A simulation perspective on knowledge management and sharing, and conflict and complexity in social systems management

There are many contemporary situations today where conflict potential is a reality. In a very large number of these situations simple patterns, resulting from the aggregation of recurring individual actions and responses, can lead to extremely complex social behaviors. Often, there are misperceptions and miss beliefs concerning these behaviors and this can create a conflict potential that is dysfunctional for groups and societies. Knowledge sharing is generally beneficial in these situations. It would be highly desirable to be able to create models that will accurately predict the outcomes of these complex systems for various knowledge sharing options. In general, this cannot be done. We can, however, often create models that will accurately simulate the processes the system uses to create outputs. The major constructs associated with such models are: the interactions and feedback relations between the various agents whose choices depend upon the decisions of others; and linearity and return to scale considerations. There are many implications associated with these models. Among them are questions of steady state versus continued evolutionary behavior, the nature and possibility of time-invariant processes, and questions of path dependence. Complexity generally emerges from the social consequences of actions and their responses at the level of the individual. Emergence occurs when interactions among elements at one level give rise to different types elements objects at another level. It generally requires new description categories that are not required to describe underlying mechanisms. There is a major difference, however, between human social organizations and institutions and piles of sand even though each can be said to emerge from actions of individual agents. The difference is, of course, that humans have the ability to recognize, to reason with reference to, and to react to emergent features. Thus, human agents distinguish patterns of collective action and their actions are affected by the presence of these patterns. In this paper, we discuss the use of complex adaptive system perspectives to support simulation models that represent social systems management approaches to enhance knowledge sharing in organizations.