The document classifies decision support systems (DSS) into several types based on user relationship, mode of assistance, scope, orientation, and focus area. Key types include active, passive, cooperative, data-driven, model-driven, knowledge-driven, and web-based DSS, each serving different decision-making needs. Additionally, it differentiates between institutional DSS for routine decisions and ad-hoc DSS for irregular decision-making scenarios.

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CHAPTER - 4
Types of Decision Support
Systems

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Decision Support Systems Classification
The decision support systems can have a
classification across different types based
on multi-criteria.

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Decision Support Systems Classification
based on User Relationship
I. Active DSS: has the capability to build
decision guidelines that are developed to
support the decision making for
solutions to issues
II. Passive DSS is does not build decision
guidelines but only provides support to
the decision making process.
III. cooperative DSS provides the decision
maker the ability to execute changes

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DSS Classification based on Mode of
Assistance
Data-driven Decision Support System
Data-driven DSS involves the access and
manipulation of data that is structured and
which includes time series functionality
handling to fulfill the external and internal
data requirements of organizations as the
data is managed.

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Model-driven Decision Support System
A model-driven decision support systems is
a specially designed model patterned after
specific parameters and features defined by
the users to include the property of support
to decision making process through the
analysis of given situations.
It does not require a large demand for data
as there is minimal need for databases

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Communication-driven DSS
It relies on a network fusion and
electronic methods to integrate core
decision makers in given situations by
consolidating the decision makers into
one environment which has all the data,
information and resources that are needed
for decision making.
This model is now formally referred to as
Group Decision Support System (GDSS).

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Document-driven (DSS)
Document management became an
important feature for organizations to
manage and store relevant documents and
other materials such as photos and images,
and audio and video files.
An alternative that is used in the retrieval of
information is the text-based system which
is also considered as effective in mining
organizational data in identifying the
location of documents.

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Knowledge-driven DSS
knowledge-driven DSS which is
considered to have started from intelligent
decision support systems with a related
perspective that these are linked to
artificial intelligence.
Is computer-based reasoning system that
provides information, comprehension and
suggestions to users to support them in
decision-making

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Web-based DSS
web-based DSS and this is viewed as a
complex and sophisticated decision support
system that has expanded its ability with the
utilization of the worldwide web and
Internet as part of the processes for
supporting decision making.
This progress in the web-based decision
support systems caused a continued
technological advancement that has also
defined the Internet

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DSS Classification based on Scope
Enterprise-wide DSS provides support to
organizations and decision makers by
integrating large databases across different
locations in order for the decision makers to
have a view over all the data warehouses.
Desktop single user DSS, in comparison to the
enterprise-wide DSS, has a smaller foundation
and is typically limited to an individual user’s
personal computer with this DSS being
designed as a point of support for managers.

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DSS Classification based on
Orientation
i. Text-oriented DSS
ii. Database-oriented DSS
iii. Rule-oriented DSS
iv. Solver-oriented DSS
v. Spreadsheet-oriented DSS
vi. Compound-oriented DS

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Contd.
A text-oriented DSS aids the decision-
making process with the storage of text-
based data that can then be accessed, utilized
and evaluated by the individual managers
and decision makers.
 database-oriented DSS involves the
storage of data and information across
different locations such as in regions which
then provides the decision makers access to
the data.

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Contd.
rule-oriented DSS provides a more intelligent
approach that incorporates the use of artificial
intelligence, which enables the leverage of rules
and processes to aid the decision makers in
suggested solutions coming from the knowledge
base.
solver-oriented DSS could be considered as
systems which are specialized as these involve
solvers which enable the analysis and development
of solutions in various areas subject areas including
finance, forecasting and optimization among many
others.

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Contd.
spreadsheet-oriented DSS provides
decision making support that require the
aspects of the development of creating,
extracting and improving knowledge.
 compound DSS is a category of DSS that
involves different orientation-based DSS
in combination in its application

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DSS Classification based on Focus
Area

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DSS Classification based onType
and Frequency of Decision Making
Institutional DSS: effectively for
programmed decisions that are executed on a
regular basis such as daily.
Ad-hoc DSS: is applicable in situations where
support for decision making is not considered
to be regular but in one-off situations.
The ad hoc DSS is meant to be used for
decisions which are not programmatic, and
the likelihood is that the data and information
in these situations are incomplete.

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END OF CHAPTER - 4
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