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The role of decision support systems
The role of decision support systems
The role of decision support systems
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Introduction:
“Decision making is concerned with evaluating and ranking possible alternatives of action” [9]. “It is a process that involves multiple steps depending on the number of viable options and scenarios” [1]. A person has to look into the pros and cons of each option and consider all the alternatives, decision maker also needs to be able to forecast the outcome of each option for the given situation and based on all these criteria can determine the best option suitable [5]. Nowadays technology is playing a vital role in helping humans take decisions in an effective way by processing the data, analyzing it and providing the alternatives to choose from. There are a lot of information systems that have emerged in the past few years which are also called “Decision support systems” (DSS), which help decision makers in identifying and solving problems by making right decisions utilizing the data and different models available[11].With the advent of emerging technologies such as Artificial Intelligence (AI) in the Information and Computing industry, have given rise to a new form of DSS called as “Intelligent Decision Support Systems (IDSS)” , that can in some way imitate human cognitive abilities in decision making [10]. “An IDSS is a decision support system that makes extensive use of the intelligence exhibited by machines or software. Ideally, an intelligent decision support system should behave like a human consultant supporting decision makers by providing full control of”: 1) acquiring data 2) evaluating the data and 3) making the final decision [6].The aim of intelligent decision support system is therefore to emulate human decision-making capabilities as closely as possible.
Traditional Decision Support Systems:
The curre...
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14. Power, Daniel J., Frada Burstein, and Ramesh Sharda. "Reflections on the Past and Future of Decision Support Systems: Perspective of Eleven Pioneers." Decision Support. Springer New York, 2011.
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16. Yan, Yalan, and Robert M. Davison. "Using decision support systems in Chinese enterprises: a study of managerial information behaviour." Information Development 27.1 (2011): 15-31.
Improve decision making on customers and sales orders based on the information provided by the new system.
Base on the case of “Your Choice Furniture”, we marked this system's analysis to formulate solutions in this report; it assisted in evaluating the impact of recent change information technologies of “Your choice furniture” business system for evaluating how well the firm will be performing.
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Bonini, C. P. (1963). Simulation of information and decision systems in the firm. Englewood Cliffs, N. J.: Prentice-Hall.
Partridge, Derek and K. M. Hussain. ARTIFICIAL INTELLIGENCE and BUSINESS MANAGMENT. Norwood: Ablex Publishing Corparation, 1992.
Davenport, T. (2006, January). Decision Making: Competing On Analytics. Harvard Business Review. Retrieved August 8, 2011, from the EBSCO database.
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A Decision Support System (DSS) is an information system at the management level of an organization that combines data, analytical tools, and models to support semistructured and unstructured decision-making. A DSS can handle low volume or massive databases optimized for data analysis. DSS has more power than other systems. They are built explicitly with a variety of models to analyze data or they condense large amounts of data into a form where they can be analyzed by decision-makers. DSS are designed so that the user can work with them directly. In the proceeding paragraphs I will give examples of some decision support systems and how they are being used.
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Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...
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The journey of my decision analysis learning process has been a roller coaster ride. While I enjoyed reading, understanding and learning about the various methodology and aspects of decision analysis, I also find myself stressed, frustrated and ready to give up. For me, the concept about what is decision analysis, the utility of decision analysis, and the topics on decision bias, ethics, complexity and controversy of decision analysis make sense to me as I understood what they are and how they can impact a decision making process. Quantitatively, while I enjoy experimenting and learning the R, Rattle and Excel Decision Tree Plan, statistically, I am frustrated as I am unable to come up with the correct answers when it comes to the quantitative models and calculations such as the probability matrices, binomials, conditional probability, and Markov modeling. Learning the functionalities and seeing an outcome from the R software and knowing what an excel can do to a set of data is intriguing yet exciting to me,
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Laudon C. & J. Laudon (2003: 5th edition) Essentials of Management Information Systems. London: Prentice Hall International Limited