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Information System

Published on January 2017 | Categories: Documents | Downloads: 8 | Comments: 0



Abstract: This paper explored the history, current state and theories of Decision
Support Systems. The current state of research on Decision support systems is also
discussed and analysis of same is presented. The paper critically analyses the nature and
state of decision support systems (DSS) research. To provide context for the analysis, a
history of DSS is presented which focuses on the evolution of a number of sub-
groupings of research and practice. There are new opportunities for enhancing decision
support with internet and data mining technologies. Some of these have led to decision
systems that can be employed in real time applications. Interaction with social network
systemsis enabling a new level of decision support technologies in recommendation
systemsas well as collaborative decision systems. The paper also gives a description of
optimization-based decision support for the next millennium along with the future
implications and challenges for the decision support.

DSS Timeline
DSS became an area of research of its own in the middle of the 1970s, before gaining in
intensity during the 1980s. In the middle and late 1980s, executive information systems
(EIS), group decision support systems (GDSS), and organizational decision support systems
(ODSS) evolved from the single user and model-oriented DSS. In the late 1970s the DSS
movement started focusing on "interactive computer-based systems which help decision-
makers utilize data bases and models to solve ill-structured problems". In the 1980s DSS
should provide systems "using suitable and available technology to improve effectiveness of
managerial and professional activities", and towards the end of 1980s DSS faced a new
challenge towards the design of intelligent workstations. Beginning in about 1990, data
warehousing and on-line analytical processing (OLAP) began broadening the realm of DSS.
As the turn of the millennium approached, new Web-based analytical applications were
introduced. The advent of better and better reporting technologies has seen DSS start to
emerge as a critical component of management design. Examples of this can be seen in the
intense amount of discussion of DSS in the education environment.
DSS Development
A synonym for DSS is knowledge-based systems, which refers to their attempt to formalize
domain knowledge so that it is amenable to mechanized reasoning. Decision support systems
are gaining an increased popularity in various domains, including business, engineering, the
military, and medicine. They are especially valuable in situations in which the amount of
available information is prohibitive for the intuition of an unaided human decision maker and
in which precision and optimality are of importance.
Group Support Systems, Web Based DSS and OLAP
Group Decision Support Systems (GDSS) have been defined as interactive computer-based
systems that facilitate the solution of ill-structured problems by a set of decision makers
which work together as a team. The main objective of a GDSS is to augment the
effectiveness of decision groups through the interactive sharing of information between the
group members and GSS are implemented typically as electronic meeting systems (EMS) and
CMCS (Computer-Mediated Communication Systems) for supporting decision makers. Tools
that support distributed teams which have been empirically tested are mainly
synchronous computer conferencing systems (i.e. discussion forum software); these
systems do not have explicit support for decision-making processes and often do not
provide tools for alternative evaluation. GDSS products, such as GroupSystems, are
LAN-based client-server applications often supporting same-time and same-place groups
working in face-to-face settings.
Data warehouses, on-line analytical processing, data mining and web-based DSS have been
broadly recognized as technologies playing a prominent role in the development of current
and future DSS. Data stored in a data warehouse are usually analyzed with the aid of on-line
analytical processing (OLAP) tools. At the same time, the Web environment becomes a
widely adopted development and delivery platform. Web-Based DSS deliver information
and/or tools to a decision maker through a Web browser that is accessing the Internet or a
corporate intranet. All the above technologies certainly facilitate diverse aspects of decision
making. Although there exist certain limitations in their suitability, they may aid DSS users to
make better and faster decisions. However, we argue that there is room for further developing
the conceptual, methodological and application-oriented aspects of the problem. The paper
describes the database capabilities, the modelling functionality and the interface design
components of the DSS the classic tool design components of DSS. They add tools such as
data warehouses, on-line analytical processing, data mining and web-based DSS as tool
developments for future DSS. These tools together with collaborative support systems, virtual
teams, and knowledge management optimisation-based DSS and active decision support are
important topics in the development of the DSS concept for the next millennium.
Decision support technologies need to exploit the relentless advances in computers and
telecommunication infrastructure, the aim being to deliver applications of enhanced
performance to decision makers around the world, while efficiently and effectively
addressing communication and collaboration issues. Mining of data warehouses and use of
analytical tools already provide decision makers with accurate information. We argue that
research work towards this direction will bridge the gap between the approaches developed
from each side, in that they will both aim at augmenting the intelligence and support required
in the complex and dynamic decision making processes of the contemporary organization.
Decision Support Systems remains a tool that can provide firms with a sustainable
competitive advantage and in many industries a robust Decision Support Systems are the rule
rather than the exception. As technologies evolve, Decision Support Systems will change and
adapt to the challenges of the new economy and firms should thus continuously be aware of
new landscapes that are being formed and streamline their Information Systems applications
with current industry trends and technological advancements.

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