Marketing models
24. January 2009 07:07
The
linear model:
Y=a+b*X
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The model is easy to visualize
and understand
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The model can approximate many
complicated functions quite well
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It assumes constant returns to
scale
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It has no upper bound on Y
-
∆Y/∆X is constant everywhere and equal to b
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It often gives managers
unreasonable guidance on decisions
The
power series model:
If we are
uncertain what the relationship between X and Y, we can use a power series
model:
Y=a+b*X+c*X^2+DX^3+…
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The model can take many shapes
-
May fit well within the range
of the data
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Normally behave badly (becoming
unbounded) outside the data range
The
fractional root model:
Y=a+b*XC
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Has a simple but flexible form
-
There are combinations of
parameters that give increasing, decreasing, and (with c=1) constant
returns to scale
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When c=1/2 the model is called
the square root model, when c=-1 it is called the reciprocal model, Y
approaches the value a when X gets large
- If a=0, the parameter c has the economic interpretation of elasticity (the percent change in sales, Y, when there is a 1 percent change in marketing effort X). When X is price, c is normally negative, whereas it is positive for most other marketing variables
Y=a/(1+e-(b+c*X) )+d
Y=abcX +d, a>0, b>0, b<1, c<1
Both the Gompetz and logistic curves lie between a lower bound and an upper bound; the Gompetz curve involves a constant ratio of successive first differences of log Y, whereas the logistic curve involves a constant ratio of successive first differences of 1/Y.
The ADBUDG Model:
Y=b+(a-b)*Xc /(d+Xc )
The model is S-shaped for c>1 and concave for 0<c<1. It is bounded berween b (lower bound) and a (upper bound). It is widely used to model response to advertising and selling effort

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