Cross-disciplinary research in analytic decision support systems
Mats Danielson, Love Ekenberg, Karin Hansson, Jim Idefeldt, Aron Larsson, Mona Påhlman, Ari Riabacke, David Sundgren
Abstract
Mats Danielson, Love Ekenberg, Karin Hansson, Jim Idefeldt, Aron Larsson, Mona Påhlman, Ari Riabacke, David Sundgren
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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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