Quantitative methods in marketing 241
models fail to give satisfactory results. In the
last few years, causal models – in particular,
LISREL – and artificial intelligence techniques
have been widely used. The fuzzy sets tech-
nique is a new method that has been applied in
marketing only very recently. Expert systems
are currently systematically applied in many
marketing problem areas. Queuing theory, net-
work planning and transportation models are
more restricted in their applications in market-
ing, as they are formulated to solve problems in
specific areas. Regarding deterministic tech-
niques, these are suitable for finding optimum
solutions to problems, particularly when set
relationships exist between the variables. In
summary, the usage of different types of mod-
els depends largely on the problem under
investigation, as well as on the type of data
available and their level of interrelationships.
This chapter has attempted to present the
application of the main quantitative methods in
marketing. A taxonomic structure was adopted
and all the techniques were broadly classified
under nine headings: multivariate methods;
regression and forecasting techniques; simula-
tion and fuzzy sets methods; operational
research techniques; causal models; hybrid
techniques; and network programming models.
Also discussed were generalized linear models,
fuzzy decision trees, self-organizing maps
(SOMs), rough set theory (RST), variable preci-
sion rough sets (VPRS), Dempster–Shafer the-
ory (DST) and chaos theory. Advantages and
limitations in the usage of each of these
methods were discussed. However, the use of
different types of methods depends largely on
the marketing management situation of the
problem under consideration.
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