remain at
least at three of the schools and is to be used not
only to teach students but is being spread to the
local community for use in action programs and
local education.
In summary, the problems with the program were
all technical rather than substantive. The professors
chosen did not all have prior experience with games;
indeed most had never used a model. They came
from a variety of disciplines and faced graduate and
undergraduate students, in small as well as large
numbers.
In the sections to follow are their own reports,
although they were all asked to follow a similar
format. In spite of the fact that the professors all
started with the same introductory City (Blue City)
and were asked to loosely follow a single format,
the individualism which grew out of the study is
most striking. This finding, like the others, is highly
pleasing and helps to attest to the success of the
idea of a single laboratory, which obviously can be
used by different professors without placing them in
a situation of artificial constraint.
The reports range in emphasis from how the
professor used the laboratory, to additions which
students made, and finally, to the validity and use-
fulness of the tool. Again, these reports stressed the
richness of this technique.
40
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CHAPTER X
Blue City on a Green Landscape:
A Gaming-Simulation at Dartmouth
by John Sommer
INTRODUCTION
During the past five years there have been few
teaching members of Academia who have discovered
themselves to be immune to the urgent press for
new, exciting, teaching innovations. This past demi-
decade has thrust an entertainment-jaded student
generation into the university classroom where many
of them believe they have paid to be amused, as
well as educated. The response of the teacher to this
set of expectations has fallen somewhere between a
national tragedy and a national scandal: that is,
many university faculty have sought "relevance"
through "podium rhetoric" or the studied adoption
of the stuttering phrases of the youth culture, rather
than through presentation of their philosophical
justifications for the kinds of knowledge they purvey.
The extensive "knowledge-shaming" and "instant-
erudition" that infuses so many campuses today is
unfortunate, and dangerous to the reputation of
Academia as a haven for unfettered learning.
In recognition of the problem of exciting this
generation of students with the quest for knowledge,
and doing this without sacrificing some heavily
paid-for scholarly traditions, I sought to introduce
some changes in the Urban Studies and City Plan-
ning Program at Dartmouth College. As the new
head of the Program in 1969 I had been made
aware of the CITY I gaming-simulation developed
by the individuals who later founded Envirometrics
I then participated hi a round of CITY I in Wash-
ington and decided that the gaming-simulation had
enormous merit as an effective teaching device. For
us at Dartmouth, the prospect of utilizing a gaming-
simulation model to complement our urban field
programs (in Boston and Montreal) seemed ideal.
From this initial contact my participation in the
project unfolded. I had no previous experience with
modeling.
Our Urban Studies Program has more than one-
hundred "concentrators" (they major in a discipline)
but we have the capability of placing only about
fifteen a year into an actual city environment. Some
students chafed at the difficulty of "doing urban
studies" in a rural area and raised some valid ob-
jections to our normal curriculum. Most of the
students (largely majors in geography, political sci-
ence, or sociology) take at least six courses from
our program, but among these we had few offerings
other than the survey and seminar type. The CITY
MODEL offered us some new, valuable opportuni-
ties, and we seized them. This was done by inserting
the gaming-simulation into our regular curriculum.
This report describes the experience we have had
with the BLUE CITY sequence of the CITY II
model during this academic year 1970-1971, where
I employed the gaming-simulation in two distinct
courses. Part II of this report describes the courses
in which it was employed, including their structures
and educational goals. Part III presents some tenta-
tive analysis of the dynamics of our play during both
courses, and Part IV hazards some conclusions
about the use of the CITY MODEL in undergrad-
uate education from our experience at Dartmouth
College.
COURSE DESCRIPTIONS
Modest flexibility in our curriculum and course
content allowed us to employ the CITY MODEL
41
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immediately in two courses; however some serious
constraints were introduced by our short term (10
weeks), the schedule of class hours which are diffi-
cult to rupture, and the responsibility to cover
certain materials in our courses which are not
within the context of the CITY MODEL. These
constraints, as well as the manifold possibilities,
operated differently in the two courses in which the
model was employed.
This portion of the report treats with Geography
10, The City of The Future (a freshman seminar,
during the Fall), and Geography 52, Urban Geog-
raphy (an advanced lecture course during the
Spring). Students from two other courses, as well
as some non-course individuals took part in the
gaming simulations: during the Geography 10
rounds sixteen of Professor Frank Smallwood's stu-
dents from Government 31, Urban Government and
Politics, took part in the play. During the Winter two
experimental rounds were run (and later regretted)
with Geography 42, a course in theoretical
geography.
Geography 10
This freshman seminar was the first I had taught
and also the first college course for the sixteen men
hi the class. The aim of the course was to introduce
these students to a seminar style of schooling as well
as to the general content of urban studies. A dis-
ciplined structure was played down rather than
emphasized. Some provocative readings were se-
lected for discussion and the CITY MODEL was
employed to help students act out ideas they were
beginning to acquire, or had previously acquired
about the city.
The course met twice a week for two hours,
thereby allowing us the minimum time needed to
complete a play of the model. In fact, I bargained
with the students to have all of our other classes
last 100 minutes if they would set aside 200 minutes
whenever we ran the model. Generally, this time
trade-off was successful with the freshmen, but it
was somewhat less successful with the students from
Government 31 who were, in effect, being excused
from three, ten page book review assignments for
this participation in the model. A few of these stu-
dents believed the time trade-off was weighted
against them despite their interest in the gaming-
simulation.
The model was run six tunes during the term, or
roughly every fourth class period. This allowed for
about ten days between runs, which was good from
the point of view of physical turn-around time from
Envirometrics, but it was judged poor by the stu-
dents, whose interest flagged while waiting for the
return of the computer output. Two formal dis-
cussions of the model were scheduled during the
term, not including the introduction of the model
but these discussions focused more on the dynamics
of the play than on the driving mechanisms of the
Model. The fact that these mechanisms were not
wholly accessible to us was not important during
the Fall when we even failed to make full use of the
information provided in the City Manual, but during
the Spring this circumstance became more of a
problem with the advanced students who wanted to
test some hypotheses.
Students were told at the beginning of the term
that their participation in the Model would count for
one-quarter of their final grade; This proved to be a
greatly subjective element of the grading process
because it was difficult to follow what each person
was doing to arrive at his interactions and decisions.
This was not troubling intellectually but it did raise
a question about mixing the nature of the course—
particularly for the larger Geography 52 course in
the Spring Term.
Geography 52
Urban Geography is a lecture course which ac-
commodates 40-50 students. Because it is a "core
curriculum" course in our Urban Studies Program
almost all of the students have had at least one
urban studies course before taking Geography 52.
Unfortunately, only about half of the students have
had a course in geography. These circumstances
sometimes make for a slow "lift-off" for the course
because "in-filling" is required for the non-
geographers.
The course meets three times a week 9:05 a.m.
to 10:20 a.m. but again I was successful in trading-
off the Saturday meeting of the class for a Tuesday
evening meeting from 6:30-8:00 in order to run the
model; in fact we never finished a Tuesday session
before 9:30 p.m., a situation that created some
problems in the latter part of the term.
I have given this course a half-dozen times and
the aims of the course have been to introduce urban
studies students to the spatial aspects of urban
phenomena, and to provide geography students an
intellectual arena in which to test ideas of the spatial
organization of human activities. There is some
responsibility to cover certain materials in the course
for the sake of both the Urban Studies Program, and
42
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the Geography Department; therefore there is less.
room for experimentation than in a Freshman
Seminar.
Required readings for the course were' aot ex-
tensive, but each student was provided with supple-
mentary reading lists and asked to consult them
regularly. Both the required and suggested readings
were designed to support discrete lectures and gen-
eral topics respectively. There was no assigned
reading on games, simulation, or modeling, although
some of the students sought references on these
subjects by the end of the term, even to the point
of creating some of their term projects along gaming
lines. The readings, then, were not specifically de-
signed to support the use of the CITY MODEL, but
it was believed that ideas from the reading would
come into play if they were perceived as usefal.
The CITY MODEL was used as a supportive,
"imploding" element in the Geography 52 course.
My participation in the Model was greater during
these rounds than those run during the Fall, but in
general I remained in the role as a technical as-
sistant, organizer, and manager. This was planned,
but it would have been forced on me anyway simply
by the pressure of handling the details of the Model.
Our scheduled discussions about the CITY
MODEL during the Spring were more analytical and
comparative than those in the Fall for the obvious
reason of experience with the model as well as a
more advanced group of students. These discussions
were often speculative with respect to the nature of
the model but frustrating because we knew that tfee
Model would remain an "opaque substance" until
we could truly subject it to experiments.
Grading participation in the Model was no less
easy for Geography 52 than for Geography 10,
especially since three of the forty-one students could
not meet at the newly scheduled hour, but this
situation was solved, in part, by introducing a new,
and very exciting gaming-examination called, THE
MUNIFICENT HEXAGON. Along with employ-
ment of the Model itself this examination provoked
more favorable reaction among students than any-
thing I have experienced during my teaching career.
Summary
The CITY MODEL was employed as an integral
part of two distinct courses during the academic
year 1970/1971. No course could be specifically
designed to focus solely on the Model. Insecurity
over my own abilities to direct a full model-based
course, and insecurity introduced by having to rely
on an outside source (Envirometrics) for the con-
duct of the course were too great to allow for un-
restrained investment. It is my conclusion from
considering the course structures of both Geography
10 and Geography 52 (in light of the goals of these
courses, within the context of the Geography Depart-
ment, and Urban Studies Program,) that a new
course needs to be designed to employ fully the
potentialities of the CITY MODEL, and other urban
gaming-simulatioras. Such a course was designed for
our summer schools 1971 and successfully operated.
It is hoped that tMs success will carry over into our
regular curriculum on an experimental basis during
1971/1972, and regularly after that. Part III that
follows examines the dynamics of the use of the
Blue City sequence at Dartmouth, and although
there will be many points of comparison between
Geography 10 and Geography 52 rounds, much of
the commentary is melded observation.
THE DYNAMICS OF THE MODEL'S USE
Introduction
The introduction of the CITY MODEL is un-
doubtedly the most difficult aspect of its use because
this is the point of ultimate ignorance of the players,
most of whom have not gamed before. There is a
real tension between the need to introduce the
model, despite its massive and complex charac-
teristics, and the need to allow play to proceed
without the gamemaster introducing his own biases
into the group of players. It is significant that play-
ers and professor alike perceived this to be the
crucial point of the model's use and strived together
to make it more readily understandable to later
players by creating a videotape introduction. It is
worthwhile discussing some aspects of the introduc-
tion of the model before proceeding to an analysis
of play.
It is obvious that the gaming experience of most
college students is limited, so the starting point for
this kind of education is assumed to be zero. Un-
fortunately, after reading the City Manual (version
of August, 1970) the student's knowledge about the
model, gaming, and his role in the gaming-simula-
tion, did not increase greatly. Two reasons account
for this: first, that version of the manual was not
very clear and the errata were numerous; second, it
was difficult for the student to believe that he was
required "to leara" the Manual for the purpose of
a game. Specifically, that version of the Manual
43
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desperately needed cross-referencing to speed up the
student's ability to find out what he needed in dis-
crete situations. In a few cases where errata existed
(and were soon thereafter corrected by Enviro-
metrics, Inc.) the most serious players became con-
fused. Probably as important a factor was the failure
of many players to familiarize themselves fully with
the Manual before convening for the first play. They
did their homework later, after they discovered the
gaming-simulation to be a serious matter.
It was very important to employ the scenario
walkthroughs provided by Envirometrics prior to
our first run; now the more recently developed
'Thumbnails" may give added support for the
initiates. There was a great deal of fumbling in the
beginning of play and some guidance and suggestion
was necessary simply to inform players of what they
could do.
A serious question must be raised about the "in-
flection state" of the model because it was discovered
that the original board layout and the brief scenario
provided go a long way toward determining later
play and later configurations. For this reason I
believe that the gamemaster should be especially
careful when deriving a scenario, in order not to
predicate the play. Normally the raison d'etre of
the original scenario is expunged by the end of three
rounds of play but there are certainly locational
decisions and human interactions produced by the
original scenario that linger much longer. It was
discovered too that in a simulated decade of play
the land use did not shift markedly, so one can assert
that the original board layout had much to do with
later play. This phenomenon of conservation, or
pattern maintenance, was generally unruptured until
"end-game phenomena" took over and players be-
came more speculative.
The actual preparation for play at Dartmouth
involved the following steps: a) an introductory
lecture on the game, preceded by a reading assign-
ment, b) display of materials, c) assigning of teams
and roles. The introductory lecture involved a dis-
cussion of gaming, a description of the three sectors
and then* output, and a demonstration of inter-
relatedness in the model, using the processes of
migration, employment and commerce as examples.
It was explained to the players that the gamemaster
could not possibly answer all of their questions and
that it was incumbent upon them to work out most
of their problems alone. Most of the students had
read the manual (but not carefully), before the
lecture and many elementary questions were asked
at this session.
Following the lecture the class was made to walk
around the game room (which later acquired the
name, URBAN/REGION SIMULATION LAB-
ORATORY), to examine the "public information"
from the first round of the game, stopping at each
set of data sheets (e.g. Personal Goods materials)
and discussing some kinds of intefactions that were
revealed in the data. This exercise never was as
successful as I had hoped it would be because the
players seemed to ignore much of the data that were
provided them, yet persisted in asking questions for
which data were available.
Teams were then assigned, largely on the basis of
preference. In some cases a flip of a coin was used
to assign persons whose preferences were in conflict.
During the Fall Term I put an older student with a
younger student, and during the Spring Term I put
experienced players with inexperienced players ir-
respective of age or class. This strategy worked
well, as evidenced by the close cooperation and
friendship that developed among players. In all cases
players were assured that sometime they would play
a different role. This assurance was not possible to
honor in all cases but a real attempt was made with-
out any feelings being ruffled.
It was extraordinarily fortunate that we had the
use of a set of rooms, particularly one large game
room, for the duration of the model's use. Two walls
of our main room were cork board and one was
chalk board, thereby facilitating information flow.
The game information could be left on the walls
during the inter-play periods and the team data
sheets could be kept nearby for ready consultation.
A 75" x 75" game board was mounted on one
wall and it proved to be the focus of attention in
much of the play. This board, and another de-
veloped by one of the students (shown hi the
videotape), were used for large scale planning by
each sector. During the second set of runs a new
position was created—that of Boardmaster, whose
main job was to provide immediate and accurate
representation of changes in the configuration of the
patterns displayed on the board. This player also
did a landuse summary at the end of play.
Aside from the large room with movable tables
and chairs, three other rooms were available most
of the time and these proved useful for private
meetings of the different sectors; indeed, during the
second set of runs each sector was assigned a differ-
ent room. One central room had two teletype
44
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terminals tied into our computer system; these were
used by players to leave messages for one another
after we developed a safeguarded Message Center
system.
Such were the conditions of introduction to the
play and to the physical surroundings of the gaming
area. Considering the lack of a true gaming center
we did well to find and use these kinds of facilities
which aided the introduction of the Model, as well
as they facilitated play. The need for better intro-
ductory procedures was still felt early in the second
set of plays, and a group of six students took on a
special project of developing a videotape introduc-
tion to the model. The tape developed was tech-
nically sound and highly informative. The tape was
played for more than 120 delegates who came from
all over the United States to attend a Conference on
Computers in Undergraduate Curricula, held at
Dartmouth during late June. The tape was accom-
panied by a talk on urban gaming models, especially
the CITY MODEL. The tape and talk were warmly
received. The tape was also used to introduce a
Summer School class to the model, and although it
seemed to help launch the play it is too soon to
assess the results.
Trend of Play
The trend of play differed radically from the Fall
run of the model to the Spring run; the difference
may be characterized as a shift from idealism to
realism, from cooperation to competition, from
"getting it together", to just plain "getting it".
Certainly there are many reasons for this shift but
I have been able to identify only three with surety.
One, the model, with its pre-digested scenario be-
came the object toward which competition was
directed and students pulled together to beat the
"given" system. Two, an unusually charismatic stu-
dent leader was the Fall term chairman, and he
chose to try to pull all elements of the city together.
Three, during the Spring term we began play with
the three sectors hi different rooms rather than to-
gether (as was done during the Fall), and the result
was heightened suspicion between sectors. In addk
tion, by Spring Term the experienced players
gravitated toward the roles of the economic sector,
leaving the social sector relatively poorly staffed.
Due to some special circumstances of play the
evaluation that follows is comparative, that is, over
the period of four rounds the play from the Fall
*Much of the economic sector evaluation was prepared
by two student assistants. Bill Price and Richard Schwager.
Term and the Spring Term were parallel rather than
sequential. Due to a lost tape at the beginning of
the Spring Term it was necessary to play rounds 4
through 7 over again. At first this was perceived as
a problem but later it was considered an asset be-
cause it afforded the possibility of reasonable com-
parison of play in a way that might not otherwise
have been achieved. The economic and the govern-
ment sectors are formally compared here but the
social sector activities are better treated in a non-
formal sense because the most interesting activities
of the social sector were outside the model.
Economic Sector*
Through these two comparable runs, one can
discern the differences and similarities in behavior of
economic sector players for each run and the under-
lying constant factors involved in the CITY MODEL
itself. Blue City, in all respects, is a small urban
area, even as of Round 7: there is only one con-
struction company, one business goods establishment
and one business services outlet. There are only two
developments of each type of national industry.
Even in the two personal services businesses and
three personal goods outlets, these industries were
plagued with recurrent overcapacity problems in
the face of slack social sector demand. The housing
shortage also contributed to producing a demand for
personal goods and personal services that was less
than it could have been. Blue City would probably
have been just as well off with smaller and healthier
PS and PG.
Data collection was accomplished by separating
each firm into its individual business establishment
components. A complicating factor was the floating
of a negative 6 billion dollar loan from E to B
during the Fall, 1970 Round 7. Unscrambling the
resulting maze of interest payments and debt pay-
ments for each firm was quite difficult. The data was
then summed on two bases—firm-wide and industry
wide, giving, for example, summed results for Eco-
nomic A and also for all RA. The data collected was
chosen in an attempt to measure growth and profit-
ability. For an individual business, these two factors
were respectively measured by total sales/rent and
net income data. For an industry of businesses, these
were summed for all of a particular business over all
firms. For a firm of businesses, growth and profit-
ability were measured respectively by net worth and
cash balance. The resulting data was used to cal-
culate percentage changes to facilitate the detection
of trends. The basic data was also used to compute
45
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a measure of liquidity, (total cash balance -r- net
worth). This was used to indicate the extent of ready
funds on hand, an indicator of growth potential for
Blue City each round. Growth, profitability, liquidity
were finally compared with population by calculation
of correlation coefficients between the various
measures, indicating how closely related some of the
phenomena were in the underlying model, and per-
haps in an actual city.
Data analysis.—The actual data accumulation
involved a sector-by-sector account of economic
decision-makers. An account was made of the sales
and net income of the teams for rounds 4 through
7 of both the original fall '70 runs (by Geography
10 and Government 31 students) and the most
recent spring '71 runs (by Geography 52 students).
An unscientific grasp of the economic progress of
Blue City over these four rounds can be obtained
from this data. The "flow" or total economy shows
a steady rise in "net income", or the value for "net
worth". Among the steady improvers over time were
the 30 RA units, the 10 RB units, and the 6 RC
units, thus increasing gains from residential owner-
ship. The business and industrial operations tended
to be more sporadic in their earnings, reflecting their
crucial necessity of frequently varying sales, suscepti-
bility to utility-tax-extra costs changes, overcapacity,
and dependence upon the mercurial social sector
activities.
These four factors are intuitively observed in
those firms which had sporadic gains—the one BG
unit, the one CI firm, and the two HI industries.
They can also be seen in the two LI and two NS
establishments which had slowly increasing sales
and incomes and especially in the one BS firm, the
two pathetic PS units, and the three PG firms which
suffered enough to lose money regularly. The CI
firm's sporadic gains resulted from a periodocity of
demand and occasional utilization of the outside
system for construction. The PS and PG units com-
bined $108 million deficit for New round 7 (vs.-$51
million for old) come from a distinct over-capacity,
that is an ingrained underdemand for Blue City's
needs, and harsh treatment by the Social Sector on
whom they rely completely.
Correlations,—Venturing into this more precise
analysis, it was necessary to invent some parameters
to check the two Rounds' results over time. Three
parameters were devised:
Profitability: (net income) -r- (sales)
Growth: percent changes of values over time
Liquidity: (cash balance) -f- (net worth)
Using these parameters, clear changes and advances
become noticeable.
In profitability, the ratios for individual economic
activities on a year by year basis ranged from —.454
to +.357; advances and declines mirror earlier
guesses. Oddly enough, the highest profits came for
RA, RB, RC for both Rounds' values; the unprofit-
able units were for PS, PG, and BS (Old only), an
indication of their ponderous natures. Low return
units were the HI, LI, NS, and CI—about .1 to .2
for profitability.
In growth, different results fall out of the data.
The net worth change, cash balance change, and
Blue City population change were analyzed for
round-to-round growth. Over the three rounds, the
relative growth of Old population was greater than
the growth of net worth, while the net worth in the
New rounds was relatively greater than the growth
of population. For the Old runs, because the growth
of net worth (29%) was re!?.lively less than the
population growth (32%) production failed to keep
pace with the population. Conversely, for the New
runs production exceeded population narrowly,
33.5% to 33%. But the interesting growth pattern
belongs to the cash balance change, important be-
cause it represents the firm's capacity to expand,
improve, or build (i.e., if you have a negative cash
balance, no money-requiring venture can be
achieved, and economic decline is signalled). Both
Rounds/Runs showed weighty declines from round
4 to 5, but Old runs' rallied to salvage an overall
13% increase; New runs were plagued with failings
in the PS + PG units, which yielded an overall
—5%% growth, or a net decline in cash balance.
This single fact conveys the relative unproductivity
in the New runs, and a cause for malaise in Blue
City for spring '71.
In liquidity, the 3rd parameter, the resulting ratios
represent the amount of funds in the net worth
available for future expansion or investment. The
values roughly parallel the growth and cash balance
findings, such that the New runs failed to reverse
the progressive decrease in liquidity over time. Both
Runs fell from round 4 highs of .374 and .411
to a low at round 5, but Old grew as New fell fur-
ther to .29. This "progressivity" is illustrated below.
Despite the short period for examination, this drop
in New's liquidity, added to its troubles with cash
balances, give the nod for general economic health
to the Old runs' productive capacity.
To augment these results, and to help clarify the
previous findings, it was necessary to try some cor-
46
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.40
g .38
£ .36
1.34
IJB
.30
\
5 6
ROUND
relation coefficients. These coefficients range from
—1 to +1, with —1 representing perfect negative
correlation (movement in opposite directions) and
+1 representing perfect positive correlation (move-
ment in same directions and at same degree).
The correlations of the three parameters were previ-
ously discus-ed. The profitability correlations for the
Old vs. New Runs of rounds 4-7 revealed high cor-
relations for: the 3 residences, the NS, LI, BS, the
PG and CI firms; low correlations for: the HI and
BG and PS firms. These results follow from earlier
thoughts, representing similar management (i.e.
decision-makers') decisions for those eight high
firms, or steady rates of increase; the low firms
came from industry's sporadic movement (HI and
BG) plus the Social Sectors' actions (PS). In gen-
eral, the 6 firms' coefficients were greater than +.9,
thereby displaying a remarkable similarity in de-
cision-making operations with respect to profitability.
The growth correlations reveal much more on
Blue City's progression through the twin sets of
rounds, "Net worth's" +.425 value stems from
New's upturn from round 6-7 when Old hit a down-
turn, "Cash balance's" high +.907 stems from a
similar movement in values (despite Old's con-
sistantiy higher values); "Population's" near-perfect
+.99 is to be expected if the twin Runs were equal,
because population increased similarly for both
Runs. The "liquidity correlations" substantiate the
earlier finding: the differing Runs possessed similar
decreases in liquidity through round 6 (the +.99
result), but had a divergence in round 7 (thus the
+.80 result).
The cross correlations represent an attempt to
analyze general trends. It is with these that interest-
ing coefficients appear. The extremely high Old "net
worth" to Old "population" correlation of +.998
represents a remarkable similarity in movement and
growth, while the New value of +.234 shows the
dissimilar trends articulated earlier. The high nega-
tive value of —.952 for New "net worth" to New
"cash balance" further shows the negative trend of
the cash balance movement, whDe the —.53 for
Old shows a mediocre relation in opposite ways. In
total, these figures lead to several conclusions:
• A relative increase in the Old run liquidity
and growth in cash balance points to its
superior advantage in investment, building,
and growth over the New run.
• High profitability correlations for almost
every branch of the economy point to a
general similarity of decisions and cog-
nizance of the play of Blue City.
• Over all 4 rounds then, the Old runs enjoyed
a better advantage for growth but both Runs
exhibited similar decision-results, with the
New runs exhibiting difficulties in its PS &
PG units being the major difference; thus
the New fared well with what it had, and
despite a negative growth in its cash balance
(which, of course restricted activity.)
Government Sector
It was agreed by almost all of the government
players who had experienced roles in other sectors
that the Government sector was the most demand-
ing of their time and energy: more people to deal
with (often aggregated at the end of the game
period), more general responsibility in decision-
making that was taken seriously, constant pressure
to balance diverse interests and to project a leader-
ship image of its own all contributed to the difficulty
of play. Although this sector has the potential to be
the most unstable of the three in terms of personnel
it proved to be remarkably stable. In fact, once a
player learned the mechanics and mores of a gov-
ernment role he was reluctant to relinquish it, even
when the Chairman changed. Moreover, the elec-
torate and the new Chairman were always anxious to
retain most of the non-elected government officials
from the previous regime. All of this suggests that
politics was relatively less important to the players
than technocratic management, and this attitude
induced a great deal of conservancy in the play. In
fact, over a cumulative total of fifteen rounds of
play the government changed hands only twice, and
it is doubtful that it would have changed a single
47
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time without artificial outside pressure from the
game director. In the elective process there was
almost no trading of votes for specific policies, and,
in general there was very little interest in politics.
At some elections the incumbent had to be reminded
to file for re-election, and in a half-dozen cases he
ran unopposed and was elected unanimously.
Neither the Social Sector nor the Economic Sector
put much pressure on the Government, but on the
whole the Government was more responsive to the
requests of the Economic Sector. There was virtually
no bribery in the play. The Social Sector players
were generally too lost and disorganized to pressure
either sector.
In a brief student analysis of selected departments
of the government where the student compared the
Fall and Spring terms of play he discovered that
aside from their obvious correlations with popula-
tion, the rates of growth of demand for both Utilities
and Municipal Services are both greater and steadier
hi the new play than in the old.* The graphs (Fig-
ures 20 and 21) show these rates of growth and
compare them to population growth.
Figure 22 shows the tax structure in Blue City.
It does not include such things as bus fares, utility
billing, and bribes, which cannot be counted as part
of the total picture. In both graphs, the Resident
Income Tax and Property Improvement Tax share
a little over 75% of the'load. The general structure
is, in itself, no cause for discontent, and thus re-
mained stable through the life of the play.
Figure 23 is perhaps the most interesting of all,
for it provides some insight into the inner workings
and intricacies of the model. A high use-index in the
school system implies that the quality of public
schooling is somewhat low. Therefore it is logical
that the parents of the children will put them where
the quality of education is best. In the case of a
high use-index, the number of children in public
school will be lower. The printout numbers have
been translated into percentages, where the number
of children in public school is a percentage of the
total number of school-age children. When the
school system's use-index is high, a smaller per-
centage of children attend public school. The actual
correlation is about —0.9.
The fluctuations of use-index in the old play and
its relative calmness in the new play is directly
attributable, again, to the longevity of the "super-
intendents of schools." A short period of "breaking
*The analysis was carried out by William White.
in" is necessary, as shown by the new play, where
conditions have been improving steadily since Round
Five.
In a department by department break down for
"services" for the two runs it is possible to compare
the differential development of the two plays.
One may conclude from a cursory examination
of the data that over the comparable four rounds
there was considerable similarity in the data for
government "services" of Highways, Schools,
Municipal Services and Utilities. No trend emerges
that cannot be explained from population increase
in the Model. This suggests that the continuity of
government decision making from the Fall term to
the Spring term was maintained.
General Trends of Play
Observations of the extended play that was car-
ried out by the Dartmouth group allows the follow-
ing categorization of the trend of play:
Characteristic Rounds
Confusion 1 and 2
Competence 3 and 4
Complacency 4 and 5
Cognition 6 and beyond
As noted above, there was general confusion for
two rounds of play as the participants frantically
explored the Model. This period was characterized
by great frustration at the seemingly overwhelming
amount of information to process and interactions
to strive for. Students often pleaded for guidance
and help and became angry if satisfactory advice
was not forthcoming.
This period of confusion was followed by a period
of relative competence in the game techniques and
relative stability of play. Questions to the Elector
dropped off sharply and some innovations and un-
usual combinations began to be formulated by a few
players. This situation lasted for two rounds of play
and was followed by one or two rounds of bored
complacency. During this period the economic sector
made money, the social sector remained dis-
organized, and the government was not pressed
from any side. There was a definite threat around
rounds 4 and 5 that students would lose interest in
play if no external pressures were introduced. In the
Fall the social sector did induce a crisis by threat of
boycotts and physical damage, but even here this
suggestion came from a non-player. In the Spring
Term the Director induced a crisis by asking the
Envirometrics Staff for an increase hi the dissatis-
48
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500,000
400,000
Population
300,000
7000
6000
MS
Units
Demand
5000
Figure 20
OLD PLAY
-i i-
6
ROUND
8
6500
5500
Utility
Demand
4500
49
-------
500,000
400,000
Population
300,000
Ftfwre21
NEW PLAY
6
8
7000
6000 -
MS
Units
Demand
5000
6500
6
ROUND
-5500
Utility
Demand
4500
50
-------
Figure 22
PROPERTY IMPROVEMENT TAX
RESIDENT
INCOME TAX
23.81%
TAX REVENUES
A COMPARISON
OLD ROUND 8
SERVICES SALES TAX 1.95%
GOODS SALES TAX 4.26%
RESIDENT AUTOMOBILE TAX 0.18%
NEW ROUND 8
SERVICES SALES TAX 2.18%
RESIDENT AUTOMOBILE TAX 0.12%
GOODS SALES TAX 5.37%
RESIDENT
INCOME TAX
31.69%
PROPERTY IMPROVEMENT
51
-------
Figure 23
V)
130
8
52
-------
FIGURE 24
Rounds
Highway
Road Maintenance
($ Millions)
Average Depreciation
before Maintenance
Road Type
1
2
3
School
Highest Use Index . . .
Lowest Use Index
% Private Education
Unmet Adult
Education Demand
Municipal Services
Highest MS Index
Lowest MS Index
Welfare Payment
Total Welfare
Utilities
Highest Cost/Unit Plant
Lowest Cost/Unit Plant . . .
Charge ($1000)
4
Fall
.987
1.7
1.4
0.9
91
62
.164
2795
121
64
$1200
$ 0
8249
7559
10.2
Spring
1.09
1.3
1.4
1.1
91
64
.129
2775
109
59
1200
0
7323
7197
9.7
Fall
1.11
2.0
1.3
1.0
200
68
.440
4705
101
89
1200
0
7589
7354
10.2
5
Spring
1.19
1.4
1.6
1.1
200
71
.409
4835
101
89
1200
0
7357
6762
9.7
6
Fall
1.62
2.4
1.4
1.5
91
73
.234
705
128
90
1200
0
7456
6736
10.2
Spring
1.52
1.8
1.2
1.7
94
72
.287
0
127
96
1200
0
7433
7399
9.7
7
Fall
1.66
2.1
1.2
1.6
92
64
.161
0
128
93
1200
0
7998
7048
10.2
Spring
1.73
1.8
1.2
1.7
99
74
.280
1317
200
200
1200
0
7568
7503
9.7
Key: FaU=Old Hun
Spring=New Run
faction index and for an economic depression. The
social crisis did occur but the economic crisis did
not. It was the general lack of economic shortage in
the model relative to the perception of possibilities
by the students that contributed to complacency.
Some students did not grow in their sophistication
beyond the complacent stage although most of them
tried to mask their lack of interest. Other students,
more than half of the players, became cognizant of
a wider arena for action, a greater number of possi-
bilities, and a deeper meaning in the play of the
game, all of which gave them a "second wind" that
carried beyond the termination of play.
CONCLUSIONS
Some of my conclusions are implicit in the fore-
going remarks, however it is worthwhile to restate
them explicity:
• The experience of using the CITY MODEL
has thoroughly convinced me that it is a
superior learning device: when used effec-
tively a greater percentage of a class is
intellectually engaged in the gaming-simula-
tion than is engaged in normal auricular
offerings. Obviously novelty has something
to do with this but it goes deeper than that
in the context of contemporary, conven-
tional academic offerings.
The use of a complex model like Blue City
requires the building of a course around it
rather than leaving it on the periphery of a
course. From a teaching standpoint I am no
longer troubled by the prospect of making
gaming-simulation the core technique in a
course. I would not, however, risk the build-
ing of a regular curricular offering along these
lines until I had secure access to the model
on our own computer—indeed such a course
would probably not pass through the cur-
riculum committee (a necessary procedure
for regular offerings at Dartmouth and most
other Universities) without assurances of
the Model's immediate availability.
The instructor should build the class up to
the use of the City Model by using some
simpler games so that the gaming concept
becomes more clearly fixed in the student's
mind before play begins. This should be part
of a general orientation to the Model and
53
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should be punctuated with lectures and dis-
cussions.
It is absolutely imperative that one or more
assistants be engaged to help run the play
and take care of the detailed work thereby
allowing the teacher to be free to discuss
ideas with the students.
To be fully effective as a teaching device the
students should be able to experiment with
the model in some controlled fashion so
that it passes from the realm of an engaging
teaching tool into a true social science lab-
oratory.
The physical environment of the gaming
area is very important to play. Access to
several rooms which do not conflict with
other classes, and the flexibility of the rooms
themselves are crucial. There should be
effective play; my preference is for twice
information of the model. A large, up-to-
date land use map is especially important.
There must be a critical mass of players
(which occurs at about twenty), to have
effective play; my preference is for twice
that number. There must also be an extended
enough period of play (number of rounds)
to allow for responsible actions to evolve.
The final round should not be divulged
ahead of time so that "end-game phe-
nomena" may be avoided.
The more different kinds of people (age,
race, education level) the more interesting
and fruitful the learning experience of the
play.
Bugs in the model should be corrected as
soon as possible because their persistence
has a deleterious effect on the play.
The Manual should be re-evaluated and re-
vised as ways to clarify instructions are
discovered.
Serious evaluation should be made of the
influence of the starting conditions of the
Model on the end result of play. This seems
to be an important area for social science
research.
Continued experimental play such as. that
carried out by the six universities would be
useful to those responsible for the develop-
ment of the Model—better still would be
the release of the Model to universities with
the capability to experiment with it and to
elaborate further its powerful teaching po-
tential.
54
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CHAPTER XI
American: CITY MODEL Usage
for Courses in Real Estate and
Urban Development Planning
by Maury Seldin*
BACKGROUND AND DEVELOPMENT
The instructor's first experience with gaming was
with CLUG hi the fall of 1967, when he taught a
capstone course for real estate majors in the School
of Business Administration of The American Uni-
versity, entitled "Seminar in Real Estate Admin-
istration." The purpose of this integrating seminar
was to provide the student with an opportunity to
bring to bear the substantive knowledge from various
courses in the solution of problems the student
would be expected to face as a decision-maker.
CLUG, a manually operated Game, was com-
paratively simple in contrast with the computerized
models such as City I and City II. Initially, the
emphasis was upon analyses useful in investment
decisions, for example, market analyses, valuations,
and forecasts of city growth and structure.
The course next used the game "Region" which
was invented during the 1967-1968 school year.
"Region" handled more variables and permitted
greater emphasis on analyses of local economic
structure and the administration of economic en-
vironment
One of the doctoral students playing the Game
was able to clearly identify a complex set of relation-
ships structured hi the Model and tie them to the
existing literature. In general, the students were able
to see how the principles they had been taught were
*The author wishes to acknowledge the assistance of
Robert P. Jones in the preparation of the last section of
this paper.
applied to real world situations, or at least to a
simulation of those situations. x
The students in that graduate class found the
urban environment mismanaged and impeding the
achievement of their objectives. To meet the prob-
lem, they applied to the public sector entrepreneurial
talents previously used in the private sector. The
result was a more favorable environment for their
private interests and better performance by the
public sector.
Based on favorable experience in graduate classes,
the Game "Region" was introduced into a capstone
undergraduate course. The level of undergraduate
student sophistication was substantially different.
That these students had a high interest in the Game
but their lack of professional competence, as com-
pared to the graduate students, was evident. The
knowledge they had supposedly acquired did not come
into play when they had opportunities to apply it.
The undergraduates needed close instruction on the
application of principles as demonstrated by the
Game. The approach taken was to assign individual
projects to each student which called for the analyses
necessary to solve a Game problem. Thus, the stu-
dent had more than an academic reason for learning
or relearning a facet of the body of knowledge or
the analytical technique.
The following year (1968) the graduate course
used the CITY I MODEL. The next year (1969) a
graduate course used the CITY II MODEL. (City I
was used for an undergraduate class in the Spring
of 1970.) The substance of this Chapter will be a
description of the use of the CITY MODEL, with
55
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emphasis on the experience of the graduate class in
the fall of 1970 and the undergraduate class in the
spring of 1971. One of the great side benefits of
teaching is that the instructor learns as he teaches.
The old adage "If you want to learn a course, teach
it," proved to be true.
At first, the approach to instruction was to let the
student get the joy of discovery as he played the
model. The student would learn principles from the
Game only to discover that he had previously
learned them in a different form. The process taught
well but slowly. In order to speed up the process, the
instructor explained the model and principles early
in the semester. While the mass of explanation was
more than could be readily digested, it did permit
the students to push deeper than they otherwise
could have. As a result, questions were asked on
matters not previously covered in the course. These
questions turned out to be of the same nature as
those the instructor was concerned with in his re-
search. Indeed, the instructor first intended to use
the Game in connection with an approach to a re-
search problem.
Many students attempted to conceptualize the
relationships brought to light by the events in the
Game. They could then use their understanding of
these relationships in their decision-making proc-
esses. The real world decision-maker is in the same
position, except that he'frequently operates under
the handicap of a lack of familarity with the body
of knowledge.
The major thrust of the instructor's research effort
was to improve real estate and urban development
decision-making on the part of real world decision-
makers as well as aspiring students.
In this case the model served as a useful tool in
handling complex abstractions with which the in-
structor had to deal. The models helped because
they became progressively closer to reality, adding
subsystems and providing greater detail in simulating
the urban system. Thus, the instructor was able to
conceptualize a process of managing the urban
development system by conceptualizing the manage-
ment of the subsystems and their coordination. A
view of the problem of managing any subsystem had
to be related to the total system. By successively
working more complex models, the instructor-
1Maury Seldin, "Location of Residential Development,"
Papers Submitted to Subcommittee on Housing Panels on
Housing Production, Housing Demands, and Developing a
Suitable Living Environment, Part I. Committee on Bank-
ing and Currency, 92nd Congress, First Session. U.S. Gov-
ernment Printing Office, June, 1971, pp. 243-262.
researcher was able to handle the more complex
abstractions on an incremental basis. This provided
the basis for conceptualization of a major research
and demonstration project which is now under way.
That major research effort involves an approach
to urban development planning which applies plan-
ning, programming, and budgeting principles to the
urban development process. Of special importance
are the criteria for balance in the system and
methods of administration where the power to con-
trol the process is strong but fractionalized. This
approach is further described in a paper entitled
"Location of Residential Development."1
A major output of this approach is information in
a form usable to decision-makers. The approach
relies substantially on the power of information as
it may be used to influence decision-makers and on
the use of information in the political process.
The research on which the instructor is currently
engaged is in the design of this system on a pilot
basis for Fairfax County, Virginia. An operational
system in the Game or in the real world, or both,
would provide a useful teaching device not only for
university students but for those who are making
the decisions in the public and private sector.
A set of value judgments or biases may have been
visible in the previous discussion. The value system
is one which holds that the use of a market mecha-
nism is desirable as a basic approach to economic
problems. While not the sole approach, it utilizes the
pursuit of self-interest to achieve community ob-
jectives. (It recognizes the important role of govern-
ment in providing an environment in which a private *
sector can operate. It further recognizes the role of
government in supplementing such activities where
the results are found wanting. In addition, it recog-
nizes the use of alternative means where the market
is not workable for various reasons.) While this is
no place to expound various philosophical views, the
aforementioned information will be helpful to the
redder in understanding the assumptions which un-
derlie the normative economic analysis and hence
the approach to business and government decision-
making.
The professional mission of improving the quality
of real estate and urban development decisions has
led to a heavy emphasis on research concerned with
improving institutional arrangements for the func-
tioning of a free society. The particular institutional
arrangements under scrutiny are those directed
toward guiding market forces so that individuals
pursuing their own objectives will tend to contribute
56
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toward the community's achievement of its objec-
tives.
Specific research by the author in the public sector
areas includes the urban development information
system now being developed in Fairfax County, Vir-
ginia; a recently completed demonstration project
on a uniform building permit system for the Wash-
ington metropolitan area, which system would
provide a data base for the aforementioned systemic
approach to urban development management; also
a recently completed study of the impact of the
construction moratorium on the Washington metro-
politan area. Other current or recent consulting
includes services rendered to the Subcommittee,! W
Housing of the House Banking and Currency Com-
mittee, and to the Office of Management and Budget,
Executive Office of the President, as well as to local
planning and government authorities. In the private
sector, his work includes consulting for developers
and coauthorship of a recent book entitled Real
Estate Investment Strategy.
COURSE DEVELOPMENT
The real estate curriculum at The American Uni-
versity came into existence some twenty years ago.
It started with a Real Estate Law course transferred
from the Sociology Department at a time when there
did not seem to be much interest in real estate and
urban development. Over the next fifteen years a
series of courses were developed which emphasized
private sector decision-making. The sixteen real
estate and urban development courses offered in
1965 for graduates and undergraduates revealed
this emphasis. The capstone course, an integrating
Seminar in Real Estate Administration, was added
in 1965. It used case material in order to give the
students an opportunity to integrate the substantive
knowledge acquired in their various courses and|fi
apply this knowledge to decision-making situations^ .t
The thrust of that course was the use of analysis in,?
the administrative process, focussing on typical real
estate decisions of valuation, market analysis, loca-
tion studies, particularly in the context of an ad-
ministrative problem.
When CLUG was introduced in the Seminar in
1967, it was possible to use the simplified model
as a basis for conducting market analyses. In the
Game, the data were readily available and so the
student could concentrate on methodology rather
than on the time-consuming and difficult problems
of gathering data. This was of significant assistance
in teaching because data are not generally available
for all the various kinds of analyses useful to demon-
strate an understanding of the body of knowledge.
"Region" provided a more realistic model and the
CITY MODELS were substantial improvements in
the simulation of the environment in which the
decisions were being made.
As the Games were being developed, so too was
the course. The emphasis changed from market
analysis, valuation, location studies and the like, to
analyses relating to the management of the real
estate resource.
One of the great merits inherent in the study of
real estate is that the resource has such distinguish-
ing characteristics that the analysis brings into focus
principles which might otherwise be clouded. Thus,
the application of planning, programming and
budgeting techniques to the administration of real
estate development enterprise illustrates the prin-
ciples of balance necessary to get from here to there.
These same principles apply for the urban develop-
ment process. The Game is a useful device for
explaining these relationships as they apply to both
business management and land use management.
Once the principles of land use management are
understood, the management of the urban develop-
ment process may be more readily grasped.
The Seminar integrates not only the real estate
decision-making from the firm-investor point of
view, but also urban land decision-making knowl-
edge from a community point of view. The relation-
ship between the two is also subject matter for the
course. While the title "Seminar in Real Estate
Administration" thus has become a misnomer, the
course continues to emphasize the real estate re-
sources, albeit in a context of urban problems as
well as business problems. Considerable attention is
also given to the relationship between the two.
While management of the urban system is considered
mainly hi terms of an environment in which to do
business, public administrators would also find it
useful in their work.
The undergraduate course entitled "Real Estate
Administration" in which the Game has been used
is likewise a capstone course for the undergraduate
real estate major. Initially, the Game did not work
as well in this course because the students did not
have sufficient substantive knowledge to integrate
at the level of sophistication intended for the course.
Attempts to shore up this deficiency have been
made first by directing the student to conduct specific
57
-------
kinds of analyses with specific references to the
literature. This has worked reasonably well in that
the students who have a reason for wanting to under-
stand a particular type of analysis do a good job in
pursuing the knowledge. However, it has been neces-
sary to transform the procedure into one in which
more readings are programmed into the course as
the Game progresses. The literature has not been
designed for this purpose, and so the progress, while
adequate, still leaves much room for further develop-
ment.
Because of curriculum changes at the under-
graduate level, a new course in urban development
is to be offered in the fall of 1971 in which the
Game will be utilized as a way of introducing the
student to the body of knowledge. The old capstone
course will go by the wayside and a new course
focussing on investment decisions will take its place.
The elementary course which is intended for under-
graduate students of various majors in business ad-
ministration focusses on the urban development
process. It is anticipated that it will include the set
of readings closely tied to the Game which is used
as a stimulus to the student pursuing the knowledge
necessary to improve his decision-making.
The differences in approach are related to the
differences in student profile. On the one hand the
graduate students are expected to be able to run a
city efficiently and to do a good job of administering
the resources which they control in the private and
public sectors. At the undergraduate level, on the
other hand, students are exposed to a body of
knowledge whose purpose is to give them a liberal
education rather than professional competency.
COURSE OBJECTIVES
The purpose of the course is to improve the
quality of real estate and urban development
decision-making through the use of a body of knowl-
edge. This objective is sought through the education
of students who are or may become the decision-
makers. The course is designed to give them an op-
portunity to conduct the analysis which leads to the
decisions and to see the consequences of those
decisions and subsequent actions. This gaming ap-
proach is different from the term project approach
in that in the Game they make the decisions and
have the opportunity to implement them. They re-
ceive a feedback from their actions. In addition,
other forces are constantly at work which alter the
effectiveness of their programs for achieving the
objective they set forth. They therefore have a
learning experience in how to deal with a changing
environment: The round-by-round play gives them
the feedback so they get significant experience in
selecting the type of analysis which is necessary to
move them toward their objectives. The allocation of
their time as well as of their Game resources is a
critical determinant of the success they hope to
achieve.
The course is designed to enable them to improve
their analytical ability. It starts out geared to the
developer-investor and others who are primarily
concerned with individual parcels of real estate. But
as the course develops, it is obvious that these
decisions must be looked at in terms of what the
rest of society is doing.
The resultant administrative process integrates
decision-making through the various disciplines. As
the Game progresses the students see that they are
at sufferance of the environment in which business
needs to perform its functions. They increase their
involvement in the management of that environ-
ment. They apply the same administrative processes
to the management of that environment. They then
learn more about the relationship between business
and society.
The types of analyses at the micro-level include
market analysis for shopping centers which are
simulated by "personal goods" and "personal
service" industries. Other market analyses are used
for various types of property to be developed. Ap-
praisals need to be made for various purposes.
Business and property analyses are made in order
to improve profitability of the enterprises. Invest-
ment portfolio analyses are conducted. In a sense,
the economic teams manage a variety of business
enterprises and a portfolio of real estate resources.
Unfortunately the income to business and the in-
come to the real estate are not separated. But, the
student is able to explore the application of princi-
ples which he has learned in his real estate and
business administration courses. He also finds that
human relations and leadership qualities become
important determinants of his success.
At the macro-level the objective is to improve the
student's understanding of how the system works.
He does this by assuming a public role in which he
does the planning and zoning or provides the trans-
portation facilities or utilities, or he may be mayor
and coordinate public sector efforts. The Game is so
devised as to provide the feedback which can be
58
-------
used as a measure of the quality of performance of
these various public sector functions. The student
then sees how the proper (effective?).-..functioning
of government influences the proper (effective?)
functioning of business, or perhaps more correctly
how the improper (ineffective?) functioning of gov-
ernment adversely influences the proper (effective?)
functioning of business.
Since the public and private interests become
interwoven, the Game provides a good way of
demonstrating decision-making in a society in which
there is some community of interest between the
public and the private. The class determines its own
standards of morality. A system of ethics and law,^
develops in a way that enables the society to func-
tion. The set of values varies with the student group,
but whatever the values, they show through in the
operation of the Game.
The operation of the public sector provides sig-
nificant opportunities to apply analytical techniques
for public decisions in much the same way analytical
techniques can be used for profit-oriented decisions.
For example, a school location decision is not so
different from a shopping center location decision.
Experience in the Game shows that the private
sector decision-makers do use that knowledge of
analytical techniques for public sector decisions.
The public sector demonstrates a need for balance
in the system. The balance is not only in the pro-
vision of public facilities but also in the private
development of the appropriate mix of land uses.
One of the great lessons of the Game and of the
course is that the urban development process mav
be managed by providing an environment in which
the private decision-makers pursuing their own ob-
jectives respond to public sector objectives. They
build where the facilities are available and at the
best place to serve the markets. Since the public
sector can control the locations where the facilities
become available, there is an opportunity to be m.
socially and politically, as well as economically re-^
sponsive. An efficient system can be developed by ,,.,,
developing balance.
The inefficiencies become expensive not only to
the developers but to the community as a whole, so
it becomes evident that it pays to have an improved
analysis of the problems of managing the environ-
ment in order to achieve public objectives, whatever
they may be.
In CITY MODEL the public objective decision-
making is complicated by the presence of a separate
social sector which is generally muted in the classes
under discussion. Some development may take place
in activating this sector. But the social sector re-
ceives little attention because of the small size of the
class and the entrepreneurial tendencies of the stu-
dents generally, as well as because of the selection
of students.
COURSE STRUCTURE
One view of how best to educate a student is to let
him work with a professor for several years on a
one-to-one basis. This will permit guidance of his
activities in reading, writing, and solving problems,
real or simulated. The feedback permits close at-
tention to individual needs. The platitudes offered
at commencement time have some merit. Formal
education has really just begun. Education before
the degree should provide experience, knowledge
and understanding that will continue to grow after
graduation.
The reason for not operating a university on a
one-to-one basis is that it is far too expensive. The
alternative is to put students in groups and perhaps
into classes and organized curricula so that a body
of knowledge may be transmitted. Universities today
may be "so well organized" that the student-teacher
relationship has gone by the wayside in the sense
of the student going to study under someone. This
is less true at the graduate level than at the under-
graduate level, but the problem is the same.
The Game provides an opportunity for the pro-
fessor to work with each and every student on the
individual students' unique problems. And while
the students are grouped together in a class and
live in this simulated society which, for them, is
very real, they are also able to pursue their educa-
tional experience on an individual basis. Many stu-
dents are uncertain about why they want to acquire
the body of knowledge. Some of them will simply
proceed on faith that it is really advantageous to
study the discipline. The Gaming decision puts them
in a situation where they know why they need to
know. They are then receptive to the opportunity to
seek out that understanding. And while the courses
are taught with lectures explaining parts of a body
of knowledge and reading material that is helpful,
there is a high degree of contact in class between
students and faculty and indeed among students who
go on to learn from each other.
The case study approach is a halfway measure in
this process. It provides a student with the oppor-
59
-------
tunity to simulate situations and to discuss them.
They get involved in someone else's problem. They
really don't get the feedback. In the Game they are
involved in their own problem. They get the feed-
back.
Typically, at the beginning of the semester the
student writes a one-page paper outlining his goals
and objectives. He then programs his activities in
order to achieve his objectives. The Game provides
a situation in which he may be measured against
the standards he sets.
Over the past few years the instructor has ex-
perimented with various mixes of Games and other
techniques. These range from building the entire
course around the Game to programming the Game
for one half of the course and projects for the other
half. When the course was in essence all Game, the
students would write many papers demonstrating
how they conducted their analyses, showing detailed
plans of what they were going to do, and the like.
The middle ground includes a heavy lecture schedule
and the use of the Game to illustrate specific points.
The minimal use of the Game occurred when term
papers were assigned separately from the Game.
This means there were very few of the short papers
in the Game, but a heavy assignment on the project.
The discussion made use of the Game for the Model.
The instructor's preference depends on the ob-
jectives in view. When the purpose is to teach
analytical techniques, many short papers work out
best. When the goal is to develop a professional
competence in some particular dimension, the term
paper works well when the Game is used as a frame
of reference. When the idea is to convey a general
understanding of the urban system and decision-
making within it, the best combination consists of
the Game plus the reading and some modest papers.
FAMILIARIZATION WITH THE MODEL
The student is introduced to the Model through
the use of a film, lectures, and the City Manual. The
film shows the excerpts of a previous play of the
Game and gives a brief narration of what to expect.
This film is supplemented by lectures which empha-
size acquiring knowledge and applying various tools
of analysis in order to improve decision-making.
Also, the students are requested to read the City
Manual to familiarize themselves with its extensive
technical contents.
The technical nature of CITY MODEL makes
an understanding of the urban system depend upon
a working knowledge of this particular Model. After
the completion of one or two rounds, supplemented
with staff assistance as to the operation and certain
basic relationships, the majority of the students are
questioned (and invited to ask questions) on how
the urban system operates. The purpose of this ses-
sion is to give each individual player a broader
conception of his role and the roles of other players
in the system. The subsequent sessions provide re-
peat opportunities to increase familiarity with the
operation of the Model and the real urban system.
TREND OF PLAY
Armed with the technical knowledge and a sim-
plistic view of the urban environment, the student
is encouraged to develop an administrative approach
utilizing the framework implicit in the planning-
programming-budgeting systems approach. The stu-
dent is expected to:
• Define his general goal which is output
oriented,
• Identify objectives which indicate conditions
or levels which must be obtained or main-
tained to successfully reach the designated
goal,
• Draft programs which are designed to
achieve the standards set by the various
objectives.
• Evaluate the programs to determine their
effectiveness (in cost/benefit terms) as com- >
pared to alternative programs.
As an example, one student's interpretation of his
political role in the urban system is abstracted as
follows:
POLITICAL GOAL School Department
Develop a school system comparable to the
best in the nation, which will provide high
quality, accessible and meaningful educational
experience to the people of Blue City.
OBJECTIVE #1
Maintain the pupil/teacher ratio at less than
15/1.
Program #1
Using population growth projections, de-
termine future student levels. Hire middle
and high income teachers, at the optimum
mix, to meet this demand.
60
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Program #2
Redistrict school boundaries to better
utilize existing resources.
Program #3
Construct new schools or add to existing
facilities as projected. (Specific round-by-
round projections are used.)
OBJECTIVE #2
Keep unmet demand for adult education at
less than 10% of the total demand.
Program #1
Similar to those for OBJECTIVE #1.
It can be seen from this example that the School
Department has:
• A definite goal (to be the best)
• Identified meaningful standards of perform-
ance (student/teacher ratio of 15/1 and
unmet demand for adults at 10% or less)
• Determined approaches to achieve these
standards (population projections, new con-
struction, redistricting, etc.)
Some of the various types of analyses which were
employed by a number of the decision-makers as
described in the discussion which follows indicate
that most analyses performed fall under the Program
category.
Economic Base
Fundamental to many papers which analyzed
Blue City for various reasons was the determination
of why the city is growing. The recommended read-
ings in Wilbur Thompson's Preface to Urban Eco-
nomics had drawn attention to "export base" theory
and the students were able to identify the following
components of the economic base of Blue City.
Sales to the National Economy
(in millions)
Industry
LI
HI
NS
Year
I
$203
$470
$208
$881
3
$233
$528
$215
$976
5
$223
$530
$323
$1,076
7
$234
$503
$526
$1,263
This is a useful exercise but its impact on
decision-making is minimal unless it is used in con-
junction with the other data.
Business Cycle
Export base analysis, since it is dependent upon
sales of goods and services outside the local econ-
omy, must be supplemented by an analysis of the
condition of the national economy. This provides a
useful yardstick for measuring economic perform-
ance. By charting the prices paid for basic industry
output, the return on investments and the interest
rate on loans and bonds, the students were able to
determine which phase of the business cycle they
were in. Most correctly identified the downtrend
of the recession. This may have been one reason for
the general hesitation of investors to make large
capital investments in Blue City.
Demographic Analysis
Other basic studies, important to public and
private decision-makers, concerned the tracing of
population growth and projecting future levels. Other
trends that were investigated included: employment
(total), employment distribution by industry, un-
employment rates and income distribution. All these
data were readily available and in a usable form
but it was concealed among mountains of other
figures. Here again the PPBS format guided the
student to assemble only the pertinent facts and
disregard peripheral information.
Housing Market Analysis
Another basic tool of the decision-makers of
Blue City, important in any geographic area where
dwelling units are in competition with one another
as alternatives for the users of housing, was the
housing market analysis. It incorporates many of
the previously mentioned types of analyses: eco-
nomic base, employment trends, income distribution
and population analysis. An additional component
of a housing market analysis is the housing stock or
inventory. The magnitude of the total housing stock
in terms of dwelling units, reflecting changes over
time, is one of the most significant items of the
reported data. In the example cited below the stu-
dent goes one step further by identifying the change
in distribution of the inventory by structural type.
Housing Inventory
(level of development)
TYPE OF DWELLING
1
Single Family (RA) 101
Garden Apt. (RB) 24
Hi-Rise Apt. (RC) 6
YEAR
4
115
31
6
7 (current)
123
37
8
61
-------
Equipped with this knowledge, plus awareness of
vacancy rates, rents, property values, and financial
market conditions, the private developer could make
a rational decision as to the advisability of a housing
investment.
Appraisal
Appraisal theory was also utilized on a number of
occasions to aid prospective purchasers and sellers
as to the market value of particular parcels of land.
The data needed for the three approaches to value
were available to the student appraiser.
In the application of the cost approach:
1. An indication of the value of the land was
available on the "market value of privately owned
land" sheet.
2. Costs to reproduce the structure new could
be obtained from the local construction industry
and the outside economy.
3. The amount of physical depreciation was indi-
cated on the individual economic output sheets.
In applying the income approach, the appraiser
has:
1. Estimated the gross income by tracing the
economic history of the property and analyzing
anticipated changes in the environment.
2. Estimated the operating expenses in the same
manner.
3. By subtraction, computed the net income be-
fore recapture (depreciation).
4. Developed or selected an acceptable method
and rate for capitalizing the net income.
In applying the market data approach, the ap-
praiser has:
1. Found similar properties in the area for which
pertinent sales, rental and operating data are avail-
able.
2. Qualified the price as to terms and bona fide
nature.
3. Compared the important characteristics of the
subject with the corresponding characteristics of each
of the comparables, by time, location, and physical
factors.
The student would then select the approach which
is most applicable to the subject property and de-
termine a final valuation.
Land Use Studies
One final group of analyses began to emerge in
the later rounds of the development of Blue City.
Urban land studies including surveys of the intensity
of land and residential development, vacant land
studies, structural and environmental quality in-
dexes, land value studies, availability of park land
and general livability studies, showed that un-
structured growth of the city caused numerous urban
problems. In this example, intensive residential de-
velopment occurred along the main western and
southern arteries, causing disproportionate traffic
congestion, school overcrowding, poor municipal
services and general social dissatisfaction. Observing
this degeneration, the zoning department initiated a
comprehensive master plan for the staged growth
of ^iue City. This plan, coupled with the support
and corresponding plans of the other departments,
has insured the future life of Blue City. By proper
management of the urban environment the ineffi-
ciencies due to imbalance can be minimized. No
longer would the public sector blindly respond to
the actions of the private sector; now the public
sector would stimulate or channel growth where it
deemed it most beneficial for the city as a whole.
INTERACTION OF STUDENTS
The dynamics of the Game consist of the series
of analyses and decisions of the types just described
and of development of interpersonal relationships
leading to group action through a political and social
process.
The students play the Game generally through
the economic role. This often results in a minimum
of student interaction early in the course because of
the nature of many economic decisions. That is to
say that economic decisions are viewed as beneficial
only to the team making the decision. Unnecessary
interrelations are thus avoided for the sake of
secrecy. Most players use the guise of ignorance
when talking with their peers early in the course
and their limited contacts are usually attempts to
acquire knowledge.
However, as the players' command over the tech-
nical content increases, so does their awareness of
the necessity of a properly functioning system. The
player realizes that his economic aspirations will not
be achieved unless his public counterpart can create
a suitable "service-rich" environment in which he
can operate. One or two students generally emerge
quickly with an extensive grasp of the system and
its technical content and assume the role of educator.
In the course last spring one student had had
62
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previous exposure with the model and was quite
familiar with its operation. In a fashion similar to
the old ward politicians this student would dispense
favors, in this case the patronage was in the form
of technical explanations, to gain the initial respect
of his constituents. Needless to say, it was a simple
matter for him to insure his election to the mayoralty
of the City.
As time passed, and the other players came to
understand their role and the roles of others, they
began to realize that the mayor, although helping
the city to function, was insuring his own economic
prominence at their expense. The coup d'etat w^s.
swift. The era of the ward politician had passed and
with this passing came the emergence of the city-
manager. The political cooperation which grew from
this new regime eventually led to full appreciation
of the efforts of others and opened up higher levels
of discussion concerning city-wide urban problems.
CONCLUSIONS
As is taught in the Game, the conclusions drawn
would be relative to objectives. If the objective is to
stimulate the student to "dig," i.e., search out the
knowledge he needs, then our experience indicates
great success. If the objective is to convey a body
of knowledge, then our experience indicates that
more developmental work is needed in order to
program instruction necessary to communicate the
body of knowledge.
In the politics of progress, university style, any
curriculum without quantitative methods, human
type studies, computer usage and gaming is simply
not with it. It is as much a case of fashion and
politics as it is of curriculum and pedagogy. The
process, even in this cynical view, does however
improve the effectiveness of what universities are
presumably doing.
If, as in the view expressed earlier, the best way
to teach and learn is on a one-to-one basis, then
the Game is a great innovation. This is so not only
because there is more time on a one-to-one ratio
of teacher-student where the teacher is the professor,
but there is a vast increase in the amount of the
one-to-one teacher-student time where the students
teach each other.
Much depends on the philosophy or assumptions,
if you wish. For those that hold what some believe
to be an archaic view, that the professor knows all,
the student nothing, and let the students come listen,
these conclusions on Game experience will be way
off base. But, for those who really believe that
commencement is the beginning of something, not
the end, and that the educational preparation in-
volves more of a student's learning that a professor's
teaching, then the conclusion is that the Game is a
great contribution in the form of providing the
attractively packaged opportunity for the student to
do what we believe he ought to do (attractively
packaged or not).
If the waves of change in university education are
following the pattern of the waves of change hi other
areas of human activity, be it the increase in the
speed with which man travels, or his abilities to
produce, control and use sound and light, or even
his abilities to solve social science problems, then
university education will take different forms. There
is much to be done with the Game as an instructional
device but there is much that has already been done
with it as a learning device.
63
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CHAPTER XII
Georgetown:
CITY MODEL at Georgetown
by Philip Patterson
INTRODUCTION
Personal Background
I began an active involvement in urban economics
in 1964 when I was graduate fellow to the single
graduate urban course in the Economics Department
at Georgetown University. Five years later, in the
Spring of 1969,1 began teaching the second graduate
urban course to be offered in economics—The
Simulation of Urban System: Econ. 484.
I have continued tq teach a Spring course under
that title ever since. I have however, never been a
fulltime teacher at the university. The class in 1969
was held at the simulation facilities of the Washing-
ton Center for Metropolitan Studies and used the
CITY I* model as a laboratory device. This first
course was subsidized in part by the WCMS through
the provision of free computer time, computing
services and space. During the course of the semes-
ter, the Urban Systems Simulation staff (of which
I was a member) at WCMS spun off and formed
an independent company called Envirometrics.
The 1970 course was held at the simulation
facilities of Envirometrics, and again, CITY I was
used as an integral part of the laboratory seminar
format. This time it was Envirometrics that sub-
sidized the overhead costs associated with the use
of the computerize model.
When the grant from the National Science
Foundation was given to Envirometrics to test the
use of the CITY MODEL in several different dis-
*CITY I was funded in large part by a contract from
the Office of Construction Services of the U.S. Office
of Education.
ciplines at several universities, I was very happy to
participate on the part of Georgetown University.
There was probably no way that I could have con-
tinued to use a computerized urban decision-making
model in my course without institutional support.
This was because none of the desired models could
be run at the university computer center with no
out-of-pocket cost.
Prior to the beginning of the 1970 course, I had
been involved in designing and using urban decision-
making models for about four years—first as a
member of the Urban Systems Simulation staff (de-
velopers of CITY I) and then as a member of the
Envirometrics staff (developers of CITY II, CITY
III, and CITY MODEL). As one of the designers
of the CITY MODEL and as one of the staff that
had run the model on many occasions, I had many
ideas about how I would like to use it. The NSF
project gave me a chance to try one of the several
alternatives I thought would be very beneficial to a
group of students.
Course Description and Class Composition
Figure 25 shows the course syllabus. Note that no
prerequisites were required and that students form
other disciplines were courted. The assignments and
term paper associated with the course were meant to
discourage any student not willing to work on a
continual basis during the entire semester.
Since the course uses a combination seminar (dis-
cussion)—laboratory (decision-making and policy-
testing) approach, it was desirable to keep a small
class size. After the first two classes, seven students
dropped the course leaving eleven persons for the
64
-------
rest of the semester. Undergraduates were allowed
to take the course if they received permission.
Several did, and the following make-up of students
by rank resulted: six graduates, three undergraduates
and two graduate auditors. All were economists but
two: a planner with eighteen years of experience and
a philosophy professor working on a master's degree
in economics.
Several of the students held fulltime jobs: one as
a banker, another for the U.S. Treasury Department,
one student, Bob Ried, was assigned to the class as
the university's fellow, which meant he was to aid
in the course hi any way designated by the in-
structor.
FIGURE 25—Syllabus
Economics 484: Simulation of Urban Systems
Phil Patterson
Department of Economics, Georgetown
University
Prerequisites: None. Students from other disciplines are
welcome.
Objectives of the course:
This seminar-laboratory course will focus on decision-
making in an urban environment through the use of a
computer-based gaming model. The course will deal ex-
plicitly with the major subsystems of the urban system,
such as employment, transportation, migration, housing,
activity systems, the provision of government services and
their financing, and others.
Methods of Instruction:
The CITY MODEL, an operational simulation model
will be used as the laboratory device for studying the urban
system. Students will become decision-makers in a hypo-
thetical metropolitan area. They will be able to pursue
whatever objectives they wish and use whatever discipline
tools they find helpful.
Assignment and Term Paper
There will be three reading reports and several other
assignments of a research nature assigned during the
semester. A research paper will be required that deals with
a specific urban issue.
Required Texts:
1. Thompson, Wilbur R. A Preface to Urban Eco-
nomics. Baltimore: The Johns Hopkins Press, forw
Resources for the Future, Inc., 1965. ($2.95 soft-
back copy)
2. Perloff, Harvey S. and Lowdon, Wingo Jr. editors.
Issues in Urban Economics. Baltimore: The Johns
Hopkins Press, for Resources for the Future, Inc.,
1968. ($5.00 softback copy)
THE COURSE
The operation of the course was strongly in-
fluenced by my previous two uses of the CITY I
model in similar circumstances. There were, how-
ever, fewer changes to the purposes of the course
than to the structure of the course.
Purpose of the Course
The single overriding purpose of the course was
to provide the students with an opportunity to learn
by being placed in a position of decision-making
authority. Some of the general things to be learned
were:
• The use and applicability of the box of
theoretical tools they had acquired in other
classes,
• The workings of a complex systems model
that was designed to be a simplified reflec-
tion of the real world urban system,
• The importance of goals and norms in
policy-making and in the life of any urban
area,
• The competitive and cooperative nature of
decisions in the economic, social and govern-
mental sectors of any metropolitan area.
Several more specific goals of the course were to:
• Acquaint the students with some of the basic
literature in urban economics.
• Provide through reading lists and class read-
ing reports some insight into the literature in
systems theory, model building, and educa-
tional games.
• Encourage original thought through the
writing of a research paper on a topic of
the students' choosing.
• Use the CITY MODEL as the integrating
element for all the activity that took place
in the course.
The last goal was of particular importance since
past experience had shown that a holistic model of
this type could be helpful in relating the theoretical
literature to everyday urban issues and problems. In
fact, my own understanding and interpretation of
the literature had changed dramatically once I had
become involved in designing and operating complex
urban decision-making models.
Course Structure
Even though the CITY MODEL is a much more
powerful tool than the CITY I model that I had used
in my previous two courses, I did not depart
radically from the format I would have used had I
still been using CITY I. My previous two semesters
convinced me to use a few strategies that I would
have used regardless of the model employed.
65
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First, start playing the game as early as possible
but preceed it by the more simple manual game of
CLUG (Community Land use Game).1 The reason
for starting play early is that almost any urban issue
that comes up in the course can be related to the
model (either to a factor contained in the model
or as a factor that could be added to the "game" or
to the "model").2 The reason for starting with
CLUG instead of CITY MODEL is that a few
students tend to make serious mistakes based upon
a misunderstanding of the model in the first or sec-
ond round of play that plague them for the rest of
the semester. By playing CLUG first, these students
have the chance to make the mistakes, and learn
from them (e.g., over-building personal goods be-
cause they do not realize that all sales must be
made locally, or purchasing land at inflated prices
miles away from roads or terminals).
Second, maintain a seminar atmosphere by having
periodic discussion in which all students are en-
couraged to participate. This is to assure that each
student take a stand on whatever topic the discussion
deals with.
Third, allow the momentum and interests of the
class to alter any pre-planned schedule for an in-
dividual class meeting. When a lively class discussion
develops and it appears to be constructive, it is
allowed to run its course.
A major difference between CITY I and CITY
MODEL from the player viewpoint is the number
of sectors. CITY I has an economic and govern-
ment sector. CITY MODEL has those two plus
a social sector. With CITY I, I had always had one
or two person teams that played the economic and
government sectors simultaneously. I decided to play
CITY MODEL with one or two person teams that
would play all three sectors simultaneously. But
1 Developed by Alen Feldt, now at the University of
Michigan.
*A useful distinction can be made between the "model"
and "game" components of a run of the CITY MODEL.
Strictly speaking the type of inputs, the operating programs,
and the computer output comprise the model. These do not
change from one run to another. The starting city con-
figuration, the allocation of assets to teams, the allocation
of players to teams, the norms of the players, the institu-
tions they create, and the win criteria they establish com-
prise the "game." Together they tend to be unique for each
group of users of the CITY MODEL.
8 For convention, "In Round 1" or "Round 1 decisions"
will refer to decisions that were made to create a Round
2 output.
'The Georgetown University play of Blue City will be
referred to as "Georgetown" to distinguish it from the
other plays.
because each sector is quite complex, I opted for
introducing the sectors one at a time; economic in
round 1, social in round 2, and government in round
3. More will be said about this later.
THE PLAY OF THE MODEL
Overview
The model was run seven times after the receipt
of Round 1 output which means that play ended with
a Round 8 output. Since the model was run with
teams operating Construction Industries, there was a
round delay for all construction. Therefore, in the
final round no construction decisions were made in
order that the play would end on a stabilized basis. In
Round 13, only economic decisions were made. In
Round 2, economic decisions and social decisions
were made. The first full round of play in which the
students assumed full decision-making power was
Round 3. Thus, the full range of the model was
available to the students for four rounds of play
(Rounds 3, 4, 5, and 6).
Teams were comprised of one or two members
and were matched alphabetically in the economic
and social sectors (i.e., Economic Team A was also
Social Team AA, etc.). Government positions were
changed once (at the end of round 5), thus allowing
each team to exercise two government functions.
Figure 26 shows the population growth for
Georgetown4 over the seven rounds of decision-
making. The total population growth of 68 percent
was quite large in terms of real life cities. This total
growth over seven rounds converts to an annual
rate of growth of 7.7 percent and places Georgetown
up in the fast growing class of cities such as Phoenix,
San Jose, Fort Lauderdale, Las Vegas, and several
other cities during the decade of the sixties.
Figure 27 shows several indicators for George-
|bwn over the eight simulated years.
General and Departmental Indicators
Several useful city indicators that are not con-
tained in the summary Demographic and Economic
Statistics are shown in Figure 28. The indicators
appear in the Figure in the same sequence as they
appear in the output. For example, the first informa-
tion after Edits is the details on migration. The key
indicator in the Georgetown City is the in-migration,
because jobs were always available in all three
classes for Rounds 4, 5, and 6. It appears very
66
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Figure 26.—POPULATION GROWTH IN THE CITY OF GEORGETOWN
600 -
500
400
Is
I 300
2
.£
200
ROUND
FIGURE 27—Georgetown Indicators
Round
4 5
% Change in
Population
Population Per
Residential
Square Mile
Average Housing
Dissatisfaction ...
Average Educational
Level
Vacancy Rate
Employed Workers .
(thousands)
Percent of Workers
Earning Under
$5000
0
1940
NA
60
6
81.6
38
1942
112
57
3
81.4
38
1972
109
88.7
37
2127
107
57
3
95.9
33
10
2326
108
54
-9
107.9
36
19
2546
90
59
-3
126.0
31
13
2430
93
58
2
136.0
34
erratic, but this is primarily due to the amount and over capacity by one PM and 59 PH's. Likewise,
type of newly constructed housing. For example, in
Round 5, mostly PL's moved in, and the only new
housing constructed was completely occupied by
Pi's. In Round 6, mostly PH's moved in, and this
was because the new RC2 at 10826 was filled to
the new level of RB at 9236 was filled with 7 PH's.
In other words, if housing had not been in short
supply, the in-migration by round would have been
even for the three classes.
A very useful indicator can be derived from the
67
-------
FIGURE 28—Indicators for the Georgetown Play, Rounds 2 through 8.
Round
Migration (Pi's)
In— PL
PM
PH
Out— PL
PM
PH
Employment
Average Cost of
Transportation PL
PM
PH
Average Transportation time.
PL unemployed
PM underemployed
PH underemployed
Highway
Road Maintenance
($ million)
Road Type
Average Depreciation
before maintenance .... 1
2
3
Bus
Fares ($ million)
Current Expenditures
Fare Schedule
Passengers (1000's)
School
High Use Index .
Low Use Index
Ratio of Private/Public
Unmet Adult Education Demand
Municipal Services
High MS Index
Low MS Index
Welfare Payment
Utilities
High Cost/Unit Plant
Low Cost/Unit Plant
Charge ($1000)
Revenue/Expenses
Parks
Population/Square Mile
(in thousands)
Chairman
Ratio of Appropriations to Taxes ....
Auto Tax
(millions of dollars)
2
7
9
10
0
5
14
260
190
280
5
35
14
3
.824
1.1
1.0
.9
.466
2.57
15$
+ 2$
4.9
197
59
.205
5085
150
143
$1500
$9704
$6926
$10
1.317
35.4
1.29
.204
3
7
10
10
10
12
7
240
200
300
5 .'7."
3
0
0
.774
.9
1.3
.6
.969
10.0
0
+54
19.8
185
62
.186
4670
151
143
$1500
8783
7658
$10 -
•879fai
Jj*
35.8?
1.21
.194
4
7
17
19
3
2
1
220
170
280
5
0
(82)
0
(63)
0
(89)
.682
1.1
1.0
.8
1.25
7.78
0
+5*
29.1
85
47
.244
3414
152
135
$1500
8607
7777
$10
1.258
34.3
.83
.962
5
46
26
3
12
2
2
190
150
270
5
0
(61)
0
(69)
0
(110)
2.18
1.8
1.2
2.0
1.34
6.86
104
+54
13.6
47
0
3.341
8433
143
121
$1500
8056
7517
$9.7
.915
34.2 ,
.74
1.48
6
9
44
87
12
2
1
220
260
330
5
0
(70)
0
(33)
0
(41)
1.36
1.9
1.3
2.0
1.33
5.68
104
+54
13.3
96
68
.243
291
149
114
$1500
8271
7106
$9.7
1.211
34.2
.86
1.84
7
36
18
57
6
3
3
230
260
260
5
0
(42)
0
(11)
0
(0)
1.64
2.2
1.5
2.3
1.88
5.22
101
+54
18.4
88
62
.303
3716
168
114
$1500
8268
6816
$9.7
.755
33.3
.93
2.06
8
17
26
16
17
1
4
240
280
370
6
0
(54)
0
(0)
0
(33)
1.92
2.0
1.4
2.2
.68
2.95
101
+54
6.6
95
60
.352
4853
175
113
$1500
11,718
6,816
$9.9
1.230
33.0
.93
2.07
Employment Details. Pi's by class employed by SC,
MS, or BUS pay a systemwide calculated average
transportation cost and take an average amount of
time to go to work, since the actual cost and time
5 The. SC and MS departments hire Pi's and then assign
them to individual SC and MS units. Pi's are not hired by
the individual SC and MS units.'
cannot be derived due to the fact that there is no
specified location for SC, MS, or BUS jobs.5 There-
fore, the transportation cost and time for employees
of these government jobs give a useful measure of
changing costs by class and over time. Since the
calculated average figure takes into account other
Pi's that use cars, or buses (and/or rapid rail if one
68
-------
exists), or walk to work. Thus, a declining dollar
cost over time such as existed for PL's from Round
1 to Round 5, would represent such things as more
bus ridership, more walking to work (Pi's working
at adjacent parcels), or reduced highway congestion.
In general, lower values would be beneficial to the
social sector.
The average transportation costs (which are based
on last round's data) reached their lowest point in
Round 5, the year after bus ridership reached its
maximum value. The change between Round 2 and
8 was detrimental to all but the PL Class. The
average PH in Round 8 was spending 32 percent
more and the average PM 47 percent more to get to
work than in Round 2. The transportation sector of
the local system certainly did not serve these citizens
well! The average travel time to work was stable at
5 units for all the rounds except the last when it
jumped to 6. Thus, the average worker was spend-
ing 20 percent more time getting to work in Round
8 than in Round 2. As city size grows, one would
expect average travel costs and time to increase if
offsetting improvements are not made in the trans-
portation system, and this in exactly what happened.
Road maintenance costs increased significantly
over time, and this was due primarily to more people
using the same old roads. It is true that some new
roads were built but the number of congested roads
increased from 3 to 13 between Rounds 2 and 8.
The bus operation was a frustrating task for all
three persons who tried a crack at it. Passengers
peaked in Round 4, but the relative cash loss to the
company was in Round 8 when expenditures ex-
ceeded fares by only 177 percent! A research paper
by one of the hapless bus operators (Appendix B)
presents a technique that might make the bus have
a chance of turning a profit and still serve a large
number of people.
The School Department started with a bad situa-
tion, in terms of disparity between the best ande
worst school units, and managed to make things?
better over time. The percentage of students going
to private schools, however, increased over time and
was very large in Round 5 when the local School
Department experienced a wholesale exodus on the
part of its teachers because of the low wages offered.
The adult education program nearly met all the
demand in only one year.
The Municipal Services Department started out
with a system that was overcrowded and ended up
with a slightly less overcrowded situation, but one
that had more inequities than before. That is the
worst served area was 17 percent worse and the
best served area was 21 percent better off at the end
of the seven rounds of decision-making. The cost to
the economic sector via increased maintenance
charges as the result of poor MS service must have
been ignored by the entrepreneurs of the local
system.
The Utility Department was improving the cost
per unit at the high cost plant very nicely until the
last round, when the cost per unit jumped 42 per-
cent. The low cost plant showed a small improve-
ment over the seven rounds. The revenue/expendi-
ture figure is deceiving because part of the expendi-
tures were accounted for by cash transfers to other
government departments.
The population per square mile of parkland
showed a small decline, which means a relative
increase in the green space per capita.
Frequency of Decisions
Figure 29 shows some of the major decision
categories and the number of successful and un-
successful decisions made each round. Two con-
clusions are readily apparent. First, a large number
of attempted decisions were declined because of
procedural or substantive errors. In face, the percent
of decisions rejected did not decline much over time.
Also, in some cases such as housing builds in Round
6, the rejected decisions were not even submitted in
the following round.
Second, the economic decisions far outweighed
the government decisions, and both types far out-
weighed social decisions. Purchase decisions de-
clined after peaking Round 3. Rent changes were
fairly numerous, and most were increases levied by
landlords in response to a seller's market. Price
changes were not numerous, as one would expect
given the monopoly position of most of the com-
mercial establishments. Salary changes peaked dur-
ing the rounds when labor was most scarce. The
activity in maintenance decisions peaked hi Rounds
2 (the first chance the teams had to improve the
quality of housing) and 5 (for an unknown reason).
Teams quickly realized the alternative uses of their
money in outside investments. Disinvestment did
occur more toward the later rounds as the national
cycle declined and as local investment money be-
came scarce. Tremendous building of businesses
took place in Round 2, and much of the rest of
the play centered around adjusting to meet this
growth available in jobs. The housing shortage was
69
-------
never sufficiently solved, but the gap opened up in
Round 4 was narrowed.
In the social sector, many time allocations were
made when the first opportunity in Round 3 pre-
sented itself. After change took place in the dollar
values of time. More lowering of dollar values would
have assisted the Bus Company in its efforts to gain
maximum ridership.
All the government decisions in Rounds 2 and
3 were director inputs, made in response to needs
expressed by the economic or social sectors. Ap-
propriations were altered from year to year (un-
changed appropriation levels require an annual in-
put). Tax policy was exercised in Rounds 4, 6, and
7. Wide spread, assessment changes were made in
Round 4 and were coordinated with the tax policy
in an attempt to intice more residential develop-
ment. More residential development did take place
in the following round, but the cause-effect relation-
ship might be tenuous. Most of the other depart-
mental activity showed little pattern other than
fewer decisions over time. The one exception to this
is the Planning and Zoning Department which
carried out a master zoning plan in Rounds 7 and 8.
FIGURE 29—Frequency of Decisions by Round—Georgetown*
Economic
Purchases
Rents
Prices
Salaries
Maintenance
Invest
Disinvest
Build-Business
Levels
Build-Housing
Units
Social
Time
Value
Government
Appropriations . .
Taxes
Assessment
Schools
Municipal Services
Highways
Bus
Planning-Zoning .
Utilities
2
6 m
15
0
0
15
7
0
cn
3
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37 CD
6
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1
4
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31
29
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4
6
8
4
24
11
1
9
2
2
0
1 [1
7 E|
15
2
3
4
12 Q
15
6
17
26
0
Round •
5
25
12
1
11
4
2
D 98 [58]
0
3
0
5 [41
21
3
6
6
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8
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73 m
3 m
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2
i— J
•Figures in boxes are the number of decisions rejected for procedural or substantive errors. Procedural errors are coding mistakes and
substantive errors are those that reflect system factors that prevent a decision from being made (e.g., lack of cash, improper zoning, lack of
utilities, etc.)
The Economic Sector
Midway through the play, the students were re-
quired to calculate the rate of return on all of their
properties and to trace back the rate of return for
the two most profitable and the two least profitable
investments. This assignment proved to be a revela-
tion to a number of the students who were unaware
of the declining profit rate that was brought about
by a rash of speculative overbuilding in Round 3.
The economic sector tended to building intensively
as opposed to extensively. Not many new parcels of
land were developed; rather, the original unde-
veloped land within the initial development area was
built upon. In fact, only one new parcel was used
for housing, even though the population increased
by 68 percent.
The Social Sector
Although the students were not active in the
social sector, two major social indicators (per capita
personal income and dissatisfaction index) both
70
-------
improved over time. The dissatisfaction level, how-
ever, did not decline as much as in most of the other
NSF cities. On the other hand, PCPI was higher in
Georgetown by a large margin than in the other
NSF university cities.
The Government Sector
Government activity in the Georgetown City in
most of the functional areas appeared to serve the
demands of the economic sector. For example, roads
and utilities were placed in the places and in the
amounts necessary for the planned economic de-
velopment. Both of these departments showed in-
dications of operating less efficiently over time.
The Highway Department was spending 30 cents
per capita for highway maintenance in Round 1 and
42 cents per capita for maintenance in Round 8.
With regard to the Utility Department, the least
efficient plant had a production cost per unit of out-
put that was 21 percent higher at the end of the
eight rounds. The production costs of the most
efficient plant, on the other hand, declined 2 percent.
The School Department reduced lthe level of
inequality (ratio of use index at the most crowded
school to the use index at the least crowded school)
over the eight years from 3.3 to 1.6. Inequality
increased with regard for municipal services, in that
the inequality index went from 1.05 in Round 1 to
1.55 in Round 8. The population per square mile
of parkland declined slightly from 35.4 to 33.0 over
the eight rounds.
SUMMARY
Student activity in the three sectors was very
uneven. Economic decisions dominated all others,
and social decisions were made sparingly. This did
not, however, generate an improvement in economic
indicators at the expense of indicators in the other
two sectors. In fact, the average rate of return on
investments hi the system declined over the eight
rounds. This was largely due to the overbuilding
that occurred midway in the play. This suggests that
the students may have observed and learned more
about the interaction of economic decisions in the
local system than of either government or social
decisions. A personal observation is that the students
learn more from the model in the sections of the
model that are most experimented with in a lab-
oratory sense.
CONCLUSIONS
• The CITY MODEL provides an excellent tool
around which to develop an urban economics course,
an urban laboratory, or an economic decision-
making seminar. A professor can focus attention on
(1) tying the urban and regional economics litera-
ture to the model play, (2) allowing the students to
experiment with decision-making (current policy
alternatives or ones of their own design), and (3)
providing the students with a chance to demon-
strate their ability to use the box of economic tools
that they have assembled in previous courses.
• The disadvantages of having a student play
all three sectors simultaneously outweighs the ad-
vantages. The main disadvantage is that the social
sector receives very little attention when a student
has an option to make decisions in the other sectors.
Perhaps, because of the nature of the social sector,
students should never have any other responsibilities
when they are playing the social sector.
Other disadvantages of playing the three sectors
simultaneously are the handling of three sets of out-
put, making decisions that cover the full scope of
the model, establishing objectives in three diverse
areas.
The advantages of playing all three sectors simul-
taneously are the educational feature of having con-
flicting interests, seeing the model and the city from
three points of view at the same time, and playing
the model with a minimum number of students.
• The CITY MODEL is a rich enough labora-
tory device that caution should be used as to how
many complementary exercises are undertaken dur-
ing the course of a single semester. I used parts of
nine of the fourteen classes with game plays (two for
CLUG and seven for CITY MODEL) and the re-
mainder of the class time was devoted to discussion
of readings, research papers, Urban Dynamics, and
the play. Taken together, I feel that I attempted to
cover too much ground. A number of readings were
never discussed, and insufficient time was given to
an analysis of the play.
• The play of a round of the model is complex
and engrossing enough so that it is usually necessary
to devote a full class period to play. A class session
that is split between game play and any topic other
than discussion of the play has a high chance of
being unsatisfactory for either the play or the other
exercise. On a number of occasions a class session
began with a discussion of assigned readings and
finished with a round of play. In each case, as stu-
71
-------
dent questionnaires confirmed, the discussion was
given secondary effort as students looked ahead to
the play. At the same time, the play of the round
did not receive the time it needed.
• The mechanics of the model are so formidable
during the first two or three rounds, that once the
students learn these, there is a chance of a let-down
on the part of some of them. There is the danger
that some of the students will feel that the purpose
of playing CITY MODEL is to learn how to play
it, rather than to learn by making decisions and
receiving continual feedback in a hypothetical urban
environment.
RECOMMENDATIONS
The recommendations will be listed under three
categories of use of the CITY MODEL: those that
apply to any user of the model in a classroom
situation, those that apply specifically to the use of
the model in an economics course, and those that
apply to the type of seminar-laboratory course that
I offered. These recommendations will be followed
by some general suggestions concerning the use of
the model.
1. Classroom Use of CITY MODEL
• Assign the social, economic, and government
teams in the model (AA, ,,A, and SC, etc.) in such
a way that the students perform tasks in only one
sector at a time. If there are a small number of stu-
dents (less than 22) make all the gameroom teams
(as opposed to the computer output or model teams)
composed of one player. For example, if there are
only twelve students, they would each comprise a
team (numbered 1 through 12) and the gameroom
team 1 might be assigned the model teams of AA
and DD, team 2 might be the sum of model eco-
nomic teams B and C, and team 12 might be the
sum of SC and MS.
If there are more than 25 students but less than
50, it would be necessary to make some two
student gameroom teams.6
"All of these recommendations are made assuming that
the user starts with the Blue City configuration which has
seven model economic teams, seven social teams, and from
eight to eleven government teams. If one of the other
starting configurations were used the number of students
constituting cut off points would be different. In fact, the
director who favors one man teams and has a large class
might want to use the Big City configuration which has 36
distinct model teams or TriCity which has 44 distinct
teams. On the other hand, a very small class might get
more use out of playing Moray County which has a start-
ing population of only 11,500 at the start of play and
only about ten model teams.
• The CITY MODEL functions performed by a
gameroom team should change several times during
the course of the play. The ideal way to have teams
assume government positions is to be elected or
appointed to them. This may not be possible at the
start of play or the political dynamics may never
evolve, so the director must be ready to change team
assignments whenever he sees the need or the benefit
of doing so. Students benefit from playing several
widely different functions during the course of the
play.
• Have access to a graduate assistant who can
handle the editing of player input forms, punch the
input cards, handle the running of the output, and
provide overall assistance during the run of the
model. This student would very well be a member
of the class. In either case, he should be well versed
in the operation of the model and in the rules of the
game.
This student will spend on the average about an
hour editing decisions, a little bit more punching
them, and whatever time is needed to input the
decisions and receive output for each round of play.
• Do not attempt to cover too much ground
during the course, and thereby take away time from
valuable discussions of the "model" and the "game"
that was played by the class. The assumptions of the
model can usefully be questioned and alternative
ones proposed. The goals, norms, and results gen-
erated by the game play should be fully explored
and the relation between individual and collective
objectives analyzed. Attempts to define the "good-
ness" of the final status of the city should be made.
• Do not split a class meeting between play of
the model and some assignment not directly related
to the play. Do not expect to get the full attention
of the students during a class once output has been
handed out.
• Devise several strategies for handling situations
when a student or the class become let down as a
result of learning the mechanics of the play or find-
ing their function too easy to perform. If the whole
class is in trouble, an outside influence such as a new
state regulation setting school quality levels, utility
rates, bonding, etc., might be made. Or natural
disaster might strike in the form of cash drains from
all economic teams or buildings being destroyed
(director inputs). Or a new federal program to assist
new town development might be made, creative
federal aid programs might be introduced, or a
federally imposed population level might be pro-
mulgated.
72
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In the case where an individual finds the game
too easy, he might be given an assignment to cal-
culate his actual rate of return of cost-effectiveness.
Or he might be given a tougher assignment. The
tough assignments are Bus Company operator (have
the service pay for itself through fares), Highway
Department (eliminate all congestion), and Assess-
ment Department (assess according to the best use
of the land).
2. Use of CITY MODEL in an Economics Course:
• Tie the urban economics literature to the
model when possible, and show where the model
does not explicitly deal with elements of economic
theory. In the latter case, there is a challenge to the
student to devise a way for including the missing
element. For example, the issue of water pollution
is absent from the version of the CITY MODEL
used in the NSF program. The student who is
interested in this omission could devise a way for
adding the water subsystem to the present urban
system contained in the CITY MODEL.
• Encourage participation in the course by stu-
dents from other disciplines. The model is an in-
terdisciplinary device through which the student of
economics may learn to appreciate the usefulness
and limitations of his particular field of study. This
learning will be aided if other students in the course
have some formal background in the complementary
disciplines of geography, political science, urban
affairs, and sociology. Likewise, the student from the
other disciplines may gain a better appreciation for
the usefulness of economics.
• Assign a research paper that is closely related
to the use, content, or outcome of the CITY
MODEL. Student papers over a number of semesters
will build up a helpful library of source material and
ideas for future classes. In this way, the output from
the students may be able to evolve to a larger re-
search product than any single semester would be
able to.
• Assign specific economic projects and reserve
adequate time for the discussion of economic topics.
The first might be accomplished with assignments to
calculate the economic base of the simulated area,
perform a PPBS analysis of the government, cal-
culate rates of return for various investments, or
estimate benefit/cost ratios for specific government
projects. The discussions could deal with these
topics hi addition to such other as the place of
macro and micro theory in the model, the economics
of space, zero population growth policies, new town
developments, model cities programs, revenue shar-
ing, conventional intergovernmental fiscal relations,
and others.
3. Use of CITY MODEL in an Urban
Semi-Laboratory Course
• Have the class scheduled at such a time that
the students do not have any limitations on the
length of time they can stay at any one meeting. The
seminar discussions that evolve or are planned
should be ended by the students on a voluntary basis
and not by a ring of a bell. But allow students to
individually drift away at any point after the first
several hours.
• Keep the class size to under 20 students so
that they can easily get to know one another on a
first name basis, and so that seminar-type discussions
in which everyone participates are possible.
• Place strong emphasis on starting the research
paper early so that discussion of the rough drafts
can take place in the seminar when useful. En-
courage the students to perform all of then: assign-
ments in such a way that it instructs the rest of the
class and furthers the class learning experience.
SUGGESTIONS
• Make the city decision-making a long run
project by having the second semester begin play
where the first semester class left off. This would
accomplish the dual purposes of providing the first
class with an added incentive for looking at the city
and their own functions in a serious way (and
avoiding any end game strategies) and of giving the
second class a detailed city history from which to
learn the model more easily and see the reasons for
the present status of the city.
• Attempt to load data into the model for a city
chosen by you or your class. This could well be a
class project that would not yield a usable con-
figuration until the following semester. Making de-
cisions for what looks like a real city may be of
some benefit and the process one must go through
to load a city teaches you a great deal about data
availability, parameter fitting, and the model itself.
• With a very large class or with several classes,
play a number of CITY MODEL configurations
simultaneously and allow a few players to act as
national businessmen who may invest a specified
73
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amount of money in any of the cities, in whatever industries, other only commercial establishments,
desired mix each year. and others only residences. Team cash balances can
• Alter the assets of economic teams before the be reduced or increased to make growth more diffi-
start of play by making some teams have only cult or easier.
74
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CHAPTER XIII
Mankato State: CITY MODEL Usage
in the Urban Studies Institute
by Robert Barrett
The CITY MODEL was utilized in the inter-
disciplinary program in Urban Studies at Mankato
State College in two formal courses which I in-
structed and one independent study course which,
the students organized. This utilization during the
1970-1971 academic year was sponsored by the
college and Envirometrics as part of an NSF project
to test the applicability of the CITY MODEL in
selected disciplines and academic institutions. The
experimentation reported upon in this chapter
proved to be an absorbing and rewarding experience
to both the students and the instructor.
INTRODUCTION
My first experience with urban simulation came
when Dr. Royce Hanson, director of the Washington
Center for Metropolitan Studies, introduced me to
the urban simulation lab which the Center had
established under the direction of Dr. Peter House.
I was afforded an opportunity to experience some
"rounds" of the game and met some of the lab staff
members. I became quite intrigued with the potential
of the urban simulation lab to provide opportunities
for theory building and concept testing in the urban
studies curriculum.
My own academic training had focused first upon
the sciences and then the social sciences leading to
graduation from Hamline University in St. Paul with
a double major in Social Science and Mathematics.
When I joined the graduate program as a fellow in
government and public administration at American
*Dr. Robert A. Barrett is Director of the interdisciplinary
Institute for Urban Studies and Professor of Political
Science. Mr. Frederick Sauer provided valuable assistance
in the accomplishment of this experiment.
University I was strongly interested in Political
Science. My interests began to focus upon the city
and its politics as I worked closely with my major
advisor, Royce Hanson. These interests grew when
I entered college teaching as a member of the
faculty at Mankato State College, a regional institu-
tion in Southern Minnesota with an enrollment of
15,000 graduate and undergraduate students.
My early interests on the Mankato State faculty
were twofold: to introduce significant opportunities
within the Political Science curriculum for the study
of cities and to work with sister disciplines, par-
ticularly the social sciences, to organize an inter-
disciplinary degree program in Urban Studies. The
first interest was realized through the adoption by
the Political Science Department of courses such as
Urban Government, Urban Planning, Urban Ad-
ministration, Urban Seminar and field study and
internship experiences in the urban environment.
The second interest matured into a healthy dialogue
and collective action by several disciplines whereby
our disciplines were married together into a B.S.
and M.A. degree program for urban generalists seek-
ing urban planning and urban management careers.
More than two dozen faculty from over one dozen
disciplines now cooperate on a refreshingly inter-
disciplinary scale to teach and research topics in
Urban Studies in the Urban Studies Institute. The
students in this program, numbering about 150, are
upper division and graduate students whose previous
experience has largely been in the social sciences.
Furthermore, our students' background has typically
been textbook oriented without substantial experi-
ences within an urban environment. Consequently,
our efforts to provide realistic urban learning en-
75
-------
vironments through intensive field study camps and
internship work experiences found a natural learn-
ing complement in the use of the urban simulation
lab.
THE COURSE
The CITY MODEL was utilized within the frame-
work of two of the core courses of the Urban
Studies curriculum. The first course was the Urban
Studies Seminar which is offered to senior and
graduate majors after they have completed a series
of discipline based courses in the social sciences.
The course is taught from an interdisciplinary ap-
proach with small enrollments (8 to 15 students)
and with an emphasis upon analysis and discussion.
In the seminar the class alternated use of the game
with seminar meetings focused upon research and
analysis of New Towns as an approach to the city
as a system. The second course was Urban Govern-
ment which is offered to junior/senior and graduate
majors and non-majors who are interested in con-
temporary governmental and political problems of
metropolitan areas. This lecture course generally
enrolls a moderate number of students (30 to 40),
and is taught from the Political Science discipline. In
this course the game was alternated with conven-
tional lectures which surveyed the standard topics
of contemporary urban"- government. Selection of
these courses for use with the CITY MODEL was
largely a factor of the course schedule and the
previous course work backgrounds of students en-
rolled in these courses. Whereas these courses had
been partially redesigned at the outset, it became
obvious during the conduct of these courses that not
only the methods but also the objectives required
serious modification. Consequently, I discovered that
the usage of urban simulation required not only a
rearrangement of the course syllabus but a major
adjustment of the course objectives of these courses
which had originally been developed to be taught
with more conventional instructional techniques.
The primary objectives for the use of CITY
MODEL in these courses were several. In the first
instance, it was hoped that the model would afford a
more multi-dimensional understanding of the city as
a system. It was hoped that theory building and
concept testing would be encouraged and would take
place within an experimental context. For instance,
concepts of decision-making and community power
are capable of close observation and testing in the
game dynamics. It was anticipated that the dynamics
of negotiation, representation, advocacy, and related
"role" activities would be meaningful and insightful
experiences. A further objective was to sharpen the
analytical capabilities of the class participants.
Finally, the use of the game was to be tested as an
effective learning experience within the established
Urban Studies curriculum.
The course described in this chapter is the Urban
Government course with an enrollment of 35 senior
and graduate students majoring in Urban Studies or
Political Science. The course was scheduled to meet
one afternoon a week for three hours and the in-
structor received continuing assistance from a gradu-
ate assistant. The game was played on alternate
weeks with an analytical and strategic discussion
taking place during those alternate weeks when the
game was not played. Figure 30 illustrates a typical
two-week schedule:
FIGURE 30—Schedule of Course Activities
A. Week I
Time
Activity
30 minutes Course assignments, general discussion.
30 minutes Distribute results from last game round,
cite highlights and trends, players record
progress toward individual objectives.
30 minutes Players analyze progress, revise role ob-
jectives, formulate strategies.
60 minutes Players negotiate with government, eco-
nomic and social sectors to maximize
progress towards stated objectives.
30 minutes ... .Players complete decisions, write out de-
cisions and report to game director.
B. Week H
120 minutes ... .Course lecture and discussion.
15 minutes Distribute "BLUECITY GAZETTE" and
"PEOPLE'S ADVOCATE".
45 minutes Hold "town meeting" to discuss and
analyze progress in game and relate game
to course objectives.
The above schedule varied for purposes of the
introductory session, examination periods and other
related coursework. In retrospect, it would have
been more advantageous to have the course meet
twice weekly for two or two and one-half hours
each meeting so that the participants would have
shorter elapsed time intervals. In the intervals be-
tween the meetings described above the graduate
assistant edited the "newspaper", prepared computer
input and output, developed visual presentations and
assisted the players. The players held numerous in-
76
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formal meetings for strategy and analysis and were
generally infected with a high level of interest and
enthusiasm.
ORGANIZATION OF PLAYERS
At the initial class meeting the students decided
who should be mayor and then self-selected their
role in the social sector or economic sector. Hence,
each of the students became a player in one of the
three sectors.
The government sector of Blue City was struc-
tured after a commission form of local government
whereby the government officials were both council
members and department commissioners. The struc-
ture was devised more for the purpose of conveni-
ence relative to the limited number of players than
for a desire to structure some "desirable" form of
local government. The government participants
were as follows: the Mayor, Transportation
Commissioner, Planning and Zoning Commissioner,
Education Commissioner, and the Public Works
Commissioner.
The Mayor was elected by a simple majority of
the class participants. Each candidate gave a plat-
form speech indicating his or her respective objec-
tives for Blue City as well as the intended short
and long-range plans. After the election of a "lib-
eral" mayor for the city, he then selected his staff
of commissioners. The Mayor's responsibility con-
sisted of overviewing the general administrative
policies for the city as well as directing the publica-
tion of the People's Advocate newspaper. The
People's Advocate, as opposed to the Blue City
Gazette, was a government publication. It assumed
the role of indicating the "accomplishments" of
Blue City to the public as well as future goals and
plans. It may be interesting to note that the opinions
expressed hi the People's Advocate and the Blue
City Gazette varied considerably. The Mayor, at
numerous meetings, characterized the Blue City
Gazette in terms of "yellow journalism".
The responsibilities of each commissioner were
as follows: the Transportation Commissioner as-
sumed the role of overseeing the building, mainte-
nance, and administrative activities of roads, bus
and rail. The Planning and Zoning Commissioner
was responsible for assessment and zoning activity
of Blue City. The Education Commissioner was
responsible for the building, maintenance and loca-
tion of public, private and vocational schools. The
Public Works Commissioner directed the building
and maintenance of municipal services and utilities.
The Economic teams, by virtue of their assigned
responsibilities, had a greater degree of influence
than did the Social teams with respect to influencing
the growth of Blue City. The assigned responsibili-
ties of the Economic decision makers involved
bidding on and/or purchasing land or developments;
changing rents, prices, salaries and maintenance
levels; transferring cash; lending, borrowing and
investing capital; and building, upgrading or de-
molishing developments. It was found preferable to
have at least two participants for each Economic
team. With a limited number of participants, it was
also determined that Economic teams should consist
of more participants than the Social teams.
The assigned responsibilities of the Social teams
involved voting, boycotting, time allocation, and
setting the dollar value of time. Apart from the
assigned responsibilities to the Social decision-
makers from the manual, it was determined that the
Social teams should have a greater degree of political
influence. A simple majority of the Social decision-
makers could recall the mayor and provide for the
election of a new mayor, and they were also given
a "veto" role through the referendum over certain
bond and zoning decisions.
The Blue City Gazette reported statistical city
data from one round to the next as well as edi-
torialized on the activity of the Mayor and his staff.
It was found that the Gazette afforded the class
participants a vehicle for assessing the development
of Blue City. The People's Advocate offered a basis
of comparison between the statistical data as well
as the Mayor's own interpretation of the data. The
use of "newspapers" was found to be an effective
communications link between the various sectors
and also aided the student's comprehension as to
"What is happening to our city?"
GAME RESULTS
At the outset of the game each of the players was
required to formulate an explicit set of objectives for
his sector and his role. Once during the term he
revised these objectives in light of experience and
changed attitudes. At the close of the term he
analyzed his own rounds of play as to how well he
achieved his objectives and what factors contributed
to his success and failure. Likewise, he evaluated
the performance of Blue City as a system and as a
77
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learning experience. A review of the results of the
student's experiences is most revealing.
In the government sector the Mayor and his
Commissioners had wished to first increase the
supply of jobs in construction and manufacturing to
lower unemployment. One method used to accom-
plish the objective was to grant public subsidies to
private housing construction and manufacturing in-
dustries. This objective was met in part during the
last round when 80 new jobs were created. Un-
employment dropped from its highest level of 8,760
workers in round three to zero unemployment in
round six. This was largely attributed to new con-
struction which offered new jobs of major impact
for the unemployed.
The second objective of the government sector
consisted of providing a higher standard of living
for the poor. The criteria for a higher standard of
living for the poor was to raise the welfare payments
from $l,500/famity/year to $2,500/family/year.
This was done by round six which was the last
round the first Mayor held office. Rounds seven,
eight, and nine, however, reflect a decreased welfare
payment to $l,600/family/year which was a differ-
ent policy by the new Mayor in the second quarter
of play.
A third objective of the Mayor was to increase
the supply of housing for low income families, par-
ticularly in the northeast section of Blue City. The
demographic map, however, indicated little or no
increase in housing for the northeast section.
A fourth objective of the Mayor was to increase
public participation by holding town meetings on
local issues and by the publication of a newspaper
called The People's Advocate. Town meetings were
held during each class session. The Mayor, however,
seemed to find a great deal of opposition to several
issues, most of which are reported in the Blue City
Gazette. (Examples of the newspapers are in Figures
31 and 32.) One issue of considerable debate, par-
ticularly from the Economic Sector, involved the
Mayor's policy to increase welfare payments. The
Economic Sector thought it more advisable to in-
crease the quality and quantity of public utilities
which would assist in the development of new con-
struction which would provide the needed jobs. As
was noter earlier, welfare payments were increased.
A recall election was then held as a result of the
wishes of the Economic Sector. The Mayor won
reelection by three votes and he termed his victory
to be a "clear mandate".
The objectives of the Commissioners of the
Mayor's departments were numerous. The Trans-
portation Commissioner wanted to increase the
number of bus routes. This objective was not
realized because of bureaucratic red tape and pro-
cedural errors. The Commissioner once unsuccess-
fully attempted to establish a bus route through a
farmer's corn field. The Planning Director's objec-
tive was thwarted when agreement upon a compre-
hensive plan was not obtained. The Education
Commissioner wanted to improve the quality of
education but continually found populated areas
without established school district boundaries. It
was also found that the average educational level
decreased from an index of 60 in round one to 57
in round six. At the same time, the student-teacher
ratio increased from 14 to 15. The Commissioner
of Public Works wanted to build a new utilities plant
to provide for expanded construction but he forgot
to transfer monies from the operating budget to the
capital construction budget.
78
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FIGURE 31
Ptoe Citp
Vol. 1
Tuesday, February 15, 1971
No. 2
MAYOR MCCARTY WINS RECALL ELECTION;
APPOINTMENTS REMAIN THE SAME
VO
Tlie "goo-goos" of BLUE CITY, in
their attempt to recall the Mayor and
his staff, failed in their efforts. By the
vote of twenty to seven, the Mayor was
retained. He was quoted as saying,
"This is a clear mandate for my pro-
grams!" The Mayor, however, was
four votes from losing his Supercar.
Perhaps the most devastating deci-
sion the Mayor has made is advocating
additional bonding for city expenses.
BLUE CITY is spending a total of
$34.09 million this year for the interest
on bonds. This represents almost a
50% increase in interest payments. In
fact, BLUE CITY is receiving almost
half off its operating capital from
bonding—the other half in taxes. If
the taxes were raised as this newspaper
advocated, we would not be spending
the city's tax money paying for the
interest on bonds. It would not surprise
this newspaper if the Mayor advocated
more bonding to pay for existing bond-
ing!
Other statistics that might be of
interest to the citizens of BLUE CITY
are: Total unemployment went up
from 6,800 to 8,760 in proportion to
an approximate increase in population
(282,000 to 287,500). Furthermore,
welfare payments remained the samel
No new jobs were created. This could
be attributed to a lack of new construc-
tion on the part of the Economic De-
cision Makers. Although construction
was attempted, the economic teams
either did not have the available re-
sources needed, the level of municipal
services was too low, or the decision
was written incorrectly. Please refer to
the computer printout (a blue X in-
dicates the decisions that were re-
jected).
The Public Works Commissioner
has no available revenue in his Capital
Account for utilities. This, in effect,
precludes any new construction for
utility service. Apparently, the Mayor
has not seen fit to allocate his budget
accordingly.
The Transportation Commissioner
failed in an attempt to build an addi-
tional road for the Nord-East section
of the city.
There are, however, several en-
lightening statistics for BLUE CITY.
First, the number of low income work-
ers has dropped from 77,500 to 72,000.
There has been an increase of medium
and high income groups in the city—
an increase of 6,000 and 5,000 people
respectively. Also, the average dis-
satisfaction level went down from 112
to 108. Housing quality improved in
grids 102-24, 25, and 26, owned by
Economic Decision Makers "G", "A",
"C" respectively. Good work!! Also,
Grid 100-32 improved, and is owned
by Economic Team "A".
There is overcrowding in virtually
the entire city. Economic Team "D"
was the only team that improved their
overcrowding in Grid 100-30. Total
welfare payments went up to over $1.3
million. BLUE CITY is on the brink
of financial crisis. New construction is
needed for new jobs which, hi turn,
brings in additional tax revenue. Taxes
must be raised in lieu of new bonding,
and the Mayor must establish a rapport
with the business community.
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FIGURE 32
00
o
people's Slbtiocate
Vol. I
Tuesday, January, 26, 1971
SCHOOLS SHOULD PROGRESS UNDER
NEW DECENTRALIZED ADMINISTRATION
In keeping with this administration's
campaign pledges, we are proud to
announce the appointment of Ronald
Bellfield as new BLUE CITY Com-
missioner of Education. Mr. Bellfield
finds his new job challenging, and will
bring to the office a high degree of
competency, having served previously
as Commissioner of Schools in New
York City.
We have in this decentralization of
administrative responsibility new spe-
cialized expertise for this critical field.
The policy of this journal will be to
keep the public abreast of the activities
which government is taking in their
behalf and with their participation.
The public officials of your city took
the following actions in recent weeks:
The Mayor:
1. Welfare' payments were increased
by $1,000 per year for each unem-
ployed worker. This begins to give even
our unemployed citizens the ability to
participate in our growth and standard
of living.
2. A small employee's auto tax of
1% was added to pay for welfare,
transportation and utilities expansion.
Department of Transportation: (Com-
missioner G. Roadrummer)
1. A new bus line was established
in the N.E. section to enable the mo-
bility needed for that area's residents
to take advantage of employment op-
portunities throughout the city. Also,
this will create new opportunities for
the residents of the whole city to par-
ticipate in the civic affairs of the whole
city.
Department of Planning, Zoning and
Assessment: (Commissioner D. Snoopy)
1. Rezoned parcel 102/22 in the
N.E. section of town to recreational
use for the establishment of a park.
This section was completely without
parks and playgrounds before this
action.
Additional tax burden for this action
is not anticipated due to pending fed-
eral funding to the extent of $50,000,
nearly the total cost of development.
Department of Public Utilities and
Schools: (Commissioner B. Mouse)
1. Increased utilities in the R3 areas
of the city to prevent rent increases
for those with fixed incomes. A bond
issue was floated to raise the output of
the utility plant from level 2 to level 3.
This should supply adequate utilities to
the areas previously under-served.
2. Applied for a federal grant to
provide additional teachers and re-
newal of the school in the N.E. section.
FUTURE PLANS:
1. A town meeting will be held Jan-
uary 26, at 7:30 p.m. to develop an
honest assessment by citizens and gov-
ernment of the problems we have and
possible solutions.
The Suggested Agenda:
1. Need for new City Vocational
School (A committee of citizens
have suggested the N.E. section)
2. Incentives needed to get overall
favorable business climate estab-
lished.
3. Highway improvements needed
4. Parks and recreational needs
5. General public school adequacy
hi BLUE CITY
6. Unemployment
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Many of the objectives of the Social and Eco-
nomic Sectors are mutually dependent upon one
another as well as the policies of the Government.
Social decision makers attempted to increase the
educational level, increase employment opportuni-
ties, increase voter registration, allocate time more
effectively, encourage convenient mass transporta-
tion, improve quality and construction of housing,
develop additional recreational areas, encourage
effective government spending, and develop a "col-
lective spirit for decision making". With reference
to the latter objective the Social decision makers
were encouraged to meet collectively relative to their
recently established power in having the deciding
vote on bond issues and major zoning changes.
The objectives of the Economic Sector were es-
sentially self-interest rather than public-interest
oriented. The basic criteria for success was economic
profit. The primary means attempted to obtain a
profit was through land development and construc-
tion. The question of conflicting objectives between
the Economic Sector and the Social and Government
Sectors did not occur relative to the type of con-
struction as originally thought. This could possibly
be attributed to the lack of a comprehensive de-
velopment plan for zoning regulation and develop-
ment. The basic conflict of objectives that arose
between the Economic, Social and Government Sec-
tors was concerned with the way in which tax dollars
were being spent. A priority issue of the Mayor's
platform was to help the poverty groups in Blue
City by increasing welfare payments. This policy
took priority over providing additional utility service
and large government subsidies to the Economic
Sector for utility construction purposes. Without the
required utility levels, additional construction was
impossible. The Economic Sector argued that build-
ing construction would provide jobs for the lower
income groups. The Mayor felt that the welfare
payments were too low and that the additional costs
of raising welfare payments to $2,500 from $1,000
should be the first priority.
Since construction and land development was
one immediate economic objective, it was generally
felt by the Economic Sector that this objective was
not met to the degree that had been projected.
Another economic objective was to bid, buy and
develop available land outside the city parameters.
This effort was made in an attempt to establish a
"New Town" which failed since many of the bids
were too low.
Perhaps the greatest value which the CITY
MODEL game possessed for the Economic Sector
was the insight gained in the necessary procedures
and consequential problems of spending dollars to
gain a profit. New Construction required the proper
zoning, capital investment, the type and availability
of land, utility service, road access, and convenient
mass transportation. Each step was confronted with
either a conflicting or cooperative effort on the part
of the Social and Government Sectors.
The Government, Economic and Social Sectors
were confronted with a number of frustrations in
attempting to meet their objectives. The challenge
of the game which coincides with the frustrations is,
in itself, a valuable learning experience. The city as
a whole did improve considerably through eight
years. With a total increase in population of 51%,
the total increase in employed workers was 55%.
There was a 65% increase in low income workers,
47% increase in middle income workers, and a
56% increase in high income workers. Through
four of the eight years there was no unemployment
and no welfare expenditures. With public school
enrollment increasing 17% and private school en-
rollment increasing 68%, the average educational
level declined 9%. The average number of new
jobs increased 60% which reflects an expanding
community. Although the city initially had an
average increase of 120% for outstanding bond
payments in the first four years, there were no
outstanding bond payments the last four years. The
increased development of Blue City was financed
with a 28% increase in revenue from taxes, much
of which is attributable to an increase in tax-paying
population rather than any substantial increase in
tax rates.
CONCLUDING OBSERVATIONS
A series of evaluations have been made of the
utilization of the CITY MODEL game in our Urban
Studies curriculum. In the first instance the partici-
pants conducted an evaluation of the game which is
summarized below with references to advantages,
disadvantages and recommendations for modifica-
tions.
81
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PARTICIPANT REACTIONS
Advantages
Increased understanding of the role of government
personnel and associated "red tape".
A better understanding of the conflicts between the
government economic and social sectors in an urban
environment, vying for a scarce resource and the need
for public service.
The City Model Game more closely assimilates a
pragmatic urban problem-solving approach than that
of a "text book" approach.
Next best thing to job experience.
A situation in which one feels the general frustration
involved in attempting to promote change. This
necessitates better communication between interests
and increases one's understanding of vested interest
as well as the cause-effect relationships between gov-
ernment, economic, and social participants.
Disadvantages
Problems in understanding the computer language as
they apply to desired decisions.
Lack of formal prerogatives in the social sector in
making decisions that would have a greater con-
sequence for the city as a whole. (This was corrected
somewhat in giving the social participants new
powers.)
The government sector did not establish a clear system
of priorities. They reacted more toward the "outside
system."
The class was made up of a relatively homogeneous
group of college students rather than a representative
heterogeneous group that generally live in an urban
society.
The time limitation in carrying out long-range pro-
grams.
Recommendations
A need for a more graphic display of the city.
More available time should be given to play of the
game with several rounds played in one day.
Initiate field trips to local units of government in
order to better translate and compare the statistical
data of Blue City with an actual urban situation of a
similar nature.
Hold town meetings at regular intervals where all class
members can participate.
Open up a means for communicating with other
schools playing the City Model Game.
Provide the social sector the power to determine the
need for bonding and zoning changes through a refer-
endum. This may be a vehicle for the social decision
makers to better organize and participate to a greater
degree in "role playing". (This was changed for the
next game.)
Provide a better understanding how specific decisions
affect the "dissatisfaction index".
Concentrate on the importance of "role playing" prior
to starting play of the City Model Game.
The objectives which I had suggested at an earlier
point in this chapter were all capable of examination
during the utilization of the game. My basic evalua-
tion is highly positive regarding the value of the
game as a learning tool. The participants demon-
strated a far more sophisticated appreciation of the
city at the close of the term. Many standard con-
cepts were applied and hence tested in the game.
The existence of conflict and personality became
important to the players. Coalition and strategy
building exercises were realistic. The frustration and
delay of the "real system" became more obvious.
The analytical techniques of the students were
tested and improved. The existence of the city with
many dimensions and a system was demonstrable.
The use of gaming improved the student/instructor
relationship and provided an absorbing learning ex-
perience for the students. Considerable student
initiative was demonstrated, including the continued
play of the game on an independent study basis.
From our use of the game it would appear more
appropriate to use the CITY MODEL in an "Urban
Systems" or "Urban Simulation" course where it is
the primary course method and the course can be
developed around the game. It is very desirable to
have the game mounted on a computer in close
proximity so as to minimize the "turn around"
inconvenience. The help of a graduate assistant or
student assistant is imperative. I would suggest that
the "intellectual payoff" of the CITY MODEL is
highest within an interdisciplinary course because
the game is an excellent interdisciplinary tool,
whereas for students from only one discipline much
of the role-playing is beyond their experience. It
would appear that this tool would have greater
advantage for advanced students rather than begin-
ning students.
Based upon this experience with gaming in the
Urban Studies curriculum, I have concluded that
gaming can perform a valuable function within the
curriculum. It is an excellent experience for students
to test and hypothesize about real urban environ-
ment relationships. The dynamics of the game are
very revealing. This model permits the urban social
scientist to enjoy many of the laboratory experiences
which prove to be of strong benefit to the Urban
Studies student.
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CHAPTER XIV
Memphis State:
CITY MODEL Experience*
by Robert Dean
INTRODUCTION
During the spring semester of the 1970-1971
school year, a group of 16 graduate students from
the Departments of Economics and Geography had
both the privilege and pleasure of "playing" the
CITY MODEL. With the exception of this writer,
none of the students had ever participated in a
simulation-gaming exercise, nor had they ever been
given much exposure to the input-output media of
computers (i.e., code sheets, punched cards, and
computer printouts)! Despite these obstacles, the
students found the interaction with the CITY
MODEL a most rewarding experience and were
eager to participate again in such a venture. Indeed,
it was the opinion of most of the students that addi-
tional sessions with the CITY MODEL would be
required if maximum benefits from the use of the
Model were to be achieved. Simply put, their argu-
ment was that the more innovative uses of the
Model can only occur after prolonged and extended
play.
The decision to utilize the CITY MODEL as one
of the principal teaching tools hi the joint seminar
with the Geography Department on urban problems
*The modeling exercises could not have been carried out
at Memphis State without the support of the Bureau of
Business and Economic Research. In particulai, a great
debt of gratitude is owed to Mr. David Gilles, a Research
Assistant in the Bureau, for his untiring efforts in oversee-
ing the modeling exercises. Without his contributions, the
gaming sessions would not have been possible.
*Insofar as I can determine, this was the first experience
at Memphis State in holding a joint course by departments
|n two different colleges. (The Economics Department is
m the College of Business Administration, and the Geo-
graphy Department is in the College of Arts and Sciences.)
was by no means accidental. Having used Alan
Feldt's Community Land Use Game (CLUG) and
Richard Duke's METROPOLIS in courses dealing
with urban planning, I was well aware of the student
interest and excitment in playing the roles of public
and private decision makers in the urban arena. In
the past, however, my experience with the use of
simulation-gaming as a teaching device had been
limited to undergraduate students. Moreover, I had
never attempted a modeling exercise with the com-
plexity and level of sophistication associated with
the CITY MODEL. Therefore, I treated the use of
the CITY MODEL as an experiment for the in-
structor as well as the students!
Because of my own limited experience in handling
a modeling effort with the degree of complexity of
the CITY MODEL, I decided to use a graduate
seminar as the testing ground for the gaming ex-
periment. I assumed (perhaps erroneously) that
graduate students would more readily grasp the
technical aspects of niter-acting with the CITY
MODEL, and that they would be better able to
make more meaningful decisions within the time
span of one semester. Graduate students from both
the Geography Department (the Geography Depart-
ment offers a heavy concentration of courses in
urban geography and planning) and the Economics
Department were invited to participate in the semi-
nar.* Because both the Geography and Economics
Departments had a number of graduate students
with full time jobs during the day, it was decided
to hold the urban problems seminar at night. In
retrospect, the decision to make the seminar avail-
able to the older, more mature graduate students
was a good one. This particular group; of students
(roughly half the class were hi this category)
83
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brought first-hand knowledge of the problems con-
fronting the Memphis Metropolitan region. Equally
important, they had had some experience in dealing
with these problems locally and fortunately were
able to transfer their work experiences in a useful
and meaningful manner to those students who had
had little work experience in the "real" world.
The course was officially designated as a Seminar
in Current Economic Problems (Economics 7190)
and was offered one night a week. Traditionally, the
instructor or teacher of this seminar is given a great
deal of freedom and latitude in course structure,
therefore it seemed to be the course best suited for
experimentation with the CITY MODEL. The stu-
dents agreed to meet from 6:30 to 10:30 p.m. on
Wednesday evenings, even though the required num-
ber of hours of class meetings would only have
called for sessions from 6:30 to 9:30 p.m. It is also
worth noting that the sessions were not held in the
traditional classroom setting. Instead, a group of
rooms and offices adjoining the University's Re-
gional Economics Library and the Library itself
were used for the gaming sessions. The more spaci-
ous conditions were instrumental in achieving a
more realistic environment for role playing in the
CITY MODEL.
THE COURSE
The seminar in urban problems had three major
objectives. The primary objective of the course was
to improve the student's understanding of the nature
and scope of such urban problems as chronic un-
employment, poverty, housing shortages, crime and
violence, inadequate health delivery systems, and
so forth. Another important objective was to get the
student to visualize the City's problems in "holistic"
or "systemic" terms. In other words, the aim was to
encourage students to view the activities of the City
as being closely related and interdependent (e.g., an
unemployment problem will exacerbate a health
problem, the loss of industry and jobs in the private
sector will reduce the number and quality of services
offered in the public sector through reduced tax
revenues, etc.). A third objective was to encourage
the student to use an interdisciplinary perspective
when dealing with urban problems—that is, to look
at the problem not only from the viewpoint of an
economist, but also from the perspective of a
geographer, planner, political scientist, etc.
The CITY MODEL was essentially used to help
achieve all of these objectives. Based on my previous
experiences with CLUG and METROPOLIS, I
found that the actual experience of dealing with a
land-use problem (e.g., zoning) makes the student
more sensitive to the broader concept of land use
planning. Thus, it was felt that the problems of
housing, unemployment, education, health, etc.,
would be more readily understood by the students
if they were able to work on these problems at the
same time they were dealing with them within the
traditional classroom and academic framework. It
was also felt that a simulation-game of the CITY
MODEL type would enhance the student's ability
to view the City as a system of interconnected
activities and institutions. Indeed, many of the out-
puts of this particular gaming model (e.g., land use
maps, economic indicator tables, etc.) are designed
in such a fashion that the City can be viewed more
easily as a single entity than as several separate
and disparate parts.
Through proper role-placement of students with
different discipline backgrounds, it was also hoped
that the modeling effort would help the students to
broaden their perspective to include the thoughts
and ideas of other disciplines when dealing with a
particular problem. In this case, the advantage of
the CITY MODEL is that it encourages interaction
between the various role players, thus making it
possible for a certain amount of "knowledge trans-
fer" to take place between disciplines.
The seminar in urban problems was essentially
developed along three lines. First, the students were
asked to read a number of books dealing with urban
issues and problems. These materials were then
discussed throughout the semester and in conjunc-
tion with the modeling effort. Second, the students
were assigned roles in the CITY MODEL and were
expected to devote a major portion of their weekly
class meetings to the gaming experiment. Third,
each student was asked to prepare a research paper
dealing with a particular local urban problem. Each
student was also asked .to present his paper at one
of the class meetings so that all of the students
would develop a certain sensitivity towards local
issues and problems at the same time they were
grappling with similar types of problems in the
CITY MODEL.
DYNAMICS OF PLAY
Insofar as the utilization of the CITY MODEL
is concerned, certain steps were taken to minimize
the students' problems in mastering the mechanics
84
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of making decisions. One full classroom session was
devoted to the discussion of the major decision-roles
in the CITY MODEL as well as the many printouts
and reports that result from each role player's
decision inputs. During the first session, each stu-
dent was assigned a particular role (i.e., social
decision maker, economic decision maker, mayor,
etc.) and asked to read that portion of the CITY
MODEL manual dealing with his role. Using the
manual as a guide, each student was also asked to
fill out a decision sheet for the next class meeting
and be prepared to answer questions concerning
each type of decision that he (she) could make.
Each student was also asked to maintain a diary
on his particular decisions as well as keep a listing
of any problems or criticisms he had of the gaming
experiment. The diary proved to be quite useful,
since both the student and instructor could review
the decisions and the reasoning behind them over a
number of gaming sessions. The diaries clearly
revealed that as the students became more knowl-
edgeable about their roles, they were able to make
a greater number of decisions within a shorter period
of time. The decisions in later rounds also appeared
to be based on more information and a better under-
standing of their possible effects on the economic
parameters of the model.
Concerning the play itself, the economic decision
makers can best be described as rather conservative,
cautious players. The aversion to risk-taking was
especially noticeable in the early rounds when the
students were quite uncertain as to the outcome of
particular decisions. Insofar as I can determine,
none of the economic decision makers had a "game
plan." Most of the decisions in the early rounds
were not made in a systematic fashion or developed
in a coordinated manner. In later rounds, however,
many decisions were made as a result of actions
taken in earlier rounds. For example, an economic
decision maker would build some housing units for
rental purposes and then find they were under-
utilized. He (she) would then consider building
commercial or manufacturing establishments close
by in order to induce more people to live in the
under-utilized housing units and build up a good
supply of labor. Just as likely, the procedure would
be reversed, and the emphasis would be on building
housing units near a previously built manufacturing
plant in order to maintain an adequate supply of
labor close to the plant.
Most of the economic decision makers made good
profits on their business operations, although losses
on particular investments were not uncommon. It
was also evident that profit maximization was the
primary motive for making decisions, subject, of
course, to the twin constraints of risk-taking and
uncertainty.
The social decision makers did not have an op-
portunity to exercise their voting power; therefore
they spent much of their time trying to improve
social conditions in the City. A few boycotts on
retail establishments were attempted, but for the
most part, their approach was to use "moral per-
suasion" on public officials and economic decision
makers to change their attitudes toward problems
such as poverty, poor housing, job discrimination,
etc. The social decision makers did succeed in
getting the mayor to establish a housing task force
to investigate the poor housing conditions in the
City. As we shall see shortly, this particular task
force was quite instrumental in getting "slum" land-
lords to improve and upgrade their properties.
The public decision makers made a concerted
effort to improve the welfare of the City, although
the indicators used to measure economic progress
do not clearly reflect the intensity of this effort.
During the early rounds, the "game plan" was to
obtain additional revenue to upgrade the school
system and municipal services, while at the same
time bring about a redistribution of the tax burden
so that it would fall more heavily on the business
community and to a lesser extent on the work force.
Lower income residents also received a tax break
through the reduction of sales taxes on goods and
services while the tax on auto owners was raised
in the hopes that the use of public transportation
would increase.
A substantial public deficit in the early rounds,
however, caused the public decision makers to
modify their target objectives until the deficit was
significantly reduced. By the sixth round, the deficit
was under control, and the earlier effort to improve
the quality of municipal services and the school
system was renewed. During this round, a serious
review was also made of the City's more pressing
problems. As a result of this review, it was decided
that more park and recreational land was needed for
the City, and money was appropriated to the plan-
ning and zoning department for this purpose. Rising
complaints from the social decision makers about
the high tax rates on lower income residents and
their deplorable housing conditions prompted the
mayor to lower the residential income tax rate and
the employee income tax rate. In addition, the mayor
85
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appointed a committee to review the housing condi-
tions in the City and provide him with recom-
mendations concerning the proper resolution of this
problem.
In the last round, an election was held, and the
incumbent mayor lost to one of the economic de-
cision makers who was dissatisfied with the higher
taxes on business properties and the move towards
a "socialist" form of government. Unfortunately, the
new mayor did not have time to carry out his con-
servative policies since the gaming sessions had to
be halted due to the end of the school semester!
A review of some of the economic and demo-
graphic growth trends reveals a fairly successful
performance for the City's economy. Figure 31
illustrates some of these trends. Chart A and B
indicate that the population increased 52 percent
and employment 46 percent over the eight rounds
of play. Thus, the City appears to have grown at a
fairly steady rate with population at a little over
6 percent per annum and employment slightly less
at 5 percent annually. The unemployment chart
shows little or no unemployment from round 3
through round 7 of play, thereby indicating a full
employment economy over most of the gaming
sessions. Although unemployment was quite low
(except for round 8), Chart C indicates that the
proportion of workers earning less than $5,000
actually increased from 38 percent to 40 percent of
the total work force during the gaming sessions.
This is somewhat alarming, since this group of wage
earners are largely unskilled and semi-skilled and
are not capable of being absorbed into more capital-
intensive industries (with higher wage rates) without
considerable retraining and additional education.
Despite this apparent weakness in the structure of
the work force, it is evident that the social welfare
of the community improved considerably during the
period of play. As Chart E indicates, per capita
income had risen steadily during the gaming session.
As of the end of the seventh round, per capita
income had reached $2,000, a 17 percent increase
over the base year figure. This improvement was
extremely encouraging to the students, especially
those that played the role of social decision maker.
With regard to certain key economic indicators,
then, the City appeared to be better off at the
end of the gaming sessions than at the start. It is
extremely difficult, however, to single out one par-
ticular factor that contributed most to this improve-
ment in economic well-being. Perhaps it was due
to the rather conservative manner in which the
public and private decision makers made decisions.
Possibly it was due to the fact that the national
economy was fairly strong during the gaming ses-
sions and therefore gave added strength to the local
export sector. Regardless of the causes, the students
were most delighted to achieve the twin objectives
of full employment and rising per capita income—
a most unlikely occurrence in the real world!
CONCLUSIONS
It should be made perfectly clear to the reader
that no attempt was made to measure with precision
the importance of the CITY MODEL as a learning
tool. Because others have traveled this road before
and have not really had much success in insolating
the contributions of simulation gaming to the learn-
ing process, I find it expedient to withhold any
comments on the degree of usefulness of the CITY
MODEL except to say that the modeling effort was
an extremely worthwhile experience in group inter-
action and certainly the highlight of the seminar.
In reviewing the course in more realistic terms,
it is fair to say that we were moderately successful
in meeting the three course objectives. Based on the
results of the research papers and the class dis-
cussions that took place before and after the gaming
sessions, it was clear that most of the students had
a better understanding of some of the gut issues
facing our cities at the end of the course than they
did at the beginning. Although I cannot support this
contention with empirical evidence, it seemed to me
that the background readings, modeling exercises,
and research papers are complementary learning
activities, i.e., one reinforces the others. In this
particular case, the background readings provided
a basic frame of reference for the role players in
the modeling effort, while the modeling effort in-
creased the students' sensitivity and awareness
towards certain urban concepts and problems. In
turn, a heightened awareness of a particular problem
made it easier to construct and implement a research
design related to that problem.
The students also became more cognizant of the
fact that the city is a system of interdependent
activities, although not with the degree of sensitivity
and understanding that I had hoped for. The lack
of real success here, however, cannot be blamed on
any inherent weakness in the CITY MODEL, but
rather on the failure of the instructor to create
opportunities for the students to use the Model's
structural relationships to better advantage.
86
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Figure 33.—ECONOMIC AND DEMOGRAPHIC TRENDS
Chart A
Population Growth
Chart B
Employment Growth
123456
Round
7 8
12345678
Round
Percent
Unemployed
6
Chart C
Unemployment Trend
Chart D
Wage Distribution
12
345
Round
678
Percent
Total Work
Force
50
40
30
20
10
» «•••••»
• *«. . „
* .' *. Und«
\ """^a^r^L^
.•X___ ^ — ***VT>~- 50
m •
^. • ^^ m
jm • MM • i^ •
• Over
*'^f''^ 10000
1 2345678
Round
5000-10000
Per Capita
Income
2000
1900
1800
1700
1600
1500
Chart E
Per Capita Income Trend
12345678
Round
The problem boils down to this: most of the
students were so involved in their own roles that
they had little time or interest in viewing the City
as a single entity or investigating the relationships
between different sectors of the economy unless their
role required them to do so. To compensate for the
students' lack of "integrating" experiences, some of
the "rap" sessions concerning the modeling exercises
focused attention on the concept of the City as an
integrating mechanism. Another approach, and one
that appeared to have greater utility, was to establish
policy task forces to review a certain problem or
issue. One of the more interesting task forces was
the Housing Commission. This particular task force
consisted of three students, and its objective was to
determine the conditions of housing in the CITY
87
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MODEL and what if anything needed to be done
to improve these conditions. After a thorough
analysis of maintenance levels on housing, the Hous-
ing Commission recommended that all housing in
the City have at least a .50 maintenance level. The
economic decision makers, of course, balked at this
proposal because it would cut down on then* profits
and in many cases result in substantial losses in
particular housing units.
Thus, the conflicting issues of economic profit and
social welfare were joined, and after several hours
of heated debate, the problem had still not been
resolved. Eventually, a new mayor reached a com-
promise with the economic decision makers whereby
the City would pay them subsidies to improve and
rehabilitate their properties. The beauty of this par-
ticular exercise, however, lay not in the solution to
the problem, but in the process through which the
problem was resolved. The students on the housing
task force had to view the problem of poor housing
conditions as essentially a problem for the whole
City to resolve, but in recommending solutions it
also had to come to grips with the fact that certain
groups or economic classes (e.g., slum landlords)
would not benefit personally from these decisions.
Because of the conflicts that result when one vested
interest group stands to lose at the expense of
another, most of the students gained a better ap-
preciation for the problems of developing a citywide
policy on housing standards as well as the delicate
relationship between housing conditions and eco-
nomic profit.
The attempt to create an interdisciplinary per-
spective in urban problem solving did not meet with
much success. Unfortunately, the structure of the
CITY MODEL does not promote this type of
learning process nor does it mitigate against it. Once
again, if the instructor is innovative, a number of
ad hoc task forces which are multi-disciplinary in
makeup can be established to consider urban prob-
lems within an interdisciplinary framework (e.g., a
task force on transportation policy would include a
sociologist, political scientist, geographer, planner,
engineer, and an economist). However, most stu-
dents—even graduate students—have not progressed
to the point where they can develop on their own
comprehensive solutions to a problem as complex
*At Memphis State, we would like to load 1970 Memphis
block and tract data on population and housing into the
CITY MODEL, develop local population and land use
growth patterns, and hi general operate the Model as a
replicate of the local development process.
as urban transportation; therefore, the task forces
would need faculty support. In turn, this would
require a team teaching effort, which was logistically
not possible for this particular seminar.
Summing up, even though the objectives of the
course were not completely achieved, it would be
unfair to say that the CITY MODEL was mainly
responsible for this lack of achievement. It should
be kept in mind that this was an experiment for
both the instructor and the students, and that in
subsequent sessions, more effective and innovative
uses of the CITY MODEL would result in higher
achievement levels. As I see it, however, the main
problem with the use of CITY MODEL is the in-
ability to manipulate the key parameters of the
Model (e.g., economic growth rates, social condi-
tions, production capacities, etc.), thereby making
it more flexible and susceptible to innovative ap-
proaches to urban problem-solving. In order to
create this type of learning environment, the students
and the instructor must know more about the inner
workings of the Model itself. In turn, this calls for
the computer programs that form the basis of the
CITY MODEL to be housed at the college or
university carrying out the modeling experiment.
The location of the CITY MODEL at each partici-
pating university would also increase the frequency
of interaction with the CITY MODEL. Moreover,
the laborious process of mailing decisions to Wash-
ington, D.C., and then waiting a week or more
for the results of these decisions tends to have a
dampening effect on the students' interest and at-
titude towards the modeling exercise. Indeed, the
most common complaint heard during the modeling
experiment was Why Can't We Get the Results of
Our Decisions Tomorrow? Although this is probably
a universal complaint and not easily solved without
terminal devices and "real time" or "shared time"
computer processing capabilities, the problem of
"output" delay would be less severe if handled
locally.
There is also a need to feed local demographic
and economic statistics into the CITY MODEL so
that students can actually work on problems that
are both important and extremely familiar to them.
This can best be done by transferring the CITY
MODEL to the local university or college carrying
out the modeling experiment.*
The other criticisms that we have of the CITY
MODEL are minor iu nature and mostly have to do
with the mechanics of "playing the game." The
majority of the students felt that the player's manual
88
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was overly complex, and that the sections dealing
with individual roles should also include decision
input formats, the procedure for making decisions,
and those computer printouts most important to a
particular role (decision maker). Another frequently
heard complaint was the inability to go to one
source or computer printout sheet for needed data.
Although this is not possible to achieve under the
present reporting system, some additional considera-
tion should be given to the data needs of each role
player and whether or not more realistic data com-
binations can be developed. For example, it would
be extremely useful for the player operating the bus
company to have the geographical locations of the
labor force and the work sites combined on one
printout sheet There was also a strong feeling
among the students that the social decision makers
were quite limited hi the number and types of de-
cisions they could make, and that this particular role
should be either expanded greatly or dropped com-
pletely in favor of new roles that emphasize the
activities of agencies dealing with health and welfare
problems.
As indicated above, however, these criticisms do
not materially detract from the basic strengths of
the CITY MODEL. Indeed, our interest in CITY
MODEL is very high, and we are anxiously looking
forward to continued interaction with the Model
during the next school year.
89
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CHAPTER XV
Conclusion
CITY MODEL was designed to be a non-scoring
game. It was to be as difficult to compare one out-
come with another as is the case with real life cities.
This conceptualization of the outcomes of the model
meant that an objective comparison of the status of
the model generated from different plays was not
expected, because each of the users was free to
decide his own criteria for the "best" or desirable
city.
However, to partially satisfy the very natural urge
to compare the model runs, the data in Figure 34
was prepared.
The five university plays are compared in terms
of four types of measures: 1) population (size,
composition, and growth), 2) land use (amount
and value), 3) business and personal income and
employment, and 4) government finance (annual
taxes and debt structure). These measures do not
provide a comprehensive set of indicators, but they
do provide a feeling for the trends that developed
during the various plays.
With regard to population growth, it is interesting
to note that the greatest total growth was associated
with those plays in which the middle income (PM)
population class became the larger part of the total
distribution. For example, in the Georgetown play
(where the total population growth was largest), the
PM class grew to be 38 percent of the population
while in the Mankato and Memphis plays (with the
least total population growth) the percentage of
PM's declined compared with the starting position.
In all the plays, the reliance or greater assess-
ments on developments compared with those for
land persisted. The residential developers lagged
behind local demand (as is indicated by the housing
vacancy rate) in all the plays except for American
where the professor (in a real estate course) placed
emphasis on the students' making development plans
and justifications.
The business income measures indicate that
Heavy Industry maintained its dominance over the
other forms of basic industry except in the case of
Dartmouth. With regard to second place in the basic
industry importance, National Services lost out to
Light Industry in every play except American. This
is a little bit surprising since the National Services
industry is the most footloose form of basic industry
and it has the least requirements for transportation
access and utility service.
All the plays developed a positive balance of
trade. The large differences among the five plays
are explained by the composition of the basic in-
dustries in each city and the success that each city
had in stemming the purchase of goods and services
from the outside system by providing adequate local
supply.
The income distribution is related somewhat to
the population distribution by class, but even more
so the general level of salaries in the five different
plays. The Georgetown play showed the largest
percentage of workers receiving over $10,000 per
year in salaries.
The cost of government increased above the base
year in all of the plays, but the different schools
selected quite different strategies for financing these
increases from tax payments and from bonds. Dart-
mouth struck a good balance and attained both a
low annual tax payment per capita and a low annual
bond payment per capita.
Meanwhile, American traded high bond payments
for low tax payments, while Memphis traded high
tax payments for low bond payments.
It should be made clear that these differences
among the various plays and the many other differ-
ences that are not reflected by these measures were
generated by the users of the model as they strove
to achieve their own unique set of individual and
collective objectives. Furthermore, the influence of
the game director on these differing measures could
90
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FIGURE 34—Comparative Measures for the Five University Plays of Blue City
Round 8 Data
Base Year
(Round 1) American Dartmouth Georgetown
Memphis State
Mankato (Round 7)
1. Population
Total Population
% Change from Base Year
Percent of Population
Low Income
Middle Income
High Income
2. Land Use
Number of Parcels with Development.
Population Density per Parcel
Total Assessed Value of Land
(millions)
Total Assessed Value of Developments
(millions)
Housing Vacancy Rate (negative
indicates overcrowding)
3. Income
Sales to National Economy
(millions)
Heavy Industry
Light Industry
National Services
Balance of Trade (millions)
Total Employed
Unemployed (percent)
Welfare Recipients
Income Distribution (% Under
$5,000/$5-10,000/Over $10,000) . .
4. Finance
Taxes Per Capita ($)
Bond Payment Per Capita ($)
Total Annual Bond Payment
($million)
275,500
_
27
36
37
41
440
$166
$450
6%
469.9
203.0
207.9
(17.1)
81,600
4.90
4,200
38/43/17
184.34
46.20
12.7
428,000
55
27
34
39
51
684
273
852
6%
532.9
473.8
572.0:):
478.6 A
133,160
0
0
36/34/28
230.09
127.59
54.6
448,500
63
26
37
37
50
717
279
950
—2%
501.7
539.3
223.1
175.5
139,560
0
0
37/35/28
203.15
16.68
7.5
462,500
68
24
38
38
52
740
259
1,149
0
723.4
565.8
457.6
647.8
131,480
0
0
35/32/31
258.95
6.90
3.2
418,000
52
27
35
38
47
668
194
667
—4%
620.2
438.3
205.9
356.8
126,920
2.16
2,800
36/35/28
271.37
107.61
45.0
374,500
36
28
34
38
46
599
177
527
—5%
494.0
304.9
298.9
268.1
116,840
0
0
35/37/26
372.89
10.49
3.9
have been large or small depending upon the impact
that Ms structuring of the play had upon the
students.
OBJECTIVES OF THE STUDY
The original objectives of the study were multi-
fold:
• To illustrate that the laboratory so desperately
needed by the social scientist to illustrate theoretical
concepts and to test "what if" questions would best
be served by a computer simulation model.
• To demonstrate that such a simulation, by com-
pressing both time and space could make compli-
cated patterns of interrelationships understandable
to students and researchers hi the field of urban
development.
• To refine a single comprehensive simulation for
teaching. This simulation, by holistically revealing
economic, social, and political variables in a metro-
politan area, was assumed to make courses more
meaningful to a student than have more traditional
methods.
• To adapt the CITY MODEL to extensive class-
room use in interdisciplinary or other social science
courses in urban affairs and analysis so that it could
be used:
as the basic teaching device in a course, or as
a means of illustrating specific principles or re-
lationships.
It appears that these objectives were met by the
project.
FINDINGS AND RECOMMENDATIONS
Following is a summary of the findings and
recommendations of the NSF sponsored use of the
model:
• It is possible to use the RIVER BASIN-
CITY MODEL to teach a variety of social
science subjects. This fact is true regardless
91
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of class size or whether the participants are
graduates or undergraduates.
The presence of a social science laboratory
in an on-going curriculum requires sub-
stantial changes in course context or the
addition of a new course.
The inclusion of a laboratory cannot be
done without some help from a colleague or
a graduate student. Further, the decision to
use the tool will require a considerable time
and effort expenditure on the part of the
professors using it.
Unanimously, the tool was considered a
valuable addition to the conventional dis-
cipline courses. This finding was affirmed
by both the professors and the students.
• The model must be installed on the campus
for really effective use. This would mean
that the model could be more fully utilized
and that the faculty and students could
experiment with it.
In summary, the experiment indicated that the
social sciences are now ready to use a computer
assisted laboratory to teach their subjects. However,
this laboratory must be packaged better and made
available to local universities and colleges so that
they may carry on individual experimentation as
part of their normal educational programs. The
results of the study showed the success of the use
of the model as a pedagogical device but also
showed the difficulty of trying to service its use from
a single centralized location.
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APPENDIX A
Scenarios
Many starting configurations may be developed
by the users of the RIVER BASIC MODEL by
making initial round input or loading a data base.
Two pre-configured regional river basin areas were
developed as part of the EPA project and are
presently available to the user of the RIVER BASIN
MODEL. These areas are called TWO CITY and
RAYWID CITY, and their characteristics are com-
pared in Figure A-l.
FIGURE A-l—Local System Comparisons of TWO
CITY and RAYWID CITY
TWO
CITY
RAYWID
CITY
Land Area (square miles) 3906 2519
Parcels of Land 625 403
Number of Political Jurisdictions. 2 3
Total Population 275,500 2,508,000
Percent Distribution by Class
High Income 37 31
Middle Income 36 34
Low Income 27 35
Percent of Workers Earning
Under $5000 33 36
Total Assessed Value of Land and
Developments (millions) $12,733 $26,296
Average Quality of Life Index .... 69 117
Average Education Level 59 49
Unemployment Rate 7.5% 13.7%
Workers Receiving Unemployment 12,800 127,240
Student-Teacher Ratio 7 6
Percent of Students Enrolled in
Private School 30 13
Features of the Water Component
Miles of River 87.5 130
Number of Rivers 3 7
Types of Polluters
Surface Water Industries ... 4 14
Municipal Outflow Points .... 2 11
Farms Contributing to Runoff 3 8
Total Sewered Population
(thousands) 276 2,508
The director or players might have a preference
for one of these two basic starting positions because
of the number of players, types of problems repre-
sented, or complexity of the local system. It should
be kept in mind that these scenarios and the starting
positions may be modified very easily by the director
making decisions before the play begins. In this
way a large number of initial starting positions are
available just from these two basic configurations.
The director should be sure to modify the
scenario he uses if he makes any modifications in
the starting position. The director should also feel
free to change the format of the scenario to provide
more or less information on the local system. For
example, more information could be presented on
the components of the quality of life indicators or
less information could be presented on the relative
status of the economic teams.
The director can derive alternative scenarios by
carefully reviewing the Round 1 output before it
is distributed to the players. Figure A-2 shows some
of the computer output sections (those circled)
that are most helpful in developing a verbal descrip-
tion of the local system.
A general note about relative wages and outside
system costs should be made for the two basic start-
ing configurations. Average salaries are 37 percent
greater in RAYWID CITY than in TWO CITY
For example, the average salary for high income
workers in TWO CITY is $10,000, whereas it is
$13,700 in RAYWID CITY. The price paid for
purchases from the outside system (for BG, BS,
PG, and PS) are also higher in RAYWID CITY
than in TWO CITY. For example, an outside system
unit of BG sells for $130,000 in TWO CITY and
for $150,000 in RAYWID CITY. These salary and
price differences are explained by the fact that data for
TWO CITY is based upon an average hypothetical
region in the U.S. in 1960. The data for RAY-
WID was derived from 1960 information for the
Cleveland-Akron areas. Salaries tended to be higher
in the Cleveland-Akron area than in the U.S. as a
whole.
93
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FIGURE A-2—Selected Computer Output That Is Most Helpful in Developing a Verbal Scenario
I. Migration
2. Water System
3. Employment
4. Commercial Allocation
5. Social Sector
6. Economic Sector
7. Social and Economic Summaries
8. Government Detail
4.1
4.2
4.3
4.4
4.5
4.6
4.7
5.1
5.2
5.3
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
6.9
RIVER BASIN MODEL OUTPUT
1 Environmental Indexes
Personal Indexes
Dissatisfaction Cutoffs
Migration Detail
Migration Statistics
'Migration Summary
Water User Effluent Content
River Quality During Surface Water Process
Water User Costs and Consumption
Coliform and Pollution Index Values
Employment Selection Information for PL Class
Employment Selection Information for PM Class
Employment Selection Information for PH Class
Part-Time Work Allocation for PH Class
Part-Time Work Allocation for PM Class
Part-Time Work Allocation for PL Class
ployment Summary
Personal Goods Allocation Summary
Personal Services Allocation Summary
Business Goods Allocation Summary
Business Services Allocation Summary
Government Contracts
Terminal Demand and Supply Table
Terminal Allocatiq^.Map
Dollar Value of Tftne
Social Decision-Mafer Output
Social Boycotts
Farm Output
Residence Output
Basic Industry Output
Commercial Output
Economic Boycott Status
New Construction Table
Land Summary
Loan Statement
Financial Summary
)Number of Levels of Economic Activity Controlled by Teams
)Employment Centers
)Economic Control Summary for Teams
) Social Control Summary for Teams
>SociaI Control Summary Totals
)Economic Graphs for Teams
Graphs for Teams
Assessment Report
Water Department Reports
mpling Station Report: Point Source Quality
ipling Station Report: Ambient Quality
Utility Department Report
Utility Department Finances
Municipal Services Department Report
Municipal Services Department Finances
Municipal Services Department Construction Table
Planning and Zoning Department Report
ichool Department Report
School Department Finances
School Department Construction Table
ighway Department Finances
Highway Department Construction Table
Rail Company Report
Bus Company Report
hairman Department Finances
'ax Summary
inancial Summary
94
-------
FIGURE A-2—Selected Computer Output That Is Most Helpful in Developing a Verbal Scenario—Continued
9. Summary Statistics
10. Maps
10.25
10.26
and Economic Statistics
Personal Goods Allocation Map
Personal Services Allocation Map
Business Commercial Allocation Map
Municipal Services Map
School Map
Utility Map
Water Usage Map
Water Quality Map
Municipal Treatment
Municipal Intake and Outflow Point Map
Surface Water Map
Farm Runoff Map
River Basin Flood Plain Map
Farm Map
Farm Assessed and Market Value Map
Market Value Map
Assessed Value Map
lomic Status Map
Highway Map
Planning and Zoning Map
arkland Usage Map
icio-Ecpnomic Distribution Map
mographic Map
Social Decision-Maker Map
Topographical Restriction Map
Government Status Map
RAYWID CITY SCENARIO
RAYWID CITY is a three county regional area
with a population of about 2.5 million. There are
a number of manufacturing establishments, farms,
and municipal sewer systems that contribute to the
pollution of the major river that runs through the
region. This local river system has a basin area that
comprises about half of the land area in the three
counties. Along with high unemployment, poor
water service, housing shortages, and inadequate
municipal services, the polluted river looms as one
of the several major problems facing the regional
area.
Figure A-3 shows a map of the regional area
encompassed by RAYWID CITY. Note that the
upper portion of the map is a lake and that some
parcels of land on the left-hand side are not con-
sidered part of the local system.
Figure A-4 shows the population distribution by
the three income classes for the three political juris-
dictions that comprise RAYWID CITY. Jurisdiction
1 clearly has the largest population. It is also the
residence for the majority of the unemployed work-
ers. The region is experiencing very high unemploy-
ment (16 percent) and all of this is concentrated
in the low income groups. The middle and high
income groups are experiencing some employment
difficulties (underemployment) in that a number
of population units have been forced to take jobs
at salaries below the level they would normally earn.
All of the very high density housing is in Juris-
diction 1, where this type of housing makes up
nearly half of the supply. In both Jurisdiction 2
and 3, single family housing is dominant and all of
the multiple family housing is of a low density
nature.
Figure A-5 shows the allocation of social de-
cision-making power among the nine teams that
comprise the social sector. Note that teams are
specialized. That is, teams initially have control over
only one income class. Team AA controls the
largest percentage of high income population units
in Jurisdiction 1, while team CC controls the ma-
jority of PR's in Jurisdiction 3. Other obvious power
blocks are team DD's control of middle income units
in Jurisdiction 1 and team II's control of low in-
come units in Jurisdiction 2.
The Economy
The economic assets of the region are quite widely
distributed among 23 economic teams. Each of these
teams is very specialized at the start of play as
95
-------
RAYWID CITY
70 7? 74 76 76
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70 72 74 76 78 80 82 84 86 88 90 92 94 96 98 100 102 104 106 108 110 112 U*
PARCELS
TOP ROH: ECONOMIC ACTIVITY TYPE
AND OPERATING LEVEL
KIDDLE ROW: (FOR BASIC INDUSTRIES)
PERCENT OF MATER RECYCLED
BOTTON ROMs (FOR BASIC INDUSTRIES)
EFFLUENT TREATMENT
TYPE AND LEVEL
PARCEL ECjfiES
XX XX UTILITY DISTRICT BOUNDARY
00 00 JURISDICTION BOUNDARY
aa m BOTH
LAKE PARCELS
96
-------
FIGURE A-4—Characteristics for the Jurisdictions of RAYWID CITY
Jurisdiction
1 2 3 Total
Population 1 662 500
Percent
High Income 30
Middle Income 35
Low Income 35
Unemployment 129 000
(Percent) (24)
Underemployment
High Income NA
Middle Income NA
Housing Types
(Percents)
Single Family 17
Multiple Family 83
High Density 20
Percent of Students Attending Private Schools . . 14
Student-Teacher Ratio in Public Schools 13
FIGURE A-5— RAYWID CITY Social Control
Summary .••«>.
V
Jurisdiction 1 Jurisdiction 2 Jurisdiction 3 "
TEAM PH PM PL PH PM PL PH PM PL
AA 441 00 50 0 0 23 0 0
BB 293 0 0 150 00 43 0 0
CC 280 0 0 156 0 0 128 0 0
DD 0 514 0 0 153 0 0 0 0
BE 0 336 0 0 70 0 0 84 0
FF 0 298 0 0 162 0 0 85 0
GG 0 0 450 0 0 49 0 0 76
HH 0 0 413 0 0 79 0 0 43
H 0 0 300 0 0 261 0 0 80
PH PM PL
Typical Salary per Worker $13,700 $6,850 $3,425
Typical Salary per PI $1,644,000 $1,096,000 $685,000
figure A-6 indicates. Teams A through D control
only manufacturing industries. Each team has con-
trol of at least one plant that is contributing large
amounts of pollution to the local river system. All
of team A's industries are in Jurisdiction 1, while
team D owns no industry there. Teams E, F, and G
control only commercial establishments.
Teams H through L control the residences in the
region, with each team having specialties. For ex-
ample, team J owns only multiple-family units in
Jurisdiction 1 and teams I and K control most of the
housing supply in Jurisdiction 3.
Ownership of the seventeen large farms in the
region is divided among teams M and N. Team M
has control of eight farms, all of which contribute
runoff pollution (from fertilizer use) to the local
564,500 281,000 2,508,000
32 35 31
34 30 34
34 35 35
5,800 0 134,800
(7) (0) (16)
NA NA 17,880
NA NA 75,040
53 76 32
47 24 68
0 0 10
2 35 13
6 17 12
river system. None of team N's farms have runoff
into the local river.
There are six realtor teams that own nothing but
land at the start of play. The undeveloped land (36
FIGURE A-6 — Economic Team Assets in RAYWID
CITY
Establishments Assets Cash
Economic Teams (Parcel locations) (Billions) (Millions)
Industrial Teams
A 6 7.9 97
B 6 5.9 200
C 6 4.2 0
D 7 7.1 163
Commercial Teams
EC £O A
J .D7 U
F 5 1.82 256
G 8 1.02 0
Landlords
H 19 1.24 67
I 25 1.97 127
J 19 2.11 103
K 26 1.82 87
L 23 .95 55
Farmers (Farms)
M 8 NA 1.5
N 9 N 1.5
Realtors (millions)
p 13 112 0
Q 12 109 0
R 11 96 .63
S 21 131 0
T 21 154 0
U 15 102 .59
Bankers
O 1.5
V .... 717
W 717
97
-------
parcels) that is within the river basin is divided
among teams P, Q and R. The undeveloped local
land (57 parcels) not within the river basin is
divided among teams S, T, and U. Teams O, V, and
W are banker teams, in that they own nothing but
cash at the start of play.
The national business cycle is in an upswing
period, and local basic industries are enjoying above
average prices on the goods that they produce and
sell to outside markets. Typical prices for heavy
industry products were 5 percent above normal and
those for light industry were 4 percent above
normal.
As noted in Figure A-5, the typical salaries for
high income workers is $13,700 and, therefore, the
typical salary per PH is $1,644,000. The PM and
PL typicals are as indicated hi Figure RC-3.
The Public Sector
The governments in the three jurisdictions are
similar in structure, but they are quite different in
size. For example, Jurisdiction 1 has six times the
population, over eight times the local tax revenue,
2.5 times as many school districts, 3.5 times as
many MS districts, and three times as many utility
districts as Jurisdiction 3. Figure A-7 shows some
of the government features for each of the jurisdic-
tions.
FIGURE A-7—Government Sector Comparisons in
RAYWID CITY
Population
Tax Revenue (millions)
Welfare Payment per
Unemployed Worker
Expenditures (millions)
Municipal Services
Schools
Congested Highway Links . ..
Worst School Use Index
Number of School
Districts
Number of MS Districts. .
Average MS Use Index ....
Worst MS Use Index ....
Highest Operating Cost
UT District
Number of Utility
Districts
Government Teams
Jurisdiction
1 2 3
1,662,500 564,500 281,000
$889 $342 $105
$2500 $2200 $1900
$218 $89
$215 $100
13 2
144 40
10
14
143
196
6
8
128
188
$45
$43
0
112
4
4
179
263
$8371 $8270 $8816
The Local Water System
As Figure A-8 shows, the local system water
quality is very poor. The worst water is quality
level 9. The rural county (Jurisdiction 3) has the
most parcels with good water, whereas Jurisdiction
2 has 10 of its 15 parcels with river water in the
very worst water quality category. Six of the major
surface water industries have no effluent treatment
whatsoever. This is contributing to many of the local
system water quality problems. All of the municipal
water districts are treating their effluents, but the
eight that have only secondary treatment are causing
part of the pollution problem.
FIGURE A-8—Water System Comparisons—
RAYWID CITY
Jurisdiction
1 2 3 Total
-Parcel of Water Quality
;l i
•" 2
3
4
5
6
7
8
9
Surface Water
Industries with
Tertiary Treatment
Secondary Treatment
Primary Treatment
No Treatment
Municipal Outflow Treatment
Tertiary
Secondary
Primary
None
.. . 1
. . —
—
—
. . —
—
...4
...5
.. 3
... 1
...2
... 1
... 2
... 2
... 4
2
—
— _
—
—
_
3
10
—
2
— —
2
1
2
16
—
—
—
—
5
2
2
2
—
1
1
2
2
19
_
—
—
_
5
6
10
15
1
S
2
6
3
8
—
"••
6
7
3
7
2
7
TWO CITY SCENARIO
TWO CITY is a regional river basin area con-
taining two political jurisdictions with a population
of about 275,000. There are a number of manu-
facturing establishments, farms and municipal sewer
systems that contribute to the pollution of the major
rivers that run through the region. Along with poor
water service, housing deficiencies and inadequate
municipal services, the polluted river looms as one
of the several major problems facing the regional
area.
The Economic Status Map (Figure A-9) shows
the regional area encompassed by TWO CITY. All
the local system population and land use activity is
98
-------
»FIGURE A - 9i«*«««**.«**«*.
IIOCITI
ECOBOBIC STtTOS B1P . BOBID 1
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IRIVERS
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31 IS 50 PtaELtlt
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99
-------
concentrated in the center of the region. The juris-
dictional boundary runs from north to south and
separates Jurisdiction 1 (on the west side) from
Jurisdiction 2. There are three sections of river that
flow through the region. Note that rivers flow
through the centers of parcels.
Figure A-10 shows the population distribution
by the three income classes for the two political
jurisdictions that comprise TWO CITY. Jurisdiction
2 has a larger rate of unemployment and all of this
is concentrated in the low income groups. The
middle and high income groups are experiencing
some employment difficulties (under-employment)
in that a number of workers are forced to take jobs
at salaries below the level they would normally
earn.
FIGURE A-10—Characteristics for the Jurisdiction
oj TWO CITY
FIGURE A-ll-
-TWO CITY Social Control
Summary
Jurisdictions
1
Population
High Income (%) .
Middle Income (%)
Low Income (%) .
Unemployment
Percent
Underemployed
Workers (number)
High Income
Middle Income ....
Housing Vacancy Rate .
Housing Types (Percents)
Single Family
Multiple Family
High Density
126,000
49
51
0
0
0
'»
NA
NA
—8
31
69
50
2
149,500
28
23
49
6,400
13.0
NA
NA
—9
20
80
26
Total
275,500
37
36
27
6,400
7.5
1,200
3,360
—8
25
75
38
Housing is in short supply in both jurisdictions.
Most of the very high density housing is in Jurisdic-
tion 1, where this type of housing makes up half of
the supply. In Jurisdiction 2, low density multiple-
family housing is dominant.
The public school system in Jurisdiction 2 is not
serving the population well, in that a large number
of the children attend private schools.
Figure A-ll shows the allocation of the social
decision-making power among the seven teams that
comprise the social sector. Note that teams are
specialized. That is, teams (with the exception of
CC and GG) initially have control over only one
income class. Team AA controls the largest per-
centage of middle income population units hi Juris-
diction 1 and DD controls all of the PL's in the local
system. Another obvious power block is team FF's
control of middle income units in Jurisdiction 2.
Team
AA . .
BB .
CC
DD
EE
FF
GG
Jurisdiction 1
PH PM PL
0
46
0
0
45
0
. . .33
106
0
22
0
0
0
0
0
0
0
0
0
0
0
Jurisdiction 2
PH PM PL
0
0
26
0
13
0
43
0
0
0
0
0
61
9
0
0
0
147
0
0
0
Typical Salary per Worker $10,000 $5,000 $2,500
Typical Salary per PI $1,200,000 $800,000 $500,000
The Economy
The economic assets of the region are distributed
among seven economic teams. Each of these teams
is fairly specialized at the start of play as Figure
A-12 indicates. Teams A and G control all of the
manufacturing industries. Both teams have control
of at least one plant that is contributing large
amounts of pollution to the local river system. All
the large polluting manufacturing plants are located
in Jurisdiction 2, but the detrimental effects of their
water borne wastes are felt primarily in Jurisdiction
1. The commercial establishments in the local system
are under the control of only three teams.
FIGURE A-12—Economic Team Assets in TWO
CITY
Industrial Parcels .
Teams
ABC
. . 3
D E F G
3
Commercial Parcels .. 21 1
Residential Parcels . 6 714713 3
Undeveloped Parcels.. 5 5 5 4244
Assets (billions) . . 2.5 .63 1.47 .94 .65 .87 2.0
Cash (millions) ... .268 68 145 91 66 102 254
Six of the seven teams control residences in the
region. Ownership of the three small farms in the
region is in the hands of Team A. All the farms
contribute runoff pollution (from fertilizer use) to
the local river system.
The national business cycle is in an upswing
period, and local basic industries are enjoying above
average prices on the goods that they produce and
sell to outside markets. Typical prices for heavy
industry products were 5 percent above normal and
those for light industry were 4 percent above normal.
100
-------
The Public Sector
The governments in the two jurisdictions are
similar in structure, but they are quite different in
service levels. For example, Jurisdiction 2 has a
slightly larger population, and it has a substantially
larger local tax revenue. Figure A-13 shows some
of the government features for each of the jurisdic-
tions. Note that all of the highway congestion and
the worst school use indexes are in Jurisdiction 2.
Jurisdiction 1, however, has a far worse average
MS use index.
The Local Water System
As Figure A-14 shows, the local system water
quality is very poor in Jurisdiction 1, even though
that jurisdiction has no major industrial polluters
within its boundaries. Level 9 water quality is the
worst water quality rating and all of Jurisdiction 1's
water is of this quality. The solution to the local
system's water quality problems will require co-
operation among the local political jurisdictions.
FIGURE A-14—Water System Comparisons—TWO
CITY
FIGURE A-13—Government Sector Comparisons in
TWO CITY
Jurisdiction
1 2
Population 126,000 149,500
Tax Revenue (millions) 62.6 82.9,
Welfare Payment per Unemployed
Worker $1,500 $1,600.
Current Expenditures (millions)
Municipal Services 11.1 26.5
Schools . . 25.5 17.5
Congested Highway Links ... .... 0 2
Worst School Use Index 72 144
Number of School Districts 2 2
Number of MS Districts .... 1 2
Average MS Use Index Ill 200
Worst MS Use Index Ill 200
Highest Operating Cost UT District $7,900 $6,801
Number of Utility Districts 1 1
Jurisdiction
1 2
Total
Parcels of Water Quality
k
(best
— 19
19
(worst)
Surface Water
Industries with
Tertiary Treatment
Secondary Treatment
Primary Treatment
No Treatment
Municipal Outflow Treatment .
Tertiary
Secondary
Primary
None
12
3
1
3
13
101
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APPENDIX B
River Basin Manuals
The RIVER BASIN MODEL is described for
player and director use in fourteen (14) separately
bound manuals. Each manual has a "161100 FRU
12/71" prefix. The final digits in each manual code
number are the identifying numbers for the specific
manuals. They are:
The RVER BASIN MODEL:
1. An Overview (109 p. — $1.00) 16110
FRU 12/71-1
2. Director's Guide (229 p. — $1.75) 16110
FRU 12/71-2
3. Economic Sector (151 p. — $1.25)
4. Social Sector (117 p. — $1.25)
5. Chan-man and Council (80 p. — $.70)
6. Assessment Department (83 p. — $.75)
7. School Department (94 p. — $1.00)
8. Municipal Services Department (93 p. —
$1.00)
9. Utility Department (129 p. — $1.25)
10. Highway Department (104 p. — $1.00)
11. Planning and Zoning Department (81 p.
— $.75)
12. Computer Output (246 p. — $2.00)
13. The Social Science Laboratory (271 p. —
$2.00)
14. Transportation Departments (94 p. —
$1.00)
These volumes are attainable from the U.S., Govern-
ment Printing Office at the indicated prices and from
the National Technical Information Service, Spring-
field, Virginia 22151.
U.S. GOVERNMENT PRINTING OFFICE) l»71 0—468-167
102
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