
We examine characteristics common to successful intelligent decision support systems. In doing this, we attempt to bridge the gap between disparate communities engaged in building various parts of these systems. Three systems were examined in detail from widely different applications and more than 20 additional systems were considered at a lower level of detail. By examining deployed decision support systems within the context of a broad framework we hope to capture the characteristics that can guide future development efforts. We see this as a first step in developing an in-depth compendium that will help bridge the gap between important yet typically isolated fields.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
