Name
Abstract | ||
|---|---|---|
Lessons learned systems (LLS) are a common knowledge management (KM) initiative among the American government agencies (e.g., Department of Defense (DOD), Department of Energy (DOE), NASA). An effective lessons learned (LL) process can substantially improve decision processes, thus representing an essential chapter in a knowledge-sharing digital government. Unfortunately, these systems typically fail to deliver lessons when and where they are needed. In this paper, we introduce, describe, and empirically evaluate the monitored distribution (MD) approach for the active delivery of lessons learned. Our results show that this just-in-time information delivery approach, embedded in a decision support system (DSS) for plan authoring, significantly improved plan execution performance measures. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/S0167-9236(02)00122-7 | Decision Support Systems |
Keywords | Field | DocType |
Knowledge management,Lessons learned systems,Just-in-time knowledge,Case-based reasoning,Noncombatant evacuation operations | Data mining,Computer science,Digital government,Decision support system,Knowledge management,Information delivery,Common knowledge,Decision process,Case-based reasoning,Government | Journal |
Volume | Issue | ISSN |
34 | 3 | 0167-9236 |
Citations | PageRank | References |
32 | 2.32 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rosina Weber | 1 | 334 | 34.42 |
| David W. Aha | 2 | 4103 | 620.93 |