Scientific Market Research with cellular automata model. It's a decision tree + statistical analysis + machine learning + artificial intelligence approach based on my doctorate thesis. Rubens Zimbres

1. SUMMARY
OF
MY
DOCTORATE
THESIS
AND
CELLULAR
AUTOMATON
MODEL
–
RUBENS
ZIMBRES
rubens.zimbres@eclipso.de
This document is a brief explanation of the steps of my Doctorate thesis. Samples of
results are given. The Cellular automaton model is presented.
The
thesis
is
available
here:
http://pt.slideshare.net/RubensZimbres/thesisrubens-­‐zimbres
In
my
doctorate
thesis
I
studied
4
constructs:
role
clarity,
involvement,
service
quality
and
behavioral
intentions
in
the
following
nomological
network.
The
research
was
diadic
and
dynamic,
made
with
clients
and
service
providers.
For
each
one
of
the
constructs,
I
did
a
comprehensive
research
where
knowledge
acquired
was
inserted
in
a
matrix,
as
seen
next
page.

2.
Then,
indicators
cited
in
literature
were
placed
in
another
matrix,
correlating
authors.

3.
Then,
the
research
phases
are
presented.
After
that,
I
did
qualitative
interviews
to
develop
the
pre-­‐test
questionnaire.
Interviews
were
transcripted,
contente
analysis
was
done,
compared
to
literature
and
quantitative
pre-­‐test
questionnaire
was
developed.
Then
I
did
a
statistical
analysis
and
I
finally
had
the
quantitative
questionnaire,
below.
An
ordinal
scale
of
5
options
was
chosen
to
allow
respondents
to
have
a
neutral
opinion,
without
being
forced
to
choose
between
two
opposites,
what
happens
in
a
scale
with
6
options.
Next
page
there
is
a
small
part
of
the
questionnaire.

4.
A
comprehensive
statistical
analysis
was
done.
Here
are
some
results:
Graphic:
Time
as
a
cliente
of
the
servisse
provider

5.
A
descriptive
analysis
was
done:
Normality
tests
were
done:
Also,
collinearity
tests
were
done:

6.
Correlations
with
factor
1
and
2
Factor
analysis
and
Cronbach's
Alpha
(for
clients).
And
the
regression
model,
with
principal
components:

7.
Finally,
the
cellular
automaton
model
was
developed
to
simulate
interactions
between
clients
and
service
providers.
I
did
two
quantitative
researches
with
interval
of
4
months.
Research
A
and
B.
My
idea
was
to
find
a
cellular
automaton
that
could
be
applied
to
research
A
(first)
and
generate
an
outcome
of
the
simulation
similar
to
research
B
(second,
after
4
months).

8.
I
had
to
find
a
rule
in
a
space
of
1
in
10
to
the
power
of
80
possibilities.
This
would
take
more
than
200
years
with
a
regular
computer,
so
I
did
a
randomly
guided
search.
The
cellular
automaton
is
a
tool
where
you
have
three
cells.
The
center
cell
is
updated
according
to
the
opinion
of
the
cells
on
the
left
and
on
the
right.
Each
CA
rule
generate
on
specific
outcome.

9.
Next
page,
the
cellular
automaton
model
workflow:

10.
The
accuracy
of
the
cellular
automaton
model
to
simulate
interactions
was
73.80%
case
by
case
and
99%
considering
mean
of
indicators.
This
is
greater
than
any
linear
regression
found
in
service
quality
literature.