ISPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001
389
Fig. 4 Criteria Contributions
Critérium DecisionPlus - (Contributions by Criteria]
Contributions to Goal from Level:Level 3
ASQUITH, PACIFIC HWY
Caringbah, Kingsway St
Canley Heights, Canley Vale Rd
Cabramatta, John St
Bondi Junction, Newland St
0.0 0.2 0.4 0.6 0.8
I j
LJ
Ci Criterium DecisionPlus - [Contributions by Criteria]
I Population Over 15
f~l Working Population
I Business Number
I I Thiessen Polygon Area
■ SELF 500M
Ü SELF_200M
■ Others
Contributions to Goal from Level:Level 3
CAMPERDOWN, GROSE ST
BURWOOD, BURWOOD RD
CAMPERDOWN, PARRAMATTA RD
CAMPERDOWN, BOOTH ST
BURWOOD, ELSIE ST
I Population Over 15
|H Working Population
I Business Number
I | Thiessen Polygon Area
■ SELF 500M
□ SELF 200M
■ Others
[ H * :
'■*a ry'a^oA r nn
5. CONCLUSION
This paper has illustrated how GIS can be integrated with
SMART models to develop an operational SDSS for business
decision-making. It should be noted, however, that because of
confidentiality considerations, no information about the financial
status of branch banks is included in the analysis. This
notwithstanding, it is demonstrated that the SDSS could be used
to generate alternative strategies based on spatial and
demographic analysis before implementing a final decision as
well as exploring whether other factors should be considered in
deciding whether or not a branch should be closed. The system
combines the functions such as a visual user interface, flexible
weighting mechanisms, sensitivity analysis and contribution
analysis capabilities to help decision makers effectively
formulate, validate and communicate complex decisions.
Further development and testing of the system is required to
fully demonstrate the usefulness of the SDSS for planning future
branch networks. In particular, additional research needs to be
undertaken to explore further the different criteria and their
weights in calculating decision scores, and to better understand
