Knowledge-based DSS for supporting ill-structured multiple criteria decisions

Ilyoo B. Hong, Doug Vogel, Jay F. Nunamaker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Focusing on qualitative reasoning processes as a key area of AI (aritifical intelligence) application for decision support, the authors propose an architecture for designing an intelligent DSS (decision-support system) that is intended to aid in MCDM (multiple-criteria decision-making) in ill-structured situations. An MCDM DSS, for its maximum contribution to organizational problem-solving, must be capable of lending effective support to high-level as well as low-level management decisions. A commercial loan approval judgement case is described to illustrate the real-world situation where decisions usually require a high degree of intuition and subjective judgment. Development of a prototype intended to partially represent application of the architecture is described. The authors conclude with suggestions for research extensions.

Original languageEnglish (US)
Title of host publicationProceedings of the Hawaii International Conference on System Science
Editors Anon
PublisherPubl by Western Periodicals Co
Pages229-240
Number of pages12
ISBN (Print)0818619139
StatePublished - Dec 1 1989
EventProceedings of the Twenty-Second Annual Hawaii International Conference on System Sciences: Decision Support and Knowledge-Based Systems Track - Kailua-Kona, Hawaii, USA
Duration: Jan 3 1989Jan 6 1989

Publication series

NameProceedings of the Hawaii International Conference on System Science
Volume3
ISSN (Print)0073-1129

Other

OtherProceedings of the Twenty-Second Annual Hawaii International Conference on System Sciences: Decision Support and Knowledge-Based Systems Track
CityKailua-Kona, Hawaii, USA
Period1/3/891/6/89

ASJC Scopus subject areas

  • Computer Science(all)

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