Geoscience Reference
In-Depth Information
terms of coverage where the main differences among the different approaches lie
in the methodology adopted to estimate coverage, by combining and elaborating
different data layers.
Special reference should be made to the so-called retail site location problem,
consisting in determining the optimal positioning of commercial sites in a given area
in order to maximize expected future profits. As this decision involves significant
financial resources and risks, the selection process requires a careful analysis
of the spatial distribution of the demand (geodemand) and of the competitors
(geocompetition). When geographical data regarding population and its attributes,
activities, private and public traffic information are available, GIS are the most
powerful tool to perform geodemand and geocompetition analysis. The objective
is in line with the Maximal Covering Location Problem where it is necessary to
define a trade area within which it is assumed that a retailer is able to attract
customers and generate sales. Among the various approaches to tackle this problem
(see for instance Mendes and Themido
2004
; Cheng et al.
2007
), Roig-Tierno et al.
(
2013
) proposed a method based on the use of data at the level of single city
blocks and the evaluation of geocompetition by defining trade areas of competitors
as a function of their facilities' size and then evaluating areas on the basis of the
overlap between individual trade areas. Then they finally ranked the set of potential
candidate locations by using AHP. Suárez-Vega et al. (
2012
) used GIS to implement
a bi-objective model considering the maximization of the captured demand and the
minimization of the cannibalization effect.
19.6
Conclusions
The recent overwhelming advances in Information and Communication Tech-
nologies (ICTs) have triggered a profound rethinking of scientific approaches
in many fields. As usual, in processes where significant gaps and discontinuity
have occurred in the use of consolidated methodologies, passionate and extensive
discussions within the relevant scientific communities are generally taking place
with researchers debating about the actual and substantial innovations produced
by technological change in their respective field. This observation has been also
evident in the vast multi and inter-disciplinary community involved in evaluating
the impact produced by the development and diffusion of GIS. In particular, in the
field of locational analysis, judgments regarding the actual opportunities offered by
GIS to effectively solve location problems may be very different. On the one hand,
more theoretically oriented researchers tend to downgrade GIS to a mere input-
output tool, capable of building sophisticated databases and knowledge bases that
external optimization models may use, assigning it a very limited added value as
far as the methodological aspects are concerned. On the other hand, researchers and
practitioners more interested in discovering opportunities to solve real problems in
a more appropriate manner, emphasize the role of GIS as crucial decision support
