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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
                                  Vll

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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
   r
 
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 z
a
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UJ
 00
 UJ
 u.

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 I
              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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 ............«...•»«»«..••••••••••••••••••••••••••••••••••••FIGURE 21**"*************************"***********************"****
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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).

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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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                                                               13

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                     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

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                                     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

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                                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
92
92
92
0
92
92
92
92
0
81
81
81
81
91
92

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
MOVED TO NEXT PARCEL
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
AFTER BIO CHANGE
EFFLUENT ADDED
MOVED TO NEXT PARCEL
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
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
BOD
IX 1001
0
0
0
0
1240004
1240004
1240004
1240004
1183640
0
1183640
1183640
1183640
1129838
0
1129838
1129838
1129838
1078481
0
1078481
1078481
1078481
1029459
0
1029459
1029459
1029459
982665
0
982665
982665
982665
937998
0
937998
937998
937998
895361
0
895361
895361
895361
854662
0
854662
854662
11
652202
622556
3100002
3722558
3722558
3722558
3553350
225831
3779181
3779181
3779181
3607400
0
3607400
3607400
3607400
3443427
0
3443427
3443427
2289413
2185348
2480010
4665358
CHLORIDES NUTRIENTS
IX 100)
0
0
0
0
775001
775001
775001
775001
697500
0
697500
697500
697500
627749
0
627749
627749
627749
564974
0
564974
564974
564974
5C8476
0
508476
508476
508476
457628
0
457628
457628
457628
411865
0
411865
411865
411865
370678
0
370678
370678
370678
333610
0
333610
333610
1164 MGO REQU!
254581
229122
155COOO
1779122
1779122
1779122
1601209
63135
1664344
1664344
1664344
1497909
0
1497909
1497909
1497909
1348118
0
1348118
1348118
896316
806684
1550001
2356685
ix loo)
33615
33615
26668
25051
12400010
12425061
12425061
12425061
11672027
0
11672027
11672027
11672027
10964631
0
10964631
10964631
10964631
10300108
0
10300108
10300108
10300108
9675859
0
9675859
9675859
9675859
9089443
180000
9269443
9269443
9269443
8707658
0
870765B
B707658
8707658
8179921
0
B 179921
B 179921
8179921
7684168
0
7684168
7684168
I RED
5863873
5508486
24928000
30436486
30436486
30436486
28591840
77155
28668995
28668995
28668995
26931472
0
26931472
26931472
26931472
25299248
0
2529924B
25299248
16820576
15801148
24800016
40601164
COLIFORM
IX 100)
0
0
0
0
1550
1550
1550
1550
1432
0
1432
1432
1432
1323
0
1323
1323
1323
1222
0
1222
1222
1222
1129
0
1129
1129
1129
1043
0
1043
1043
1043
963
0
963
963
963
890
0
890
890
890
822
0
822
822

627
579
1550
2129
2129
2129
1967
137
2104
2104
2104
1944
0
1944
1944
1944
1796
0
1796
1796
1194
1103
3100
4203
TEMPERATURE AGE OF
IX 100)
0
0
0
0
12400
12400
12400
12400
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

0
0
12400
12400
12400
12400
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
24800
24800
OFS
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
AGE OF AMOUNT
HLM
0
0
0
0
1
1
2
2
2
0
2
3
3
3
0
3
4
4
4
0
4
5
5
5
0
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

0
0
1
1
2
2
2
0
2
3
3
3
0
3
4
4
4
0
4
5
5
5
1
1
IMGDX1DOI
15000
15000
11900
11900
3100
15000
15000
15000
15000
0
15000
16200
16200
16200
0
16200
17000
17000.
17000
0
17000
17000
17000
17000
0
17000
17000
17000
17000
10000
17000
17500
17500
175 DO
0
17500
17500
17500
17500
0
17500
17500
17500
17500
0
17500
18000

13736
13736
7100
18000
18000
18000
18000
1164
18000
18000
18000
18000
0
IBOOO
18000
18000
18000
0
18000
18500
12300
12300
6200
18SOO
18

-------
Figure 11.—SAMPLE OF QUALITY OF LIFE OUTPUT FOR POPULATION GROUPS
                        ROUND 1
                      ROUND 2
  —QUALITY OF LIFE INDEX-
—QUALITY OF LIFE INDEX—
                                         H
                        89  10
3  4
               6
8  9  10
                                  19

-------
«*«••**•***••••*•***•****•*•****••** *****'
                            TVOCXTY
                      fliTBI Q01LITI BAP
***•»»*** #»#»****•*********•>***»**** *****!
FIGURE 12
   TO   72   74    76   76   80   82  ' 81   86   88   90   92   9*   96
                                                                     «**•*•***•*••**••***********•**********

                                                                      98   100  102  104  106  108   110   112
                                                            FOOSD   1


                                                           116   118
12
14
16
It
20
22
24
26
28
30
32
3*
36
38
•0
«2
44
46
•8
SO
52
-
54
56
58
«0
»

....
BOD
*_..
-- . .


M—
BOD
....

....
....


«—- —
....


— -~
.__.
BOD
*-._



— _
^_—


„_,
-—••-<




....
	 	
— —
f 1
f — ™


___
— _.
....
....
-- — H
r i
P 1< P 1
BOD
__-_
....
/
— — —
....
....
h-.~



„__
CBOD
»_.._
....
,

....
— —



— —



—


F i
T 1
800



....
-




....



'





.
BOD



....
— --.
h»«


f«.









81 6
M 6
BOD



....





....








Bl 3
Bl 6
Bl 6
BOD
I 	 	
It 4



t— .
'

>....


i 	







U 3
Bl •
BC 1







BA 3
B» 1
BC 2
11 2._.-
BB 2
Bl 4





	 ^


....
BS 1|RB 2
1
1
K— __*..-.
BC 1|
I
I
BB 2|
1
1
«,,
1
1
1
1
1
1
1
>A-i
1
1
1
1
1
1
1
1
1
1
1
1
1
1
I
1
1
1
1
1
1
1
	 .4 	
1
1
1
1
1
1
1
1
1
1
Bl 4|
1
1
Bl 3|
1
1
111 21
1

I — ..







....







....














Bl X < < < <
111 3
— .-
F 3

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F 3







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F 3







H-— -




	







	






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....


	








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*..__*
                                                                                                                           12
                                                                                                                           16
                                                                                                                           22
                                                                                                                           32
                                                                                                                           38
                                                                                                                           50
                                                                                                                            56
                                                                                                                            58
                                                                                                                            60
  70   72   74   76   78   80   82    84   86   88   90   92   94   96   98   100   102   104  106  108  110  112  114  116  118
    PIBCtLS

       TOP IOB: ICOBOBIC ICTITITI  TIPB
                1ID OPBB1TIBG  LBTE1
                FIBB nra ir riBn  OB PIBCBL
    BIDDU BOB: 50BF1CI B1TEB  00111*1 B1TXBS
    BOTTOB SOB: IOBST P01LIT1BT
        PIBCBL EDGES

        >»T<  DIBBCTIOB OF FLOB
        	  BO HTEB FLOIIB6
              BBTIEBB P1ICELS
          LIKE P1ICI1S
                                                          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

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 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

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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

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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

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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

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 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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                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.
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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

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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

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  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

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                                         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

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                            Figure 23
V)
                                                           130
                                                          8
                                52

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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

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   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

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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
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15
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Round •
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    •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

-------
  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

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 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.
                                                      82

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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.
                                           92

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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

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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

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RAYWID CITY


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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)
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XX XX UTILITY DISTRICT BOUNDARY
00 00 JURISDICTION BOUNDARY
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                                                    LAKE PARCELS
                                                       96

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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

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                                                          IRIVERS
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                                                                      18.  80.1  £4)1  86.  100. 100.1 80. 100. 100  100.  100.  1000
                                                                                                                             0 26
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                                                                   0
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                      ZOBIBG  LtBD USE   ZOIIBG  OSE
                      —  til OSE          33  BS
                      10  1BI BDSIIESS     34  PG
                      20  BI.LI.CI         35  PS
                      21  BI               40  Bl.BB.BC
                      22  LI               41  Et
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                      31  IS               50  PtaELtlt
                      32  EG
                                                              99

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 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

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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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