DECISION SUPPORT SYSTEMS APPLICATIONS IN FUTURE STUDIES

Abstract

In Futures Studies a worthwhile future is searched for all human beings. In such approach many issues are required to be identified and strategically solved. However, the complexity of related systems makes the process of decision-making and reaching to a single view; difficult. This is as a result of fundamental changes in current era and the spread of knowledge in all areas. The development of data, on one hand, and the limit power of human being, on the other hand, is placed against each other. The effective application of decision support systems in recent years and the successful results of implementing them in various industries are indicators of high potential of these tools to be integrated with Futures Studies techniques to depict a desirable future in various areas. Combining the strengths of decision support systems and human’s mind can fill the gap between the future insights, decrease the risk of decision-making and make the process of Futures Studies more comprehensive.

Full text

INTERNATIONAL JOURNAL OF MODERN MANAGEMENT & FORESIGHT
JOURNAL HOMEPAGE: IJMMF.COM ISSN: 2204-0072.
VOL. 1, ISSUE 9, PUBLISHED ONLINE on SEPTEMBER 2014, pp. 237-246.
DECISION SUPPORT SYSTEMS APPLICATIONS IN
FUTURE STUDIES
EHSAN MEHRABANFAR1*, SABINA NOBARI2
1* Faculty of Management, Science & Technology, Amirkabir University of Technology, Tehran, Iran
Corresponding Author email: e.mehrabanfar@gmail.com
2 Azerbaijan National Academy of Sciences, Baku, Azerbaijan
sabinanobari@yahoo.com
ABSTRACT
In Futures Studies a worthwhile future is searched for all human beings. In such approach many issues are
required to be identified and strategically solved. However, the complexity of related systems makes the
process of decision-making and reaching to a single view; difficult. This is as a result of fundamental changes
in current era and the spread of knowledge in all areas. The development of data, on one hand, and the limit
power of human being, on the other hand, is placed against each other. The effective application of decision
support systems in recent years and the successful results of implementing them in various industries are
indicators of high potential of these tools to be integrated with Futures Studies techniques to depict a
desirable future in various areas. Combining the strengths of decision support systems and human’s mind can
fill the gap between the future insights, decrease the risk of decision-making and make the process of Futures
Studies more comprehensive.
KEYWORDS: Future Studies, Decision-making Theory, Decision Support Systems, Scenario Planning.
1. INTRODUCTION
Future and discovery of its facts have constantly been the man’s main goal since the creation of humans on
earth. Through the history, various methods have been used to achieve this goal as once prediction and
forecasting was the foundation of such methods. However, knowledge is now well-ordered and offers Futures
studies as a basis for better comprehension of future. In this regard, various qualitative and quantitative
techniques are used to achieve possible or desirable futures. By analyzing current trends or depicting a
pleasant future, each method tries to discuss and conclude about probable scenarios. Undoubtedly, the main
goal is drawing a better future by discovering steps toward that. However, there is no method being able to
comment in certainty about the predicted scenarios. So, strategic studies have a close connection with Futures
studies because choosing a superior future depends on active players of future decision maker and the steps
they would take.
Futures Studies is a prescriptive-descriptive approach trying to analyze new complicated systems by its
incorporated methods and clears the way toward a desirable future. Various changes in constituent
parameters of the new effective systems in humans’ life urge them to use Futures studies bearing the nature
of decision-making. Due to the variety and integration of causal relations between factors resulting from
human’s nature, technology, history, culture and time; decision-making in Futures studies requires strategic
measures. In holistic perspective of futures studies, this approach makes some decision gaps for researchers
and confirms the difference in researchers’ views about key issues. On the other hand, the recent emergence
of decision support systems and their effective functions in predicting and optimizing the systems and
today’s troubled organizations have focused the researchers’ attention on using these tools. Therefore, it is
possible to achieve an optimum point in macro and complicated processes of decision-making by combining
in human processing benefits and humans’ dynamic intelligence. This is observed in research literature about

Page | 238
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
scenario planning combined with decision support systems and a key step toward emphasizing on using such
system is humans’ creative power.
Decision-making is the principle and the basis of strategic management. According to Morris Blundel, it is
impossible to predict the future but it is possible to make it. This idea clarifies the importance of decision-
making; correct decisions would definitely bring a desirable future. Making correct decision in taking
strategic steps toward a good future requires correct decisions which are consistent with current situations.
Decision support systems are a set of human’s powers along with the power of computer bringing forth a
better future. This research tries to determine the past and future places and their mutual effects by defining
the principles of futures studies and explaining its origin. In this regard, the role of strategic decision in
creation of an optimum future is clear. This requires to be shaped through applicable methods. One of these
methods is to rely on decision support systems having practical functions coupled with Futures Studies
techniques.
2. STUDYING THE PRINCIPLES OF FUTURES STUDIES
Human beings throughout history have passed different stages based on futuristic views. People of 16th
century saw future as past and didn’t think radical changes as usual matters. However, people of 19th century
and after that observed abundant changes throughout their lives and children’s and fathers’ model life has
been changed. Currently, the rapid trend of changes necessitates the recognition and the right perception of
future which has the highest level of socio-economic advantages. However, organized studies of Futures
studies have been shaped since World War II, particularly in 1940. Generally, after this historical period a
new era has started that has made a lot of changes in different stages one of which is modern futures studies.
This approach occurred in two different forms in US and Europe. In US, futures studies was formed to
develop by Study of technology and military actions while its origin in Europe was based on making changes
in society and democratic components. In time, the process of shaping and growing the subjects of Futures
studies has continued in different countries such as Sweden (Kaijser and Tiberg, 2000). In US, industrial-
military complexes and RAND took the initial steps by studying on strategic planning (Cornish, 1977). In
first steps, the main goal was applying it in potential development of national security gradually entering
different societies in 60s and 70s. International Institute for Applied Systems Analysis, Austria, is one of the
pioneers in studies about futures studies. In cooperation with Western countries and USSR, the institute
carried out many global researches in different areas (Grubler, 1990). Having an effective role in research
about analyzing systems, the Swedish National Defense College could be impressive in studies about
uncertainty, programming and scenario planning (Schwartz, 1988). In cooperation with this institute, the
secretariat for Futures studies in Sweden was formed. Theses studies, specially the method of scenario
planning, were applied for major international companies such as Shell. French School of "La Prospective"
was founded by Michel Godet and Gaston Berger (Berger, 1967). In recent years, most of countries have
founded various institutes in the area of Futures studies to apply several sciences.
Futures studies is both an art and a science. According to Vandel Bell (2010), Futures studies is a science
because, based on Thomas Kuhn, science is the same as the process of problem solving as a paradigm. On the
other hand, whether as an art or a science, Futures studies as an art is a holistic method. Holism refers to this
fact that recognizing the components without primary identification of the whole is meaningless. This
concept is obvious in the nature of Futures studies as Futures studies techniques are based on recognizing the
whole subject before recognizing the components. For example, physics is a reductionist science and stands
against holism, it is because actions and reactions of components are impressive and shape a part of the
nature of the whole system.
Among other qualities of futures studies, it can be referred to the nature of accuracy in its changes. Whether
possible, probable or desirable, futures occur as a result of a change made in current situation. If the
impressive conditions become complicated and effective components of a system are increased, systems will
become chaotic. According to the chaos theory, in such system little change in a component may have a high
level of influence on the fate of all components. This concept has its roots in butterfly effect. The present
environmental conditions of current systems are indicators of complications of systems. Therefore, more

Page | 239
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
chaotic systems compared to the past are observed. So, despite of triviality and inconsequentiality, changes
may alter the whole situation of available systems.
In Futures studies, Vandel Bell (2010) believe that time is a continuous, linear, one-way and irreversible
phenomenon. Within time, events occur before or after each others. In fact it explains the sequence of past,
present and future. Such insight into pass of time indicates the importance of occurrences at the time of
upheavals. On the other side, the primacy of events is highly important and enough attention to the causal
relations is mandatory. This refers to the importance of past steps in future events as trivial or major changes
have severe effect on past and current events. This approach has been posed in the chaos theory. When the
systems become more complicated, some step should be taken to reach the goal of Futures studies which is
achieving a desirable future.
Another feature of Futures studies is its influence in the present time. Researches done by research groups
reveal some trends like the growth of population in the world, reduction of sweet water, growth of the
distance between poor and rich, spread of illnesses and immune microorganisms and their new types,
terrorism, human environment dynamic, change in women’s conditions, religions, tribal and racial behaviors,
IT, organized villainy, economic growth, old nuclear power plant, spread of HIV and change in the nature of
labor. These trends show a negative picture of future. Here, the main point is the effect of future on present.
In other words, when a future is expected bad, different manners is released of predicting a positive future.
Actually, the results from Futures studies have impact on present time and would be considered as the effect
of future on present time.
Futures studies is radically a soft science and depends on socio-cultural exchanges. According to Vandel Bell
(2010), there is no singular theory in terms of social changes and future upon which researchers agree about.
The main reason inherits from cultural transactions of nations and their mutual relations as futuristic thinking
has always been troublesome. Michael Fukuyama’s predictions about the future of the world and the
civilizations exchange is one example
In future study, various methods and techniques is needed to take steps forward. Another feature is using
combined methods or using several methods at the same time in a single study. Some of these methods are as
follow:
A. Methods of Identifying a Subject: Environmental examination, SWOT analysis, thematic surveys;
B. Explorative Methods (Checking a Trend): Trend extrapolation, simulation, smart prediction,
trend analysis, historical analysis;
C. Creative Methods: Surveying and consulting, brainstorming, analysis of reciprocal effect, Delphi
Method
D. Scenario Planning
All above methods need to have correct insights into the principles of futures studies. What a method ends in
is the result of both the method and the users’ correct insights into. By using human perception and proved
principles, future is studied in all these methods. For instance, trends analysis and future extrapolation is one
of these methods. However, there are wild cards or less probable events and high effects occurred in times.
They are against the available trends and have happened like a tsunami occurred in East Asian countries. This
example shows an uncertainty in a space depicted for future and should become clear by these methods and
users.
Futures studies is followed by three types of insights or approaches. In the first approach, the main goal is
predictive mode of thinking. This is true in Delphi method. This method is based on wise experts and derived
from the Oracle of Delphi, ancient Greece. A similar method is employed for predicting the future. However,
with the emergence of new sciences and passing the time of Galileo and Newton, the scientific method of
prediction has been replaced which is highly successful. The other side of this approach is the method of
trends analysis which predicts the future by observing the trends and a particular trend in past.
The second approach is accepting this fact that future is the eventuality mode of thinking. Basically, the
general viewpoint is that one should be prepared for everything because there is no certainty and there are

Page | 240
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
many probabilities about different issues. The method of scenario planning is one instance of such thinking
approach.
The third approach is the visionary mode of thinking. This means depicting a better future in a huge scale.
There are many works have been carried out in this regard, including Utopia by Thomas More or The
Republic by Plato. Back casting is of instances of this approach trying to depict an ideal future, coming back
from it and arriving at now.
3. DECISION SUPPORT SYSTEMS
Though many researches have been carried out about how to decide and how not to decide, there is no clear
definition for the term “decision” in management literature. Malach (1994) believes that decision is an action
among all available options. On the other side, Mittenzberg identifies it as a commitment to a measure. The
difference between these two approaches originates from this fact that Malach focuses on choice while in
Mittenzberg definition this focus is more on the outcome of decisions. So, decision has two dimensions: first,
choosing an action and second, the outcome of that action that both shape the process of decision-making and
decision maker should care deeply about both of them.
Most of scholars identify the management of decision as of the basics of management. Herbert Simon, with a
pioneering theory of human choice and administrative decision-making, thinks that management and
decision-making are the same subjects. Other management theorizers like Peter Drucker confirm this idea
and believe that decision-making forms the main constituent part of management science. A manager mostly
making a correct decision fulfills his/her commitments. Other duties reveal themselves in this fact. In this
regard, if a duty is incorrectly done but other duties are done correctly, the company will take no advantages.
The reverse is also true.
Decision-making in organizations has three levels and the strategic decisions are in the highest rank. The
totality of the organizations is influenced by these decisions. They are longer in terms of time dimension and
bigger on the ground of the scope of influence (Malach, 1994). In the other dimension, there are tactical
decisions having a minor time and effect limit comparing with strategic decisions. Anthony (1965) called
these decisions as management control. In this level, management tries to be assured of allocating
organization’s resources in the direction of macro goals. According to Malach (1994), these decisions are on
the ground of strategic decisions. The lowest level is operational decisions. Anthony (1965) believes that
these decisions are the process of guaranteeing effective and efficient operations. The main point in division
of organizational decisions is needed information for each level of decisions. In this case, in lower levels,
smaller amount of information is needed.
To make a decision correct and valid information is needed. According to Rezaeian (2001), information
flows like bleed in the vessels of organizations. Therefore, decision-making directs organizations toward
their determined and strategic goals. Herbert Simon classifies decisions into two planned and unplanned
groups based on their level of complication. The first group is repetitive and ordinary decisions and does not
need specific information. The second group does not have any particular trend and they are considered as
new decisions. In this case, information can not be easily accessed by organizations (Daft, 2004).
In another classification, Turban et al. (2002) categorize information into three groups of structured,
unstructured and semi-structured. Structured decisions have already planned in the organization and the
needed principles have been prepared. Unstructured decisions are emerging resolutions with high level of
complication. Information can not be easily accessed for solving the problems. Semi-structured decisions are
placed in a point between the above mentioned decisions.
Regarding the wide range of decisions which had to be made and the growth of complexity in the
organizations due to new technologies, in 1971, decision support systems were created by Lester for the first
time in Carnegie Company. They appeared in order to consult and help owners analyze their decisions
(Turban, 1985). For the first time, Fergosen and Jones (1969) presented a report of using these systems with
the aid of computers and they succeeded to implement the practical program of production planning by 7094
IBM. However, this event was as a result of a historic event occurred by Michael Scott Morton in 1967. He
explained this method in his thesis in Harvard University (Power, 2007). Six major applications of this

Page | 241
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
method include pricing and routing, planning and prediction, investment evaluation, pricing and
advertisement and finally price evaluation. They are concluded by Dankel (2002) and based on major
American Companies in different industries. Among effective and practical features the reduction of decision
cost and the growth of accuracy can be referred. This helps managers quickly reach a better decision and
more efficient operation by combining their knowledge with a computer model. This support system can
operate individually and in group. It finally transfers outputs to users and creates a practical relation over line
and in graphic form. In fact, a user-friendly environment will be shaped.
Decision support systems can be useful in making semi-structured and unstructured decisions. Laudon (2001)
thinks different types of these decisions are more useful for administrators of organizations. Although they
can be used in all levels of management, they can not replace the process of decision-making. Laudon (2001)
also states that such system is highly flexible and allows users to implement different models of decision-
making on it. Based on his classification, decision support systems receive a small amount of data as input;
carry out interactional simulation analyses as processing procedure and present reports and analyses as
output. Among other features we can refer to being user-friendly and easily access to information. These
systems were first designed for managers but they were promoted to be used by teams and in group works.
The last version has been designed for virtual organizations (Shim et al. 2002).
The advantages of this system are summarized in several dimensions. The first most important dimension is
increasing the profit of decision maker (Alter, 1980). This reduces the duration of decision-making and the
related activities. The other benefit is high quality of made decisions (Maracas, 2003). By presenting a tool
for interaction and cooperation with other employees, this system improves the organizational
communications. These communications may result in receiving positive comments from other colleagues.
Sharing and transferring knowledge are two main components of knowledge management and are considered
as other functions of these systems (Alter, 1980). Implementation of such systems in an organization can lead
in development of decision-making and individual and organizational learning skills. For instance, it may
result in better understanding of organization and the strengths and weaknesses of organization would
become clearer. Decision support systems can increase the organization controlling because limitations make
decisions consistent with each other in different stages (Malach, 2004).
Regarding the mentioned limitations, decision support systems have some negative sides such as lack of
creativity, intuition and imagination. These systems are limited to data, knowledge and their model and they
are not beyond that. The available user’s link is not smart enough for interaction and application. There is no
comprehensive system to be applied for all content grounds and instead they are applied in trivial matters
(Maracas, 2003).
To be formed, a computer-based decision support system needs four elements of model management,
management of data, management of knowledge and management of user’s link. If these elements are placed
correctly along each other, an appropriate system will be established. In Turban’s classification, user is also a
main part of the system (Turban and Arson, 1997).
Many researchers like Bhargava & Power (2001) have classified decision support systems based on
application, output and other parameters such as efficiency of system into model driven, communication
driven, data driven, document driven and knowledge driven systems. These names are each based on one
singular subject. For example, communication driven systems focus more on communication, cooperation
and decision support. Model driven systems support by optimization models. Data driven systems includes a
large amount of data and support analyses. They create a situation to show and manipulate the different set of
data. They include a data warehouse providing the needed information based on subject and the time of
managers’ decisions. Document driven systems work on gathering, classification and management of
unstructured document. Other groups are rule driven or intelligence driven model. The practical techniques in
artificial intelligence and smart systems are used in knowledge driven systems (Power, 2002).

Page | 242
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
To study decision support systems, three dimensions are considered. The first one is based on the process of
decision-making. Accordingly, the main purpose is decreasing or covering the weaknesses of decision-
making or cognitive limitations of decision-makers (Silver, 1991). The purpose of the second dimension is
meeting the decision-maker’s needs which can be determined by an analyzer. For example, lack of
information can be one of these needs (Silver, 1991). The other dimension is the environment of decision-
making which is beyond the decision-maker and refers to the ground of decision-making. One way is
coordinating and facilitating the mutual relations of decision-makers (Hollsopple & Winston, 1996). One
instance of the fist type help is a cognitive decision system which has been implemented by Chen and Lee
(2003) to make strategic decision. The purpose of this system is decreasing the tensions of decision-making
and scenario planning improves applications by sending information and comparable items. The example of
the second type is decision support systems to increase creativity created by Forgionne and Newman (2007).
This system helps users analyze their needed knowledge, main ideas and the structure of problem-solving and
simulate their solutions.
At the beginning of 1990s, four new components caused a revolution in decision support systems. Data
warehouse was forerunner of these changes and followed by two other changes. Data mining and on-line
analytical processing (OLAP) made radical changes in implementation of these systems. And the most
important change was internet. Data warehouse helps user to gather data from several bases. On-line
analytical processing is a software technique helping users have quick access to a large amount of data. This
method has become modernized through data mining method. Data mining tries to provide further facilities
for users through nervous system and the methods of statistical analysis. It can find models among data; due
to this fact it is called a discovery method (Shim, 2002).
Decision support systems are employed in various industries and applications such as management issues,
military sciences, and management of natural resources, controlling and managing environment and urban
planning.
4.THE ROLE OF DECISION SUPPORT SYSTEMS IN FUTURES STUDIES
In the methods of Futures studies researchers are seeking to describe the future or prescribe a better future.
To manage the future, prescriptive methods should be employed to be able to initiate appropriate strategies of
future since the present time. In descriptive methods, the role of decision-making is weaker but in
prescriptive methods it is more impressive. As stated before, past conditions the present but some images of
future create a particular form of present. This means that images of future result in current measures and the
current situation builds up the future. Decision-making theory shapes the basis of more futuristic researches.
Decision-making has pragmatist nature and the theory of decision-making tells that the images of future state
the current social events as problem and specify that how it is possible to keep these events as they are or
how can depict a new design for them.
One of the most practical methods in Futures studies is scenario planning with the purpose of drawing
various options for. Scenario is derived from the term cinema and it relates back to the years before
organized studies about futures studies. This term was first used by RAND (Sumiker, 1993) but now it is an
important part of Futures studies. Scenario is a descriptive story caring about a particular part of future. There
are three types of scenario each of which are divided into two types. The first group is predictive one type of
which is “what if” and the other type is “forecast”. The second group is explorative which is divided into two
types of strategic and external. In this group this question is posed: “what sort of event may happen”. The last
one is normative with two divisions of preserving and transformational. In this group this question is posed:
“how can we achieve to what is desirable” (Borjson, 2005).
Due to the complexity and high uncertainty of human societies, scenario planning cannot achieve all certain
facts of future. It just states futures which have been obtained by its method. This method is so practical and
useful; so that Shell Company could evaluate the probable outcomes of reduction of petroleum prices and
identify the possible solutions by this method. Then, despite of tough swing in petroleum price, the company

Page | 243
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
could achieve a huge profit by management of the crisis. After petroleum crisis in 1979 this method was been
widespread (Shuartz, 1991).
In scenario planning, the first step is identifying the fundamental subjects and decisions in which our
organization is involved. In this step we care about the organization and its short-time future. In the next
steps, impressive factors in external environment are identified. After ranking them, the logic of scenario is
determined, the details is written and the relation of decisions and scenarios are assessed. Scenario planning
is a step by step process and a stage which go forward by decision maker. The general and the final role of
decision-making are played by the panel. For example, Platino (2005) have presented a model for
management of water resources by decision support system. This model reduces the risk of existing
uncertainties. In this approach uncertainties have drawn by decision tree in a multistage environment; this
model can reach a definite decision by analyzing the scenario.
Decision support & future studies center (DSFS) is an active institute in case of using decision support
system for anticipating the future and have implemented successful projects. It was founded in 2002 as an
independent consulting unit in Computer and Information College of Cairo University to show the
importance of using DSS in all management levels. The institute has employed this system in futures studies,
project management and operation management and governmental management.
Another method of Futures studies is Delphi method designed by RAND in 1950s in US. The history of this
method comes back to the shrines in ancient Greece and it is based on the ideas of wise experts by using
questionnaire and repeating it. In fact, this method was established upon the opinions of a group not a single
person (Kurnish, 1977). Other than Delphi method, some other Delphi-based methods have also shaped. On
modified Delphi method was designed by Bast et al. (1986). In this method, on the basis of first questionnaire
different opinions will be shaped and the traditional Delphi is then implemented again. It is on the foundation
of various and probable future. Another modified method is a combination of Delphi method and back-
casting, which was created by Hujer (1998). At first, a desirable future is depicted by scenario planning. Then
according to the traditional Delphi method, the method of achieving that scenario is evaluated.
Regarding structural similarity with the method of scenario planning, different Delphi methods can be
implemented more effectively by decision support systems because the methods can be combined and
compared with scenario planning. As said before, in Futures studies the best technique is combining several
methods. However, this approach requires more resources and costs. If the members of Delphi panel have
access to a system connected to the basic center, the output will be better. In traditional Delphi method cross
impact analysis method is used to prevent isolation decisions from logic and causal relation.
As a result of this weakness, the method of morphological field analysis was created in order to analyze the
mutual relations of systems. As this method was highly used, it was placed in the analysis of policies and
futures studies. FOI has designed software called CASPER taking advantage of this method. Richi (1997)
states that by introducing variables such as geography, size and functional preference, this method integrates
several scenarios and assesses reciprocal correlation coefficient. This method was used for missile defense
system in Sweden. Any defined variable in this software can have more that 50 to 100 thousand states. To
reduce the number of output a pair of state is judged. Here, maintenance is internal consistency and
solidarity.
The method of morphological field analysis is used in the model of external explorative scenario and in two
types of normative model. The traditional Delphi model is used in predictive method. The traditional Delphi
is used in this group and with insight into discovery of a desirable future in the normative model and both
predictive and transferring types.
5. CONCLUSION
Undoubtedly, one of the most important measures of all active systems is to have the power of choosing is
decision-making. Small decisions can be turned into big decisions. As stated before, decision-making is a

Page | 244
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
separable process. It is a process with different levels in any of which information is needed. It is a
categorized process and each person can not involve in. Decision-making from the starting point which is the
emergence of the problem and in the process of analysis, choosing options, selection and observing the
outcome is a clear, programmable and organized process which can be studied part by part. Decision is
process-based and the stages of emergence should be cared. Thus, decision support systems may involve in
the process of decision-making. They may be useful for planning and classifying the information, providing
accuracy, time and easy access for different people in huge systems. These systems consider all available
components such as technical, personal, psychological, time or even ethical. This issue is the basis and the
root of decision support systems in twentieth century and their growth in twenty first century.
On the other hand, Futures studies is a holistic and complicated issue and involves in macro systems. There
are a lot of components affecting on because Futures studies look for unknowns influencing over present.
However, to create future, knowing past and present is a vital issue. In this subject, time is a linear and
irreversible concept flowing point to point. To anticipate the next points and prescribe the positive points,
strategic measures and demanding major decisions with high scale in time and effect are used. In fact a
correct and in time prescription can determine the fate of a system.
In the science of futures studies, many qualitative and quantitative methods of anticipation have been used.
Scenario planning, as one of these methods, is employed combined with decision support systems. The
studies reveal that using these systems is useful because computers can aid in the process of decision-making
and reducing the risks. Consequently, both the dimension of decision outcome and the dimension of choosing
a decision have occurred correctly and the process of decision-making would be effective and efficient.
On the basis of futures studies principle, future is more complicated because the current systems would be
more complicated in terms of content, components and structure over the time. The chaotic system can be
unpredictable because a small change in a component may have effect on the whole system. This anticipation
for the future can be a clear reason for using computers in decisions of complicated systems because humans’
ability in programming and analyzing a large amount of data is limited especially as data is daily upgraded.
On the side of principles of futures studies, using smart systems with high processing capability is so useful
because they are more comprehensive and more accurate than mind models (Bell, 1997). Human measures
like weather systems are influenced by various parameters and events. Therefore, anticipating the probability
of events is difficult or even impossible (Borjeson, 2005). By combining these systems with the methods of
Futures studies like scenario planning, Delphi method, simulation and adjusting their outputs with each other,
better outputs are released despite of consuming less time and fewer resources and be more prepared for a
desirable future which is the ultimate purpose of Futures studies and any science. In this regard, the existing
disagreements among researchers would be reduced and the view points would be more fruitful and reliable.
REFERENCES
Alter S (1980). Decision support systems: Current practices and continuing challenges. Reading, MA:
Addison-Wesley.
Alvani M (2004). General management, fifteenth edition, Ney Publication, Tehran, Iran.
Anthony R.N. (1965). Planning and control systems: A framework for analysis.
Bhargava H, & Power D.J (2001.) Decision support systems and web technologies: a status report, America’s
Conference on Information Systems, 3–5 August, Boston, MA.
Bell W (2010). Principles of Futures studies, Publication of University of National Defense, Tehran, Iran.
Bell W (1997). Foundations of Futures Studies: Human science for a new era. Volume 1: history, purposes
and knowledge. New Brunswick, NJ, Transaction Publishers.

Page | 245
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
Berger G (1967). Etapes De La Prospective, Presses Universitaires de France, Paris, France.
Best G.G, Parston, et al. (1986). Robustness in Practice-The Regional Planning of Health Services. J. Opl.
Res. Soc. Vol.37, Issue5, 463-478.
Borjeson, L and et al(2005). Towards a user's guide to scenarios - a report on scenario types and scenario
techniques, Environmental strategies research–Department of Urban studies Royal Institute of Technology,
Stockholm, Sweden.
Chen J.Q, & Lee S.M. (2003). An exploratory cognitive DSS for strategic decision making. Decision
Support Systems, Vol.36, Issue 147-160.
Cornish, E. (1977). The study of The Future: an Introduction to the Art and Science of Understanding and
Shaping Tomorrows World, World Future Society, Washington, USA.
Daft Richard (2004), Theoretical Principles and Designing Organization, (translated by Ali Parsaian and
Seyed Mohammad Arabi), Third Edition, Cultural Researches Center, Tehran, Iran.
Dankel D (2002). Decision Support Systems: Misconceptions and Reality, SAE Special Publications, Society
of Automotive Engineers.
Forgionne, G. & Newman, J. (2007). An experiment on the effectiveness of creativity enhancing decision-
making support systems, Decision Support System, Vol. 42, 2126- 2136.
Grubler, A. (1990). The Rise and fall if Infrastructures, Dynamism of Evolution and Technological Change
in Transport, Heidelberg, Physica-Verlag. Harvard University, Division of Research Graduate School of
Business Administration, Boston, USA.
Höjer M (2000). What is the point of IT? Backcasting urban transport and land-use futures. Department of
Infrastructure and Planning, Stockholm, Royal Institute of Technology, Sweden.
Holsapple C.W, & Whinston A.B (1996). Decision support systems: A knowledge-based approach. West
Publishing Company, Minneapolis/St. Paul, USA.
Kaijser A, and Tiberg J (2000). From OR to Futures studies: The Establishment , Diffusion and
Transformation of the systems approach in Sweden 1945-1980, In systems Experts and computers: The
Systems Approach in Management and Engineering, World War2 and After, Edited by Agatha C. Hughes
and Tomas Hughes, MIT Press, London, Uk.
Laudon, K. (2001). Management Information Systems: A contemporary Perspective, McMillan Publishing
Company, New York, USA.
Lonnroth M, Johansson T, and Steen B. (1978). Sol eller uran-att Valja energiframtid. Liber Forlag,
Stckholm, Sweden.
Mallach E.G. (1994). Understanding decision support systems and expert systems, Irwin, Burr Ridge,
Illinois, USA.
Marakas G.M (2003). Decision support systems in the 21st Century (2nd ed.). Pearson Education,
Prentice Hall, Upper Saddle River, New Jersey, USA.
Mintzberg H, Raisinghani D, & Théorêt A (1976). The structure of unstructured decision processes,
Administrative Science Quarterly, Vol.21, 246-275.

Page | 246
MEHRABANFAR & NOBARI (2014)
VOL1, NO.9, PP. 237-246
Power D.J (2007). A Brief History of Decision Support Systems, Handbook on Decision Support System,
Springer Heidelberg, Germany, 121-140.
Pallottino et al. (2005). Environmental Modeling & Software, Vol.20, 1031–1042.
Shoemaker P, & Van der Heiden K (1992). Integrating Scenarios into Strategic planning at Royal Dutch
Shell, Planning Review, Vol.20, Issue 3, 41-46.
Rezaeian A (2002). Information Management System, first edition, Samt, Tehran, Iran.
Schwartz P (1991). The art of the long view, Doubleday, New York, USA.
Shim P, Warkentin M, Courtney J, Power D, Sharda R,, & Carlson C (2002). Past, present, & Future of
Decision Support Technology, Decision Support systems, Vol.33, 111-126.
Silver, M.S. (1991). Systems that support decision makers: Description and analysis. John Wiley & Sons,
Chichester, England.
Turban E (1985). Decision Support and Expert systems: Managerial Perspectives. McMillan Publishing
Company, New York, USA.
Turban, E. McLean, J. & Wetherbe, J. (2002). Decision Support systems and intelligent systems, 5 Th
editions, prentice hall, Inc, New Jersey, USA.