Rather than implement mathematically-based simulations, the
Worldwide Web Instructional Committee (WWWIC) develops
agent-based simulations. In general, there are three kinds of
agents employed in these simulations.
1) Atmosphere Agents,
lending local color and a measure of authenticity,
to the environment. These agents are largely designed for their
entertainment value. In Dollar Bay these include a Fire Inspector, a
Juggler, a Beat Cop, and so forth.
2) Infrastructure Agents,
contributing in a meaningful way to the
"play" of the game.
These agents are essential to the pedagogical
goals of the educational environment.
In Dollar Bay these include the Customers who
effect economic demand, to a lesser extent, the Employees who control the day-to-day workings
of each synthetic retail establishment, and the agents who supply wholesale goods, direct
advertising services, provide banking and so forth.
3) Intelligent Tutoring Agents
monitor, mentor, and remediate the human learners
in the performance of their roles.
The tutoring agents are being developed as
sub-topic experts who
have access to problem solving experiences,
context sensitive help and advice,
conceptual and procedural tutorials,
stories of success and failure within their
particular sub-topic,
and conversational networks for learner
interaction.
Economic Environments: Dollar Bay (and Blackwood)
WWWIC economic environments (Dollar Bay and Blackwood) are networked, multi-player,
simulation-based, interactive multi-media, educational
games.
The pedagogical domain is micro-economics, in
particular, retailing.
The teaching goals revolve around the strategic
importance of "targeting" specific customer groups in order to
gain competitive advantage in the retail marketplace.
Similar to the WWWIC science-based simulations, these games
provide a simulation that rewards analytical problem
solving -- the business equivalent of the scientific method.
Economic models are typically built on the idea of demand
and supply functions
where economic entities maximize their welfare
when the market achieves equilibrium.
These are mathematical models filled with rigor, but difficult
to create, maintain, modify, or debug.
Agent-based economic models develop rational agents
as heterogeneous individuals with divergent theories.
They allow us to relax assumptions about perfect
rationality, rational expectations, and perceptual maximization of expected
utility.
To date, agent-based models have been used in the
social sciences to explore patterns of spatial
segregation, the evolution of
cooperation, the emergence of
money, cultural evolution, market processes, electoral politics, state formation, and
group stability.
The Model of Consumer Decision Making
The Dollar Bay economic model assumes rational,
cost-minimizing consumers
Therefore,
consumers consider travel costs, search costs, service benefits, and
product quality as well as price when making buying decisions.
Dollar Bay models
the entire consumer population by defining it in terms of cluster groups
(CG).
The concept of
cluster groups is similar to the idea of psychographic segmentation,
employed by many advertisers and marketers. Psychographic
segmentation is the classification of a population into groups which share
similar values, attitudes, and lifestyles (Rice, 1988;
Piirto, 1990). The premise is
that persons with similar values and lifestyles will have similar buying
behavior.
Psychographic
segmentation is a growing method in marketing, for it promises insight into
the emotional and lifestyle factors, which motivate consumer's buying
behavior.
A
cluster group (consumer group) is a coherent segment of the population
where the members are alike in age, income, life narrative, interests,
values, and lifestyles. As a consequence
the members of a cluster group have similar consumer behavior.
The Dollar Bay game uses product classes and models as its level
of representation
A model
represents a particular good for sale, and
a product class
is used to describe the market for an entire class of goods.
All models in the
same product class compete with each other while no models in different
product classes compete.
In the Dollar Bay
game, a product class contains all information on each consumer's
attraction for a particular product.
The
representation of any particular product is composed of:
1)
Average potential
demand (APD).
2)
A percentage number
for each cluster group's relative level of interest compared to the overall
all potential demand (PD).
3)
A dollar amount for
unit search cost (USC) for each cluster group.
4)
A unit
transportation cost for each cluster group, unit service benefit (USB) and
unit quality benefit (UQB) the cluster group receives from the store and/or
product.
5)
All possible
features of the product, price sensitivity (PS) of cluster groups.
6)
A maximum dollar
amount (MAX) and a minimum dollar amount (MIN).
Based on the
information stored in the product class representation,
the Customer
agents decide the amount of a particular product, at what price, from which
stores they would buy.
The individual purchasing
decisions of these agents implement the economic activity of Dollar Bay.
In Dollar Bay there
are 20 distinct cluster groups.
cg1
|
Working Class: middle aged couples with
children, renters
|
cg2
|
White Collar Singles: young singles, renters, upwardly mobile
|
cg3
|
College students.
|
Table 1: Sample Cluster Groups
There are seven
small towns in the region that comprises Dollar Bay.
Each of these
towns has its own particular flavor, composed of very different populations
mixes.
For example there
is Copper Harbor, mostly made up of college students and professors,
or Silver River,
home to most of Dollar Bay's young professionals.
The population
for the three example cluster groups in Silver River is:
cg1
|
Working Class
|
1255 persons
|
cg2
|
White Collar
Singles
|
4123 persons
|
cg3
|
College Students
|
1185 persons
|
Table 2: Sample Cluster Groups as Population on Product
A model
represents a particular good for sale,
while a product
class is used in this implementation to describe the market for an entire
class of goods.
For example, the furniture
model "Econo Sleeper" is a bed possessing certain features and
quality level.
While the product
class "bedroom furniture" contains data about the market for all
beds,
|
Cluster Group Name
|
I
|
USB
|
UQB
|
UTC
|
USC
|
PS
|
MIN
|
MAX
|
cg1
|
Working Class
|
60%
|
$1
|
$80
|
$25
|
$25
|
130%
|
$80
|
$400
|
cg2
|
White Collar
Singles
|
180%
|
$10
|
$120
|
$10
|
$20
|
90%
|
$200
|
$600
|
cg3
|
College Students
|
210%
|
$8
|
$100
|
$30
|
$30
|
100%
|
$100
|
$600
|
Table 3: The product Class Definition for Bedroom Furniture
Product Class Definition
The
product class definition is the heart of the Dollar Bay simulation.
It contains all
information on consumers’ likes and dislikes for a given product.
Dollar Bay uses
the explicit data about consumer preferences stored in the product class
definition to generate consumer behavior.
Based on the
information stored in the product class representation, consumers decide
1)
how much of a
product they want to buy,
2)
which stores they
buy from and
3)
how much they can
afford to spend.
By changing the
data in the product class definition, one changes the consumer behavior
generated
by the simulation
(see Table 3).
A product class
definition contains firstly a number for the average potential demand
(APD),
which is the
average number of persons who will be want to buy the product over a given
time.
All
other information is stored in a table,
with all the
cluster groups on one axis and all the features and consumer values on the
other.
Each
column is a dimension of the consumers’ decision making.
The values
underneath represent the value of the cluster groups.
In the product
class definition, each cluster group has a percentage number for their relative level of interest
compared to the overall average potential demand (I).
So cluster groups
with high interest in a product class will have a percentage number over
100% while those with low values will be below 100%.
These numbers
were based loosely upon market research information obtained from Simmons
demographic data (Simmons, 1993).
For each cluster
group a dollar amount is given for unit search cost (USC).
The unit search
cost is the cost for a group to gain information about a particular store
per unit of distance between store and consumer.
The greater the
distance between store and buyer the more expensive it is for a consumer to
learn about what the store is selling and at what prices.
This unit search
cost is used to simulate advertising.
Unit
transportation cost (UTC) is the
unit cost to each cluster group of getting to a store and getting the
product back home.
Some cluster
groups are more mobile than other and therefore have lower transportation
costs.
For example,
retired persons have very high transportation cost, while families with
homes, who own cars, have much lower transportation costs.
The product class
definition also contains data about benefits that products or stores may
offer.
The product class
definition gives values for unit service benefit (USB)
The unit service
benefit is a dollar amount a cluster group is willing to pay for a unit of
added service.
and unit quality benefit
(UQB).
The unit quality
benefit is the dollar amount a cluster group is willing to pay for a unit
of added quality.
Both of these
benefits will be subtracted from the price of a model in calculating the
overall consumer's real cost.
Also contained in
the product class definition is an enumeration of all the possible features a model of this class may have.
For example a bed
may be a springed bed or a waterbed.
In Dollar Bay
furniture has the features of size, type, and quality.
Models have the
features enumerated in their product class definition.
Different
features are valued differently by different consumer groups.
For each feature
enumerated, the product class definition contains each cluster group's
value for that feature in dollars.
This is the
amount a cluster group will pay for that feature.
Some features may
be so disliked by a particular cluster group that they have a negative
value for them,
which means
players would need to offer a lower price than for a product without the
feature, in order to make them want to buy it.
The product class
definition also contains data about cluster group sensitivity to price
in the form of a
percentage number called price sensitivity (PS).
This percentage
tells how sensitive a group is compared to an average price sensitivity,
where 100% means
that a cluster group has average price sensitivity,
and a lower
number means that the cluster group is less concerned about getting the
best buy.
Finally, product
class definitions also contain two numbers for each cluster group which
represent how much they can afford to spend:
a
maximum dollar amount (MAX),
which is the price at which no one in the cluster group can afford to buy
the product and
a
minimum (MIN), which is the price
at which everyone in the cluster group can afford to buy the good.
All these values
will be used to calculate consumers' decision making.
Model
Definition
A
model represents a particular item that players sell – it is an
instantiation of the abstract product class.
Each
model has a pointer to its parent product class definition, along with its
name, feature settings, manufacturers suggested retail price (MSRP), and an
iconic picture.
Three
models created for the Dollar Bay game are shown in Table 4.
Model Name
|
Econo-Sleeper 500
|
Super Sleeper 1200
|
Ultra Waveless 900
|
Model Description
|
“a econo priced, low quality spring-bed”
|
“a high priced, excellent quality spring-bed”
|
"a high-priced, excellent quality waterbed”
|
MSRP
|
$310
|
$600
|
$700
|
Quality
|
Quality: Low (=0)
|
Quality: High (=3)
|
Quality:High (= 3)
|
Feature
|
Kind = spring
|
Kind = spring
|
Kind = water
|
Table 4: Three Models of the Bedroom Furniture Product Class
Tom's
furniture store, hoping to attract bargain hunters, sells only the
Econo-Sleeper 500 for $310, while
Bob's
tries to attract up-scale clients with the Super Sleeper 1200, selling for
$800, and the Ultra Waveless 900 selling for $700.
Advertising
Dollar
Bay models the effect of advertising by
first determining
the search cost, to a consumer group, of finding out if a particular store
sold a desired item
and at what price
they sold it – if that store did not advertise.
This is found by
multiplying the cluster group's unit search cost (USC), found in the
product class definition (Table 3),
by the unit
distance between store's town and consumer's town.
Advertising
reduces that search cost by some percentage.
The amount an ad
reduces this search cost is called the percentage search cost reduction
(RSC).
Different
advertising reaches different consumers.
Dollar Bay models
an advertisement by giving, for each cluster group, a percentage number for
the reduction in search cost.
Different
advertisements in different media and different sizes have different
percentage numbers (Table 5):
|
Cluster Group Name
|
Leisure Section,
Quarter Page, RSC
|
Sports Section,
Quarter Page, RSC
|
cg1
|
Working Class
|
8%
|
5%
|
cg2
|
White Collar
Singles
|
15%
|
10%
|
cg3
|
College Students
|
5%
|
20%.
|
Table 5: Quarter Page Print Ads
Bob's
takes out a quarter page advertisement in the Leisure section while
Tom’s
takes out a quarter page advertisement in the sports section.
For
the working class cluster group, a quarter page advertisement in the
leisure section reduces search cost 8%,
while
one in the sports section reduces search cost 5%.
A
quarter page ad in the sports section reduces college students’ search cost
20%,
while
one in the leisure section only 5%.
The
Dollar Bay game supports several forms of media.
Algorithm
Each turn, the virtual consumers decide what they
want to buy,
how much, and from whom.
The model of consumer decision-making has four
main steps:
Each group of
customers decides how much of a particular product they want to buy.
They decide which
stores they like best.
They visit
stores, searching for the product.
If they find it,
they decide whether to buy it
Step 1. The Level of Consumer Interest in
a Product.
First,
each cluster groups’ potential demand (PD) in each product is
determined.
The
server obtains this by looking at the population representation and the
product type definition.
A
particular cluster groups’ level of interest is calculated by taking the
population in each cluster group
and
multiplying it by the percentage potential market of that group for that
product. The formula for
potential demand is:
PD= P * I * ADM
where:
PD
= potential demand
P = population
I = demand index
ADM
= average demand.
This is repeated for each cluster group in an
area, and then for all areas in Dollar Bay.
For
example, the potential weekly demand for beds for three sample cluster
groups living in Silver River are shown in Table 6:
|
Cluster Group Name
|
Potential Demand (PD)
|
cg1
|
Working Class
|
23
|
cg2
|
White Collar Singles
|
223
|
cg3
|
College Students
|
75
|
Table 6: Potential Demand
That
is, there are 223 White Collar Singles (cg2) in Silver River who want to
buy beds every week plus 75 college students and 23 working class families.
Step 2. Real Cost to Cluster Groups is
Calculated.
Next, each
cluster groups’ real cost is calculated for all products for sale in a
product type.
Real cost is
calculated with the following formula:
RC
= P + TC + SC - (SB + FB).
where
RC
= real cost
P = price
TC
= transport cost
SC
= search cost
SB
= service benefit
FB
= feature benefit.
The
transport cost is calculated by:
TC
= 2 * UTC * D(S,C);
where
TC = transportation
cost
UTC = unit transport cost
for the cluster group
D(S,C)
= distance from store to cluster group neighborhood.
In
Table 3, the UTC for white-collar singles is $10 – this represents the
notion that college students have less personal resources and less cars
than many other cluster groups and therefore view transportation as more
costly. Thus, college students
are much more likely to shop in their own areas.
The search cost
are calculated:
SC
= RSC *(USC * D(S,C) ^2)
where
SC = search cost to
cluster group
RSC = % reduction in search
cost from ads by store
USC = unit search cost to
cluster group
D(S,C)
= distance between store and cluster group.
The
service benefit is calculated as:
SB
= USB * SL
where
SB = service benefit of store to
cluster group
USB
= unit service benefit of cluster group
SL = service level set by store (an
integer from 0 to 4).
In Dollar Bay there are three levels of
quality: basic, good, and
high.
These three levels are represented with the set
[0,1,3].
The working class cluster group may have an $80
unit quality benefit UQB (see Table 3).
While white-collar singles have a UQB of $120.
Super Sleeper 1200 beds are high quality (quality
= 3).
Working class families will see this as a $240
discount
while white-collar singles will see it as a $360
discount.
Therefore white-collar singles will be willing to
spend $120 more for the bed,
since high quality is more valued by them.
In this way, Dollar Bay models the different
values and tastes important to different consumer group
decision-making. A model may
have any number of features.
This allows us to make products, which are more and more complex,
with any number of features which effect consumers’ decision-making.
|
Cluster Group Name
|
Tom's
Econo-Sleeper 500
|
Bob's Super
Sleeper 1200
|
Bob's Ultra
Waveless 900
|
cg1
|
Working Class
|
$384
|
$498
|
$598
|
cg2
|
White Collar
Singles
|
$341
|
$288
|
$338
|
cg3
|
College Students
|
$368
|
$412
|
$542
|
Table 7: The Real Cost to the Three Example Cluster Groups Living in
Dollar Bay,
for the Three Kinds of Beds for Sale in the Two Stores
Step 3. Percentage Distribution of Sales
Based on Real Cost
Next, consumer
group sales are distributed based on real cost to the cluster group.
The lower a
model’s real cost relative to other models real cost to a cluster group,
the greater that
model's share of the overall demand for that cluster group.
This is done with
a simple distribution formula:
PSD = ( 100% / n) + PS (ARC -
PRC).
where
PSD = percentage sales distribution for a store.
PS
= price sensitivity of a cluster group for a product class
n
= number of stores in a particular market.
ARC = average real cost for all models sold by
all stores in a product class,
PRC = a single players real cost to a cluster
group.
This
formula returns a percentage of the total demand of a cluster group for a
product a store's particular model has won. If all stores were to offer the same model at the same
price in the same location with the same service level, then they would
split the demand evenly between them.
For the example we are working on it comes like this:
|
Cluster Group Name
|
Tom's
Econo-Sleeper 500
|
Bob's Super
Sleeper 1200
|
Bob's Ultra
Waveless 900
|
cg1
|
Working Class
|
62%
|
32%
|
6%
|
cg2
|
White Collar
Singles
|
28%
|
43%
|
29%
|
cg3
|
College Students
|
50%
|
40%
|
10%
|
Table 8: Percentage of Total Demand Assigned to Each Model for Sale in Each Store
Step 4. Consumer Group Determines How Much
They Can Afford
In the last step,
each cluster group determines how much of their desire for a product they
can afford
to actually
satisfy. This is done with the
following formula:
AFD = 100% + (100% (min- price)/(max - min))
where
AFD
= percentage of a cluster group that can afford a particular price
price = actual price of a model
min
= the price at which all members of a cluster group can afford the
model (Table 3).
max
= the price at which no members of a cluster group can afford the
model (Table 3).
Generally
the wealthier a consumer group, the higher the min and max numbers will
be.
For the beds’
product class, Table 3 shows that the maximum for white-collar singles is
$800 and the minimum is $200.
|
Cluster Group Name
|
Tom's
Econo-Sleeper 500
|
Bob's Super
Sleeper 1200
|
Bob's Ultra Waveless
900
|
cg1
|
Working Class
|
5%
|
0%
|
0%
|
cg2
|
White Collar
Singles
|
76.50%
|
85.30%
|
77%
|
cg3
|
College Students
|
46.40%
|
37.60%
|
11.60%
|
Table 9: Percent Affordability in Dollar Bay Per Cluster Group, Per Store, Per Model of the
Bed Product Class
Therefore the
most any white-collar single will pay for a bed is $800, though very few
will.
Any white-collar
single is willing to pay $200 for a bed.
Therefore, even
if players’ stores have a monopoly, they can often increase sales by
decreasing prices.
Dollar Bay
calculates total sales by multiplying potential demand
in each cluster
group by affordability and market distribution.
These steps are
repeated for all cluster groups in all towns over the entire region of
Dollar Bay.
|
Cluster Group Name
|
Tom's
Econo-Sleeper 500
|
Bob's Super
Sleeper 1200
|
Bob's Ultra
Waveless 900
|
cg1
|
Working Class
|
1
|
0
|
0
|
cg2
|
White Collar
Singles
|
48
|
82
|
50
|
cg3
|
College Students
|
17
|
11
|
1
|
Total
|
|
66
|
93
|
51
|
Table 10: Total Sales in Dollar Bay by Cluster Group, Per Store, Per Model of Bed