Decision Support Systems and Representation Levels in the Decision Spine

Abstract

Problem solving has been defined as the complex interplay of cognitive, affective, and behavioural processes with the aim to adapt to external or internal demands or challenges (Heppner & Krauskopf, 1987). In the realm of organizational decision-making, Herbert Simon (1977) describes the problem-solving process as moving through three stages: intelligence, design, and choice. In this context, design focuses on “inventing, developing and analysing possible courses of action,” where the design artefact being constructed for this purpose constitutes the “representation of the problem.” While a wide range of representation means and calculi have been proposed for decision problem solving purposes, practical implementations generally involve applying one or more of these means to develop the structure of the problem within one or more frames. Typically, these are future-scenario frames, multi-attributed preference frames, and rule base-frames (Chatjoulis & Humphreys, 2007). Simon (1977) characterized decision problems according to the degree of problem-structure that was pre-established (or taken for granted as “received wisdom,” or “the truth about the situation that calls for a decision”) at the time participants embark on the decision problem solving process. He placed such problems on a continuum ranging from routine (programmed, structured) problems with well-specified solutions to novel, complex (unprogrammed, unstructured) with ambiguous solutions.