The Architecture of an Information System for the Support of Alternative Generation.

Author List: MacCrimmon, Kenneth R.; Wagner, Christian;
Journal of Management Information Systems, 1991, Volume 8, Issue 3, Page 49-67.
The pre-choice stages of the problem solving process are more difficult to support through information systems than choice itself. Systems that facilitate problem formulation and solution finding are typically either expert system programs with narrow application domains or programs dealing with easily quantifiable problems. In contrast, this paper introduces a decision support system, GENI, that operates independent of domain, aiding the user in general problem solving tasks. The system's purpose is to support the problem solving process, rather than be a substitute for the human problem solver, by providing structure and by using different stimuli to prompt the user for data input. To deal with broad classes of complex qualitative problems, no single processing mode is sufficient. Hence the techniques in GENI differ mainly An earlier version of this paper was originally published in the Proceedings of the TwentyFourth Hawaii International Conference on System Sciences (IEEE Computer Society Press, 1991). This research was supported in part by the Social Sciences and Humanities Research Council of Canada and by the U.S. National Science Foundation (Grant SES-9016305). We thank Nick Keenan for his assistance in developing portions of the software described in the paper. in the interface, that is, the types of stimuli displayed, and the types of data recorded. GENI's user interface is built around a standard dialog function that can be modified by means of parameter settings. Experimental results show that differences in the interface content can lead to significant differences in problemsolver performance.
Keywords: Decision Support System; Idea Generation; Idea Generation Software; Problem formulation
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#31 0.125 problem problems solution solving problem-solving solutions reasoning heuristic theorizing rules solve general generating complex example formulation heuristics effective given finding
#6 0.100 data used develop multiple approaches collection based research classes aspect single literature profiles means crowd collected trend accuracy databases accurate
#142 0.098 creativity ideas idea creative individual generation techniques individuals problem support cognitive ideation stimuli memory generate enhance generated solutions solving quality
#287 0.098 design systems support development information proposed approach tools using engineering current described developing prototype flexible built architecture environment integrated designing
#129 0.072 expert systems knowledge knowledge-based human intelligent experts paper problem acquisition base used expertise intelligence domain inductive rules machine artificial task
#28 0.060 cultural culture differences cross-cultural states united status national cultures japanese studies japan influence comparison versus china participants country singapore diverse
#113 0.060 support decision dss systems guidance process making environments decisional users features capabilities provide decision-making user paper findings systems.decision components computer-based
#183 0.060 explanations explanation bias use kbs biases facilities cognitive making judgment decisions likely decision important prior judgments feedback types difficult lead
#220 0.060 research study different context findings types prior results focused studies empirical examine work previous little knowledge sources implications specifically provide
#283 0.060 interface user users interaction design visual interfaces human-computer navigation human need cues studies guidelines laboratory functional developed restricted know guided