| Article ID: | iaor1993837 |
| Country: | Canada |
| Volume: | 30 |
| Issue: | 1 |
| Start Page Number: | 1 |
| End Page Number: | 14 |
| Publication Date: | Feb 1993 |
| Journal: | INFOR |
| Authors: | Nazareth Derek |
| Keywords: | artificial intelligence: decision support, decision theory: multiple criteria, programming: multiple criteria |
Decision support systems (DSS) and multiple criteria decision making (MCDM) models are generally aimed at supporting nonstructured decision making. Despite overlapping goals and sustained development in both fields for the last fifteen years, there are few examples of truly integrated working systems that possess all the functionality of DSS, yet provide the rich support for decision making offered by MCDM. This paper examines some of the reasons for the lack of ready adoption of ideas, concepts, and proven strategies of each discipline in the complementary discipline. The role of each discipline vis-a-vis the other is explicated, and barriers to integration discussed. Some suggestions to counter them are presented. Since each field can benefit from the use of techniques developed in the other, their continued independent development would certainly be counter-productive.