2006Unpublished venueRequires access

Cross-disciplinary research in analytic decision support systems

Mats Danielson, Love Ekenberg, Karin Hansson, Jim Idefeldt, Aron Larsson, Mona Påhlman, Ari Riabacke, David Sundgren

Open publisher page 3 citations

Abstract

A main problem in decision support contexts is that unguided decision making is difficult and can lead to inefficient decision processes and undesired consequences. Therefore, decision support systems (DSSs) are of prime concern to any organization and there have been numerous approaches to delivering decision support from, e.g., computational, mathematical, financial, philosophical, psychological, and sociological angles. A key observation, however, is that effective and efficient decision making is not easily achieved by using methods from one discipline only. This paper describes some efforts made by the DECIDE Research Group to approach DSS development and decision making tools in a cross-disciplinary way

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What this paper is about

A main problem in decision support contexts is that unguided decision making is difficult and can lead to inefficient decision processes and undesired consequences. Therefore, decision support systems (DSSs) are of prime concern to any organization and there have been numerous approaches to delivering decision support from, e.g., computational, mathematical, financial, philosophical, psychological, and sociological angles. A key observation, however, is that effective and efficient decision making is not easily achieved by using methods from one discipline only. This paper describes some efforts made by the DECIDE Research Group to approach DSS development and decision making tools in a cross-disciplinary way

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

A main problem in decision support contexts is that unguided decision making is difficult and can lead to inefficient decision processes and undesired consequences. Therefore, decision support systems (DSSs) are of prime concern to any organization and there have been numerous approaches to delivering decision support from, e.g., computational, mathematical, financial, philosophical, psychological, and sociological angles. A key observation, however, is that effective and efficient decision making is not easily achieved by using methods from one discipline only. This paper describes some efforts made by the DECIDE Research Group to approach DSS development and decision making tools in a cross-disciplinary way

Key concepts: Decision support system, Decision engineering, R-CAST, Management science, Prime (order theory), Computer science, Business decision mapping, Discipline

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