Information Technology Reference
In-Depth Information
Fig. 4.
Conceptual framework of the DSS
These impacts are increasingly important aspects of decision in transport invest-
ments. To take care of this, the analyst component incorporates, and automatically
computes, a set of key performance indicators (KPIs) hierarchized by their measuring
aim (e.g., evaluate client satisfaction, financial and organizational performance).
The IDSS can integrate several types of other advanced modern technologies, such
as knowledge-based modules, and internet and web capabilities (e.g., free map ser-
vices, map visualisation and on-line trip requests. According to Liu et al. [15], an
IDSS which combines the use of models, analytical techniques, data access and re-
trieval functions, by using advanced differentiated technologies (this is the case), will
have the advantage (in relation to traditional “static” DSS) in providing consistent,
coordinated, active and global support for the various managers/analysts on their dif-
ferent levels of decision-making processes.
4
Discussion
In general, the amount of data available (e.g. detailed traffic operations events and
conditions) is huge, and only a relatively small fraction of that is adequately trans-
lated into information that is used by managers. In most cases, this is restricted to
the information that is easily obtained by applying traditional query database opera-
tions and graphical displays, including standard statistical elements (e.g. historical
means and deviations of traffic volumes) in general-purposed tables, graphs and
maps. But, in fact, much more information can be potentially gathered from real
data: (1) further performance measures can still be obtained by traditional forms;
(2) deeper information, somehow hidden in the databases, can be highlighted by
applying more advanced analytical methods, such as data mining, optimization and
